[Federal Register Volume 86, Number 88 (Monday, May 10, 2021)]
[Proposed Rules]
[Pages 25070-25790]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-08888]



[[Page 25069]]

Vol. 86

Monday,

No. 88

May 10, 2021

Part II

Book 2 of 2 Books

Pages 25069-26798





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 Proposed Policy Changes and Fiscal Year 2022 Rates; 
Quality Programs and Medicare Promoting Interoperability Program 
Requirements for Eligible Hospitals and Critical Access Hospitals; 
Proposed Changes to Medicaid Provider Enrollment; and Proposed Changes 
to the Medicare Shared Savings Program; Proposed Rule

  Federal Register / Vol. 86 , No. 88 / Monday, May 10, 2021 / Proposed 
Rules  

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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-P]
RIN 0938-AU44


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

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

ACTION: Proposed rule.

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SUMMARY: We are proposing to revise 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. In addition, we are proposing to rebase and 
revise the hospital market baskets for acute care hospitals, update the 
labor-related share, and provide the market basket update that would 
apply to the rate-of-increase limits for certain hospitals excluded 
from the IPPS that are paid on a reasonable cost basis, subject to 
these limits for FY 2022. We are also proposing policies relating to 
Medicare graduate medical education (GME) for teaching hospitals to 
implement certain recent legislation. The proposed rule would also 
update 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. In 
this FY 2022 IPPS/LTCH PPS proposed rule, we are proposing to extend 
New COVID-19 Treatments Add-on Payment (NCTAP) for certain eligible 
products through the end of the fiscal year in which the PHE ends and 
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 are also proposing to repeal the collection of market-based 
rate information on the Medicare cost report and the market-based MS-
DRG relative weight methodology, as finalized in the FY 2021 IPPS/LTCH 
PPS final rule.
    We are proposing to establish new requirements and revise existing 
requirements for eligible hospitals and critical access hospitals 
(CAHs) participating in the Medicare Promoting Interoperability 
Program. We are also providing estimated and newly established 
performance standards for the Hospital Value-Based Purchasing (VBP) 
Program, and proposing updated policies for the Hospital Readmissions 
Reduction Program, Hospital Inpatient Quality Reporting (IQR) Program, 
Hospital VBP Program, Hospital-Acquired Condition (HAC) Reduction 
Program, and the PPS-Exempt Cancer Hospital Reporting (PCHQR) Program, 
and the Long-Term Care Hospital Quality Reporting Program (LTCH QRP). 
Additionally, due to the impact of the COVID-19 PHE on measure data 
used in our value-based purchasing programs, we are proposing to 
suppress several measures in the Hospital VBP, HAC Reduction, and 
Hospital Readmissions Reduction Programs. In connection with our 
measure suppression proposals for the FY 2022 Hospital VBP Program, we 
are also proposing to revise the scoring and payment methodology for 
the FY 2022 program year such that hospitals will not be scored using 
quality measure data that are distorted by the effects of the COVID-19 
public health emergency (PHE) and will not receive Total Performance 
Scores or adjustments to their payments as a result. Similarly, we are 
proposing to suppress affected measures for the FY 2022 HAC Reduction 
Program such that hospitals will not be scored using distorted quality 
measure data and will not receive Total HAC Scores based on those data. 
For the Hospital Readmissions Reduction Program, we are proposing to 
suppress one affected measure under the proposed measure suppression 
policy for the FY 2023 applicable period such that hospitals will not 
be assessed using distorted quality measure data and will not receive 
payment reductions based on those data.
    In addition, we are proposing to change, clarify, and codify 
Medicare organ acquisition payment policies relative to organ 
procurement organizations (OPOs), transplant hospitals, and donor 
community hospitals. Also, we are proposing to add regulation requiring 
that state Medicaid agencies accept valid enrollments from all 
Medicare-enrolled providers and suppliers for purposes of processing 
claims for Medicare cost-sharing liability for services furnished to 
Medicare-Medicaid dually eligible individuals in order to alleviate a 
long-standing problem related to claiming Medicare bad debt.
    Additionally, we are proposing to amend the Medicare Shared Savings 
Program regulations to allow eligible accountable care organizations 
(ACOs) participating in the BASIC track's glide path the opportunity to 
maintain their current level of participation for performance year (PY) 
2022.

DATES: To be assured consideration, comments must be received at one of 
the addresses provided in the ADDRESSES section, no later than 5 p.m. 
EDT on June 28, 2021.

ADDRESSES: In commenting, please refer to file code CMS-1752-P. Because 
of staff and resource limitations, we cannot accept comments by 
facsimile (FAX) transmission.
    Comments, including mass comment submissions, must be submitted in 
one of the following three ways (please choose only one of the ways 
listed):
    1. Electronically. You may (and we encourage you to) submit 
electronic comments on this regulation to http://www.regulations.gov. 
Follow the instructions under the ``submit a comment'' tab.
    2. By regular mail. You may mail written comments to the following 
address ONLY: Centers for Medicare & Medicaid Services, Department of 
Health and Human Services, Attention: CMS-1752-P, P.O. Box 8013, 
Baltimore, MD 21244-1850.
    Please allow sufficient time for mailed comments to be received 
before the close of the comment period.
    3. By express or overnight mail. You may send written comments via 
express or overnight mail to the following address ONLY: Centers for 
Medicare & Medicaid Services, Department of Health and Human Services, 
Attention: CMS-1752-P, Mail Stop C4-26-05, 7500 Security Boulevard, 
Baltimore, MD 21244-1850.
    For information on viewing public comments, we refer readers to the 
beginning of the SUPPLEMENTARY INFORMATION section.

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, Graduate Medical 
Education, Capital Prospective Payment, Excluded Hospitals, Medicare 
Disproportionate Share Hospital (DSH) Payment

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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], Dylan Podson, 
[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.
    Katie Lucas, (410) 786-7723, Amanda Michael, (410) 786-5834, and 
Kellie Shannon (410) 786-0416, Organ Acquisition Payment Issues.
    Naseem Tarmohamed, (410) 786-0814, or 
[email protected], for issues related to the Shared 
Savings Program.

SUPPLEMENTARY INFORMATION: 
    Inspection of Public Comments: All comments received before the 
close of the comment period are available for viewing by the public, 
including any personally identifiable or confidential business 
information that is included in a comment. We post all comments 
received before the close of the comment period on the following 
website as soon as possible after they have been received: http://www.regulations.gov/. Follow the search instructions on that website to 
view public comments.

Tables Available Through the Internet on the CMS Website

    The IPPS tables for this FY 2022 proposed 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 
Proposed rule Home Page'' or ``Acute Inpatient--Files for Download.'' 
The LTCH PPS tables for this FY 2022 proposed 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-P. For 
further details on the contents of the tables referenced in this 
proposed rule, we refer readers to section VI. of the Addendum to this 
FY 2022 IPPS/LTCH PPS proposed 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 That Would Be 
Implemented in This Proposed Rule
    D. Summary of the Provisions of This Proposed Rule
    E. Advancing Health Information Exchange
    F. Use of FY 2020 or FY 2019 Data in the FY 2022 IPPS and LTCH 
PPS Ratesetting
II. Proposed 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. Proposed FY 2022 MS-DRG Documentation and Coding Adjustment
    D. Proposed Changes to Specific MS-DRG Classifications
    E. Recalibration of the FY 2022 MS-DRG Relative Weights
    F. Proposed Add-On Payments for New Services and Technologies 
for FY 2022
III. Proposed 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. Proposed Occupational Mix Adjustment to the FY 2022 Wage 
Index
    F. Analysis and Implementation of the Proposed 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 Proposed Budget Neutrality Adjustment
    H. Proposed FY 2022 Wage Index Tables
    I. Proposed Revisions to the Wage Index Based on Hospital 
Redesignations and Reclassifications
    J. Proposed 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. Proposed Labor-Related Share for the FY 2022 Wage Index
IV. Proposed 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

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    A. Proposed Changes in the Inpatient Hospital Updates for FY 
2021 (Sec.  412.64(d))
    B. Rural Referral Centers (RRCs)--Proposed Annual Updates to 
Case-Mix Index and Discharge Criteria (Sec.  412.96)
    C. Proposed Payment Adjustment for Low-Volume Hospitals (Sec.  
412.101)
    D. Proposed Indirect Medical Education (IME) Payment Adjustment 
Factor (Sec.  412.105)
    E. Proposed 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: Proposed Updates and 
Changes (Sec. Sec.  412.150 Through 412.154)
    H. Hospital Value-Based Purchasing (VBP) Program: Proposed 
Updates and Changes (Sec. Sec.  412.160 Through 412.167)
    I. Hospital-Acquired Conditions (HAC) Reduction Program: 
Proposed 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--Proposed 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. Proposed Changes to the IPPS for Capital-Related Costs
    A. Overview
    B. Additional Provisions
    C. Proposed Annual Update for FY 2022
VII. Proposed Changes for Hospitals Excluded From the IPPS
    A. Proposed Rate-of-Increase in Payments to Excluded Hospitals 
for FY 2022
    B. Critical Access Hospitals (CAHs)
VIII. Proposed 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. Proposed Changes to the LTCH PPS Payment Rates and Other 
Proposed Changes to the LTCH PPS for FY 2022
IX. Proposed 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. Proposed Changes to the Medicare Promoting Interoperability 
Programs
X. Proposed 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--Proposed Policy Changes 
(Sec.  455.410)
    B. Organ Acquisition Payment--Proposed Policy Changes (Part 413, 
Subpart L)
    C. Medicare Shared Savings Program--Proposed Policy Changes 
(Sec.  425.600)
XI. MedPAC Recommendations
XII. Other Required Information
    A. Publicly Available Files
    B. Collection of Information Requirements
    C. Response to Public Comments
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. Proposed 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. Proposed Adjustments for Area Wage Levels and Cost-of-Living
    C. Calculation of the Proposed Prospective Payment Rates
III. Proposed Changes to Payment Rates for Acute Care Hospital 
Inpatient Capital-Related Costs for FY 2022
    A. Determination of the Proposed Federal Hospital Inpatient 
Capital-Related Prospective Payment Rate Update for FY 2022
    B. Calculation of the Proposed Inpatient Capital-Related 
Prospective Payments for FY 2022
    C. Capital Input Price Index
IV. Proposed Changes to Payment Rates for Excluded Hospitals: Rate-
of-Increase Percentages for FY 2022
V. Proposed Changes to the Payment Rates for the LTCH PPS for FY 
2022
    A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2022
    B. Proposed Adjustment for Area Wage Levels Under the LTCH PPS 
for FY 2022
    C. Proposed Cost-of-Living Adjustment (COLA) for LTCHs Located 
in Alaska and Hawaii
    D. Proposed Adjustment for LTCH PPS High-Cost Outlier (HCO) 
Cases
    E. Proposed Update to the IPPS Comparable/Equivalent Amounts to 
Reflect the Statutory Changes to the IPPS DSH Payment Adjustment 
Methodology
    F. Computing the Proposed Adjusted LTCH PPS Federal Prospective 
Payments for FY 2022
VI. Tables Referenced in This Proposed 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 Proposed Policy Changes
    I. Effects of Proposed Changes in the Capital IPPS
    J. Effects of Proposed Payment Rate Changes and Policy Changes 
Under the LTCH PPS
    K. Effects of Proposed Requirements for Hospital Inpatient 
Quality Reporting (IQR) Program
    L. Effects of Proposed Requirements for the PPS-Exempt Cancer 
Hospital Quality Reporting (PCHQR) Program
    M. Effects of Proposed Requirements for the Long-Term Care 
Hospital Quality Reporting Program (LTCH QRP)
    N. Effects of Proposed 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. Proposed FY 2022 Inpatient Hospital Update
    B. Proposed Update for SCHs and MDHs for FY 2022
    C. Proposed FY 2022 Puerto Rico Hospital Update
    D. Proposed Update for Hospitals Excluded From the IPPS for FY 
2022
    E. Proposed 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 proposed rule would make 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 would make payment and policy changes for 
inpatient hospital services

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provided by long-term care hospitals (LTCHs) under the long-term care 
hospital prospective payment system (LTCH PPS). This proposed rule also 
would make policy changes to programs associated with Medicare IPPS 
hospitals, IPPS-excluded hospitals, and LTCHs. In this FY 2022 proposed 
rule, we are continuing policies to address wage index disparities 
impacting low wage index hospitals; including a proposal to implement 
the imputed floor wage index provision of the American Rescue Plan Act 
of 2021; including proposals related to new technology add-on payments; 
and proposing to repeal the collection of market-based rate information 
on the Medicare cost report and the market-based MS-DRG relative weight 
methodology, as finalized in the FY 2021 IPPS/LTCH PPS final rule. This 
proposed rule also includes proposals to implement provisions of the 
Consolidated Appropriations Act of 2021 relating to payments to 
hospitals for direct graduate medical education (GME) and indirect 
medical education (IME) costs.
    We are proposing to establish new requirements and revise 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 
proposing 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 proposing 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 proposing 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.
    Under various statutory authorities, we either discuss continued 
program implementation or are proposing to make 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 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

[[Page 25074]]

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(a)(23) of the Act, which specifies Medicaid 
provider enrollment requirements. States may set reasonable standards 
relating to the qualifications of providers but may not restrict the 
right of beneficiaries to obtain services from any person or entity 
that is both qualified and willing to furnish such services.
2. Summary of the Major Provisions
    The following is a summary of the major provisions in this proposed 
rule. In general, these major provisions are being proposed as part of 
the annual update to the payment policies and payment rates, consistent 
with the applicable statutory provisions. A general summary of the 
proposed changes in this proposed rule is presented in section I.D. of 
the preamble of this proposed rule.
a. Proposed 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 proposing to make an adjustment of 
+0.5 percent to the standardized amount.
b. Proposed Changes to 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 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). At the same 
time, we also believe 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.
    Therefore, we are proposing to extend 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 are proposing 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.
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 proposed rule we discuss our analysis of the best 
available data for use in the development of this FY 2022 IPPS/LTCH PPS 
proposed 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 proposed rule, we are proposing to use 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. In section I.O. of Appendix A of this proposed 
rule, we are also 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.
d. Proposed 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

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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 would 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 proposing to apply this policy in a budget neutral 
manner by applying an adjustment to the standardized amounts.
e. Proposed 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 proposed rule for 
a summary of the provisions of section 9831 of Public Law 117-2 that we 
are proposing to implement in this proposed rule.
f. Proposed 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, 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 proposed rule, we are proposing to update our estimates of 
the three factors used to determine uncompensated care payments for FY 
2022. We are also proposing to continue 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 proposing to continue to use the low-income insured days proxy to 
calculate Factor 3 for these hospitals for FY 2022. We are proposing 
certain methodological changes for calculating Factor 3 for FY 2022.
    Additionally, we are proposing to revise our regulation governing 
the calculation of the Medicaid fraction of the DSH calculation. Under 
this proposal, patient days of individuals receiving benefits under a 
section 1115 waiver program would be counted in the numerator of the 
Medicaid fraction only if the patient directly receives inpatient 
hospital insurance coverage on that day under a waiver authorized under 
section 1115(a)(2) of the Act.
g. Reduction of Hospital Payments for Excess Readmissions
    We are proposing to make 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 
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 proposed rule, we are proposing 
the following policies: (1) To adopt a cross-program measure 
suppression policy; (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 are also requesting 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 are also seeking 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.
h. 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 proposed rule, we are proposing 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,

[[Page 25076]]

All-Cause, Risk-Standardized Mortality Rate Following Pneumonia (PN) 
Hospitalization (MORT-30-PN) measure for the FY 2023 program year. We 
are also proposing to revise the scoring and payment methodology for 
the FY 2022 program year such that hospitals' Total Performance Scores 
will not include calculations based on these measures. 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 proposing not to award a TPS to any hospital for the 
FY 2022 program year. Instead, we are proposing 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 proposing to remove the CMS Patient Safety and Adverse 
Events Composite (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 proposing to update the baseline periods for 
certain measures affected by the ECE granted in response to the COVID-
19 PHE and to make a technical update to our terminology used in the 
Hospital VBP Program regulations.
i. 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 proposed rule, we are proposing to: 
(1) Clarify our ECE policy; (2) adopt a cross-program measure 
suppression policy; (3) apply that measure suppression policy to 
suppress certain program data; and (4) update the regulatory text to 
reflect that our Hospital Compare website has been renamed and is now 
referred to as Care Compare.
j. 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 proposed rule, we are proposing to 
make several changes. We are proposing to adopt 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 proposing to remove five measures: (1) Death Among 
Surgical Inpatients with Serious Treatable Complications (CMS PSI-04) 
beginning with the FY 2023 payment determination; (2) Exclusive Breast 
Milk Feeding (PC-05) (NQF #0480) beginning with the FY 2026 payment 
determination; (3) Admit Decision Time to ED Departure Time for 
Admitted Patients (ED-2) (NQF #0497) beginning with the FY 2026 payment 
determination; and two stroke-related eCQMs beginning with the FY 2026 
payment determination; (4) Anticoagulation Therapy for Atrial 
Fibrillation/Flutter eCQM (STK-03) (NQF #0436); and (5) Discharged on 
Statin Medication eCQM (STK-06) (NQF #0439).
    We are requesting 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 are also requesting 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. In this proposed rule, we are also requesting 
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, beginning with the CY 2023 reporting period/FY 2025 
payment determination, we are proposing to require hospitals 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 
proposing 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 proposing an update 
to revise 42 CFR 412.140(a)(2) and 42 CFR 412.140(e)(2)(iii) replacing 
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 proposing to revise 
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 proposing to extend the effects of the educational review 
process for chart-abstracted measures beginning with validations 
affecting the FY 2024 payment determination.
k. 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 proposed rule, we are proposing to remove the Oncology: 
Plan of Care for Pain--Medical Oncology and

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Radiation Oncology (NQF #0383) (PCH-15) measure beginning with the FY 
2024 program year, adopt the COVID-19 Vaccination Coverage Among 
Healthcare Personnel measure beginning with the FY 2023 program year, 
make a technical update to the terminology we use in the program, and 
codify existing PCHQR Program policies in our regulations.
l. Medicare Promoting Interoperability Program
    For purposes of reducing the burden on eligible hospitals and CAHs, 
we are proposing several changes to the Medicare Promoting 
Interoperability Program. Specifically, we are proposing: (1) To 
continue 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 to increase 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) 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; (3) to 
modify the Provide Patient's Electronic Access to Their Health 
Information measure to establish a data availability requirement 
beginning with encounters with a date of service on or after January 1, 
2016, beginning with the EHR reporting period in CY 2022; (4) 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; (5) to require 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); 
(6) 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; (7) to remove attestation statements 2 and 
3 from the Promoting Interoperability Program's prevention of 
information blocking requirement; (8) 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; and (9) 
to adopt 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 four eCQMs from the measure set beginning 
with the reporting period in CY 2024 which is in alignment with the 
proposals for the Hospital IQR Program. We are amending our regulation 
texts as necessary to incorporate several of these proposed changes.
m. Proposed 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 proposed rule, 
we are proposing 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 proposing 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 are 
soliciting comment on alternative approaches or data sources that could 
be used in Medicare fee-for-service (FFS) ratesetting. The proposed 
repeal of these policies would result in a reduction of 63,780 annual 
burden hours for all hospitals.
n. Proposed Implementation of Sections 126, 127 and 131 of the 
Consolidated Appropriations Act (CAA) of 2021
    In this proposed rule, we are including proposals to implement 
sections 126, 127 and 131 of the Consolidated Appropriations Act (CAA) 
of 2021. Section 126(a) of the CAA amended section 1886(h) of the Act 
by adding a new section 1886(h)(9) of the Act requiring the 
distribution of additional residency positions to qualifying hospitals. 
Section 127 of the CAA amended section 1886(h)(4)(H)(iv) of the Act to 
specify that in the case of a hospital not located in a rural area that 
established or establishes a medical residency training program (or 
rural track) in a rural area, the hospital, and each such hospital 
located in a rural area that participates in such a training, is 
allowed to receive an adjustment to its full-time equivalent (FTE) 
resident limit. Section 131 of the CAA amended section 1886(h)(2)(F) of 
the Act to provide an opportunity to hospitals with such extremely low 
or $0 per resident amounts (PRAs) that meet certain criteria to reset 
and establish new PRAs if the hospital trains resident(s) in a cost 
reporting period beginning on or after enactment [December 27, 2020] 
and before the date that is 5 years after enactment [December 26, 
2025]. Section 131 also amended section 1886(h)(4)(H)(i) of the Act to 
provide an opportunity for hospitals that meet certain criteria and 
that have very small FTE resident caps to replace those caps if the 
Secretary determines the hospital begins training residents in a new 
program beginning on or after enactment (December 27, 2020) and before 
5 years after enactment (December 26, 2025). We refer readers to 
section V.J.2. of this proposed rule for rule for a summary of the 
provisions of sections 126, 127, and 131 of the CAA that we are 
proposing to implement in this proposed rule.
o. Proposed Changes to Organ Acquisition Payment Policy
    In section X.B.2.h. of the preamble of this proposed rule, we are 
proposing to revise and codify the Medicare usable organ counting 
policy to count only organs transplanted into Medicare beneficiaries so 
that Medicare more accurately records and pays its share of organ 
acquisition costs.
p. Medicare Shared Savings Program
    We are proposing to make 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 this proposal, 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 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).
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 proposed rule.
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BILLING CODE 4120-01-C

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

[[Page 25083]]

updates to the LTCH PPS are included 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 That Would Be 
Implemented in This Proposed 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. Consolidated Appropriations Act, 2021 (Pub. L. 116-260)
    Sections 126, 127 and 131 of the Consolidated Appropriations Act, 
2021 made a number of changes to various sections of the Act relating 
to payment for direct GME and IME costs to hospitals.
a. Section 126 of the Consolidated Appropriations Act, 2021
    Section 126 amended section 1886(h) of the Act by adding a new 
section 1886(h)(9) requiring the distribution of additional residency 
positions to qualifying hospitals. Section 1886(h)(9)(A) requires that 
for FY 2023, and for each succeeding fiscal year until the aggregate 
number of full-time equivalent residency positions distributed is equal 
to 1,000, the Secretary shall initiate separate rounds of applications 
from hospitals for these additional residency positions. The Secretary 
is required, subject to certain provisions in the law, to increase the 
otherwise applicable resident limit for each qualifying hospital that 
submits a timely application by the number of positions that may be 
approved by the Secretary for that hospital. The Secretary is required 
to notify hospitals of the number of positions distributed to them by 
January 31 of the fiscal year of the increase, and the increase is 
effective beginning July 1 of that fiscal year. Section 1886(h)(9)(A) 
also limits the aggregate number of such positions made available in a 
single fiscal year across all hospitals to no more than 200.
    In determining the qualifying hospitals for which an increase is 
provided, section 1886(h)(9)(B) requires the Secretary to take into 
account the demonstrated likelihood of the hospital filling the 
positions made available within the first 5 training years beginning 
after the date the increase would be effective, as determined by the 
Secretary.
    Section 1886(h)(9)(B) of the Act also requires a minimum 
distribution for certain categories of hospitals. Specifically, the 
Secretary is required to distribute at least 10 percent of the 
aggregate number of total residency positions available to each of four 
categories of hospitals. Stated briefly, and discussed in greater 
detail in later in this proposed rule, the categories are as follows: 
(1) Hospitals located in rural areas or that are treated as being 
located in a rural area; (2) hospitals in which the reference resident 
level of the hospital is greater than the otherwise applicable resident 
limit; (3) hospitals in states with new medical schools or additional 
locations and branches of existing medical schools; and (4) hospitals 
that serve areas designated as Health Professional Shortage Areas 
(HPSAs). Additionally, section 1886(h)(9)(F)(ii) of the Act defines a 
qualifying hospital as a hospital in one of these four categories.
    Section 1886(h)(9)(C) of the Act places certain limitations on the 
distribution of the residency positions. First, a hospital may not 
receive more than 25 additional full-time equivalent residency 
positions. Second, no increase in the otherwise applicable resident 
limit of a hospital may be made unless the hospital agrees to increase 
the total number of full-time equivalent residency positions under the 
approved medical residency training program of the hospital by the 
number of positions made available to that hospital.
b. Section 127 of the Consolidated Appropriations Act, 2021
    Section 127 of the CAA amended section 1886(h)(4)(H)(iv) of the Act 
to

[[Page 25084]]

specify that in the case of a hospital not located in a rural area that 
established or establishes a medical residency training program (or 
rural tracks) in a rural area, the hospital, and each such hospital 
located in a rural areas that participates in such a training, is 
allowed to receive an adjustment to its full-time equivalent (FTE) 
resident limit.
c. Sections 131 of the Consolidated Appropriations Act, 2021
    Section 131 of the CAA amended section 1886(h)(2)(F) of the Act to 
provide an opportunity to hospitals with such extremely low or $0 per 
resident amounts (PRAs) that meet certain criteria to reset and 
establish new PRAs if the hospital trains resident(s) in a cost 
reporting period beginning on or after enactment [December 27, 2020] 
and before the date that is 5 years after enactment [December 26, 
2025]. Section 131 of the CAA also amended section 1886(h)(4)(H)(i) of 
the Act to provide an opportunity for hospitals that meet certain 
criteria and that have very small FTE resident caps to replace those 
caps if the Secretary determines the hospital begins training residents 
in a program year beginning on or after enactment (December 27, 2020) 
and before 5 years after enactment (December 26, 2025).

D. Summary of the Provisions of This Proposed Rule

    In this proposed rule, 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 are 
proposing to make in this proposed rule.
1. Proposed Changes to MS-DRG Classifications and Recalibrations of 
Relative Weights
    In section II. of the preamble of this 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 Public Law 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.
2. Proposed Changes to the Hospital Wage Index for Acute Care Hospitals
    In section III. of the preamble of this proposed rule we are 
proposing to make revisions 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 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.
3. Proposed Rebasing and Revising of the Hospital Market Baskets
    In section IV. of the preamble of this proposed rule, we are 
proposing to rebase and revise the hospital market baskets for acute 
care hospitals and update the labor-related share.
4. Other Decisions and Proposed Changes to the IPPS for Operating Costs
    In section V. of the preamble of this proposed rule, we discuss 
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.

[[Page 25085]]

5. Proposed FY 2022 Policy Governing the IPPS for Capital-Related Costs
    In section VI. of the preamble to this proposed rule, we discuss 
the proposed payment policy requirements for capital-related costs and 
capital payments to hospitals for FY 2022.
6. Proposed Changes to the Payment Rates for Certain Excluded 
Hospitals: Rate-of-Increase Percentages
    In section VII. of the preamble of this proposed rule, we discuss--
     Proposed changes to payments to certain excluded hospitals 
for FY 2022.
     Proposed continued implementation of the Frontier 
Community Health Integration Project (FCHIP) Demonstration.
7. Proposed Changes to the LTCH PPS
    In section VIII. of the preamble of this 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.
8. Proposed Changes Relating to Quality Data Reporting for Specific 
Providers and Suppliers
    In section IX. of the preamble of this proposed rule, we address 
the following:
     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 are also seeking 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.
9. Other Proposals Included in This Proposed Rule
    Section X. of the preamble to this proposed rule includes 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.
10. Other Provisions of This Proposed Rule
    Section XI. of the preamble to this proposed rule includes our 
discussion of the MedPAC Recommendations.
    Section XII. of the preamble to this 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.
11. 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 this proposed rule, we 
set 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 this proposed rule, we address 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.
12. 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.
13. 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.
14. 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.
15. 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 address these recommendations in Appendix B of this 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.

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

[[Page 25086]]

Information Technology (ONC) participate inin 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.
---------------------------------------------------------------------------

    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'') 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 bills 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.
    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, as we discuss in this section. 
Accordingly, we question whether these data sources are the best 
available data to use for the FY 2022 ratesetting. One factor in 
assessing whether these data sources represent the best available data 
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

[[Page 25087]]

2019). Another factor is to what extent the decision to use the FY 2019 
or FY 2020 data differentially impacts the FY 2022 IPPS ratesetting.
    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 have been administered. 
Overall, about 125.8 million people, or 37.9 percent of the U.S. 
population, have 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 have 
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 have received at least one dose of 
vaccine; 63.7 percent are fully vaccinated. Nearly one-half (48.3 
percent) of people 18 or older have received at least one dose of 
vaccine; 30.3 percent are fully vaccinated. Nationally, COVID-19-
related emergency department visits as well as both hospital admissions 
and current hospitalizations have risen among patients ages 18 to 64 
years in recent weeks, but emergency department visits and 
hospitalizations among people ages 65 years and older have 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 recent 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, we believe 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 leads us to conclude based on the 
information available to us at this time 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 calls 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.
---------------------------------------------------------------------------

    \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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    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, 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 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 is 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. We note 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.
    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.
    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 bills from IPPS hospitals received as of July 2020. 
Those bills 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 bills, the 
change in average case-mix in FY 2020 was 2.8 percent. Based on these 
bills 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

[[Page 25088]]

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 bills from IPPS 
hospitals received as of July 2020, for this 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 is 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 lead us to believe that FY 
2020 is not the best overall approximation of inpatient experience in 
FY 2022. We believe 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 earlier, whether the data is a better overall 
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. 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] TP10MY21.004
    

[[Page 25089]]


    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 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.
    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 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.
    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 this 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.
---------------------------------------------------------------------------

    Under an assumption that the FY 2022 inpatient experience will be 
more similar to FY 2019 data, we estimate 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 estimate 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, 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, we have highlighted two factors in the decision 
regarding the best available data to use in the FY 2022 ratesetting. 
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, 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, we believe for purposes of this proposed rule that 
FY 2019 is 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. After 
analyzing this issue, and as discussed previously, we have 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, we are proposing 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 are 
proposing 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 section II.D. of the preamble of this proposed rule). 
Similarly, we are proposing 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 proposed FY 2022 IPPS MS-DRG 
relative weights (as discussed in greater detail section II.E. of the 
preamble of this 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.) 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 proposed use of the FY 2019 data for 
the FY 2022 ratesetting in this proposed rule. We have clearly 
identified throughout this proposed rule where and how we are proposing 
to use alternative data than what ordinarily would be used for the 
proposed FY 2022 IPPS and LTCH PPS ratesetting, including certain 
provider specific information.
    As discussed in section I.O. of Appendix A of this proposed rule, 
we are also 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

[[Page 25090]]

which we may consider finalizing based on consideration of comments 
received. To facilitate comment on this alternative for FY 2022, we are 
making available the FY 2020 MedPAR file and the FY 2019 HCRIS file 
that we would ordinarily have provided in conjunction with this 
proposed rule. We are also making available the MS-DRG and MS-LTC-DRG 
relative weighting factors and length of stay information calculated 
using the FY 2020 data we would have ordinarily used. We are providing 
a file comparing the budget neutrality and other ratesetting 
adjustments calculated under our proposal with those adjustments 
calculated under this alternative approach. Finally, we are making 
available other proposed rule supporting data files based on the use of 
the FY 2020 data that we ordinarily would have provided, including: The 
IPPS and LTCH PPS Impact Files; the AOR/BOR File; the Case Mix Index 
File; and, the Standardizing File. We refer the reader to section I.O. 
of Appendix A of this proposed rule for more information on where these 
supplemental files may be found.

II. Proposed 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).

C. Proposed 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.

[[Page 25091]]

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 
58444-58445), 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. Proposed Adjustment for FY 2022
    Consistent with the requirements of section 414 of the MACRA, we 
are proposing to implement a 0.5 percentage point positive adjustment 
to the standardized amount for FY 2022. This would constitute a 
permanent adjustment to payment rates. We plan to propose the final 
adjustment required under section 414 of the MACRA for FY 2023 in 
future rulemaking.

D. Proposed Changes to Specific MS-DRG Classifications

1. Discussion of Changes to Coding System and Basis for Proposed 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 Proposed 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. 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.
    As noted, 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 proposed 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].
    As we did for the FY 2021 IPPS/LTCH PPS proposed rule, for this FY 
2022 IPPS/LTCH PPS proposed rule we are providing a test version of the 
ICD-10 MS-DRG GROUPER Software, Version 39, so that the public can 
better analyze and understand the impact of the proposals included in 
this proposed rule. We note that this test software reflects the 
proposed GROUPER logic for FY 2022. Therefore, it includes 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 associated with this proposed rule and does 
not include the diagnosis codes that are invalid beginning in FY 2022 
as reflected in Table 6C.--Invalid Diagnosis Codes--FY 2022 and Table 
6D.--Invalid Procedure Codes--FY 2022 associated with this proposed 
rule. These tables are not published in the Addendum to this proposed 
rule, but are available via the

[[Page 25092]]

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 proposed rule. Because the 
diagnosis and procedure codes no longer valid for FY 2022 are not 
reflected in the test software, we are making available a supplemental 
file in Table 6P.1a that includes 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 are making available a supplemental file in Table 6P.1b 
that includes 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 
will have access to the test software allowing them to build case 
examples that reflect the proposals included in this proposed rule. In 
addition, users will be 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 are proposing to the MS-DRGs for 
FY 2022. We are inviting 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 this proposed 
rule. In some cases, we are proposing changes to the MS-DRG 
classifications based on our analysis of claims data and consultation 
with our clinical advisors. In other cases, we are proposing 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 this proposed rule, we are proposing 
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 are also providing 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 this 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 bills 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 bills 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 refer 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.''
    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 25093]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.005

    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, we 
stated earlier that for this FY 2022 IPPS/LTCH PPS proposed rule, 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.
    For this FY 2022 IPPS/LTCH PPS proposed rule, using the March 2020 
update of the FY 2019 MedPAR file and the September 2020 update of the 
FY 2020 MedPAR file, we also 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 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. 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 refer the reader to Table 6P.1c 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.

[[Page 25094]]

    In light of the public health emergency (PHE), we have concerns 
about the impact of implementing this volume of MS-DRG changes at this 
time, and believe 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 are proposing 
to delay the application of the NonCC subgroup criteria to existing MS-
DRGs with a three-way severity level split until FY 2023, and proposing 
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.
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 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.
    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 refer 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 this proposed 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. 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 are proposing 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 this proposed 
rule and available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/.

[[Page 25095]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.006

    In connection with our proposed assignment of the listed procedure 
codes to Pre-MDC MS-DRG 018, we are also proposing 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.
3. MDC 03 (Diseases and Disorders of Ear, Nose 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/

[[Page 25096]]

Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/. 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 proposed rule, we discuss each of these separate, but 
related requests.
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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.368

    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.
    We reviewed this request and note 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 
note 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 
refer 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 note 
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, 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 and 
Throat), given the stated rationale for the request.
    Upon our review, we believe 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 believe that 
the codes are appropriate for assignment

[[Page 25097]]

in MDC 03 and note that the three procedure codes were previously 
assigned to MS-DRGs 133 and 134 (Other Ear, Nose, Mouth and 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.''
    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 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 agree 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 this 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 are proposing 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 proposed rule for further discussion 
regarding the designation of these codes as Extensive O.R. procedures 
versus Non-extensive O.R. procedures and our proposed reassignment of 
these codes from MS-DRGs 981, 982, and 983 to MS-DRGs 987, 988, and 989 
for FY 2022.
b. Other Ear, Nose, Mouth and Throat O.R. Procedures
    As stated 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. In this section 
of this proposed 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 this FY 
2022 IPPS/LTCH PPS proposed 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.007

    We reviewed this request and similar to the discussion in the prior 
section for the separate but related request, we note 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 continue to believe that the 82

[[Page 25098]]

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 note 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 note 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 are proposing 
to maintain the current structure for MS-DRGs 143, 144, and 145 for FY 
2022.
    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 this proposed 
rule for further discussion of this request, as well as our proposed 
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
    We received a request 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
[GRAPHIC] [TIFF OMITTED] TP10MY21.008

    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 mentioned 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 reviewed this request and believe 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. 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 are proposing to maintain the structure of MS-DRGs 190, 
191, and 192 for FY 2022.
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 proposed rule, we discuss our 
review of the procedures and our proposal for

[[Page 25099]]

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 refer 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.
    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.009

    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 are proposing 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 this proposed 
rule (which is available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    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 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 this 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.
    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

[[Page 25100]]

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

[[Page 25101]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.010


[[Page 25102]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.011

BILLING CODE 4120-01-C
    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 are proposing to remove procedure codes 
0DQ50ZZ, 0DQ53ZZ, 0DQ54ZZ, 0DQ57ZZ, and 0DQ58ZZ from the logic in MDC 
04 for FY 2022.
    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 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 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 
this 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.
    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.012


[[Page 25103]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.013

    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 this proposed 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 this 
proposed 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 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).

[[Page 25104]]

    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.
    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.014

    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 note 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.

[[Page 25105]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.015

    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 note 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.016


[[Page 25106]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.017

    We refer 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 note 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 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 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 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 are proposing 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. 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 
agree that these procedures clinically align with the other procedures 
that are currently assigned to MS-DRGs 163, 164, and 165. We refer the 
reader to Table 6P.2c associated with this proposed rule for the list 
of procedure codes we are proposing for reassignment from MS-DRGs 166, 
167, and 168 to MS-DRGs 163, 164, and 165 in MDC 04.
    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
    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

[[Page 25107]]

currently assigned to MS-DRG 215 (Other Heart Assist System Implant). 
We refer 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 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 this 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.
    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 note that the requestor suggested that the cases 
reporting a procedure code describing

[[Page 25108]]

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).
    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] TP10MY21.018

    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 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.
    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] TP10MY21.019

    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).

[[Page 25109]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.020

    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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.021

    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. The data analysis shows that for the 
cases in MS-DRG 215 reporting ICD-10-PCS codes 02HA0RJ, 02HA3RJ or 
02HA4RJ without a

[[Page 25110]]

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] TP10MY21.022

    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 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).
[GRAPHIC] [TIFF OMITTED] TP10MY21.023

    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:

[[Page 25111]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.024

    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 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). 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] TP10MY21.025

    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).

[[Page 25112]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.026

    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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.027

    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

[[Page 25113]]

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] TP10MY21.028

    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).
[GRAPHIC] [TIFF OMITTED] TP10MY21.029

    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.
    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 state 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, our clinical advisors support reassigning

[[Page 25114]]

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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.030

    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 25115]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.031

    As with our simulation based on the March 2020 update of the FY 
2019 MedPAR file, 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. 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 are proposing 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.
b. Type II Myocardial Infarction
    We received a request 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.
    To begin our analysis, we reviewed the GROUPER logic. 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 note 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).
    Our clinical advisors reviewed this issue and do 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.'' Our clinical 
advisors believe 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 state the diagnosis of myocardial infarction describes 
myocardial cell death due to inadequate

[[Page 25116]]

oxygen supply to the myocardium for a prolonged period, regardless of 
the subtype. Our clinical advisors state, 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 are not proposing to reassign diagnosis code 
I21.A1 from MS-DRGs 280 through 285.
    During our review of this issue we 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 refer 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, our clinical 
advisors recommend 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 are proposing 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 
this proposed 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 
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 note 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 propose 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 a MCC in these MS-DRGs.
    In summary, for FY 2022, we are proposing to maintain the current 
structure of MS-DRGs 280 through 285. We are also proposing 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.
c. Viral Cardiomyopathy
    We received three separate but related requests 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] TP10MY21.369

    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

[[Page 25117]]

procedures such as cardiac catheterization or coronary angioplasty are 
performed for a principal diagnosis of viral cardiomyopathy.
    To begin our analysis, we reviewed the GROUPER logic. 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. 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.
    Our clinical advisors agree that the diagnosis of viral 
cardiomyopathy is clinically related to the other diagnoses in ICD-10-
CM subcategory B33.2. They believe 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 are 
proposing 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). 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.
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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.032

    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 response to this final policy, for this FY 2022 IPPS/LTCH PPS 
proposed rule, we received a request to again review the MS-DRG 
assignment of cases involving LAAC procedures with an open approach. 
The requestor disagreed with CMS's 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.
    Our clinical advisors reviewed this request and continue to support 
the reassignment of ICD-10-PCS procedure

[[Page 25118]]

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 state 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. 
Our clinical advisors continue 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 are proposing 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.
e. Surgical Ablation
    We received a two-part request 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 days, 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.
    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 its 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 reviewing 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.

[[Page 25119]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.033

    In 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). 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.
    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. 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 believe 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 are proposing 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. 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. We refer the 
reader to section II.D.15. of the preamble of this proposed rule for 
the discussion of the surgical hierarchy and the complete list of our 
proposed modifications to the surgical hierarchy in MDC 05.
    As mentioned earlier 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.

[[Page 25120]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.034

    The requestor performed its own analysis and stated that it 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 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).
    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] TP10MY21.035

    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 5.8 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 table.

[[Page 25121]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.036

    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.037

    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 table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.038

    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.
    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. Our clinical advisors reviewed this issue and do not 
recommend changing the assignment of procedure codes describing 
percutaneous endoscopic surgical ablation. Therefore, for these 
reasons, we are proposing to maintain the current structure of MS-DRGs 
219 and 220.
f. Drug-Eluting Stents
    We received a request 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

[[Page 25122]]

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 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.
    Based on a review of the procedure codes that are currently 
assigned to MS-DRGs 246, 247, 248 and 249, our clinical advisors agree 
that further refinement of these MS-DRGs may be warranted. However, 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, our clinical advisors recommend 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 this proposed rule. Therefore, we believe it would be 
more appropriate to consider this request further during our 
comprehensive procedure code review in future rulemaking.
6. MDC 08 (Diseases and Disorders of the Musculoskeletal System and 
Connective Tissue)
a. Knee Joint Procedures
    We received a request 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.039

    The requestor also provided the following procedure codes that 
describe the procedure code combinations for right knee joint removal 
and replacement procedures for CMS's review and consideration.

[[Page 25123]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.040

    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.
    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. Adding these procedure codes will improve 
clinical coherence and ensure more appropriate MS-DRG assignment for 
these cases.
    Therefore, for FY 2022, we are proposing 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.
b. Pelvic Trauma With Internal Fixation
    We received a 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 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 crosswalked 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

[[Page 25124]]

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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.041

    The requestor also provided the following diagnosis code 
subcategories that it stated identify diagnoses describing pelvic 
fracture.
[GRAPHIC] [TIFF OMITTED] TP10MY21.042

    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 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.

[[Page 25125]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.043

[GRAPHIC] [TIFF OMITTED] TP10MY21.044

    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 note 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 this 
proposed 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 this proposed 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.

[[Page 25126]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.045

    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.
    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.046


[[Page 25127]]


    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. 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 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 this proposed rule (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.047

    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.
    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 this proposed rule (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    We believe further analyses of these internal fixation for pelvic 
trauma cases in the claims data is warranted. We note 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

[[Page 25128]]

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.
    We refer 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. Additional time 
is needed for data analysis given the volume of these code combinations 
and corresponding data. We also 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. Our clinical 
advisors also believe that future data findings may demonstrate 
additional variance in resource utilization for this patient 
population. We further note 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 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 are proposing 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)
    We received a request 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 reimbursement 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 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.
    The following ICD-10-PCS procedure code identifies the performance 
of CRRT.

[[Page 25129]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.048

    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. Our clinical advisors agree 
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, 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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.049


[[Page 25130]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.050

    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 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:

[[Page 25131]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.051

    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 note 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.
    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 are unable to ascertain from the claims data the 
resource use specifically attributable to CRRT during a hospital stay. 
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 reflects, 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 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.

[[Page 25132]]

    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] TP10MY21.052

    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 note 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 is shown in the following table:

[[Page 25133]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.053

    The claims data in this table also 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. 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.
    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 25134]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.054


[[Page 25135]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.055

    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 25136]]

reporting the use of CRRT. Our findings are shown in this table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.056


[[Page 25137]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.057

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 25138]]

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.
    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, 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 
believe 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, 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 believe 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 are not proposing to create new MS-DRGs for cases reporting the use 
of continuous renal replacement therapy.
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.
    We received a request 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].
    The following ICD-10-PCS procedure codes identify the intravenous 
administration of ANDEXXA[supreg].
[GRAPHIC] [TIFF OMITTED] TP10MY21.058

    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. Our clinical advisors agree 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

[[Page 25139]]

ANDEXXA[supreg] is reported for different clinical scenarios, 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
[GRAPHIC] [TIFF OMITTED] TP10MY21.059


[[Page 25140]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.060

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 25141]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.061


[[Page 25142]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.062

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

[[Page 25143]]

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.
    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
[GRAPHIC] [TIFF OMITTED] TP10MY21.063


[[Page 25144]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.064

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 note 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 note 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 25145]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.065

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]. 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

[[Page 25146]]

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 note 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 believe it is premature to 
consider a proposal for cases involving ANDEXXA[supreg] therapy for FY 
2022. 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. The claims data also reflect a wide variance with 
regard to the frequency and average costs for these cases reporting the 
use of ANDEXXA[supreg]. Moreover, 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. 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, 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 recognize 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. 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 note 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.
    We acknowledge 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, 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 note that we are 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 this proposed 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.
    Therefore for the reasons stated previously, for FY 2022 we are not 
proposing any MS-DRG changes for cases involving the intravenous 
administration of ANDEXXA[supreg].
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 becomes available to determine if further 
modifications to the severity level are warranted.
[GRAPHIC] [TIFF OMITTED] TP10MY21.066

    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-

[[Page 25147]]

DRGs 814, 815, and 816. We noted that the GROUPER logic for MS-DRGs 
814, 815, and 816 will include a principal diagnosis of T89.89XA with a 
secondary diagnosis of any CRS code as shown in this section of this 
proposed rule.
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 this proposed 
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] TP10MY21.067

    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] TP10MY21.068

    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 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 T89.89XA with a secondary diagnosis 
of any CRS code. However, with the finalization of new diagnosis code 
T80.82-, diagnosis code T89.89XA would no longer be reported and these 
cases would instead report new diagnosis code T80.82XA, effective with 
discharges on and after October 1, 2020. As shown in Table 6A 
associated with this proposed rule, we are proposing 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. 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 T89.89XA with a secondary 
diagnosis code of any CRS code would no longer be appropriate or 
necessary.
    Therefore, we are proposing to revise the structure of MS-DRGs 814, 
815, and 816 by removing the logic that includes a principal diagnosis 
of T89.89XA 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

[[Page 25148]]

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] TP10MY21.069

    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 response to this final policy, for this FY 2022 IPPS/LTCH PPS 
proposed rule, we received a request 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. 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 resources to place inferior vena cava filters 
across the patient population should be proposed.
    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, 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:

[[Page 25149]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.070

    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] TP10MY21.071

    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.
    In response to the request to exclude ICD-10-PCS code 06H03DZ from 
a list of qualifying procedures if CMS's analysis did not support 
creating a three-way split for MS-DRGs 829 and 830, 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's analysis did not 
support creating a three-way split for MS-DRGs 829 and 830, the change 
in designation from O.R. procedure to non-O.R. procedure is recent, 
only becoming effective October 1, 2020. Our clinical advisors continue 
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. Our clinical advisors state our FY 2021 final 
policy results in an O.R. designation of 06H03DZ that better reflects 
the associated technical complexity and hospital resource use of this 
procedure. 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 this proposed rule. We continue to 
develop our process and methodology, and will provide more detail in 
future rulemaking.
    In summary, based on the results of our analysis, for FY 2022, we 
are proposing to maintain the current structure of MS-DRGs 829 and 830.
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.

[[Page 25150]]

    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 are proposing 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 this proposed 
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 note 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 25151]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.072

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

[[Page 25152]]

approach, therefore the three procedure codes identified (0W310ZZ, 
0W313ZZ, and 0W314ZZ) warrant assignment to the ``craniotomy'' MS-DRGs.
    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''.
    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] TP10MY21.074

[GRAPHIC] [TIFF OMITTED] TP10MY21.075

    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.

[[Page 25153]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.076

[GRAPHIC] [TIFF OMITTED] TP10MY21.077

    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.
    Our clinical advisors stated these procedures 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 believe 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 are proposing 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.
    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 are proposing 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.

[[Page 25154]]

    As discussed in section II.D.3.a. of the preamble of this proposed 
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] TP10MY21.078

    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, 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 are proposing 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.
    As discussed in section II.D.4.b. of the preamble of this proposed 
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.

[[Page 25155]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.079

    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.
    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 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

[[Page 25156]]

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] TP10MY21.081

    In 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, 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 are proposing 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.
    As also discussed in section II.D.4.b. of the preamble of this 
proposed 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. 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 are proposing 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.
    As discussed in section II.D.11.c.24. of the preamble of this 
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

[[Page 25157]]

Diagnosis with MCC, with CC, without CC/MCC, respectively).
    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, our clinical advisors believe a non-extensive 
O.R. designation is suitable for this procedure.
    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, 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 are proposing 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.
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 proposed rule, we 
are 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,

[[Page 25158]]

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.
    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, we will provide more detail on this analysis and the 
methodology for conducting this review in future rulemaking.
    In this proposed 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 are proposing to change the designation of 
procedure codes from non-O.R. procedures to O.R. procedures, we also 
are proposing 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.
    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, we detail and respond to some 
of those requests. With regard to the remaining requests, our clinical 
advisors believe it is appropriate to consider these requests as part 
of our comprehensive review of the procedure codes as previously 
discussed.
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] TP10MY21.082

    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.
    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.

[[Page 25159]]

procedures in the ICD-10 MS-DRG Version 38.1 Definitions Manual.
[GRAPHIC] [TIFF OMITTED] TP10MY21.083

    We reviewed these procedures and our clinical advisors agree 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. These procedures do not typically require the resources of 
an operating room, and are not surgical in nature. Therefore, we are 
proposing 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. Under this proposal, these procedures would no longer 
impact MS-DRG assignment.

[[Page 25160]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.084

[GRAPHIC] [TIFF OMITTED] TP10MY21.085


[[Page 25161]]


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.
    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 agree 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.
    Upon further review and consideration, our clinical advisors agree 
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 are proposing 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).
(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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.086

    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. Our clinical 
advisors reviewed this issue and disagree 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 state 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 state 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 are proposing to maintain the current non-O.R. 
designation of ICD-10-PCS procedure codes 0N9R0ZZ, 0N9T0ZZ, and 
0N9V0ZZ.
(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

[[Page 25162]]

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. Our clinical advisors 
reviewed this issue and disagree 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 note 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 state that thoracoscopic drainage of the pleural 
cavities is performed for distinct indications in clinically different 
scenarios. Our clinical advisors state 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 note 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 are proposing to maintain the current non-O.R. 
designation of ICD-10-PCS procedure codes 0WC94ZZ and 0WCB4ZZ.
(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.
    We note 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.
    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 agree with the 
requestor that procedure codes 0BBN0ZX and 0BBP0ZX would typically 
require the resources of an operating room. Our clinical advisors also 
agree that procedure codes 0BBN0ZX and 0BBP0ZX would typically require 
the resources of an operating room. Therefore, we are proposing 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 (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).
(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] TP10MY21.087

    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

[[Page 25163]]

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 
agree 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 are 
proposing 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 are also proposing 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).
(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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.088

    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 proposed 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) and, for 
the reasons discussed, we are proposing to maintain the assignment in 
MS-DRGs 273 and 274 (Percutaneous and Other Intracardiac Procedures 
with and without MCC, respectively) in MDC 05.
    Our clinical advisors reviewed this related issue and believe 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. The ICD-10-CM diagnosis codes used to report 
atrial fibrillation are currently assigned to MDC 05 (Diseases and 
Disorders of the Circulatory System). Our clinical advisors believe 
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 state 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. When performed with an open approach 
or percutaneous endoscopic approach, these procedures share similar 
factors such as complexity, and resource

[[Page 25164]]

utilization with all other LAAC procedures. Therefore, we are proposing 
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.
(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] TP10MY21.089

    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. Our clinical advisors reviewed this issue and disagree 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 
state the percutaneous endoscopic drainage of joints can be performed 
using local or regional anesthesia, and general anesthesia is not 
always required. 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 are proposing to maintain the 
current non-O.R. designation of ICD-10-PCS procedure codes 0S9C4ZZ, 
0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 0R9J4ZZ, and 0R9K4ZZ.
(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, 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. Our clinical advisors 
reviewed this issue and disagree that procedure codes describing the 
arthroscopic irrigation of joints should be designated as O.R. 
procedures. Our clinical advisors 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. Instead, the arthroscopic irrigation 
of joints is generally performed with other definitive procedures such 
as debridement or synovectomy. We note 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 are proposing to maintain 
the current non-O.R. designation of ICD-10-PCS procedure codes 3E1U48X 
and 3E1U48Z.
(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.

[[Page 25165]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.090

    Our clinical advisors reviewed the procedures described by these 
four procedure codes and agree 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 are proposing 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 are also 
proposing 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 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).
(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] TP10MY21.091

    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. 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] TP10MY21.092


[[Page 25166]]


    Our clinical advisors reviewed the procedures described by these 
eight procedure codes and agree 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 are proposing 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).
(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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.093

    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 agree 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 are proposing 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).
(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.

[[Page 25167]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.094

    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. While we 
disagree that drainage procedures are comparable to extirpation 
procedures, we agree with the requestor that these 22 ICD-10-PCS 
procedure codes typically require the resources of an operating room. 
Our clinical advisors state 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 are proposing 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).
(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.

[[Page 25168]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.096

    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.
    Our clinical advisors reviewed this request and do 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 are proposing to maintain the 
current non-O.R. designation for procedure codes 0JPT0MZ, 0JPT02Z, 
0JPT0WZ, 0JWT0MZ, 0JWT0WZ, and 0JWT03Z for FY 2022.
(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.
    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. In reviewing this request, we also 
identified the following four related codes:
[GRAPHIC] [TIFF OMITTED] TP10MY21.097

    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. While we agree 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 do not agree that these procedures should 
be designated as O.R. procedures. Our clinical advisors state 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.
    With advancements in procedural techniques, feeding devices are 
most commonly placed using a percutaneous endoscopic approach. Our 
clinical advisors state feeding devices are usually not placed using an 
open surgical approach; this approach is

[[Page 25169]]

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 state 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 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.
    Therefore, we are proposing to maintain the current non-O.R. 
designation of ICD-10-PCS procedure code 0DHA0UZ. We are also proposing 
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. Under 
this proposal, this procedure would no longer impact MS-DRG assignment.
(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.
    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. In 
reviewing this request, we also identified the following four related 
codes:
[GRAPHIC] [TIFF OMITTED] TP10MY21.098

    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. Our clinical advisors reviewed this request and do not 
agree that unilaterally all laparoscopic procedures should be 
designated as O.R. procedures. 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 state 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. Our clinical advisors 
believe 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 are 
proposing to maintain the current non-O.R. designation of ICD-10-PCS 
procedure codes 0DH64UZ and 0DHA4UZ.
(16) Endoscopic Fragmentation and Extirpation of Matter of Urinary 
Tract
    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 25170]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.099

    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. 
Our clinical advisors reviewed this issue and disagree that procedures 
describing the endoscopic fragmentation of calculi within the kidney 
pelvis, ureter, bladder, and bladder neck are typically performed in 
the operating room. 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 are 
proposing 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] TP10MY21.100

    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. To review the 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 25171]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.101

    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. 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 state 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, 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 are proposing to maintain the current non-O.R. 
designation of ICD-10-PCS procedure codes 0TCB8ZZ and 0TCC8ZZ. We are 
also proposing 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. Under this 
proposal, these procedures would no longer impact MS-DRG assignment.
(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 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.
    Our clinical advisors reviewed this procedure and do 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 are proposing to maintain the current non-O.R. 
designation for procedure code 0TP98DZ for FY 2022.
(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.
    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 are 
proposing to maintain the current non-O.R. designation for procedure 
code 0TJ789ZZ for FY 2022.
(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.

[[Page 25172]]

The six procedure codes are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.102

    We note that under the ICD-10-PCS procedure classification, biopsy 
procedures are identified by the 7th digit qualifier value 
``diagnostic'' in the code description.
    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 are proposing to 
maintain the current non-O.R. designation for procedure codes 0TB08ZX, 
0TB18ZX, 0TB38ZX, 0TB48ZX, 0TB68ZX, and 0TB78ZX for FY 2022.
(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] TP10MY21.103

    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 are proposing to maintain 
the current non-O.R. designation for procedure codes 0T767DZ, 0T777DZ, 
and 0T787DZ for FY 2022.
(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] TP10MY21.104


[[Page 25173]]


    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 rom. Therefore, we 
are proposing to maintain the current non-O.R. designation for 
procedure codes 0T763DZ, 0T773DZ, and 0T783DZ for FY 2022.
(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.
    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 are proposing to 
maintain the current non-O.R. designation for procedure code 00T7D8DZ 
for FY 2022.
(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.
    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 are 
proposing to maintain the current non-O.R. designation for procedure 
code 0VQ50ZZ for FY 2022.
(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.
    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. 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. 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 are proposing 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. 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 this proposed rule for further 
discussion related to procedure code 0T9D0ZZ.
(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. Our clinical advisors reviewed this 
issue and disagree 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. 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

[[Page 25174]]

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. 
Our clinical advisors also disagree that procedures described as the 
transvaginal repair of the vagina are typically performed in the 
operating room under general anesthesia. Our clinical advisors state 
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 are proposing to maintain the current non-O.R. 
designation of ICD-10-PCS procedure code 0UQG7ZZ.
(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] TP10MY21.105

    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.
    We note that we have addressed requests related to these procedures 
in previous rulemaking (85 FR 58511 through 58517). Our clinical 
advisors reviewed this request and disagree 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 are proposing to maintain 
the current non-O.R. status for the ten procedure codes listed 
previously for FY 2022.
12. Proposed 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

[[Page 25175]]

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.
    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 note 
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 proposed rule for the discussion of the 
proposed changes to the ICD-10-CM and ICD-10-PCS coding systems for FY 
2022.
    For this FY 2022 IPPS/LTCH PPS proposed rule, we received several 
requests to change the severity level designations of specific ICD-10-
CM diagnosis codes. Our clinical advisors believe it is 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 stated 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.
c. Potential Change to Severity Level Designation for Unspecified 
Diagnosis Codes for FY 2022
    For this FY 2022 IPPS/LTCH PPS proposed rule, 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 are requesting public comments on a 
potential change to the severity level designations for ``unspecified'' 
ICD-10-CM diagnosis codes that we are considering adopting for FY 2022.

[[Page 25176]]

Specifically, we are 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 this proposed rule.
    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 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 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 believe more robust claims data 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 are soliciting 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 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 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 are 
requesting public comments on making this change to the severity level 
designation for these unspecified ICD-10-CM diagnosis codes for FY 
2022.
    The diagnosis codes for which we are soliciting comments on a 
change in severity level designation as described in this proposed rule 
are shown in Table 6P.2a (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). We note we are also 
making 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 mentioned 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 are 
displaying 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 this 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

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Version 38.1 and column E displays the potential changes to the 
severity level designation that we are 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.
    This table shows the Version 38.1 ICD-10 MS-DRG categorization of 
diagnosis codes by severity level.
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    We are requesting 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] TP10MY21.107

    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.
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    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 previously, we are requesting 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 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

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reflect each health care encounter and improve the reliability and 
validity of the coded data.
d. Proposed Additions and Deletions to the Diagnosis Code Severity 
Levels for FY 2022
    The following tables identify the proposed additions and deletions 
to the diagnosis code MCC severity levels list and the proposed 
additions 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--FY2022;
    Table 6I.2-- Proposed Deletions to the MCC List--FY2022; and
    Table 6J.1-- Proposed Additions to the CC List--FY2022.
e. Proposed 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.
    As discussed in section II.D.12.c. of the preamble of this proposed 
rule, we are requesting 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 refer the reader to Table 6P.3a associated with this 
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 is 
being 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. 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 a NonCC severity level for FY 2022, we would also 
finalize the removal of these codes from the CC Exclusions List for FY 
2022.
    We received three requests related to the CC Exclusions List logic, 
as we discuss in this section of this proposed rule.
    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.

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    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 reviewed diagnosis codes O99.891, O99.892 and O99.893 with 
respect to the principal diagnosis collection list 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

[[Page 25182]]

system or etiology, with the exception of the ``other specified'' 
subcategory (O99.8) as displayed in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.111

    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 ``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 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.
    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 are unable to fully evaluate these 
conditions for FY 2022, therefore, we will continue to analyze for 
future rulemaking.
    For the reasons discussed, 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 are proposing to remove diagnosis codes O99.891, O99.892, 
and O99.893 from the CC Exclusions List logic principal diagnosis 
collection lists. Specifically, we are proposing to remove those 
diagnosis codes from the following principal

[[Page 25183]]

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 also received a request 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 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 believe 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 disagree 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 are 
proposing to maintain the structure of principal diagnosis collection 
list number 0744 in the CC Exclusions List logic for FY 2022.
    Finally, we received a request 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] TP10MY21.112

    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.
    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 are proposing to revise the CC Exclusions Logic list for diagnosis 
codes I11.0 and I13.2 when reported as a principal diagnosis to ensure 
they are consistent in the CC and MCC diagnoses they exclude. In the 
following table we show the findings for each diagnosis code in 
category I50 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 
what our proposal is under the CC Exclusions List logic for FY 2022.
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    We are proposing 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 this FY 2022 IPPS/LTCH PPS proposed 
rule. Therefore, we have developed Table 6G.1.--Proposed Secondary 
Diagnosis Order Additions to the CC Exclusions List--FY 2022; Table 
6G.2.--Proposed Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2022; Table 6H.1.--Proposed Secondary Diagnosis 
Order Deletions to the CC Exclusions List--FY 2022; and Table 6H.2.--
Proposed Principal Diagnosis Order Deletions to the CC Exclusions 
List--FY 2022. 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 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. For Table 6H.1, each secondary diagnosis code 
proposed 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 proposed deletions to the CC Exclusions 
List are provided in an indented column immediately following the 
affected principal diagnosis. Tables 6G.1., 6G.2., 6H.1., and 6H.2. 
associated with this proposed rule are available via the internet on 
the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.

[[Page 25186]]

13. Proposed 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 and Table 6E.--Revised Diagnosis Code 
Titles for this proposed rule.
    These tables are not published in the Addendum to this 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 this proposed rule. As discussed in section II.D.16. of the 
preamble of this proposed 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.
    We are proposing 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. In addition, 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 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 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 proposed 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 6G.1.--Proposed Secondary Diagnosis Order Additions 
to the CC Exclusions List--FY 2022;
     Table 6G.2.--Proposed Principal Diagnosis Order Additions 
to the CC Exclusions List--FY 2022;
     Table 6H.1.--Proposed Secondary Diagnosis Order Deletions 
to the CC Exclusions List--FY 2022;
     Table 6H.2.--Proposed Principal Diagnosis Order Deletions 
to the CC Exclusions List--FY 2022;
     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.
14. Proposed 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.
    For this FY 2022 IPPS/LTCH PPS proposed rule, we address the MCE 
requests we received by the November 1, 2020 deadline. We also discuss 
the proposals we are making based on our internal review and analysis.
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 this proposed 
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 are proposing to add the following new 
ICD-10-CM diagnosis codes to the External Causes of Morbidity edit code 
list.
[GRAPHIC] [TIFF OMITTED] TP10MY21.115


[[Page 25187]]


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 this proposed 
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 are proposing 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] TP10MY21.116

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 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 this proposed 
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 are proposing 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] TP10MY21.117

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 this proposed 
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. In addition, 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 are proposing to add the following new and, if these 
instructional notes are finalized, existing ICD-10-CM diagnosis codes 
at subcategories M40.1 and M41.5, to the Unacceptable Principal 
Diagnosis edit code list.
BILLING CODE 4120-01-P

[[Page 25188]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.118

BILLING CODE 4120-01-C
    In addition, as discussed in section II.D.13. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are

[[Page 25189]]

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 are proposing to 
delete these codes from the Unacceptable Principal Diagnosis edit code 
list.
[GRAPHIC] [TIFF OMITTED] TP10MY21.119

e. Unspecified Codes
    As discussed in section II.D.12.c. of the preamble of this proposed 
rule, we are requesting public comments on a potential change to the 
severity level designations for ``unspecified'' ICD-10-CM diagnosis 
codes that we are considering adopting for FY 2022. In connection with 
that request, we are also requesting 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 refer the reader to 
table 6P.3a (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. This edit could signal to the 
provider that a more specific code is available to report. We believe 
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 are 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.
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. Proposed 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

[[Page 25190]]

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 proposed 
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.
    For this 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 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 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 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 this proposed rule, we are proposing to revise the 
surgical hierarchy for the MS-DRGs in MDC 05 for FY 2022. Specifically, 
we are proposing 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] TP10MY21.120

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: http://cms.hhs.gov/
Medicare/Coding/ICD9ProviderDiagnosticCodes/

[[Page 25191]]

codes.html. 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 mentioned 
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 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 these code proposals 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 proposed 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, and Table 6E.--Revised Diagnosis Code Titles for this 
proposed 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 rule, they are not subject to comment in the proposed 
rule. Because of the length of these tables, they are not published in 
the Addendum to the proposed rule. Rather, they are available via the 
internet as discussed in section VI. of the Addendum to the proposed 
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].
    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] TP10MY21.121

    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.
    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

[[Page 25192]]

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 (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 this 
proposed rule, we are soliciting 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.
    In addition, 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 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] TP10MY21.122


[[Page 25193]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.123

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 (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 this 
proposed rule, we are soliciting public comments on the most 
appropriate MDC, MS-DRG, and operating room status assignments for

[[Page 25194]]

these codes for FY 2022, as well as any other options for the GROUPER 
logic.
    We note 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 Public Law 
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.
    At 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 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 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 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 note, 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 believe that the advances in technology that have occurred since

[[Page 25195]]

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 code) 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 
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 note that 
historically, coders would hand-write any updates or notes directly 
into their code books. In addition, 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 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 note 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 updates 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 updates 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 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. 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. 
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.
    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 note 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.
    ICD-9-CM addendum and code title information is published on the 
CMS website at: http://www.cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/index.html?redirect=/icd9ProviderDiagnosticCodes/01overview.asp#TopofPage. 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.
    For FY 2021, there are currently 72,621 diagnosis codes and 78,136 
ICD-10-PCS procedure codes. As displayed in Table 6A.--New Diagnosis 
Codes and in Table 6B.--New Procedure Codes associated with this 
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 are 147 new diagnosis codes and 106 new 
procedure codes that have been finalized for FY 2022 at the time of the 
development of this proposed rule. 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.

[[Page 25196]]

    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. Proposed Changes for FY 2022
    For FY 2022 we are proposing not to add any MS-DRGs to the policy 
for replaced devices offered without cost or with a credit. We are 
proposing to continue to include the existing MS-DRGs currently subject 
to the policy as displayed in the following table.
BILLING CODE 4120-01-P

[[Page 25197]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.124


[[Page 25198]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.125

BILLING CODE 4120-01-C
    The final list of MS-DRGs subject to the IPPS policy for replaced 
devices offered without cost or with a credit will be included in the 
FY 2022 IPPS/LTCH PPS final rule and also will be issued to providers 
in the form of a Change Request (CR).

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

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

1. Data Sources for Developing the Relative Weights
    In accordance with our proposal as discussed in section I.F. of 
this proposed rule, for the purposes of establishing the FY 2022 MS-DRG 
relative weights, we are proposing 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

[[Page 25199]]

proposed rule for further discussion of our analysis of the best 
available data for purposes of the FY 2022 ratesetting and our related 
proposals.
    Consistent with our established policy, in developing the MS-DRG 
relative weights for FY 2022, we are proposing 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 bills. The FY 2019 MedPAR data used in this 
proposed rule include discharges occurring on October 1, 2018, through 
September 30, 2019, based on bills 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 proposed relative 
weights includes data for approximately 9,217,828 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 
proposed 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 proposed 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 proposed 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 are 
proposing to use the March 31, 2020 update of the FY 2018 HCRIS for 
calculating the proposed FY 2022 cost-based relative weights. 
Consistent with our historical practice, for this FY 2022 proposed 
rule, we are providing the version of the HCRIS from which we 
calculated these proposed 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 Proposed 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, we are also making 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.
2. Methodology for Calculation of the Relative Weights
a. General
    We calculated the proposed FY 2022 relative weights based on 19 
CCRs, as we did for FY 2021. The methodology we are proposing 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 proposed FY 2022 MS-DRG classifications discussed in sections 
II.B. and II.F. of the preamble of this proposed 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 
are proposing 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.

[[Page 25200]]

     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 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 are also proposing 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 proposed 
national average CCRs developed from the FY 2018 cost report data, 
consistent with our proposed FY 2022 ratesetting discussed in section 
II.A.4 of the Addendum of this proposed rule.
    The 19 cost centers that we used in the proposed 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 proposed 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 proposed 19 
national cost center CCRs. If we receive comments about the groupings 
in this supplemental data file, we may consider these comments as we 
finalize our policy.
    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

[[Page 25201]]

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 proposed 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.
    We are inviting public comments on our proposals related to 
recalibration of the proposed FY 2022 relative weights and the changes 
in relative weights from FY 2021.
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 proposed rule for discussion of the procedure codes for 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies that 
we are proposing 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 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 are proposing to use the same FY 2019 MedPAR claims data 
for FY 2022 ratesetting that we did for the FY 2021 final rule, we are 
also proposing 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 
proposed rule. Using the same methodology from the FY 2021 IPPS/LTCH 
PPS final rule, we are proposing 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:
     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.
     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.
     Calculate an adjustor by dividing the average cost 
calculated in step 1 by the average cost calculated in step 2.
     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 are 
also proposing 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 are 
proposing 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 this proposed rule, each 
case identified as a clinical trial case was adjusted by 17 percent. As 
we did for FY 2021, we are proposing 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 proposed rule, we are also 
soliciting

[[Page 25202]]

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 may consider finalizing for FY 2022 based on consideration of 
comments received. We note 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.
3. Development of Proposed National Average CCRs
    Consistent with our proposal to use the FY 2019 data for the FY 
2022 ratesetting, as discussed earlier in this section, we are 
proposing 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 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 proposed relative weight.
    The proposed FY 2022 cost-based relative weights were then 
normalized by an adjustment factor of 1.820783 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 proposed 19 national average CCRs for FY 2022 are as follows:
    [GRAPHIC] [TIFF OMITTED] TP10MY21.126
    
    [GRAPHIC] [TIFF OMITTED] TP10MY21.127
    

[[Page 25203]]


    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 are proposing to use that same case 
threshold in recalibrating the proposed 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 are proposing 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.128

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)

[[Page 25204]]

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 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 are 
presented in a data file that is available on the CMS website, along 
with the other data files associated with this 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 this proposed rule, we are proposing 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 proposed 
rule for further discussion of our analysis of the best available data 
for FY 2022 ratesetting and our related proposals. For the FY 2023 
proposed threshold values, consistent with our proposal, we are 
proposing 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 
proposed rule, we are also considering, 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. 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 are making available the threshold values calculated 
using the FY 2020 claims data at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. 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

[[Page 25205]]

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 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: Cinical 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

[[Page 25206]]

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 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

[[Page 25207]]

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 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-7-23-15.pdf.
    As we indicated in the FY 2009 IPPS final rule (73 FR 48554), we 
invite 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 this 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,

[[Page 25208]]

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.
    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 this 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 are not 
summarizing those written comments in this proposed rule that are 
unrelated to the substantial clinical improvement criterion. In section 
II.H.5. of the preamble of this proposed rule, we are summarizing 
comments regarding individual applications, or, if applicable, 
indicating 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. Proposed FY 2022 Status of Technologies Approved for FY 2021 New 
Technology Add-On Payments
    In this section of the proposed rule, we discuss the proposed FY 
2022 status of 23 technologies approved for FY 2021 new technology add-
on payments, 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 proposed 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. As of the time of the 
development of this proposed rule, CONTEPO has not yet received FDA 
marketing authorization.
a. Proposed Continuation of New Technology Add-On Payments for FY 2022 
for Technologies Still Considered To Be New
    In the table in this section of the proposed rule, we present 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 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).
    The table in this section lists the technologies for which we are 
proposing 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. This table also presents 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 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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b. Proposal To Extend 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 approval (that is, 
marketing authorization) 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 population has been frequent or infrequent.
    However, in light of the unique circumstances for FY 2022 
ratesetting, for which we are proposing 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 this 
proposed rule, 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 this proposed 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 this proposed 
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 question 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 this proposed 
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 this proposed rule, we 
believe for purposes of this 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 this proposed 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 on 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 are proposing to use FY 2019 data for the 
FY 2022 ratesetting for circumstances

[[Page 25212]]

where the FY 2020 data is significantly impacted by the COVID-19 PHE. 
Because we believe the FY 2020 MedPAR claims data is significantly 
impacted by the COVID-19 PHE, we are 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 refer the reader to section I.F. of the 
preamble of this proposed rule for a further discussion on our analysis 
of the best available data for 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. Because we are 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 believe it would be appropriate to 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. Accordingly, we are 
proposing to use our authority under section 1886(d)(5)(I) of the Act 
to provide for a one-year extension of new technology add-on payments 
for FY 2022 for those technologies listed in the table that follows. We 
note 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 this proposed 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 note that this table also presents 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 refer 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 are inviting 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 finally note, with regard to ContaCT which is a technology sold 
on a subscription basis, we continue 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.

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BILLING CODE 4120-01-C
5. FY 2022 Applications for New Technology Add-On Payments (Traditional 
Pathway)
a. Aidoc Briefcase for PE
    Aidoc Medical Ltd. (Aidoc) submitted an application 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 \7\ and 
it is estimated to be the third largest cause of cardiovascular death 
after coronary artery disease and stroke.8 9 10 11 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.12 13 14 
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.
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    \7\ 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.
    \8\ 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.
    \9\ 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.
    \10\ 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.
    \11\ 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.
    \12\ 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.
    \13\ 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.
    \14\ 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.
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    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. According to the applicant, there 
are currently no ICD-10-PCS procedure codes to adequately describe 
Briefcase for PE. The applicant submitted a request for approval of a 
unique ICD-10-PCS procedure code to identify use of the technology 
beginning FY 2022.
    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

[[Page 25218]]

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 have the following concerns regarding whether the technology 
meets the substantial similarity criteria and whether it should be 
considered new. We note 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 are 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 invite comment on whether Briefcase for PE represents a 
new mechanism of action. We note 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 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 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 invite public comments on whether Briefcase for PE meets the 
newness criterion.
    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 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] TP10MY21.136

    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.\15\ 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.\16\
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    \15\ 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).
    \16\ Ibid.
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    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

[[Page 25219]]

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.\17\ 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).
---------------------------------------------------------------------------

    \17\ 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 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, the applicant appears 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 question whether the 
cost per patient varies based on the utilization of the technology by 
the hospitals. We are 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 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 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 also invite 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.
    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.\18\ 
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 US and 1 outside US) 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).
---------------------------------------------------------------------------

    \18\ 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.\19\ 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.
---------------------------------------------------------------------------

    \19\ 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

[[Page 25220]]

the FDA pivotal study.20 21 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.
---------------------------------------------------------------------------

    \20\ 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).
    \21\ 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, 2020).\22\ 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.
---------------------------------------------------------------------------

    \22\ 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.\23\
---------------------------------------------------------------------------

    \23\ 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.\24\ 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.
---------------------------------------------------------------------------

    \24\ 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.\25\ 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

[[Page 25221]]

implementation of Briefcase for PE for flagging patients with PE 
resulted in significant reduction of 30- and 120-day all-cause 
mortality.
---------------------------------------------------------------------------

    \25\ 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 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 note 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 note 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 
note 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 invite 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 note 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 are 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 are inviting public comments on whether Briefcase for PE meets 
the substantial clinical improvement criterion.
    We received a written public comment from the applicant in response 
to the New Technology Town Hall meeting regarding the application of 
Briefcase for PE for new technology add-on payments.
    Comment: The applicant responded to questions received at the New 
Technology Town Hall Meeting. First the applicant was asked what the 
sensitivity and specificity of the standalone device is for identifying 
pulmonary embolism and how the sensitivity and specificity of the 
radiologist alone compare to the sensitivity and specificity of the 
radiologist when using the device. The applicant responded by 
reiterating the sensitivity and specificity data provided in the FDA 
pivotal study and restating that Briefcase for PE is a computer-aided 
triage and notification system that is not intended to aid in the 
diagnosis of PE but rather, Briefcase for PE identifies cases of 
suspected PE on CTPAs and, via triage and notification, prioritizes 
these cases for radiologist review.26 27 The applicant 
further restated that this triage and notification modifies the 
traditional radiology workflow in which images are reviewed on a FIFO 
basis to reduce the time-to-open-exam from over one hour to several 
minutes (standard of care vs. Briefcase for PE). The applicant restated 
that this reduction in time-to-open-exam has been demonstrated to 
improve patient outcomes, including hospital length of stay and post-
discharge mortality. The applicant further noted that, because 
Briefcase for PE is a triage and notification system, no patient harm 
results from false positives or false negatives that may occur. The 
applicant explained that with respect to false positives, these 
suspected cases of PE will be triaged and the radiologist will be 
notified, prompting earlier review and diagnosis of the CTPA image by 
the radiologist. The applicant explained that for cases of PE that are 
missed by Briefcase for PE (that is, false negatives), the radiologist 
will review these CTPA images on a FIFO basis the same as today's 
standard of care and that triage and notification do not occur in the 
standard of care.
---------------------------------------------------------------------------

    \26\ Aidoc Briefcase for PE--Pivotal Study 1--FDA 510(k)--
K190072. http://www.accessdata.fda.gov/cdrh_docs/pdf19/K190072.pdf.
    \27\ Weikert T, Winkel DJ, Bremerich J, et al. Automated 
detection of pulmonary embolism in CT pulmonary angiograms using an 
AI-powered algorithm. Eur Radiol. 2020;30(12):6545-6553. 
doi:10.1007/s00330-020-06998-0.
---------------------------------------------------------------------------

    Second, the applicant was asked if Briefcase for PE decreased time 
outside of clinical trial protocols and how the applicant can be 
certain reducing time-to-notification affects the time period between 
when the CTPA is completed and the study is interpreted. In response, 
the applicant again reiterated data from the FDA pivotal study in 
restating that implementation of Briefcase for PE saves on average 60.2 
minutes relative to the standard of care FIFO clinical workflow and 
that data maintained by Aidoc demonstrate that real-world performance 
of Briefcase for PE is consistent with the results achieved in the FDA 
study. The

[[Page 25222]]

applicant also submitted data summarized previously indicating mean 
time-to-open, as measured by calculating the time between when a 
notification first became available in the application and the time of 
open, was 2.13 minutes (median: 1.0/IQR: 2.0). The applicant restated 
that in addition to measuring the mean time-to-open, the open rate, or 
the percentage of notifications opened, was measured for this same 
population and the open rate was found to be 97 percent (min: 80 
percent, max: 100 percent), with over 90 percent of notifications found 
to be opened in under 5 minutes.\28\
---------------------------------------------------------------------------

    \28\ Avondo, J. Yalon R., Ashkenasi C. Radiologist Engagement 
Analysis Across US Facilities with Aidoc Briefcase for PE. Internal 
study performed by the applicant (unpublished).
---------------------------------------------------------------------------

    Also in response to this second question, the applicant reiterated 
data describing an independent analysis performed by Raskin, et al., 
examining the impact of Briefcase for PE implementation on 30- and 120-
day all-cause mortality for all patients age 18 years or older with a 
diagnosis of PE on CTPA and admitted to Sheba Medical Center in Tel 
Aviv, Israel. The applicant restated data described previously 
indicating that investigators found that the post- Briefcase cohort had 
significantly reduced 30- and 120-day all-cause mortality compared to 
the pre-Briefcase cohort--14.9 percent vs 11.0 percent and 26.1 percent 
vs 20.4 percent, respectively. The applicant stated these observed 
effects equate to a reduction ratio of 26.6 percent (p <0.05) and an 
odds-ratio of 1.425 (95 CI: 1.01-2.02) for 30-day all-cause mortality 
and a reduction ratio of 21.8 percent (p <0.05) and an odds-ratio of 
1.34 (95 percent CI: 1.05-1.81) for 120-day all-cause mortality.\29\
---------------------------------------------------------------------------

    \29\ 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).
---------------------------------------------------------------------------

    Response: We appreciate the applicant's comments. We will take 
these comments into consideration when deciding whether to approve new 
technology add-on payments for Briefcase for PE.
b. Amivantamab
    Johnson & Johnson Health Care Systems, Inc. submitted an 
application for new technology add-on payments for amivantamab for FY 
2022. Amivantamab is intended for the treatment of metastatic non-small 
cell lung cancer (NSCLC). The applicant stated amivantamab 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, 
amivantamab 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 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, amivantamab (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. 
The applicant stated they are seeking a Biologics License Application 
(BLA) for amivantamab for the treatment of patients with metastatic 
NSCLC with EGFR exon 20 insertion mutations whose disease has 
progressed on or after platinum-based chemotherapy and have not yet 
received FDA marketing authorization. Per the applicant, amivantamab is 
administered as an infusion on a 28 day cycle; weekly for the first 
cycle and then every 2 weeks, and continued until disease progression 
or unacceptable toxicity. The applicant stated there are currently no 
ICD-10-PCS procedure codes that uniquely identify the use of 
amivantamab. We note the applicant submitted a request for approval of 
a unique ICD-10-PCS procedure code to identify use of the technology 
beginning in FY 2022.
    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 amivantamab 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.

[[Page 25223]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.137

    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 amivantamab 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 is currently no FDA-approved therapy for this 
patient population, and the most commonly used therapies are associated 
with limited efficacy.
    In summary, the applicant asserted that amivantamab should be 
considered new and not substantially similar to an existing technology 
because the mechanism of action of amivantamab for treating NSCLC is 
unique and it treats a distinct patient population.
    We are inviting public comments on whether amivantamab is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    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] TP10MY21.138

    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 amivantamab in the absence of a unique ICD-10-PCS code.

[[Page 25224]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.139

    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.\30\ The applicant stated that, of those patients, 10-15 
percent are EGFR-mutations patients,31 32 and of those, at 
least 9 percent have atypical EGFR mutations like exon 20 ins.\33\ 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 amivantamab, which 
the applicant used for the cost analysis.
---------------------------------------------------------------------------

    \30\ ``What is Lung Cancer?'' American Cancer Society. 1 October 
2019: https://www.cancer.org/content/cancer/en/cancer/lung- cancer/
about/what-is.html.
    \31\ Wee, P., & Wang, Z. (2017). Epidermal growth factor 
receptor cell proliferation signaling pathways. Cancers, 9(5), 52.
    \32\ Pao, W., & Girard, N. (2011). New driver mutations in non-
small-cell lung cancer. The Lancet Oncology, 12(2), 175-180.
    \33\ 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 
amivantamab would be administered during an inpatient stay. The 
applicant stated that amivantamab will typically be administered in the 
outpatient setting, and that it assumed that amivantamab 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 amivantamab 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 amivantamab 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 
amivantamab 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 amivantamab 
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 amivantamab to map to a 
new or different MS-DRG for FY 2022.
[GRAPHIC] [TIFF OMITTED] TP10MY21.140

    The applicant assumed patients receiving amivantamab would receive 
one dose of the drug during their inpatient stay. Because amivantamab 
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 amivantamab, 
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 maintains the 
technology meets the cost criterion.
    Based on the information provided by the applicant, we have 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 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.

[[Page 25225]]

    In its analysis, the applicant appears to take a sample of a larger 
case population based on clinical data. It is unclear whether the 
applicant is taking a simple random sample or a targeted sample of 
cases. We note 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 would like to understand the process used by the 
applicant to identify this targeted sample. Under either approach, we 
would request information on how a sampling of cases from the greater 
population is more representative of potential amivantamab patients.
    We are inviting public comments on whether amivantamab meets the 
cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that amivantamab represents a substantial clinical 
improvement over existing technologies. The applicant asserted several 
claims of substantial clinical improvement for amivantamab: (1) 
Amivantamab 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.\34\ Per the applicant, the current standard of care for the 
initial treatment of exon 20 insertion metastatic NSCLC is platinum-
based chemotherapy; \35\ 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.\36\ 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.\37\ 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. According to the applicant, based on the 
Breakthrough Therapy designation for amivantamab, it is anticipated 
that amivantamab's first expected approval will be for the second-line 
treatment of exon 20 insertion metastatic NSCLC.
---------------------------------------------------------------------------

    \34\ 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.
    \35\ 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.
    \36\ 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.
    \37\ 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 amivantamab 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.\38\ Part 1 
was a dose escalation study used to establish the recommended Phase 2 
dosing regimen.\39\ Part 2 was a dose expansion study to assess safety 
and efficacy at the recommended Phase 2 dosing regimen.\40\ The primary 
efficacy endpoint was the overall response rate per Response Evaluation 
Criteria in Solid Tumors v1.1.\41\ Key secondary endpoints included 
clinical benefit rate (CBR), duration of response (DOR), progression-
free survival (PFS), and overall survival (OS).\42\
---------------------------------------------------------------------------

    \38\ https://clinicaltrials.gov/ct2/show/study/NCT02609776 
https://clinicaltrials.gov/ct2/show/study/NCT02609776
    \39\ 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.
    \40\ Ibid.
    \41\ Ibid.
    \42\ 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.\43\ 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.\44\ The safety 
population

[[Page 25226]]

(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.\45\
---------------------------------------------------------------------------

    \43\ Ibid.
    \44\ Ibid.
    \45\ Ibid.
---------------------------------------------------------------------------

    In the efficacy population, the median age was 62.\46\ In addition, 
59 percent of the patients were female, 49 percent of the patients were 
Asian, and 47 percent had a history of smoking.\47\ Median time from 
initial diagnosis was 17 months with a range of 1-130 months.\48\ 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.\49\
---------------------------------------------------------------------------

    \46\ Ibid.
    \47\ Ibid.
    \48\ Ibid.
    \49\ Ibid.
---------------------------------------------------------------------------

    In the safety population, 98 percent of patients experienced a 
treatment-related adverse event.\50\ 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.\51\ 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.\52\
---------------------------------------------------------------------------

    \50\ Ibid.
    \51\ Ibid.
    \52\ 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.\53\ 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.\54\ 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.\55\ 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.\56\ 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.
---------------------------------------------------------------------------

    \53\ 2020 ASCO Annual Meeting: Park, K, et al. J Clin Oncol 
38:2020 (suppl; abstr 9512).
    \54\ 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.
    \55\ Ibid.
    \56\ 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).\57\ 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.\58\ 
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).\59\ 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.\60\ 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).\61\
---------------------------------------------------------------------------

    \57\ 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.
    \58\ Ibid.
    \59\ Ibid.
    \60\ Ibid.
    \61\ 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.\62\ 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.\63\ 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.
---------------------------------------------------------------------------

    \62\ 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.
    \63\ 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] TP10MY21.141


[[Page 25227]]


    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.\64\
---------------------------------------------------------------------------

    \64\ 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.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether the technology meets the 
substantial clinical improvement criterion. Currently, results provided 
by the applicant are based on an ongoing Phase 1 trial. We are 
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 note that the only study cited by the 
application to establish substantial clinical improvement is a single-
armed study assessing the safety and efficacy of amivantamab in the 
target population. As noted by the applicant, no formal comparisons to 
other therapies have been made. Without the ability to control for 
factors such as study design, patient characteristics, etc., we may be 
unable to determine whether any differences seen are the result of 
amivantamab's potentially superior efficacy or confounding variables. 
We also note that the single-arm study design results in an inability 
to distinguish between the effect of amivantamab treatment, a placebo 
effect, and the effect of natural course of the disease.
    We are inviting public comments on whether amivantamab meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
amivantamab.
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.\65\ DLBCL is characterized 
by spreading of B-cells through the body that have either arrived de 
novo or by the transformation from indolent lymphoma.
---------------------------------------------------------------------------

    \65\ 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).\66\ These regimens result in long-lasting remission 
in more than 50% of patients.\67\ 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.\68\ 
Patients with relapses of aggressive B-cell lymphomas are believed to 
have a poor 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.69 70 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.\71\ 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.
---------------------------------------------------------------------------

    \66\ 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).
    \67\ Ibid
    \68\ Ibid
    \69\ 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).);
    \70\ 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).
    \71\ 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).\72\
---------------------------------------------------------------------------

    \72\ 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.\73\
---------------------------------------------------------------------------

    \73\ 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.\74\
---------------------------------------------------------------------------

    \74\ 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.

[[Page 25228]]

    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.\75\
---------------------------------------------------------------------------

    \75\ 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 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 cetuximba 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.\76\ 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.\77\ 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].
---------------------------------------------------------------------------

    \76\ 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).
    \77\ 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-

[[Page 25229]]

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 are concerned whether a differing production 
and/or dosage represents a different mechanism of action as compared to 
previously FDA-approved CAR T-cell therapies. We are 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 express 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 note 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.\78\ We note 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 is unclear whether Breyanzi[supreg] would in fact treat a 
patient population different from other CAR T-cell therapies that treat 
patients with DLBCL.
---------------------------------------------------------------------------

    \78\ Lisocabtagene maraleucel Biologics License Application 
(BLA).
---------------------------------------------------------------------------

    We are inviting public comments on whether Breyanzi[supreg] is 
substantially similar to other technologies and whether 
Breyanzi[supreg] meets the newness criterion.
    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
[GRAPHIC] [TIFF OMITTED] TP10MY21.142


[[Page 25230]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.143


[[Page 25231]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.144

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 and 
KYMRIAH, 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.
    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 are 
uncertain how representative this data is for use in the applicant's 
cost analyses given this potential for variability.
    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 welcome comment on this issue.

[[Page 25232]]

    We invite public comment on whether 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 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 
lisocabtagene maraleucel 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.\79\ 
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.
---------------------------------------------------------------------------

    \79\ 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.\80\ 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.81 82 83 84 85 86 87 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

[[Page 25233]]

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.88 89
---------------------------------------------------------------------------

    \80\ National Comprehensive CancerNetwork Treatment of Cancer: 
Guidelines, 2019. NCCN, 2019.
    \81\ 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).
    \82\ 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).
    \83\ 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).
    \84\ 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).
    \85\ 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).
    \86\ 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).
    \87\ 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).
    \88\ YESCARTA[supreg] United States Prescribing Information USPI 
(2019).
    \89\ KYMRIAH[supreg] United States Prescribing Information USPI 
(2018).
---------------------------------------------------------------------------

    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 as 
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).90 91
---------------------------------------------------------------------------

    \90\ YESCARTA[supreg] USPI (2019).
    \91\ KYMRIAH[supreg] USPI (2018).
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application, we are 
concerned that there are 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 
are 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 does provide a 
comparison of the ORR, CR, PR and DOR across all three CAR T-cell 
therapies. While we note 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 note 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 are concerned as to whether these 
differences translate to clinically meaningful differences or 
improvements. Breyanzi[supreg] appears to demonstrate similar patient 
outcomes to that of YESCARTA[supreg] and we question 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, it is unclear whether this suggests that 
Breyanzi[supreg] is a treatment option for patients who cannot be 
treated with these existing CAR T-cell therapies, given that the FDA 
label for YESCARTA[supreg] and KYMRIAH[supreg] appears to not 
specifically exclude these patient populations. Finally, we are 
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 express concern regarding the safety and efficacy 
of this feature given its lack of testing.
    We are inviting public comments on whether Breyanzi[supreg] meets 
the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
Breyanzi[supreg] or at the New Technology Town Hall meeting.
d. Ciltacabtagene Autoleucel
    Janssen Biotech, Inc., submitted an application for new technology 
add-on payments for ciltacabtagene autoleucel for FY 2022. 
Ciltacabtagene autoleucel is an autologous chimeric-antigen receptor 
(CAR) T-cell therapy directed against B cell maturation antigen (BCMA) 
for the treatment of patients with multiple myeloma.
    Ciltacabtagene autoleucel refers to both JNJ-4528, an 
investigational BCMA-directed CAR T-cell therapy for previously treated 
patients with multiple myeloma, and LCAR-B38M, the investigational 
product (ciltacabtagene autoleucel) being studied in China. Both JNJ-
4528 and LACAR-B38M are representative of the same CAR T-cell therapy, 
ciltacabtagene autoleucel. Ciltacabtagene autoleucel has not yet 
received FDA approval.
    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 the 
clinical presentations mentioned previously and from other plasma cell 
dyscrasias for the purposes of prognosis and treatment.\92\ 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 U.S. 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 \93\

[[Page 25234]]

and approximately 25% of patients have a median survival of 2 years or 
less.\94\
---------------------------------------------------------------------------

    \92\ 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-
anddiagnosis?search=multiple%20myeloma&source=search_result&selectedT
itle=1~150& usage_type=default&display_rank=1.
    \93\ Cowan AJ, Allen C, Barac A, Basaleem H, Bensenor I, Curado 
MP, Foreman K, Gupta R, Harvey J, Hosgood HD, Jakovljevic M, Khader 
Y, Linn S, Lad D, Mantovani L, Nong VM, Mokdad A, Naghavi M, Postma 
M, Roshandel G, Shackelford K, Sisay M, Nguyen CT, Tran TT, Xuan BT, 
Ukwaja KN, Vollset SE, Weiderpass E, Libby EN, Fitzmaurice C. Global 
Burden of Multiple Myeloma: A Systematic Analysis for the Global 
Burden of Disease Study 2016. JAMA Oncol. 2018 Sep 1;4(9):1221-1227.
    \94\ Biran N, Jagannath S, Chari A. Risk stratification in 
multiple myeloma, part 1: characterization of high-risk disease. 
Clin Adv Hematol Oncol. 2013 Aug;11(8):489-503.
---------------------------------------------------------------------------

    According to the applicant, introduction of new treatment options 
in the last 2 decades has extended the median survival of multiple 
myeloma patients. The applicant asserted that the introduction of 
proteasome inhibitors (PI) (e.g., bortezomib, carfilzomib, and 
ixazomib), histone deacetylase inhibitors (e.g., panobinostat, 
vorinostat), immunomodulatory agents (IMiD) (e.g., thalidomide, 
lenalidomide, and pomalidomide), monoclonal antibodies (daratumumab and 
elotuzumab), and stem cell transplantation, have allowed numerous 
therapeutic options for patients with multiple myeloma (Rajkumar 2020). 
According to the applicant, the National Comprehensive Cancer Network 
(NCCN) recommended treatment regimen for first-line therapy of multiple 
myeloma is Bortezomib (a proteosome inhibitor (PI)), lenalidomide (an 
immunomodulatory agent (IMiD)) and dexamethasone.\95\ The strategy of 
triplet therapies for patients with newly diagnosed multiple myeloma, 
followed by high-dose chemotherapy and autologous stem-cell 
transplantation for eligible patients, and subsequently consolidation 
and maintenance therapy, is the current treatment roadmap for 
patients.\96\ However, despite these treatments, according to the 
applicant, most patients will relapse after first-line treatment and 
require further treatment \97\ with only 50% survival of relapsed 
patients after 5 years.98 99 As multiple myeloma progresses, 
each subsequent line of treatment is associated with shorter 
progression free survival (PFS) and decreased rate, depth, and 
durability of response and worsening of quality of life.\100\ In 
addition, cumulative and long-term toxicities are often associated with 
long-term therapy (Ludwig, 2018). Thus, according to the applicant, 
there remains an ongoing need for additional therapeutic approaches 
when the disease is resistant to available therapy.
---------------------------------------------------------------------------

    \95\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021-
September 9, 2020.
    \96\ Branagan A, Lei M, Lou U, Raje N. Current Treatment 
Strategies for Multiple Myeloma. JCO Oncol Pract. 2020 Jan;16(1):5-
14.
    \97\ Sonneveld P, Broij lA. Treatment of relapsed and refractory 
multiple myeloma. Haematologica. 2016;101(4):396-406.
    \98\ SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
    \99\ GLOBOCAN database 2018; https://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf.
    \100\ Yong K, Delforge M, Driessen C, Fink L, Flinois A, 
Gonzalez-McQuire S, Safaei R, Karlin L, Mateos MV, Raab MS, Schoen 
P, Cavo M. Multiple myeloma: patient outcomes in real-world 
practice. Br J Haematol. 2016 Oct;175(2):252-264.
---------------------------------------------------------------------------

    The applicant asserts that relapsed and refractory multiple myeloma 
(RRMM) constitutes a specific unmet medical need. According to the 
applicant, patients with r/r disease are defined as those who, having 
achieved a minor response or better, relapse and then progress while on 
therapy, or experience progression within 60 days of their last 
therapy.\101\ The introduction of a new class of agents, CD38-targeting 
monoclonal antibodies (CD38 MoABs), daratumumab and isatuximab, have 
improved options in r/r patients.\102\ The applicant asserts that given 
these advances, guideline recommendations following first-line therapy 
are varied, with treatment options including combinations of novel 
agents with existing standard of care regimens, and triplet and 
quadruplet regimens, creating a complex treatment landscape.\103\ 
According to the applicant, while triplet regimens should be used as 
the standard therapy for patients with multiple myeloma, elderly or 
frail patients may be treated with double regimens.104 95 
The applicant further states that for patients with RRMM who have 
received at least 3 prior lines of therapy including a PI, an IMiD and 
an anti-CD38, there does not exist a standard or consensus for 
treatment at this time, and often, supportive care/palliative care is 
the only option.\105\
---------------------------------------------------------------------------

    \101\ Castelli R, Orofino N, Losurdo A, Gualtierotti R, Cugno M. 
Choosing treatment options for patients with relapsed/refractory 
multiple myeloma. Expert Rev Anticancer Ther. 2014 Feb;14(2):199-
215.
    \102\ Van de Donk NWCJ, Richardson PG, Malavasi F. CD38 
antibodies in multiple myeloma: back to the future. Blood. 2018 Jan 
4;131(1):13-29.
    \103\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021--
September 9, 2020.
    \104\ Ibid.
    \105\ Maples KT, Joseph NS, Harvey RD. Current developments in 
the combination therapy of relapsed/refractory multiple myeloma. 
Expert Rev Anticancer Ther. 2020 Sep 24.
---------------------------------------------------------------------------

    According to the applicant, multiple myeloma remains incurable and 
most patients eventually relapse, even with the advent of new 
treatments.\106\ The applicant further states that novel, innovative 
therapies are needed to improve long-term survival and outcomes. The 
applicant asserts that CAR T-cell-based therapies offer potential 
advantages over current therapeutic strategies. According to the 
applicant, while other therapies require long-term repetitive 
administration generally until progression of disease, CAR T-cell 
therapy is a single infusion treatment due to live T-cell expansion in 
the patient and long-term disease response. The applicant asserts that 
ciltacabtagene autoleucel is an autologous CAR T-cell therapy directed 
against B cell maturation antigen (BCMA) for the treatment of patients 
with multiple myeloma. The applicant states that BCMA, a protein that 
is highly expressed on myeloma cells \107\ and is a member of the tumor 
necrosis factor (TNF) receptor family, plays a central role in 
regulating B-cell maturation and differentiation into plasma 
cells.\108\ BCMA is selectively expressed on a subset of B cells 
(plasma cell neoplasms including myeloma cells) and is more stably 
expressed specifically on the B cell lineage, compared with key plasma 
cell marker CD138 which is also expressed on normal fibroblasts and 
epithelial cells.109 110 111 These expression 
characteristics, per the applicant, make BCMA an ideal therapeutic 
target for the treatment of multiple myeloma.112 113 
Ciltacabtagene autoleucel, according to the applicant, is a unique, 
structurally differentiated BCMA-targeting chimeric antigen receptor 
with two distinct BCMA-binding domains that can identify and eliminate 
myeloma cells.
---------------------------------------------------------------------------

    \106\ Rajkumar SV, Kumar S. Multiple myeloma current treatment 
algorithms. Blood Cancer J. 2020 Sep 28;10(9):94.
    \107\ Cho SF, Anderson KC, Tai YT. Targeting B Cell Maturation 
Antigen (BCMA) in Multiple Myeloma: Potential Uses of BCMA-Based 
Immunotherapy. Front Immunol. 2018 Aug 10;9:1821.
    \108\ Ibid.
    \109\ Ibid.
    \110\ Tai YT, Anderson KC. Targeting B-cell maturation antigen 
in multiple myeloma. Immunotherapy. 2015;7(11):1187-99.
    \111\ Palaiologou M, Delladetsima I, Tiniakos D. CD138 
(syndecan-1) expression in health and disease. Histol Histopathol. 
2014 Feb;29(2):177-89.
    \112\ Ibid.
    \113\ Frigyesi I, Adolfsson J, Ali M, Christophersen MK, 
Johnsson E, Turesson I, Gullberg U, Hansson M, Nilsson B. Robust 
isolation of malignant plasma cells in multiple myeloma. Blood. 2014 
Feb 27;123(9):1336-40.
---------------------------------------------------------------------------

    The applicant asserts that CAR T-cell technology is a form of 
immunotherapy and is a ``living drug'' that utilizes specially altered 
T cells, part of the immune system, to fight cancer. A

[[Page 25235]]

sample of the patient's T cells are collected from the blood, then 
modified in a laboratory setting to express a chimeric antigen receptor 
(CAR).\114\ Chimeric antigen receptors are specifically designed 
receptor proteins that are made up of three distinct features: (1) A 
target recognition domain (typically derived from a single domain of an 
antibody) that sits on the cell's exterior, (2) a co-stimulatory domain 
on the cell's interior that boosts activation, enhances survival and 
expansion of the modified cells, and (3) an interior stimulatory domain 
that supports activation and target killing.\115\ The binding domain 
expressed on the surface of T cells gives them the new ability to 
target a specific protein. When the target is recognized, the 
intracellular portions of the receptor send signals within the T cells 
to destroy the target cells. These engineered CAR T-cells are reinfused 
back into the same patient which enables these specialized T cells to 
latch onto the target antigen and abolish the tumor cells.
---------------------------------------------------------------------------

    \114\ June CH, Sadelain M. Chimeric Antigen Receptor Therapy. N 
Engl J Med. 2018 Jul 5;379(1):64-73.
    \115\ Sadelain M. Chimeric antigen receptors: driving immunology 
towards synthetic biology. Curr Opin Immunol. 2016 Aug;41:68-76.
---------------------------------------------------------------------------

    According to the applicant, ciltacabtagene autoleucel is a CAR T-
cell immunotherapy designed to recognize myeloma cells and target their 
destruction. Ciltacabtagene autoleucel's CAR T-cell technology consists 
of harvesting the patient's own T cells, programming them to express a 
chimeric antigen receptor that identifies BCMA, a protein highly 
expressed on the surface of malignant multiple myeloma B-lineage cells, 
and reinfusing these modified cells back into the patient where they 
bind to and eliminate myeloma tumor cells. The applicant asserts that, 
unlike the chimeric antigen receptor design of currently approved CAR 
T-cell immunotherapies, which are composed of a single-domain antibody 
(sdAbs), ciltacabtagene autoleucel is composed of two antibody binding 
domains that allow for high recognition of human BCMA (CD269) and 
elimination of BCMA expressing myeloma cells. The two distinct BCMA-
binding domains, according to the applicant, confer avidity and 
distinguish ciltacabtagene autoleucel from other BCMA-targeting 
products. The BCMA binding domains are linked to the receptor's 
interior costimulatory (4-1BB) and signaling (CD3[zeta]) domains 
through a transmembrane linker (CD8a). These intracellular domains are 
critical components for T cell growth and anti-tumor activity \116\ in 
the body once CAR T-cells are bound to a BCMA target on multiple 
myeloma cells.
---------------------------------------------------------------------------

    \116\ Maher J, Brentjens RJ, Gunset G, Rivi[egrave]re I, 
Sadelain M. Human T-lymphocyte cytotoxicity and proliferation 
directed by a single chimeric TCRzeta/CD28 receptor.
---------------------------------------------------------------------------

    With respect to the newness criterion, according to the applicant, 
ciltacabtagene autoleucel was granted Breakthrough Therapy designation 
in December 2019 for the treatment of patients with RRMM who have 
previously received a PI, an IMiD, and an anti-CD38 antibody. In 
December 2020, the applicant submitted a Biologic License Application 
(BLA) with the FDA but at the time of the development of this proposed 
rule, it has not yet received FDA approval. The applicant stated that 
procedures involving the administration of ciltacabtagene autoleucel 
can be reported using the following ICD-10-PCS procedure codes: XW033C3 
(Introduction of engineered autologous chimeric antigen receptor t-cell 
immunotherapy into peripheral vein, percutaneous approach, new 
technology group 3); and XW043C3 (Introduction of engineered autologous 
chimeric antigen receptor t-cell immunotherapy into central vein, 
percutaneous approach, new technology group 3). The applicant noted 
that there are currently no ICD-10-PCS codes that uniquely identify 
procedures involving the use of ciltacabtagene autoleucel. The 
applicant submitted a request for unique ICD-10-PCS codes to describe 
the administration of ciltacabtagene autoleucel beginning in FY 2022. 
The applicant also noted that they will submit a request for a 
Healthcare Common Procedure Coding System (HCPCS) code specific to the 
administration of ciltacabtagene autoleucel once the product is 
eligible for such a code.
    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 asserts that ciltacabtagene 
autoleucel has a unique mechanism of action because it has two distinct 
binding domains that confer avidity to the BCMA antigen, a 4-1BB 
costimulatory domain and a CD3z signaling domain, whereas other CAR T-
cell products have only one target binding domain. However, we note 
that idecabtagnene vicleucel, another CAR T-cell therapy for which an 
application for new technology add-on payments was submitted for FY 
2022, as discussed later in this section, appears to have a mechanism 
of action that is similar to that of ciltabatagene: 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 idecabtagene vicleucel CAR construct 
includes an anti-BCMA scFv-targeting domain for antigen specificity, a 
transmembrane domain, a CD3-zeta T cell activation domain, and a 4-1BB 
costimulatory domain. Antigen-specific activation of idecabtagene 
vicleucel results in CAR-positive T cell proliferation, cytokine 
secretion, and subsequent cytolytic killing of BCMA-expressing cells.
    The applicant also asserts that its mechanism of action differs 
from Blenrep's mechanism of action. Blenrep is a BCMA-targeting agent 
indicated in the treatment of RRMM. According to the applicant, Blenrep 
belongs to the class of antibody-drug conjugates, which are therapies 
that are essentially composed of a monoclonal antibody linked to a 
toxic drug. Once the antibody portion of Blenrep recognizes BCMA on 
multiple myeloma cells, the toxin is released into cells, resulting in 
cell death. Therefore, according to the applicant, ciltacbtagene 
autoleucel's mechanism of action differs from Blenrep's. Additionally, 
the applicant states that there is currently no commercially available 
CAR T-cell product that binds to the BCMA antigen. Lastly, the 
applicant provided a list of other currently available treatments for 
multiple myeloma and a description of their mechanisms of action (Table 
1).

[[Page 25236]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.145

    With regard to whether a product is assigned to the same DRG when 
compared to an existing technology, the applicant expects that cases 
involving the administration of ciltacabtagene autoleucel will be 
assigned to the same MS-DRG, MS-DRG 018 (Chimeric Antigen Receptor 
(CAR) T-cell Immunotherapy), as other CAR T-cell therapies.
---------------------------------------------------------------------------

    \117\ Cook G, et al. Crit Rev Oncol Hematol. 2018;121:74-89.
    \118\ Nejadmoghaddam MR, et al. Avicennna J Med Biotechnol. 
2019;11(1):3-23.
    \119\ Pufall MA. Adv Exp Med Biol. 2015;872:315-33.
    \120\ Siddik ZH. The Cancer Handbook. New York: John Wiley & 
Sons, Ltd; 2002.
    \121\ Podar K, et al. Expert Opin Pharmacother. 2020 
Mar;21(4):399-408.
---------------------------------------------------------------------------

    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 asserts that ciltacabtagene autoleucel is indicated for a 
broader population than other available therapies, specifically 
multiple myeloma patients having received three prior therapies.
    In summary, the applicant asserts that ciltacabtagene autoleucel 
meets the newness criterion and is not substantially similar to other 
available therapies because it has a unique mechanism of action with 
two distinct binding domains that confer avidity to the BCMA antigen, 
and because it treats a different patient population, RRMM patients who 
received three prior therapies. However, we note that ciltacabtagene 
autoleucel may have a similar mechanism of action to that of 
idecabtagene vicleucel, for which we received an application for new 
technology add-on payments for FY 2022 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. Per the new 
technology add-on payment application for idecabtagene vicleucel, the 
technology's mechanism of action is described as targeting B-cell 
maturation antigen (BCMA), which is expressed on the surface of normal 
and malignant plasma cells. The chimeric antigen receptor (CAR) 
construct includes an anti-BCMA scFv-targeting domain for antigen 
specificity, a transmembrane domain, a CD3-zeta T cell activation 
domain, and a 4-1BB costimulatory domain. Antigen-specific activation 
of idecabtagene vicleucel results in CAR-positive T cell proliferation, 
cytokine secretion, and subsequent cytolytic killing of BCMA-expressing 
cells. Because of the potential similarity with the BCMA antigen and 
other actions, we believe that the mechanism of action for 
ciltacabtagene autoleucel may be the same or similar to that of 
idecabtagene vicleucel.
    We believe that ciltacabtagene autoleucel may not treat the same or 
similar patient population as currently existing treatments. However, 
we believe that ciltacabtagene autoleucel and idecabtagene vicleucel 
may treat the same or similar disease (RRMM) in the same or similar 
patient population (patients who have previously received a proteasome 
inhibitor (PI), and immunomodulatory agent (IMiD) and an anti-CD38 
antibody). Accordingly, as it appears that ciltacabtagene autoleucel 
and idecabtagene vicleucel are purposed to achieve the same therapeutic 
outcome using the same or similar mechanism of action and would be 
assigned to the same MS-DRG, we believe that these technologies may be 
substantially similar to each other such that they should be considered 
as a single application for purposes of new technology add-on payments. 
We are 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 
idecabtagene vicleucel and ciltacabtagne autoleucel are substantially 
similar to each other and therefore should be considered as a single 
application for purposes of new technology add-on payments.
    We are inviting public comment on whether ciltacabtagene autoleucel 
meets the newness criterion, including whether ciltacabtagene 
autoleucel is substantially similar to idecabtagene vicleucel and 
whether these technologies should be evaluated as a single technology 
for purposes of new technology add-on payments.

[[Page 25237]]

    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 Ciltacabtagene autoleucel. 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] TP10MY21.146

    The applicant chose to limit its analysis to MS-DRG 016 (Autologous 
Bone Marrow Transplant W CC/MCC or T-Cell Immunotherapy) because 
patients receiving autologous bone marrow transplant (BMT) are 
generally patients with relapsed or refractory multiple myeloma and are 
most similar to patients who would be eligible to receive CAR T-cell 
therapy. The claim search conducted by the applicant resulted in 1,215 
claims mapped to MS-DRG 016 using the FY 2019 MedPAR. The applicant 
determined an average unstandardized case weighted charge per case of 
$1,237,393. The applicant used the New Technology Threshold for FY 2022 
from the FY 2021 IPPS/LTCH PPS final rule for MS-DRG 018. 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 ciltacabtagene autoleucel. 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 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 
and the potential for hospitals' charging practices to differ for these 
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 and KYMRIAH, the CAR T-
cell products used in those claims, to arrive at a CCR of 0.295. The 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $1,646,522, which it stated exceeded 
the average case-weighted threshold amount of $1,251,126. 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 are 
uncertain how representative this data is for use in the applicant's 
cost analyses given this potential for variability.
    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 invite public comment on whether ciltacabtagene autoleucel meets 
the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that it believes that ciltacabtagene autoleucel 
represents a substantial clinical improvement over existing 
technologies because it: (1) Offers a treatment for a patient 
population with limited options and continued disease progression, 
despite having been treated with multiple prior therapies; and (2) 
provides a significantly improved clinical outcome relative to other 
therapies, either approved or still under FDA review, used in the 
relapsed and refractory multiple myeloma setting. With regard to the 
applicant's assertion that ciltacabtagene autoleucel offers a treatment 
for a patient population with limited options and continued disease 
progression, despite having been treated with multiple prior therapies, 
the applicant cited results from the CARTITUDE-1 STUDY, a Phase 1b/2, 
open-label, multicenter, multi-national (including US) study to 
evaluate the safety and efficacy of ciltacabtagene autoleucel in adult 
patients who have RRMM who have previously received a PI, an IMiD, and 
an anti-CD38 antibody. The applicant asserts that ciltacabtagene 
autoleucel was granted Breakthrough Therapy designation for patients 
who have RRMM who have previously received a PI, an IMiD, and an anti-
CD38 antibody, based on data from the Phase1b/2 CARTITUDE-1 study. One 
hundred thirteen patients were enrolled in the study. Sixteen patients 
discontinued the study, including 9 patients who died due to 
progressive disease. Ninety-seven patients received ciltacabtagene 
autoleucel. The Phase 1b portion of the study included 29 of the 97 
patients.
    Two patients died during the study: one due to CRS and one due to 
acute myeloid leukemia (not treatment-related). Twenty-four of the 
remaining patients were ongoing in the Phase 1b dose confirmation 
period, with an additional 59 patients ongoing in the Phase 2 portion. 
The primary objective of the Phase 1b portion of the trial was to 
confirm the safety of the selected dose based on the data from the 
ongoing Phase 1 trial in China (Legend-2), as discussed later in this 
section. The primary objective of the Phase 2 portion of the trial is 
to evaluate the efficacy of ciltacabtagene autoleucel.
    The applicant asserts that at median follow-up of 12.4 months, 
ciltacabtagene autoleucel led to a 97% overall response rate (ORR) in 
all 97 study patients who

[[Page 25238]]

received ciltacabtagene autoleucel.\122\ The applicant asserts that 
this unprecedented overall response rate of (97%), represents early, 
deep, and durable responses in all patients, minimal residual disease 
negativity (meaning minimal residual cancer cells after treatment to 
the -nth degree) in the majority of patients who achieved a complete 
response (CR) and a very manageable toxicity profile. The applicant 
provided a comparison of the ORR in phase 1 studies for other therapies 
used to treat RRMM and noted the following: idecabtagene vicleucel ORR 
73%,\123\ daratumumab ORR 31%,\124\ Selinexor ORR 26% \125\ and Blenrep 
ORR 31%.\126\
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    \122\ Madduri D et. al. CARTITUDE-1: Phase 1b/2 Study of 
Ciltacabtagene Autoleucel, a B-Cell Maturation Antigen-Directed 
Chimeric Antigen Receptor T-Cell Therapy, in Relapsed/Refractory 
Multiple Myeloma
    \123\ Munshi et al. ASCO 2020
    \124\ Usmari et al. Blood 2016, 128(1), 37-44.
    \125\ Chari A et al N Engl J Med 22019, 38 2(8);727-738
    \126\ DREAMM2 Lonai S et al Lancet 2019.
---------------------------------------------------------------------------

    The applicant further asserts that ciltacabtagene autoleucel led to 
early and deep clinical responses in the phase1b/2 portion of the 
CARTITUDE-1 study at median follow up of 12.4 months. Results of 
CARTITUDE-1 showed a 97% overall response rate (ORR) with 67% of 
patients attaining a stringent complete response (sCR) and 93% of 
patients attaining a very good partial response (VGPR) or better after 
receiving a low dose (median of 0.72 million CAR T-cells per kilogram) 
of ciltacabtagene autoleucel within approximately a year. ORR and depth 
of response were independent of BCMA expression on myeloma cells at 
baseline. The median time to first response was one month (range, 0.9-
8.5).\127\
---------------------------------------------------------------------------

    \127\ Berdeja JG, Madduri D, Usmani SZ, Singh I, Zudaire E, Yeh 
TM, Allred AJ, Olyslager Y, Banerjee A, Goldberg JD, Schecter S, 
Geng D, Wu X, Carrasco-Alfonso M, Rizvi S, Fan F, Jakubowiak AJ, 
Jagannath S. Update of CARTITUDE-1: A phase Ib/II study of JNJ-4528, 
a B-cell maturation antigen (BCMA)-directed CAR-T cell therapy, in 
relapsed/refractory multiple myeloma. Journal of Clinical Oncology. 
2020 38:15_suppl, 8505-8505.
---------------------------------------------------------------------------

    The applicant also asserted that most patients attained a status of 
minimal residual disease (MRD)-negativity by the time they were 
evaluable for a complete response (CR). Of evaluable patients, 93.0% 
achieved MRD 10-5 negativity. Fifty-eight percent of 
patients were both MRD negative and in sCR at MRD detection level of 
10-5. Median time to MRD 10-5 negativity: 1 month 
(0.8-7.7). Among patients with 6 months individual follow-up, most had 
ciltacabtagene autoleucel CAR+ T-cells below the level of 
quantification (2 cells/[mu]L) in peripheral blood.
    In addition, progression-free survival (PFS) at 12 months was 77% 
(95% CI; 66.0-84.37).\128\ The applicant believes this represents a 
substantial clinical improvement when compared to existing technologies 
that treat RRMM. The applicant further asserts that nearly all of the 
individuals participating in the study (22 of the 29 patients) were 
alive and continued showing no signs of disease progression after a 
period of 9 months. Median PFS was not reached. At median follow-up of 
12.4 months, there were 14 deaths during the Phase 1b/2 study: One due 
to cytokine release syndrome (CRS) and hemophagocytic 
lymphohistiocytosis (HLH), one due to neurotoxicity, and 12 due to 
other causes.\98\ The applicant asserts that the CRS was manageable in 
most patients. CRS was the most common adverse event (AE) (94.8%) 
observed in the CARTITUDE-1 study. The median time to onset of CRS was 
7 days (range 1-12 days) post ciltacabtagene autoleucel infusion. The 
median duration of CRS was 4 days. Eighty-seven patients (94.6%) 
experienced Grade 1-2 CRS and 5 patients (5% experienced grade 3 or 
greater CRS)122.
---------------------------------------------------------------------------

    \128\ Ibid.
---------------------------------------------------------------------------

    The applicant noted that neurotoxicity with immune effector cell-
associated neurotoxicity syndrome (ICANS) was infrequently observed in 
the context of CRS and was generally low grade. Neurotoxicity with 
ICANS was observed in 20 patients (20.6%) including 10 patients (10.3%) 
with Grade 3 or above toxicity.122
    The LEGEND-2 study \129\ is an ongoing Phase 1, single-arm, open-
label, multicenter, first-in-human trial to determine the safety and 
efficacy of ciltacabtagene autoleucel (LCAR-B38M in China) in the 
treatment of patients with relapsed or refractory multiple myeloma. 
Enrollment in this investigator-initiated study (study proposed, 
initiated, and conducted by an investigator that is funded by industry) 
completed in November 2017; a total of 74 patients with RRMM have been 
treated with ciltacabtagene autoleucel CAR T-cell therapy. The clinical 
cutoff for the analysis of these 74 patients was February 6, 2018 with 
updated survival and efficacy data as of November 26, 2019 (which 
represents 2 years of follow-up from the date of the last subject's 
infusion). Seventeen patients (17/57-29%) died during the study and 
follow up period (19 months) mostly due to progressive disease. None 
were related to cytokine release syndrome or neurotoxicity, the two 
most common adverse events associated with CAR T-cell therapy. At data 
cutoff, 57 patients had received LCAR-B38M CAR T-cells.
---------------------------------------------------------------------------

    \129\ Zhao et al. Journal of Hematology and Oncology. (2018) 
11:141.
---------------------------------------------------------------------------

    The applicant further asserts that outcomes from the LEGEND-2 study 
show that cilltacabtagene autoleucel provides a significantly improved 
clinical outcome relative to other therapies, either approved or still 
under FDA review, used in the RRMM setting. At cutoff, the median 
follow-up was 19 months [17-22]. The overall survival (OS) rate at 18 
months was 68% with a median duration of response (mDOR) of 22 months. 
Of MRD-negative patients with CR, 91% were still alive at data cut, 
with a 27 month mDOR. The median time to first response was 1.1 months. 
There was no relationship between best response and baseline BCMA 
expression level or weight-adjusted CAR T-cells infused.\105\
    The applicant asserts that of patients in the LEGEND-2 study with 
CR, 39 of 42 were minimal residual disease negative (MRD-neg) and 
remained RRMM progression-free. The median PFS rate for all treated 
patients was 20 months; median PFS for MRD-neg patients with CR was 28 
months. At 18 months, the PFS rate was 50% for all patients and 71% for 
MRD-neg patients with CR. Seventeen patients died during the study and 
the follow-up period. The causes of death included progressive disease 
(PD; n=11), disease relapse, PD with lung infection, suicide after PD, 
esophageal carcinoma, infection, pulmonary embolism and acute coronary 
syndrome (n=1 each). Of these, 4 did not achieve partial response (PR) 
or better; and 1 was not evaluable.
    From the LEGEND-2 study, the median time to onset of CRS was 9 days 
(range, 1-19) with a median duration of 9 days (range, 3-57); all but 1 
CRS events resolved. Tocilizumab (46%), oxygen (35%), vasopressor 
(11%), and intubation (1 patient) were used to treat CRS. Neurotoxicity 
with grade 1 aphasia, agitation and seizure-like activity was observed 
in 1 patient in the LEGEND-2 study. The applicant believes that since 
ciltacabtagene autoleucel displayed a manageable CRS safety profile 
that it represents a substantial clinical improvement over existing 
therapies.
    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for 
ciltacabtagene autoleucel, we note that there are no head-to-head 
comparisons of ciltacabtagene autoleucel and other CAR T-cell therapies 
and BCMA-targeted

[[Page 25239]]

therapies. We also note that the applicant chose to use ORR data as a 
measure of substantial clinical improvement rather than the available, 
and more clinically relevant, OS data.
    We are inviting public comment on whether ciltacabtagene autolecuel 
meets the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
ciltacabtagene autoleucel.
e. COSELA (trilaciclib)
    G1 Therapeutics submitted an application for new technology add-on 
payments for Trilaciclib for FY 2022. COSELA (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\
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    \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, Trilaciclib is a first-in-class 
myelopreservation therapy that has the potential to mitigate 
chemotherapy-induced myelosuppression (CIM). Trilaciclib 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. Trilaciclib 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 trilaciclib 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 lymphocytes are CDK 4/6 
dependent, trilaciclib's mechanism of action is believed to preserve 
these cells by temporarily arresting their proliferation during 
chemotherapy. In this way, trilaciclib 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 trilaciclib 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. CDK4/6 
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.
    COSELA (trilaciclib) received FDA's New Drug Application approval 
on February 12, 2021. COSELA is for intravenous use only. The 
recommended dose of COSELA 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, trilaciclib 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 as the applicant states 
that there are no existing ICD-10-PCS codes that uniquely identify the 
administration of trilaciclib.
---------------------------------------------------------------------------

    \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 trilaciclib, 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, trilaciclib 
binds to and inhibits the activity of CDK4/6, thereby blocking the 
phosphorylation of

[[Page 25240]]

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 
trilaciclib will be assigned the same MS-DRG as existing technologies. 
The applicant did not explicitly state to which MS-DRG(s) trilaciclib 
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 trilaciclib is the only 
proactive (preventive) multilineage (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, trilaciclib's benefit is 
coupled to its administration schedule (that is, trilaciclib 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.
---------------------------------------------------------------------------

    We note that the information provided by the applicant in response 
to whether trilaciclib treats the same or similar type of disease or 
the same or similar patient population, appears to only speak to the 
first criterion and whether trilaciclib has a mechanism of action that 
is different than existing technologies; however, we believe 
trilaciclib appears to treat the same patient population and disease as 
existing therapies. We are inviting public comments on whether 
trilaciclib is substantially similar to an existing technology and 
whether it meets the newness criterion.
    With respect to the cost criterion, the applicant conducted the 
following analysis to demonstrate that trilaciclib meets the cost 
criterion. In identifying the cost of trilaciclib, 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 trilaciclib, 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.

[[Page 25241]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.147

[GRAPHIC] [TIFF OMITTED] TP10MY21.148

    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

[[Page 25242]]

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 trilaciclib 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 trilaciclib 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 note that in listing the 
codes it used to identify cases that may be eligible for the use of 
trilaciclib, the applicant provided several ICD-10 codes that lack four 
digits and thus, are considered invalid. We would be interested in 
understanding the basis for the applicant's choice of codes. We also 
note 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, the applicant is making the 
assumption that SCLC cases are randomly distributed amongst all cases 
from which the applicant sampled. By randomly sampling the population, 
the applicant is selecting a subsample that is ideally similar to the 
population with less variance. 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 
question the appropriateness of the sampling used and whether it 
accurately represents cases that would use the technology.
    Finally, with respect to pricing, it appears that the applicant's 
final inflated average case-weighted standardized charge per case 
reflects pricing prior to the availability of more current total 
wholesale acquisition cost. We therefore request 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 are inviting public comment on whether trilaciclib 
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 trilaciclib significantly 
improves clinical outcomes for a patient population as compared to 
currently available treatments, the applicant stated that the 
administration of trilaciclib 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 trilaciclib 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 
trilaciclib 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 trilaciclib 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

[[Page 25243]]

receive trilaciclib (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 trilaciclib 
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 trilaciclib group versus 38 in the 
placebo group. The applicant stated that treatment with trilaciclib 
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 trilaciclib (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 Trilaciclib 
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 trilaciclib versus eight days for placebo. 
The proportion of patients experiencing severe G4 neutropenia was 
reported at 41% for trilaciclib 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 trilaciclib 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 trilaciclib 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 trilaciclib reduces the proportion of patients 
experiencing grade 3/4 anemia in comparison to placebo. In the sixth 
claim, the applicant asserted that trilaciclib 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 trilaciclib and placebo. The 
trilaciclib 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 trilaciclib 
was 3% versus placebo at 9%; the rate of therapeutic intervention with 
G-CSF for trilaciclib at 29% versus 56% for placebo; the proportion of 
patients experiencing grade 3/4 anemia for trilaciclib at 20% versus 
32% for placebo; and the rate of therapeutic intervention with red 
blood cell transfusions for trilaciclib 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 trilaciclib 
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 trilaciclib 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 trilaciclib 
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 trilaciclib 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 
note that 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 note 
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 note that 
trilaciclib 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 note the lack of any statistical correction for multiple 
comparisons. We note that

[[Page 25244]]

in sources provided by the applicant, mean duration of severe 
neutropenia was assessed in day increments.160 161 162 163 
However, it is not clear that zero days would indicate that those 
patients experienced no severe neutropenia. Specifically, we question 
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 note 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 invite public comments as to whether trilaciclib meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
trilaciclib.
f. 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.\165\ 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. 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.
---------------------------------------------------------------------------

    \165\ 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,

[[Page 25245]]

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 believes 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, we 
believe that the mechanism of action for Ellipsys may be the same or 
similar to the original version of the Ellipsys system, which received 
FDA approval on June 22, 2018. 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.\166\ In addition, 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.\167\ Though the applicant maintains that 
performing this additional step in all cases, as opposed to some, leads 
to superior clinical outcomes, we are unclear if this has any bearing 
on newness for this technology or if it represents a change in the 
mechanism of action of this device. We note 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 welcome public comments on whether the change 
in the Ellipsys IFU represents a change to the device's mechanism of 
action.
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    \166\ 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.
    \167\ 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.
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    We also note that differences in mechanism of action between 
Ellipsys and WavelinQ were not included. We note 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 are inviting public comments on whether Ellipsys is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    With regard to the cost criterion, the applicant conducted the 
following analysis to demonstrate that the technology meets the cost 
criterion.
    The applicant searched the FY 2019 MedPAR claims data file with the 
FY 2019 IPPS/LTCH PPS final rule correction notice IPPS Impact File to 
identify potential cases representing patients who may be eligible for 
treatment using the Ellipsys. The applicant stated that currently, 
there are two ICD-10-PCS procedure codes that describe percutaneous AVF 
in the radial artery: 031B3ZF (Bypass right radial artery to lower arm 
vein, percutaneous approach) and 031C3ZF (Bypass left radial artery to 
lower arm vein, percutaneous approach). The applicant stated that these 
codes are not specific to percutaneous AVF formation using thermal 
energy. We note that the applicant submitted a request for approval for 
a unique ICD-10-PCS code for the use of the Ellipsys beginning FY 2022. 
The applicant stated that if the procedure were reported with the 
previously mentioned procedure codes, Ellipsys would be mapped to the 
following MS-DRGs:
[GRAPHIC] [TIFF OMITTED] TP10MY21.149

    The applicant added that ICD-10 codes 031B3ZF and 031C3ZF were new 
effective October 1, 2019 and therefore do not appear in the 2019 
claims data. According to the applicant, the most common MS-DRGs for 
patients admitted with chronic kidney disease and who received an open 
procedure for creation of an AVF are shown below.

[[Page 25246]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.150

    The applicant has not made a request for Ellipsys to be mapped to a 
new MS-DRG for FY 2022.
    The applicant stated that claims which had a diagnosis code for 
Chronic Kidney Disease (CKD) stage IV, CKD stage V, or ESRD and which 
included an open bypass of the subclavian artery to upper arm vein or 
the radial artery to lower arm vein during the same stage were included 
in the cost analysis. The applicant stated they used the following ICD-
10 codes in their analysis to identify claims.
[GRAPHIC] [TIFF OMITTED] TP10MY21.151

    Cases mapping to the top five MS-DRGs by volume were selected, 
which resulted in 689 cases or 79% of case volume.
    The applicant determined an average unstandardized case weighted 
charge per case of $91,190.
    The applicant did not remove charges for prior technology because 
the cases identified included an open procedure that is not performed 
using a specific device. However, the applicant stated that all charges 
for the operating room (OR) were removed as the procedures involving 
the technology would not always be performed in an OR. The applicant 
stated that departmental charges were standardized using the factors 
from the standardization file released with the FY 2021 final rule. 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 technology, the applicant used the national average CCR for the 
Supplies and Equipment cost center of 0.297 from the FY 2021 IPPS/LTCH 
PPS final rule. The applicant added charges for other items and 
services related to the technology; half of the average departmental 
charges for the OR removed in a prior step were added back to the per 
case charge, by MS-DRG, as procedures using the technology would 
sometimes be performed in an OR. The applicant calculated a final 
inflated average case-weighted standardized charge per case of 
$119,158, which exceeded the average case-weighted threshold amount of 
$91,190 by $27,967. 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 note that the applicant used claims with open subclavian artery 
bypass to upper arm vein, in addition to radial lower arm fistulas, as 
a proxy for Ellipsys cases. The applicant stated that Ellipsys may 
provide an alternative to these cases in some instances where AVF 
placement in the radial arteries is possible but the surgeons are 
unfamiliar with the procedure. However, we question if these are the 
most appropriate proxy, as Ellipsys should not replace radiocephalic 
fistulas, per standard guidelines that recommend wrist fistulas first; 
and it would be more likely that surgeons would use Ellipsys over upper 
arm fistulas than a subclavian fistula, which is used rarely in 
standard practice.
    We are inviting public comments on whether the Ellipsys[supreg] 
Vascular Access System meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that the Ellipsys[supreg] Vascular Access System 
represents a substantial clinical improvement over existing 
technologies. Broadly, the applicant outlined three comparators with 
respect to which it asserted Ellipsys provides a substantial clinical 
improvement: (1) Percutaneous AVF with the WavelinQTM (4F) 
EndoAVF System; (2) percutaneous AVF (pAVF) with the prior version of 
Ellipsys; and (3) surgical AVF (sAVF).
    With respect to the first comparison, Ellipsys as compared to 
WavelinQ, the applicant stated that Ellipsys has improved outcomes 
including technical success and cumulative patency. The applicant cited 
the following to support superiority of Ellipsys over WavelinQ: (1) 
Higher fraction of cases with clinically functional AVFs; (2) speedier 
maturation; (3) more durable AVFs; and (4) smaller failure rate. 
According to the applicant, no head-to-head clinical trial is 
available, but they provided one retrospective study that provides a 
direct comparison between the two pAVF systems to support their claims.
    Shahverdyan et al. performed a retrospective review of 100 patients 
undergoing percutaneous fistula creation at a single site in Germany 
between December 2017 and December 2019 to compare outcomes with pAVF

[[Page 25247]]

creation using the Ellipsys and WavelinQ systems.\168\ In this single-
operator, comparative case series, 65 Ellipsys procedures and 35 
WavelinQ procedures were completed, following a procedure sequence 
algorithm for selecting the type of vascular access. Per the study, 
wrist sAVF was the first choice as per standard practice guidelines, 
followed by proximal forearm pAVF, resulting in 100 pAVFs using 
Ellipsys (n=65) and WavelinQ (n=35). Demographics for the study 
patients included 69 percent male and median age of 64.1 years. There 
were no significant differences between WavelinQ and Ellipsys patients 
in age, Body Mass Index (BMI), Chronic Kidney Disease (CKD) status, AVF 
history, or presence of diabetes, though the WavelinQ group had a 
higher proportion of males. The primary endpoints were technical 
success, time to maturation, functional patency, and time to first 
clinical use, and median follow-up was 186.5 days. The study reported 
technical success, defined as post-procedure ultrasound examination 
demonstrating a patent anastomosis and fistula flow, with Ellipsys at 
100 percent vs. 97 percent with WavelinQ (p=0.35). Interventions were 
performed in approximately 27 percent of cases for both technologies, 
and the number of interventions per patient-year was 0.96 vs. 0.46, 
respectively.
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    \168\ Shahverdyan et al., ``Comparison of Outcomes of 
Percutaneous Arteriovenous Fistulae Creation by Ellipsys and 
WavelinQ Devices,'' Journal of Vascular and Interventional Radiology 
2020; 31(9): 1365-1372. (Published on-line August 11, 2020.)
---------------------------------------------------------------------------

    Per the applicant, the study demonstrated a higher fraction of 
cases with clinically functional AVFs using Ellipsys, as fistula 
maturation at four weeks was 68.3 percent with Ellipsys vs. 54.3 
percent with WavelinQ (p=0.1709), and at the end of the study period, 
83.3% and 71.4% respectively. In addition, the applicant stated that 
successful dialysis access was achieved in 79.5 percent of Ellipsys 
cases vs. 60.9 percent for WavelinQ cases among patients on dialysis 
(p=0.0711). The applicant also stated that the study demonstrated that 
Ellipsys results in speedier maturation with Ellipsys demonstrating a 
median time to cannulation of 60 days vs. 90 days with WavelinQ 
(p=0.3676). Next, the applicant stated that use of Ellipsys 
demonstrated more durable AVFs, with a secondary patency rate (the time 
from fistula creation to fistula abandonment, including any 
interventions) at 12 months of 82 percent as compared to 60 percent 
with WavelinQ, and a functional patency rate of 100% vs 85.7%, 
respectively. We note that primary patency (the time from fistula 
creation to the first intervention) between groups was not 
significantly different. Lastly, access failure occurred in 15.4 
percent of Ellipsys patients vs 37.1 percent of WavelinQ patients 
(p=0.0137), which demonstrated that use of Ellipsys results in a 
smaller failure rate, according to the applicant.
    With regard to the second comparison, Ellipsys compared to the 
previous version of the technology, the applicant states that since the 
IFU dated 8/9/19 now states that balloon angioplasty should be 
performed at the time of the creation procedure, they believe that 
Ellipsys should be considered a different device. Per the applicant, 
this subtle difference is of key clinical importance to successful use 
of Ellipsys, as this method decreases the time to two-needle 
cannulation (2NC) and also improves initial flow, resolving vascular 
spasm at the time of the procedure and reducing early thrombosis. The 
applicant further states that performing balloon angioplasty 100 
percent of the time also decreases the number of secondary procedures. 
To support these claims, the applicant compared results from the 
Ellipsys pivotal trial that used the earlier IFU, in which angioplasty 
was performed simultaneously on 19% of patients, with the Ellipsys 
post-market registry that implemented the change and performed the 
additional step on 100% of patients.
    Ellipsys's pivotal trial was a prospective, single-arm, non-
inferiority study of 107 patients at five sites to compare Ellipsys 
with a 90-day performance goal based on a meta-analysis of surgical 
results from the literature.\169\ Inclusion criteria included vascular 
anatomy specific to the indications for Ellipsys, age between 18 and 80 
years old, and CKD stage IV or V. Exclusion criteria included recent 
surgery or major illness within 6 weeks, acute or active infection, and 
use of immunosuppressive medication. Of 261 patients evaluated, a total 
of 117 met inclusion and exclusion criteria, with 28 percent excluded 
due to unsuitable anatomy. 107 were included in the intent to treat 
(ITT) population after each study site completed 2 proctored 
procedures. Demographics included 73 percent male, mean patient age of 
56.7 years, and mean BMI of 31.2 percent. All patients in the ITT 
population received a pAVF with Ellipsys between the proximal radial 
artery and perforating vein, followed by separate maturation 
procedures. The primary efficacy endpoint of the study was maturation 
success, defined as brachial artery flow volume greater than or equal 
to 500ml/min and target vein diameter greater than or equal to 4mm in 
more than 49 percent of patients at 90 days. This performance goal was 
obtained from a meta-analysis of 8 studies of open sAVF, where the 
weighted least squares mean success rate was 62 percent, and the lower 
bound from a 2-sided 95 percent lower confidence interval was 49 
percent. The primary safety endpoint was the absence of device-related 
complications at 90 days. Access failure occurred in 4/107, with a 
technical success rate of 95 percent. The primary endpoint was met by 
86 percent at 90 days (the 97.5 percent lower confidence interval was 
77.9 percent), exceeding the 49 percent performance goal (p<0.0001). 
Cumulative patency was 91.6 percent at 90 days and 86.7 percent at 1 
year. During the 12-month study, 88 percent of the patients on 
hemodialysis (71 of 81) had successful 2-needle cannulation, including 
63 patients on dialysis at enrollment and 18 who initiated dialysis 
during the study. The mean time to cannulation was 114.3 days  66.2 (34-345 days). Per the authors, spasm of the perforating 
vein was easily treated with vasodilators and balloon dilation as a 
matter of routine care. Nineteen percent of patients (20/107) received 
balloon dilation during the index procedure, and second stage 
maturation procedures included 113 balloon dilations in 77 patients. A 
total of 205 maturation procedures were performed on 99 patients at a 
mean of 35.1 days. An additional 66 maintenance procedures were 
performed in 35 patients at a mean of 17 days, for a total of 271 
secondary procedures during the 12 months of the study (2.7 per patient 
year).
---------------------------------------------------------------------------

    \169\ 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.et al.,
---------------------------------------------------------------------------

    The Ellipsys post-market registry by Hull et al. was a prospective 
single-operator study of 60 patients receiving a pAVF with Ellipsys at 
a single outpatient US site in an attempt to understand patient 
selection, maturation, and cannulation with pAVFs.\170\ Patient 
demographics included 57 percent male, mean age of 64, and mean BMI of 
30.7. 123 patients with ESRD stages IV and V were evaluated by 
ultrasound to determine suitability for AVF. Ninety-two percent were 
eligible for sAVF and 61 percent

[[Page 25248]]

were eligible for pAVF. Of the 95 patients who received an AVF, 63 
percent (60) received pAVF and 37 percent (35) received sAVF. All 60 
pAVF patients underwent pAVF creation under ultrasound guidance, 
followed by balloon dilation, as compared to the pivotal trial where 
only 19 percent had balloon dilation as part of the index procedure. 
After 4 weeks, maturation and suitability for dialysis were assessed. 
The fistulas were considered suitable when palpable on examination and 
the target vein had 500ml/min flow volume and 5mm diameter. Fifty-two 
additional maturation procedures, including balloon dilation in 62 
percent, were performed in 40 of 60 patients to achieve adequate flow 
volume and diameter in the target vein. Physiologic maturation was 
achieved in 93 percent (56 of 60 patients) with a mean time of 40.4 
days  4.3, and of the remaining 4 patients, one thrombosed 
and three died prior to maturation. In the 54 patients requiring 
dialysis, 87 percent achieved 2NC at a mean of 76.8 days. Six month 
cumulative patency and functional patency were both 94 percent. 70 
maintenance procedures were performed in 63 percent. Only 2 patients 
achieved 2NC without an additional procedure. The authors noted that 
this study is limited by a modest sample size and single-site study 
with surgeons experienced in pAVF creation, and that results were not 
compared to surgery.
---------------------------------------------------------------------------

    \170\ Hull JE, Deitrick J, Groome K, ``Maturation for 
Hemodialysis in the Ellipsys[supreg] EndoAVF Post-Market Registry,'' 
Journal of Vascular and Interventional Radiology 2020; 31(9): 1373-
1381. (Published on-line August 13, 2020.)
---------------------------------------------------------------------------

    According to the applicant, the post-market registry demonstrated 
the significant clinical differences between performing balloon 
angioplasty as part of the index procedure 19 percent of the time (as 
seen in the pivotal trial) compared to 100 percent of the time. The 
results showed that the average time to 2NC decreased from 100 days to 
70 days. The study also compared initial AVF flow between the studies, 
which increased to 649 ml/min from 330.4 ml/min, attributed to the 
reduction in instances of venospasm due to balloon dilation.\171\ 
According to the study investigators, this decrease in venospasm and 
higher flow led to a reduction in early thrombosis from 11 percent to 2 
percent. Lastly, the applicant compared the number of secondary 
procedures between the two studies with the following table:
---------------------------------------------------------------------------

    \171\ Hull JE, Deitrick J, Groome K, ``Maturation for 
Hemodialysis in the Ellipsys[supreg] EndoAVF Post-Market Registry,'' 
Journal of Vascular and Interventional Radiology 2020; 31(9): 1373-
1381. (Published on-line August 13, 2020.)
[GRAPHIC] [TIFF OMITTED] TP10MY21.152

    Per the applicant, despite the higher standard for maturation in 
the second study (5mm target vein diameter vs 4mm in the pivotal 
study), the number of maturation procedures decreased, while 
maintenance procedures increased. Overall, secondary procedures 
decreased with the new protocol, as described in the table submitted by 
the applicant.
    With respect to the third comparison, Ellipsys as compared to sAVF, 
the applicant stated that Ellipsys creates a side-to-side fistula with 
a percutaneous approach while sAVFs for the most part create end-to-
side fistulas. According to the applicant, in patients that have 
suitable anatomy for pAVF creation, this method of fistula creation 
contributes to improved outcomes in five ways: (1) Higher fraction of 
cases with clinically functional AVFs; (2) decreased time to two-needle 
cannulation; (3) more durable AVFs; (4) decreased need for secondary 
interventions; and (5) patient satisfaction with Ellipsys AVFs. 
According to the applicant, no head-to-head studies or randomized 
trials between Ellipsys and sAVFs are available, and instead, results 
of key variables of interest were compared using studies with 
comparable results for sAVFs from published literature. The applicant 
provided 2 prospective single-arm studies and 5 retrospective studies, 
including the studies previously discussed, to support these claims. 
They also submitted data from one unpublished study. Aside from the 
Ellipsys pivotal trial, the Ellipsys post-market registry, and the 
comparison study with WavelinQ already summarized, the remaining 
studies are summarized below.
    The 2-year results of the pivotal trial were analyzed 
retrospectively by Beathard.\172\ 105 patients with 2 year follow-up 
data were included, and of these, 103 had functioning fistulas and all 
were receiving dialysis except 3. Cumulative patency at 18 and 24 
months was 92.8 percent and 91.6 percent, respectively. Patient 
experience with pAVF was assessed among those who had received a 
previous access procedure (\1/3\). When compared to their previous 
procedure, patients rated Ellipsys as the same in 68 percent, better or 
much better in 29 percent, and worse in 3 percent. Patients mentioned 
difficulty with cannulation due to unfamiliarity of dialysis staff with 
pAVF, but commented on the lack of surgical scar and short recovery 
time. Among all patients who responded, 93 percent rated their access 
as very good or excellent.
---------------------------------------------------------------------------

    \172\ Beathard et al., ``Two-year cumulative patency of 
endovascular AVF'' JVA 2020; 21: 350-356.
---------------------------------------------------------------------------

    A retrospective review of 34 patients who received pAVF between May 
2017 and November 2018 at a clinic in France was submitted.\173\ 
Patients included had ESRD, were not candidates for wrist fistulas, and 
met the anatomic criteria for use of Ellipsys. Demographics included 
patients that were 58 percent male, 65 percent Caucasian and 35 percent 
African, and a mean age of 62 years old. After fistula creation with 
Ellipsys, all anastomoses received balloon dilation. Twenty-four of 34 
patients had successful 2NC within 6 weeks. Forty-four percent of 
patients did not require secondary interventions, and 12 percent 
required additional dilation within 4 weeks to improve maturation. Two 
patients converted to a surgical fistula due to cannulation 
difficulties. No patients developed steal syndrome or aneurysmal 
changes in the one year follow-up period. Study authors noted that one 
benefit of pAVF over sAVF is the potential for multiple outflow 
cannulation veins, as compared to a sAVF in the same location, where 
the median cubital vein is ligated to augment flow into a single 
vessel.
---------------------------------------------------------------------------

    \173\ Hebibi et al, ``Clinical hemodialysis experience with 
percutaneous arteriovenous fistulas created using the 
Ellipsys[supreg] vascular access system,'' Hemodialysis 
International 2019; 23(2): 168-172.
---------------------------------------------------------------------------

    Another study provided was a retrospective cohort study of 232

[[Page 25249]]

consecutive patients who underwent pAVF creation with Ellipsys at a 
single center in France.\174\ An Ellipsys pAVF was the second choice 
after a radiocephalic surgical wrist fistula. Patients were 63 percent 
male, with a mean age of 64 years old (25-92). Balloon angioplasty was 
considered part of the index procedure and performed in all cases. 
Technical success was achieved in 99 percent. At 1 year, the primary 
patency rate was 54 percent and the secondary patency rate was 96 
percent with a mean follow up of 252 days. The most frequent 
intervention (35 percent of patients) was additional balloon 
angioplasty. Eleven percent of patients underwent procedures for 
superficialization of deep veins. Average maturation time by clinical 
or ultrasound criteria was 4 weeks, and successful cannulation was 
established in less than 2 weeks in 10 percent of patients. No 
significant adverse events related to the procedures occurred. Three 
patients (1 percent) required later conversion to sAVF, two due to 
occlusion of the anastomosis and one due to rupture of the perforator 
during an angioplasty procedure and pseudoaneurysm. The authors 
conclude that pAVFs have reduced need for reinterventions and result in 
a moderate-flow fistula with shared venous drainage. They further state 
that minimally invasive AVF creation with the low risk of complications 
seen using Ellipsys can be particularly beneficial in older patients, 
especially since the lower flow fistula as compared to brachial artery 
inflow AVFs decreases the risk of cardiac issues. They conclude that 
large-scale randomized studies are needed to confirm their findings.
---------------------------------------------------------------------------

    \174\ Mallios et al., ``Mid-term results of percutaneous 
arteriovenous fistula creation with Ellipsys vascular access system, 
technical recommendations and an algorithm for maintenance,'' 
Journal of Vascular Surgery 2020; 72(6): 2097-2106. (Published on-
line April 7, 2020.).
---------------------------------------------------------------------------

    In another study, a case series of 14 patients who achieved early 
cannulation with an Ellipsys pAVF underwent retrospective review at an 
outpatient department in Europe.\175\ In these patients, cannulation 
within 14 days post creation was performed using plastic cannulas in 
order to avoid catheter insertion or replacement for dialysis. The 
procedure was successful in all except one case. Primary patency at 12 
months was 66 percent and cumulative patency was 100 percent, with the 
authors concluding that this success suggests that pAVF could serve as 
an alternative to catheter for immediate dialysis.
---------------------------------------------------------------------------

    \175\ Mallios et al., ``Early cannulation of percutaneously 
created AVFs'', Journal of Vascular Access 2020; 21(6): 997-1002. 
(Published on-line December 19, 2019.)
---------------------------------------------------------------------------

    The applicant also submitted preliminary unpublished results from a 
3-year follow up of 99 of the pivotal trial patients, stating that 
while Ellipsys AVFs required more maturation procedures, in the 2 years 
following creation they required fewer maintenance procedures as 
compared to results for sAVF reported in the literature, with an 
average of 0.83 vs. 3.41, respectively. Additionally, they stated that 
at every follow-up period, Ellipsys showed improved cumulative patency 
over sAVF results from the literature, with rates of 90 percent vs 46 
percent at 36 months.
    The applicant summarized results from all of the studies to support 
each claim of Ellipsys's superiority over sAVF by comparing to 
historical controls in the literature. For the claim of more clinically 
functional AVFs, the applicant summarized results from 4 studies, 
demonstrating 2NC in 88 percent at one year and 95 percent at 2 years, 
87 percent with an average follow up of 282 days, and 82 percent within 
6 weeks.176 177 178 179 This was compared to a value of 53.4 
percent successful cannulation for sAVF from a study that looked at the 
effect of age over 65 on clinical outcomes for radiocephalic and 
brachiocephalic AVF.\180\ For the claim of decreased time to 2NC, the 
applicant summarized the results from 5 studies, demonstrating a mean 
time to 2NC for Ellipsys of 100.2 days, 65.5  45.7 days, a 
range of 10 days to 6 weeks, 4 weeks, and 60 
days.181 182 183 184 185 This was compared to a mean of 136 
days for sAVFs, taken from the United States Renal Data System.\186\ 
For the claim of more durable AVFs, the applicant summarized results 
from 5 studies demonstrating Ellipsys's cumulative patency at 12 
months, ranging from 82 percent to 100 percent, and 91.6 percent at 24 
months.187 188 189 190 The applicant compared these results 
to a patency rate of 65 percent for sAVFs found in the USRDS 
database.\191\ The applicant further stated that preliminary results 
from the pivotal trial 3 year follow-up reinforce this claim, as they 
found that the cumulative patency using Ellipsys was 90 percent at 36 
months, compared to a historical value of 46 percent for sAVFs. For the 
claim of decreased secondary interventions (including maturation and 
maintenance procedures), the applicant summarized outcomes from 3 
studies demonstrating 0.96 secondary interventions per patient year in 
the study by Shahverdyan et al.; 2.63 interventions per year in the 
pivotal trial; and an average of 0.83 maintenance inventions per 
patient in the 2 years following creation in the preliminary results of 
the 3 year follow-up by Hull et al. The applicant stated that a 
comparable value for sAVFs is

[[Page 25250]]

3.41 over 2 years.\192\ Finally, for the claim of patient satisfaction, 
the applicant cited results of the patient survey performed by Beathard 
et al., stating that the survey indicated a high level of satisfaction 
with Ellipsys, with 93 percent rating their access as very good or 
excellent, and 95 percent rating their lack of pain as very good or 
excellent. Additionally, patients noted the lack of scar, short 
recovery time, and ease of use with Ellipsys.\193\
---------------------------------------------------------------------------

    \176\ 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.
    \177\ Beathard GA, et al., ``Two-year cumulative patency of 
endovascular arteriovenous fistula,'' Journal of Vascular Access 
2020; 21: 350-356.
    \178\ Hull JE, Deitrick J, Groome K, ``Maturation for 
Hemodialysis in the Ellipsys[supreg] EndoAVF Post-Market Registry,'' 
Journal of Vascular and Interventional Radiology 2020; 31(9): 1373-
1381. (Published on-line August 13, 2020.)
    \179\ Hebibi H, et al., ``Clinical hemodialysis experience with 
percutaneous arteriovenous fistulas created using the 
Ellipsys[supreg] vascular access system,'' Hemodialysis 
International 2019; 23(2): 16 8-172.
    \180\ Weale A, et al., ``Radiocephalic and Brachiocephalic 
Arteriovenous Fistula Outcomes in the Elderly,'' Journal of Vascular 
Surgery 2008; 47(1): 144-150.
    \181\ 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.
    \182\ Hull JE, Deitrick J, Groome K, ``Maturation for 
Hemodialysis in the Ellipsys[supreg] EndoAVF Post-Market Registry,'' 
Journal of Vascular and Interventional Radiology 2020; 31(9): 1373-
1381. (Published on-line August 13, 2020.)
    \183\ Hebibi H, et al., ``Clinical hemodialysis experience with 
percutaneous arteriovenous fistulas created using the 
Ellipsys[supreg] vascular access system,'' Hemodialysis 
International 2019; 23(2): 168-172.
    \184\ Mallios A, Bourquelot P, Franco G, et al., ``Mid-term 
results of percutaneous arteriovenous fistula creation with Ellipsys 
vascular access system, technical recommendations and an algorithm 
for maintenance,'' Journal of Vascular Surgery 2020; 72(6): 2097-
2106. (Published on-line April 7, 2020.)
    \185\ Shahverdyan R, et al., ``Comparison of Outcomes of 
Percutaneous Arteriovenous Fistulae Creation by Ellipsys and 
WavelinQ Devices,'' Journal of Vascular and Interventional Radiology 
2020; 31(9): 1365-1372. (Published on-line August 11, 2020.)
    \186\ United States Renal Data System. 2016 USRDS Annual Data 
Report: Epidemiology of kidney disease in the United States. 
National Institutes of Health, National Institute of Diabetes and 
Digestive and Kidney Diseases, Bethesda, MD, 2016.
    \187\ Beathard GA, et al., ``Two-year cumulative patency of 
endovascular arteriovenous fistula,'' Journal of Vascular Access 
2020; 21: 350-356.
    \188\ Mallios A, Bourquelot P, Franco G, et al., ``Mid-term 
results of percutaneous arteriovenous fistula creation with Ellipsys 
vascular access system, technical recommendations and an algorithm 
for maintenance,'' Journal of Vascular Surgery 2020; 72(6): 2097-
2106. (Published on-line April 7, 2020.)
    \189\ Shahverdyan R, et al., ``Comparison of Outcomes of 
Percutaneous Arteriovenous Fistulae Creation by Ellipsys and 
WavelinQ Devices,'' Journal of Vascular and Interventional Radiology 
2020; 31(9): 1365-1372. (Published on-line August 11, 2020.)
    \190\ Mallios A, et al., ``Early cannulation of percutaneously 
created arteriovenous hemodialysis fistulae,'' Journal of Vascular 
Access 2020; 21(6): 997-1002. (Published on-line December 19, 2019.)
    \191\ Al-Jaishi, Ahmed A., et al. ``Patency rates of the 
arteriovenous fistula for hemodialysis: a systematic review and 
meta-analysis.'' American Journal of Kidney Diseases (2014) 63(3): 
464-47.
    \192\ Lee T, et al., ``Long-Term Outcomes of Arteriovenous 
Fistulas with Unassisted versus Assisted Maturation: A Retrospective 
National Hemodialysis Cohort Study,'' Journal on American Nephrology 
2019; 30(11):2209-2218.
    \193\ Beathard GA, et al., ``Two-year cumulative patency of 
endovascular arteriovenous fistula,'' Journal of Vascular Access 
2020; 21: 350-356.
---------------------------------------------------------------------------

    We note that only one of the studies submitted by the applicant in 
support of a finding of substantial clinical improvement for Ellipsys 
has a comparator arm (retrospective comparison), and none were created 
with a methodology to demonstrate superiority. In addition, some 
studies may be limited by potential bias due to single operator and/or 
single site design, and comparisons to sAVF were made using various 
historical controls from different studies with no statistical 
analyses, making it difficult to account for confounding variables. We 
further note that the studies used physiologic endpoints as a surrogate 
outcome for fistula maturity instead of a clinically functional fistula 
as determined by successful 2-needle cannulation. Of interest, a number 
of the studies submitted concluded that there is a further need for 
head-to-head, larger scale, or longer trials to confirm claims of 
superiority of pAVF over surgical AVF and other pAVF devices. We note 
that the applicant provided one retrospective study with a small sample 
size to support the claim of superiority of Ellipsys over WavelinQ. 
Though this study by Shahverdyan et al. demonstrated numerically better 
outcomes for multiple endpoints with Ellipsys, we note that outcomes 
did not reach statistical significance for primary patency, technical 
success, maturation rates, time to cannulation, or fistula success, and 
we note the potential for bias with the single operator/single site 
study design.
    We note that the decreased interventions and time to 2NC using 
Ellipsys were reported from studies performed outside of the US, where 
practice patterns are different. Per the Hull et al. study, practice in 
the US is to direct flow into a single upper arm vein to meet 
established guidelines for fistula flow diameter depth and length, 
whereas in the European studies, multiple outflow veins were 
accepted.\194\ The authors further state that allowing multiple outflow 
veins decreases the number of secondary maturation procedures used to 
direct flow, but requires advanced cannulation techniques, ultrasound 
guidance, and plastic access cannulas that are not available in the US. 
These techniques and the use of plastic cannulas also allow for early 
cannulation of the fistula in European studies. For these reasons, we 
question whether the European results are generalizable to the US 
population.
---------------------------------------------------------------------------

    \194\ Hull et al., ``Maturation for Hemodialysis in the Ellipsys 
EndoAVF Post-Market Registry,'' Journal of Vascular and 
Interventional Radiology 2020; 31(9): 1373-1381. (Published on-line 
August 13, 2020.)
---------------------------------------------------------------------------

    When comparing the new protocol for Ellipsys (always performing 
balloon angioplasty) to the De Novo protocol (sometimes performing 
balloon angioplasty), Ellipsys demonstrated a reduced number of 
maturation procedures and faster time to cannulation; however, more 
maintenance procedures were required than the De Novo protocol. In 
addition, the investigators did not account for potential confounding 
variables between the different studies, which could have affected 
outcomes in order to compare the two studies used to claim superiority. 
We further note that previously, balloon angioplasty was nearly always 
performed, whether as part of the index procedure, as a maturation 
procedure, or as a maintenance procedure, and it continued to be a 
necessary secondary intervention after adoption of the new procedural 
step.
    We are inviting public comments on whether the Ellipsys[supreg] 
Vascular Access System demonstrates improvement over each of the three 
comparators and meets the substantial clinical improvement criterion.
    We received public comments in response to the New Technology Town 
Hall meeting regarding the application of the Ellipsys[supreg] Vascular 
Access System for new technology add-on payments.
    Comment: The applicant submitted a public comment providing an 
additional study and addressing questions posed at the town hall 
meeting. The study provided is a single-center retrospective comparison 
article in press of Ellipsys and sAVF by Harika et al. 107 patients who 
received pAVF with Ellipsys at this center between May 2017 and May 
2018 were compared to an equal number of consecutive patients who 
received a surgical fistula in the same time period. Patients with 
grafts or lower extremity fistulae were excluded and baseline 
characteristics and demographics were comparable between groups. All 
pAVFs were created by a single surgeon, while the sAVFs were created by 
4 surgeons. Primary outcomes were primary and secondary patency rates, 
as well as maturation as determined by AVF utilization, or >4mm 
diameter and >500ml/lt flow for pre-dialysis patients. Secondary 
outcomes assessed secondary interventions and rate of complications. 
Per the applicant, at 6 weeks, pAVF maturation rates were higher 
compared to the sAVF arm (65 percent vs 50 percent, p=0.01). In 
addition, primary patency in the sAVF group was higher than pAVF at 12 
months (86 percent vs 61 percent, p<0.01) but comparable at 24 months 
(52 percent vs 55 percent, p=0.48), and secondary patency rates were 
not significantly different between groups at 12 or 24 months. Rates of 
secondary interventions were divided between percutaneous and surgical 
interventions. At 2 years, the rate of percutaneous reinterventions was 
similar but the sAVFs required more surgical revisions (36% vs. 17%). 
Differences in total interventions between groups did not reach 
statistical significance at 12 and 24 months. The study authors 
conclude that pAVF's better aesthetic result, short procedure time, and 
ability to perform easily in an outpatient office procedure center 
indicates that Ellipsys has many benefits, but large prospective 
randomized multicenter studies are needed to confirm the outcomes 
demonstrated in this study.\195\
---------------------------------------------------------------------------

    \195\ Harika G, et al., ``Comparison of surgical versus 
percutaneously created arteriovenous hemodialysis fistulae,'' 
Journal of Vascular Surgery 2020; accepted for publication December 
5, 2020, in press.
---------------------------------------------------------------------------

    In response to a question regarding the need for a head-to-head 
comparison between WavelinQ and Ellipsys to determine superiority, the 
applicant stated that there are no randomized controlled trials 
available but the study (summarized previously) by Shahverdyan et al. 
provides a reasonable comparison of the two. Per the applicant, the 
algorithm to choose which procedure to perform reflected ``real-world'' 
choices, and the results demonstrated that Ellipsys offers substantial 
clinical improvement over WavelinQ. In response to a comment 
questioning the available 2-year data using the current version of 
Ellipsys, the applicant stated that the 2-year follow up study 
(Beathard et al.) of the pivotal trial captured results of patients 
treated with immediate angioplasty, as that was done in 19 percent of 
patients even

[[Page 25251]]

before the procedural change. The applicant further stated that the 
current version of Ellipsys differs only by the addition of this 
procedural step, and studies after the pivotal trial adopted this 
practice to better results, with this combination of results indicating 
that the balloon angioplasty step improves outcomes over a multi-year 
period. In addition, the applicant stated that the Harika et al. study 
(summarized previously) had a 2-year study period, and all patients had 
immediate balloon angioplasty. In response to a question regarding the 
comparability of pAVF in the proximal radial artery with a sAVF in the 
same location, the applicant stated though they are created 
differently, they are functionally comparable once mature, and neither 
typically requires superficialization.
    Next, in response to a question regarding what the fewer short-term 
complications using Ellipsys are as compared to sAVF, the applicant 
stated that these include lower wound morbidity due to minimal 
incisions, fewer aneurysms, avoidance of vasospasm, and lower incidence 
of clinically significant steal syndrome. The applicant stated that in 
sAVF, clinically significant steal syndrome can occur in as many as 11 
percent of cases, but it is rare in reports of pAVFs placed with 
Ellipsys. The applicant summarized information on complications with 
Ellipsys from the studies previously discussed and stated that (1) 
Harika et al \196\ reported that sAVFs had a substantially higher rate 
of wound healing and infections, as well as more occurrences of steal 
syndrome and aneurysm; (2) Hull et al's prospective safety and efficacy 
study \197\ examined possible complications in detail and most 
complications did not appear at all; (3) the Ellipsys pivotal trial 
\198\ reported no complications due to vessel perforation, dissection, 
or distal embolization were reported; (4) in the Hull et al. Maturation 
Study,\199\ several adverse events were reported including one 
hematoma, one arm swelling, and one case of steal syndrome; and (5) 
Mallios et al's report on mid-term results \200\ reported no 
complications, other than cases treated with balloon angioplasty and 
one case of arm swelling.
---------------------------------------------------------------------------

    \196\ Harika G, et al., ``Comparison of surgical versus 
percutaneously created arteriovenous hemodialysis fistulae,'' 
Journal of Vascular Surgery 2020; accepted for publication December 
5, 2020, in press.
    \197\ Hull JE, Elizondo-Riojas G, et al., ``Thermal resistance 
anastomosis device for the percutaneous creation of arteriovenous 
fistulae for hemodialysis,'' Journal of Vascular and Interventional 
Radiology 2017; 28: 380-387.
    \198\ 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.
    \199\ Hull et al., ``Maturation for Hemodialysis in the Ellipsys 
EndoAVF Post-Market Registry,'' Journal of Vascular and 
Interventional Radiology 2020; 31(9): 1373-1381. (Published on-line 
August 13, 2020.)
    \200\ Mallios et al., ``Mid-term results of percutaneous 
arteriovenous fistula creation with Ellipsys vascular access system, 
technical recommendations and an algorithm for maintenance,'' 
Journal of Vascular Surgery 2020; 72(6): 2097-2106. (Published on-
line April 7, 2020.)
---------------------------------------------------------------------------

    The applicant also addressed a final question in its public comment 
regarding the definition of improved durability. The applicant stated 
that this is an umbrella term used to reflect the useful life of an AVF 
for dialysis, and can include different patency measures.
    Response: We thank the applicant for its comments and will take 
this information into consideration when deciding whether to approve 
new technology add-on payments for the Ellipsys[supreg] Vascular Access 
System. With regard to the Harika et al. study provided, we note that 
prespecified subgroup analyses of pAVF vs elbow fistulae (e-AVF) and 
pAVF vs wrist fistulae were also compared, with elbow fistula 
considered to be the most similar comparator to ``real world'' vascular 
access practice patterns. When comparing outcomes between e-AVF and p-
AVF groups in this study, differences in total interventions, 
maturation at 6 weeks, and secondary patency rates were not 
significantly different. e-AVF also demonstrated higher 12 month 
primary patency (p=0.02). We further note that though the applicant 
asserted that Ellipsys decreases the need for secondary interventions 
as compared to sAVF, this study did not demonstrate a statistically 
significant difference between arms for total interventions at 12 or 24 
months, and we are concerned that this may not demonstrate a 
substantial clinical improvement for Ellipsys over sAVF.
    Comment: Another public comment was submitted in response to the 
Town Hall meeting. The commenter stated that during the FY 2022 New 
Technology Town Hall Meeting, Avenu Medical relied upon a single 
published study to support claims of substantial clinical improvement 
for Ellipsys over WavelinQ. Per the commenter, this study indicated 
that limitations of the review include those of any retrospective 
analysis on nonrandomized data and possible selection bias.\201\ Per 
the commenter, the authors of the study concluded that both of the 
devices had high technical success rates and adequate flow volumes, as 
well as no significant difference in primary patency, and that the 
devices may serve different patient populations, since patients can be 
anatomically eligible for one or the other. The commenter concludes 
that it is important that both technologies are available as treatment 
options for Medicare beneficiaries and they believe CMS should consider 
new technology add-on payments for the two pAVF systems together. They 
also stated that CMS should designate a new technology add-on payment 
category for devices used in percutaneous creation of an AVF.
---------------------------------------------------------------------------

    \201\ Shahverdyan R., et al. ``Comparison of Outcomes of 
Percutaneous Arteriovenous Fistulae Creation by Ellipsys and 
WavelinQ Devices,'' Journal of Vascular and Interventional Radiology 
2020; 31(9): 1365-1372. (Published on-line August 11, 2020.)
---------------------------------------------------------------------------

    Response: We thank the commenter for their input and will take this 
information into consideration when deciding whether to approve new 
technology add-on payments for the Ellipsys[supreg] Vascular Access 
System. We note that we are unclear with regard to the commenter's 
request for a new technology add-on payment category, as the IPPS 
payment system does not utilize categories, and this request may be 
referring to another payment system.
g. ENSPRYNG\TM\ (satralizumab-mwge)
    Genentech, Inc. submitted an application for new technology add-on 
payments for the ENSPRYNG\TM\ (satralizumab-mwge) injection (ENSPRYNG) 
for FY 2022. According to the applicant, ENSPRYNG 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 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.\202\ The applicant states, 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 in a timely 
manner while the patient is still

[[Page 25252]]

admitted. Therefore, according to the applicant, ENSPRYNG 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.
---------------------------------------------------------------------------

    \202\ 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).\203\ The applicant asserts that NMOSD has an estimated 
prevalence of 0.1-10 per 100,000 individuals, affecting nearly 15,000 
individuals in the United States.\204\ NMOSD occurs in children \205\ 
and adults \206\ of all races \207\ and disproportionately affects 
African and Asian females aged 30 to 40 years.\208\ 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,\209\ and brainstem,\210\ 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.\211\ 
Around 60% of patients relapse within one year of diagnosis, and 90% 
relapse within 3 years.\212\ 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.\213\
---------------------------------------------------------------------------

    \203\ 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.
    \204\ 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.
    \205\ 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.
    \206\ 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.
    \207\ 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.
    \208\ 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.
    \209\ 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.
    \210\ National Organization for Rare Disorders (NORD[supreg]). 
Neuromyelitis Optica Spectrum Disorder. https://rarediseases.org/rare-diseases/neuromyelitis-optica/. Accessed August 19, 2020.
    \211\ Wingerchuk DM. Diagnosis and Treatment of Neuromyelitis 
Optica. Neurologist 2007;13(1)2-11. doi:10.1097/
01.nrl.0000250927.21903.f8.
    \212\ 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.
    \213\ 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.\214\ 
Disease-induced disability and symptoms have a considerable impact on 
patients' ability to work and thrive in social activities and personal 
relationships.\215\ The applicant added that the loss of motor and 
sensory function leads to approximately 50% of patients requiring a 
wheelchair \216\ and 62% of patients becoming functionally blind \217\ 
within 5 years of diagnosis.\218\ 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.
---------------------------------------------------------------------------

    \214\ Beekman J, Keisler A, Pedraza O, et al. Neuromyelitis 
optica spectrum disorder. Neurol.-Neuroimmunol. Neuroinflammation 
2019;6(4)e580. doi:10.1212/nxi.0000000000000580.
    \215\ Ibid.
    \216\ 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.
    \217\ 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.
    \218\ 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 received FDA BLA 
approval on August 14, 2020. The applicant added that ENSPRYNG was 
granted Fast Track designation \219\ and Breakthrough Therapy 
designation \220\ by the FDA. The applicant stated that ENSPRYNG 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 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 beginning FY 2022.
---------------------------------------------------------------------------

    \219\ 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.
    \220\ 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 purposed 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.\221\ The 
applicant stated that there are presently two other FDA-approved 
therapies for patients with AQP4-IgG positive NMOSD: SOLIRIS 
(eculizumab),\222\ which was approved in 2019, and UPLIZNA 
(inebilizumab-cdon), which was approved in 2020.\223\
---------------------------------------------------------------------------

    \221\ 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.
    \222\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \223\ UPLIZNA (inebilizumab) [prescribing information]. 
Gaithersburg, MD: Viela Bio, Inc.; 2020.
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    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 is an interleukin-6 (IL-6) receptor 
antagonist indicated for the treatment of NMOSD in adult patients who 
are AQP4-IgG positive.\224\ According to the applicant, ENSPRYNG 
targets soluble and membrane-bound IL-6 receptors to inhibit IL-6 
signaling and subsequently disrupt downstream inflammatory

[[Page 25253]]

effects that contribute to the pathophysiology of NMOSD; \225\ ENSPRYNG 
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.\226\
---------------------------------------------------------------------------

    \224\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \225\ 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.
    \226\ 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, for which a precise 
mechanism of action is unknown but is presumed to involve inhibition of 
AQP4-IgG-induced terminal complement C5b-9 deposition; \227\ UPLIZNA, 
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; \228\ azathioprine, for which a precise mechanism of action is 
unknown; \229\ Rituxan, which targets CD20 antigen on B cells and leads 
to profound B cell depletion, principally over an antibody-dependent 
cell cytotoxicity mechanism; \230\ 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; \231\ and prednisone, which is 
a synthetic adrenocortical steroid drug with predominately 
corticosteroid properties.\232\ 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 has a unique and distinct 
mechanism of action.
---------------------------------------------------------------------------

    \227\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \228\ UPLIZNA (inebilizumab) [prescribing information]. 
Gaithersburg, MD: Viela Bio, Inc.; 2020.
    \229\ IMURAN (azathioprine) [prescribing information]. Roswell, 
GA: Sebela Pharmaceuticals Inc.; 2018.
    \230\ RITUXAN (rituximab) [prescribing information]. South San 
Francisco, CA: Genentech, Inc.; 2019.
    \231\ 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.
    \232\ 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 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 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 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 may be 
contraindicated in patients with unresolved serious Neisseria 
meningitidis infections; and (2) SOLIRIS and UPLIZNA are administered 
as IV infusions which not all patients may be willing to receive.
    In summary, the applicant asserts ENSPRYNG 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. We note that the applicant states that the use of 
ENSPRYNG may not involve treatment of the same or similar patient 
population when compared to SOLIRIS 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 question if UPLIZNA may also be a treatment 
option for patients with meningococcal disease. We further question 
whether patients who are unwilling to receive an IV infusion would 
constitute a new patient population for NMOSD. We invite public comment 
on whether ENSPRYNG involves the treatment of the same or similar 
patient population when compared to existing technologies.
    We are inviting public comments on whether ENSPRYNG is 
substantially similar to other technologies and whether ENSPRYNG meets 
the newness criterion. 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, which is also 
indicated for NMOSD, and the second which is specific to ENSPRYNG.
    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, 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 charges 
for related or prior technologies because, per the applicant, ENSPRYNG 
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 using the same 
methodology as the first analysis, described previously. The applicant 
calculated a final inflated

[[Page 25254]]

average case-weighted standardized charge per case of $175,021, which 
exceeded the case-weighted threshold of $47,813. The applicant asserted 
that ENSPRYNG meets the cost criterion based on these analyses.
    Based on the information provided by the applicant, it is 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 are seeking 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, the applicant should impute a minimum case number of 11. We are 
inviting public comments on whether ENSPRYNG meets the cost criterion, 
including whether the use of another CCR would substantially alter the 
results of the applicant's analysis.
    With regard to the substantial clinical improvement criterion, the 
applicant asserts that ENSPRYNG 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 is the only FDA-approved treatment for NMOSD 
that is subcutaneously administered; \233\ and (4) the totality of 
circumstances demonstrates ENSPRYNG, 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.
---------------------------------------------------------------------------

    \233\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
---------------------------------------------------------------------------

    The SAkuraStar (NCT02073279) \234\ 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 
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 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.
---------------------------------------------------------------------------

    \234\ 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-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.235 236 The annualized relapse rate for AQP4-IgG 
positive patients was 0.1 (95% CI, 0.05-0.2) in the ENSPRYNG group and 
0.5 (95% CI, 0.3-0.9) in the placebo group.\237\ The proportion of 
relapse-free AQP4-IgG positive patients at week 96 was 77% in the 
ENSPRYNG group and 41% in the placebo group.\238\ According to the 
applicant, the study concluded that ENSPRYNG monotherapy reduced the 
rate of NMOSD relapse compared with placebo in the overall trial 
population and had a favorable safety profile.
---------------------------------------------------------------------------

    \235\ 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.
    \236\ 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.
    \237\ 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.
    \238\ 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) \239\ 
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.
---------------------------------------------------------------------------

    \239\ US Department of Health and Human Services. Active Study 
 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

[[Page 25255]]

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 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 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 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.\240\ The 
proportion of relapse free AQP4-IgG positive patients at week 96 was 
92% in ENSPRYNG plus IST group and 53% in the placebo plus IST 
group.\241\
---------------------------------------------------------------------------

    \240\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \241\ 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 plus IST group had at 
least one adverse event compared to 95% in the placebo plus IST 
group.\242\ The safety profile of ENSPRYNG 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; and the most frequently reported AEs 
in the OST period were consistent with the double-blind period.\243\
---------------------------------------------------------------------------

    \242\ 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.
    \243\ 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. According to the 
applicant, ENSPRYNG is the only FDA-approved treatment for NMOSD that 
is administered subcutaneously.\244\ 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 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 
states 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.
---------------------------------------------------------------------------

    \244\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
---------------------------------------------------------------------------

    In their fourth claim, the applicant states the totality of 
circumstances otherwise demonstrate that ENSPRYNG, relative to 
technologies previously available, substantially improves the treatment 
of Medicare beneficiaries. The applicant asserts that a cross trial 
comparison between ENSPRYNG and SOLIRIS (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 and SOLIRIS and their clinical trials. 
Per the applicant, the first distinction is that in the registrational 
study for SOLIRIS, a higher proportion of patients receiving SOLIRIS 
than those receiving a placebo discontinued their participation in the 
clinical trial (17% vs 6%).\245\ During the double-blind period of 
SAkuraSky trial, however, a total of three patients (7%) in the 
ENSPRYNG group and 10 patients (24%) in the placebo group discontinued 
the trial agent.\246\ The applicant states that discontinuation of 
SOLIRIS may be associated with relapse and hospitalization. The second 
distinction made by the applicant is that the prescribing information 
for ENSPRYNG \247\ does not bear a black-box warning, in contrast to 
that of SOLIRIS.\248\ The third distinction is that patients must be 
vaccinated against Neisseria meningitidis before receiving SOLIRIS 
\249\ and no such requirement applies to ENSPRYNG.\250\ 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 94.172.6 weeks in the ENSPRYNG 
group and 66.061.4 weeks in the placebo group.\251\ 
However, the median trial durations were shorter in the SOLIRIS trial, 
at 90.93 and 43.14 weeks (minimum-maximum, 6.4-211.1 and 8.0-208.6) for 
the SOLIRIS and placebo groups, respectively.\252\
---------------------------------------------------------------------------

    \245\ 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.
    \246\ 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.
    \247\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \248\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \249\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \250\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \251\ 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.
    \252\ 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 \253\ and SAkuraSky \254\ 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 ENSPRYNG to be assessed both in 
patients who were

[[Page 25256]]

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 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 or placebo; the 
efficacy of SOLIRIS monotherapy was a sub analysis,\255\ and UPLIZNA 
was tested only in a single Phase 3 clinical trial as a monotherapy 
with only a 28-week randomized, controlled period.\256\ According to 
the applicant, ENSPRYNG has received approval by regulatory authorities 
in Japan,\257\ Canada, and Switzerland \258\ for the treatment of both 
adults and adolescents (12-17 years of age) with NMOSD. The applicant 
asserts that patients in the ENSPRYNG clinical trials likely are 
representative of Medicare patients despite their mean ages (45.3 years 
for the ENSPRYNG arm of SAkuraStar \259\ and 40.8 years for the 
ENSPRYNG arm of SAkuraSky \260\) being less than 65, as NMOSD is so 
severe that patients may qualify for disability accompanied by Medicare 
benefits regardless of their age.\261\ The applicant explained that a 
severe onset attack causing increased disability is reported to occur 
in 45% of patients with NMOSD \262\ and that 52.4% of US-based NMOSD 
patients report severe problems with mobility,\263\ which is consistent 
with definitions of disability used by the Social Security 
Administration (SSA).\264\ 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,\265\ and the 
two conditions are frequently confused due to similarities between 
clinical presentations.\266\ 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.\267\
---------------------------------------------------------------------------

    \253\ 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.
    \254\ 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.
    \255\ 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.
    \256\ 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.
    \257\ 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.
    \258\ Heo Y. Satralizumab: First Approval. Drugs 
2020;80(14)1477-1482. doi:10.1007/s40265-020-01380-2.
    \259\ 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.
    \260\ 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.
    \261\ Social Security Administration. Medicare Information. 
https://www.ssa.gov/disabilityresearch/wi/medicare.htm. Accessed 
September 10, 2020.
    \262\ 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.
    \263\ 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.
    \264\ Social Security Administration. How You Qualify. https://www.ssa.gov/benefits/disability/qualify.html. Accessed October 2, 
2020.
    \265\ 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.
    \266\ 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.
    \267\ Social Security Administration. How You Qualify. https://www.ssa.gov/benefits/disability/qualify.html. Accessed October 2, 
2020.
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    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for ENSPRYNG, 
we note that while the applicant provided data comparing ENSPRYNG 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 states reasons why a comparison could not be 
made, additional information would help inform our assessment of 
whether ENSPRYNG demonstrates a significant clinical improvement over 
existing technologies for outcomes such as time to first relapse and 
annual relapse rate. In addition, while we understand that there may be 
potential benefits related to the self-administrative delivery of 
ENSPRYNG, we question 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 are inviting public 
comments on whether ENSPRYNG meets the substantial clinical improvement 
criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for ENSPRYNG.
h. 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 idecabtagene vicleucel for FY 2022. Idecabtagene viclecuel 
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). 
Idecabtagene vicleucel 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.\268\ Data from the U.S. 
Surveillance, Epidemiology, and End Results (SEER) registry estimate 
32,000 new cases of MM and

[[Page 25257]]

13,000 deaths from MM annually in the U.S. 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 \269\ and approximately 25% of patients have a median 
survival of 2 years or less.\270\ With respect to the newness 
criterion, idecabtagene vicleucel received FDA approval on March 26, 
2021, and has marketing authorization under the name of Abecma[supreg] 
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 idecabtagene vicleucel 
contains a cell suspension of 300 to 460 x 106 CAR T-cells.
---------------------------------------------------------------------------

    \268\ 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&selectedTit
le=1~150&usage_type=default&display_rank=1.
    \269\ 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.
    \270\ 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.
---------------------------------------------------------------------------

    The applicant submitted a request for unique ICD-10-PCS codes that 
describe the administration of idecabtagene vicleducel at the September 
2020 Coordination and Maintenance Committee meeting. The following 
codes were approved to describe procedures involving the administration 
of idecabtagene vicleucel: XW033L7 (Introduction of idecabtagene 
vicleucel immunotherapy into peripheral vein, percutaneous approach, 
new technology group 7) and XW043L7 (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 asserts that idecabtagene 
viceleucel 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, idecabtagene viceleucel 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 cell activation domain, and a 4-1BB costimulatory 
domain. Antigen-specific activation of idecabtagene viceleucel 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, idecabtagene vicleucel's mechanism of action is different 
because it is a CAR T-cell therapy. The applicant states 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-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 states 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 states 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 
idecabtagene vicleucel. 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 
idecabtagene vicleucel, 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 asserts that the key feature 
that distinguishes idecabtagene vicleucel from CD-19 directed CAR T-
cell therapies is the BCMA targeting domain. According to the 
applicant, idecabtagene vicleucel's BCMA targeting domain means that 
idecabtagene vicleucel 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, idecabtagene 
vicleucel 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 idecabtagene vicleucel 
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, idecabtagene vicleucel will 
be the first and only anti-BCMA CAR T-cell therapy available to treat 
RRMM. The applicant further asserted that idecabtagene vicleucel 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 idecabtagene 
vicleucel 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 
question whether idecabtagnene vicleucel'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

[[Page 25258]]

submitted for FY 2022 as discussed previously. Both idecabtagene 
vicleucel 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 are 
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 idecabtagene 
vicleucel 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 are inviting public comments on whether idecabtagene vicleucel 
is substantially similar to an existing technology and whether it meets 
the newness criterion.
    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 idecabtagene vicleucel. 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] TP10MY21.153

    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 idecabtagene vicleucel. 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 are 
uncertain how representative this data is for use in the applicant's 
cost analyses given the potential for variability.
    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 invite public comment on whether idecabtagene vicleucel meets 
the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that it believes that idecabtagene vicelucel 
represents a substantial clinical improvement over existing 
technologies because: (1) The totality of the circumstances regarding 
idecabtagene vicleucel's clinical efficacy, safety, and data make clear 
that idecabtagene vicleucel substantially improves, relative to 
services or technologies currently available, the treatment of Medicare 
beneficiaries with RRMM; (2) idecabtagene vicleucel has superior 
effectiveness compared to existing therapies; (3) idecabtagene 
vicleucel fills an unmet need as demonstrated by the patient population 
in its registrational study, which is reflective of real-world RRMM 
patients and (4) idecabtagene vicleucel improves quality of life for 
patients with RRMM.
    In support of its assertion that the totality of the circumstances 
regarding idecabtagene vicleucel's clinical efficacy, safety, and data 
make clear that idecabtagene vicleucel 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 idecabtagene 
vicleucel. 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

[[Page 25259]]

refractory to triple therapy). Efficacy results showed an ORR of 50% 
for patients (n=4) receiving the target idecabtagene vicleucel dose of 
150 x10\6\; 68.6% for patients (n=70) receiving the target dose of 300 
x10\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 
idecabtagene vicleucel was 73.4%.
    The applicant asserts that in the KarMMA study, patients who 
received idecabtagene vicleucel 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.271 272 273 274 275 276 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%).\277\ According 
to the applicant, these safety results confirm that idecabtagene 
vicleucel has the potential to offer a meaningful benefit to Medicare 
beneficiaries. The applicant also asserts that idecabtagene vicluecel 
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 idecabtagene vicleucel in 
a heavily pre-treated RRMM patient population.
---------------------------------------------------------------------------

    \271\ 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.
    \272\ 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.
    \273\ 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.
    \274\ 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.
    \275\ 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.
    \276\ 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.
    \277\ 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 note 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, idecabtagene vicleucel 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.\278\
---------------------------------------------------------------------------

    \278\ Ibid.
---------------------------------------------------------------------------

    To support its assertion that idecabtagene vicleucel has superior 
effectiveness compared to existing therapies, the applicant provided 
results from the KarMMa-RW study,\279\ 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 
idecabtagene vicleucel 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.
---------------------------------------------------------------------------

    \279\ 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 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 idecabtagene 
vicleucel treatment in the KarMMa cohort vs the similar real-

[[Page 25260]]

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).\280\ The applicant asserts that results were 
consistent across subgroups including patients aged >=65 years.
---------------------------------------------------------------------------

    \280\ 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 
idecabtagene 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 idecabtagene vicleucel in the KarMMa study, 
CR was 1% for patients in the STORM study vs 33% for patients treated 
with idecabtagene vicleucel 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 idecabtagene vicleucel in the KarMMa 
study, and PFS was 3.7 months for patients in the STORM study vs 8.8 
months for patients treated with idecabtagene vicleucel 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 idecabtagene vicleucel in the KarMMa study, CR was 3% for patients 
in the DREAMM-2 study vs 33% for patients treated with idecabtagene 
vicleucel 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 idecabtagene vicleucel 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 idecabtagene vicleucel in the KarMMa study.
    Because idecabtagne vicleucel showed improved ORR, CR, medDOR and 
PFS when compared to Xpovio[supreg] and Blenrep, the applicant asserts 
that idecabtagne vicleucel provides a substantial clinical improvement 
over these existing therapies.
    To support that idecabtagene vicleucel fills an unmet need as 
demonstrated by the patient population in its registrational study, the 
Phase 2 KarMMa study, the applicant asserts 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 idecabtagene vicleucel offers significantly improved 
outcomes for RRMM compared with currently available therapies. The 
applicant asserts 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 >=65 years) \281\ 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).\282\ 
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.
---------------------------------------------------------------------------

    \281\ Cancer Stat Facts: Myeloma, NCI SEER, https://seer.cancer.gov/statfacts/html/mulmy.html (last visited Oct. 7, 
2020).
    \282\ 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 idecabtagene vicleucel improves 
quality of life for patients with RRMM, the applicant referenced 
idecabtagene vicleucel'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 ealth/QoL scale, and 6 single item measures.\283\ The QLQ-MY20 
consists of 20 questions addressing 4 myeloma-specific HRQoL domains 
(disease symptoms, side effects of treatment, future perspectives, and 
body image).\283\ 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 idecabtagene 
vicleucel, of whom 121 (94.5%) and 120 (93.8%) were evaluable for HRQoL 
by QLQ-C30 and QLQ-MY20, respectively. At baseline, idecabtagene 
vicleucel 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 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 idecabtagene vicleucel provides meaningful 
improvements in HRQoL and self-reported symptoms associated with 
heavily pretreated RRMM and demonstrate that idecabtagene vicleucel 
provides meaningful improvement in both global function and symptoms 
related to MM.
---------------------------------------------------------------------------

    \283\ 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 
idecabtagene vicleucel, we question whether, due to the lack of 
randomization, there is sufficient evidence to establish the efficacy 
of idecabtagene vicleucel compared with current alternatives. It is 
unknown whether the superior

[[Page 25261]]

outcomes for idecabtagene vicleucel in the KarMMA study, which 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 note 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 are inviting public comment on whether idecabtagene vicleucel 
meets the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Techology Add-on Payment Town Hall meeting notice published in the 
Federal Register regarding the substantial clinical improvement 
criterion for idecabtagene vicleucel.
i. 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.\284\ 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.\285\
---------------------------------------------------------------------------

    \284\ Heit, John A. ``Epidemiology of venous thromboembolism.'' 
Nature reviews. Cardiology vol. 12,8 (2015): 464-74. doi:10.1038/
nrcardio.2015.83
    \285\ 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.\286\ In 
catheter-directed thrombolysis, a thrombolytic agent is infused 
intravascularly adjacent to the clot burden through a percutaneous 
transcatheter.\287\ In percutaneous mechanical thrombectomy, the 
thrombus is lysed or removed mechanically. The therapies may be used 
separately or in conjunction with one another.\288\
---------------------------------------------------------------------------

    \286\ 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.
    \287\ 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/.
    \288\ 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.\289\
---------------------------------------------------------------------------

    \289\ 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 indicated that there is no unique ICD-10-PCS 
procedure code to describe the use of INDIGO[supreg] with Lightning. 
The applicant submitted a request for a unique ICD-10-PCS code to 
identify the technology beginning FY 2022.
    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 states 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 FDA 510(k) authorization for pulmonary embolism on 
April 22, 2020 under FDA

[[Page 25262]]

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] TP10MY21.154

    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 states that PE is 
not the same disease as arterial and venous thromboembolism; the 
patient populations may overlap, but are not identical.
    We have the following concerns 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 does 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 question 
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 
device through the lumen of the catheter to break up the thrombus. It 
is also 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 is 
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 note 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 believe 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 note 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 note 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

[[Page 25263]]

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 note 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 invite public comment on whether INDIGO[supreg] with Lightning 
is substantially similar to other technologies and whether 
INDIGO[supreg] with Lightning meets the newness criterion.
    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:

[[Page 25264]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.155

    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.

[[Page 25265]]

    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 note 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 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 invite public comment on whether INDIGO[supreg] with Lightning 
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 \290\ 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.
---------------------------------------------------------------------------

    \290\ 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,\291\ 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.\292\
---------------------------------------------------------------------------

    \291\ 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
    \292\ 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 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.
    We note that 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. 
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 note 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. The applicant did not demonstrate superior outcomes 
using INDIGO[supreg] with Lightning compared to INDIGO[supreg] without 
Lightning.
    We note 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 note that in the poster study, all patients were 
maintained on anticoagulation following thrombectomy with 
INDIGO[supreg], so it is difficult to assess the DVT

[[Page 25266]]

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 note 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.\293\
---------------------------------------------------------------------------

    \293\ 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 question 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 invite public comment on whether INDIGO[supreg] with Lightning 
meets the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
INDIGO[supreg] with Lightning or at the New Technology Town Hall 
meeting.
j. Ischemia Care Respiratory and Stroke Test Kit or ISC-REST
    Ischemia Care submitted an application for new technology add-on 
payment for Ischemia Care Respiratory and Stroke Test Kit (ISC-REST) 
for FY 2022. Per the applicant, ISC-REST is a test kit composed of 
three tests to stratify the cause of ischemic strokes by 
differentiating those that originate in the heart, called cardioembolic 
(CE) strokes, and those that originate in the arteries, called large 
artery atherosclerotic (LA) strokes, once it has been determined that a 
patient has not suffered a hemorrhagic stroke. According to the 
applicant, ISC-REST is made up of three tests: (1) ISCDx, (2) the 
QIAstat-Dx Respiratory SARS-CoV-2 Panel, and (3) the QIAGEN Access 
Anti-SARS-CoV-2 Total Test. According to the applicant, the three test 
results provide information related to the cause of ischemic stroke and 
coronavirus disease 2019 (COVID-19) status to prevent a recurrent 
stroke. Per the applicant, the first of the three tests, ISCDx, is a 
blood test that uses RNA expression from whole blood to differentiate 
between CE and LA stroke, two types of ischemic stroke. According to 
the applicant, once blood is drawn, the RNA expression in the blood 
sample is analyzed and matched to the gene expression signatures and 
patterns associated with CE stroke and LA stroke. Per the applicant, 
the second test, the QIAstat-DX respiratory SARS-CoV-2 Panel, is a 
multiplexed nucleic acid real-time polymerase chain reaction (PCR) test 
intended for the qualitative detection and differentiation of nucleic 
acid from 22 respiratory pathogens, including the SARS-CoV-2 virus, in 
nasopharyngeal swabs. According to the applicant, the third test is the 
QIAGEN Access Anti-SARS-CoV-2 Total Test, a rapid, digital lateral flow 
serological test to detect antibodies to SARS-CoV-2 in human serum and 
plasma.
    According to the applicant, the ISC-REST kit is intended to be used 
when a patient presents at the hospital with an ischemic stroke, within 
30 hours of symptom onset and with a National Institutes of Health 
Stroke Scale (NIHSS) score of >=5. The NIHSS measures stroke-related 
neurologic deficit and has predictive validity for long-term stroke 
outcome.\294\ Per the applicant, the ISC-REST kit is intended for use 
at the time of the standard evaluation, at the same time that normal 
blood samples are collected when a patient is admitted to the hospital 
for stroke. According to the applicant, to use the ISC-REST kit, blood 
is drawn into a PaxGene tube (for the ISCDx test), a nasal swab is 
obtained (for the QIAstat-Dx Respiratory SARS-CoV-2 Panel), and an 
additional blood sample is drawn (for the QIAGEN Access Anti-SARS-CoV-2 
Total Test). Per the applicant, the hospital sends all three samples to 
a single laboratory, the Clinical Laboratory Improvement Amendments 
(CLIA) certified Ischemia Care laboratory, for processing and 
reporting. According to the applicant, three results are reported: (1) 
A result for whether the gene expression in the blood sample was 
consistent with CE stroke or LA stroke, (2) a result for respiratory 
screening that includes COVID-19, influenza, and other respiratory 
illnesses, and (3) a result for COVID-19 antibodies to determine 
whether the patient previously had COVID-19.
---------------------------------------------------------------------------

    \294\ Schlegel, Daniel et al., ``Utility of the NIH Stroke Scale 
as a Predictor of Hospital Disposition,'' Stroke, 2003;34:134-137, 
https://doi.org/10.1161/01.STR.0000048217.44714.02.
---------------------------------------------------------------------------

    According to the applicant, the number of cryptogenic ischemic 
strokes, or ischemic strokes where the cause is unknown, is concerning. 
The applicant states that there are 695,000 ischemic strokes each year 
in the United States, with 185,000 of these events being recurrent 
strokes. Per the applicant, for up to 40% of ischemic strokes, or 
roughly 250,000 ischemic strokes, the cause is cryptogenic.\295\ The 
applicant states that when the cause of stroke is identified, secondary 
stroke prevention protocols may be adapted to prevent a bigger, more 
costly, and severe recurrent stroke. The applicant explains that 
cryptogenic stroke leads to high recurrence risk in cases of undetected 
atrial fibrillation. The applicant also explains that typically the 
diagnosis of the causes of stroke is complex, inconsistent across 
hospitals, expensive, and inconclusive. Further, the applicant claims 
that the cryptogenic rate is higher for stroke patients with COVID-19 
than stroke patients without COVID-19, citing a retrospective study of 
patients hospitalized at a major New York health system between March 
and April 2020 that found that the cryptogenic rate was 65% for COVID-
19 positive patients.\296\ In that study, out of 3,556 patients that 
were hospitalized and diagnosed with COVID-19 during that time, 32 
patients or under 1% of the sample size experienced an ischemic stroke. 
The study found that the standard stroke diagnostic workup did not 
establish the ischemic stroke etiology for a significant proportion of 
patients in the study with concurrent

[[Page 25267]]

COVID-19 infection and ischemic stroke: cryptogenic stroke diagnosis 
was twice more prevalent in COVID-19-positive patients (65.6%), 
compared with both COVID-19-negative contemporary stroke patients 
(30.4%) and ischemic stroke patients hospitalized in the same hospital 
system during the same time period the year prior (25.0%).
---------------------------------------------------------------------------

    \295\ Saver, Jeffrey L., ``Cryptogenic Stroke,'' N Engl J Med, 
May 26, 2016, [374:2065-2074] DOI: 10.1056/NEJMcp1503946, available 
at: https://www.nejm.org/doi/10.1056/NEJMcp1503946.
    \296\ Shadi Yaghi, et al. SARS-CoV-2 and Stroke in a New York 
Healthcare System, Stroke. 2020; 51:2002-2011. DOI: 10.1161/
STROKEAHA.120.030335, available at: https://www.ahajournals.org/doi/10.1161/STROKEAHA.120.030791.
---------------------------------------------------------------------------

    While the applicant states in the application that there is no 
standard of care pathway to determine the cause of stroke, a stroke 
patient presenting at the hospital is typically evaluated using a 
standard evaluation that includes imaging and hematologic testing to 
determine if the patient is a candidate for intervention. Diagnosing 
the cause of stroke, per the applicant, often requires expensive 
testing, risk to the patient, and invasive procedures, without a 
guarantee of a definitive diagnosis. The applicant explains that each 
suspected cause requires a focused workup to confirm the suspicion. 
Additionally, the applicant points out, a negative result in one 
pathway does not mean a positive result in another pathway. The 
applicant claims that the inability to accurately stratify patients by 
cause of stroke often results in either limiting use of advanced 
patient testing or performing too many tests. The applicant further 
claims that diagnosing the cause of stroke and preventing recurrent 
stroke using a standard evaluation is even more challenging for 
ischemic stroke patients with COVID-19 because these patients are 
presenting at younger ages and without traditional comorbidities, 
eliminating many of the traditional causes of stroke.
    While the applicant states that it is unclear to clinicians whether 
COVID-19 is a separate cause of stroke or aggravates comorbidities to 
cause a stroke, the applicant claims that the information that the ISC-
REST kit would provide is important, as clinicians currently know very 
little about the vascular effects of COVID-19. The applicant states 
that the ISC-REST kit ties all of the clinical diagnosis pieces 
together: Respiratory viral and bacterial organism presence, COVID-19 
antibody presence, and CE or LA stroke. Per the applicant, this 
combined testing is convenient for the clinician and also raises 
awareness about the COVID-stroke connection by providing real world 
evidence.297 298 Additionally, the applicant explains that 
traditional diagnosis of ischemic stroke cause is often complex, 
inconsistent, expensive, inconclusive and may require more invasive 
diagnosis procedures, such as implantable cardiac monitoring or 
transcranial doppler. Ultimately, according to the applicant, the 
traditional process to stratify the cause of stroke may require months 
or years of additional tests post event.
---------------------------------------------------------------------------

    \297\ Patients with Coronavirus Disease 2019 (COVID-19) vs 
Patients With Influenza, JAMA Neurol. 2020;77(11):1366-1372.
    \298\ COVID-19 Is an Independent Risk Factor for Acute Ischemic 
Stroke, American Journal of Neuroradiology, August 2020, 41(8):1361-
1364.
---------------------------------------------------------------------------

    With respect to the newness criterion, each of the three tests in 
ISC-REST, as well as the ISC-REST test kit as a whole, have varying FDA 
authorization statuses and separate indications. The applicant stated 
in their application that they are seeking Emergency Use Authorization 
(EUA) from the FDA for the ISC-REST test kit. The applicant shared that 
the intended indication of ISC-REST is to provide three critical 
diagnostic tests in the same kit for convenience of the user during the 
COVID-19 public health emergency. For the ISCDx test, the applicant 
stated that the test had completed the requirements of the Clinical 
Laboratories Improvement Amendments (CLIA) analytical validations and 
is available as a Laboratory Developed Test. ISCDx's intended 
indication is to aid in the diagnosis of CE and LA stroke, when 
hemorrhagic stroke is ruled out, in conjunction with standard clinical 
evaluation and in the context of the patient's clinical history and 
other diagnostic test results. The test could also be used as part of 
the clinical evaluation and patient risk assessment. The QIAstat-Dx 
Respiratory SARS-CoV-2 Panel was granted an EUA on March 30, 2020 and 
is intended for patients suspected of COVID-19 by their healthcare 
provider for the detection and differentiation of nucleic acid from 
SARS-CoV-2 and the following organism types and subtypes: Adenovirus, 
Coronavirus 229E, Coronavirus HKU1, Coronavirus NL63, Coronavirus OC43, 
SARS-CoV-2, Human Metapneumovirus A+B, Influenza A, Influenza A H1, 
Influenza A H3, Influenza A H1N1/pdm09, Influenza B, Parainfluenza 
virus 1, Parainfluenza virus 2, Parainfluenza virus 3, Parainfluenza 
virus 4, Rhinovirus/Enterovirus, Respiratory Syncytial Virus A+B, 
Bordetella pertussis, Chlamydophila pneumoniae, and Mycoplasma 
pneumoniae. The applicant states that results are for the 
identification of SARS-CoV-2 RNA, however, negative results do not 
preclude SARS-CoV-2 infection and should not be used as the sole basis 
for patient management decisions. According to the applicant, there is 
no EUA request pending approval for the QIAGEN Access Anti-SARS-CoV-2 
Total Test.
    The applicant stated that there are currently no ICD-10-PCS 
procedure codes that uniquely identify the use of ISC-REST. The 
applicant submitted a request for approval of a unique ICD-10-PCS 
procedure code to identify use of the technology beginning FY 2022. The 
applicant provided 81 ICD-10-PCS codes that they stated could be used 
to identify cases involving the use of ISC-REST in the interim. These 
81 ICD-10-CM diagnosis codes are associated with cerebral infarctions, 
occlusions, and other neurological conditions consistent with ischemic 
stroke presentations.
    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 similar mechanism of action to achieve a therapeutic outcome, 
according to the applicant, there are no blood tests for stroke or its 
causes. The applicant also stated that there is no blood testing for 
the cause of stroke combined with COVID-19 screening.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG when compared to an existing 
technology, the applicant stated that the ISC-REST kit is not replacing 
an existing technology and reiterated that ISCDx is a blood test that 
stratifies ischemic stroke patients into CE and LA stroke causes The 
applicant stated that the technology would map to MS-DRGs 061,062, 063, 
064, 065, 066, 067, 068 and that it is not requesting for ISC-REST 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, the applicant 
stated that there are no existing technologies to stratify stroke 
populations by cause.
    We note the following concerns regarding whether the applicant 
meets the newness criterion. Under the regulations at 42 CFR 
412.87(e)(2), CMS only considers, for add-on payments for a particular 
fiscal year, an application for which the new technology has received 
FDA marketing authorization by July 1 prior to the particular fiscal 
year. While the applicant stated that ISCDx, one of the three tests in 
ISC-REST test kit, has completed the requirements of the Clinical 
Laboratories Improvement

[[Page 25268]]

Amendments, we note that this is not considered FDA marketing 
authorization as required in our regulations for the new technology 
add-on payment.\299\
---------------------------------------------------------------------------

    \299\ 42 CFR 412.87(e)(2).
---------------------------------------------------------------------------

    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).
    As previously summarized, the applicant is seeking an EUA from the 
FDA for the ISC-REST test kit. 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.
    We also refer the reader to our comment solicitation in section 
II.F.7 of the preamble of this 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.
    Additionally, we are uncertain whether the mechanism of action of 
ISC-REST can be considered new. While the applicant claims that there 
is currently no other blood test available that identifies the cause of 
ischemic stroke through RNA biomarkers, we note that clinicians may 
order blood tests as part of the stroke consultation to gather 
information about stroke risk factors and other medical problems which 
may have caused the stroke.\300\ In addition, we note that there are 
several types of RNA biomarker tests for stroke that have been 
developed and used in other settings, and we therefore note that this 
may not represent a new mechanism of action for ISC-REST. Similarly, we 
are not certain whether the QIAstat-Dx Respiratory SARS-CoV-2 Panel and 
QIAGEN Access Anti-SARS-CoV-2 Total Test components of ISC-REST have 
unique mechanisms of action, as they may be similar to other PCR nasal 
swabs and serology tests for COVID-19 that are currently in use during 
the COVID-19 public health emergency. We welcome public comment 
regarding whether ISC-REST has a unique mechanism of action even if 
some or all of its test components do not have unique mechanisms of 
action individually. Because ISC-REST delivers three separate test 
results through three separate tests, it is unclear whether the 
combination of the tests in one kit could be viewed as representing a 
unique mechanism of action over and above the mechanisms of action of 
the tests if they were to be performed separately.
---------------------------------------------------------------------------

    \300\ Mayo Clinic Staff, Stroke Diagnosis, Feb. 9, 2021, https://www.mayoclinic.org/diseases-conditions/stroke/diagnosis-treatment/drc-20350119.
---------------------------------------------------------------------------

    With regard to whether the technology maps to the same or different 
MS-DRG as existing technologies, though the applicant did not state 
whether it believes the technology meets this criterion, we believe 
that under the proposed indication for ISCDx, ISC-REST would not be 
used until a patient had a confirmed ischemic stroke. Therefore, under 
the proposed indication, it seems that the technology would map to the 
same MS-DRGs as cases involving the standard of care for ischemic 
stroke and cerebral infarction. However, it appears that there may be 
scenarios where a patient has an occlusion or some other neurological 
condition that makes the patient present with stroke-like symptoms, 
without having had a stroke or infarction. We invite comments on 
whether, for this reason, cases involving the use of the technology may 
be assigned to the same or different MS-DRGs as cases not only 
involving the standard of care for ischemic stroke and cerebral 
infarction, but also nonspecific cerebrovascular accidents and pre-
cerebral occlusions.
    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, we note the 
applicant's statement that there are no existing technologies to 
stratify stroke populations by cause does not address whether the 
technology meets this criterion. CMS requests comments on whether ISC-
REST kit would be used as a diagnostic aid in the treatment of similar 
diseases and patient populations as the current standard-of-care 
ischemic stroke diagnosis evaluation.
    We are inviting public comments on whether ISC-REST is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    With regard to the cost criterion, the applicant provided the 
following analysis. The applicant used claims data from one hospital 
system, made up of

[[Page 25269]]

three hospitals with a total of 87 health care providers. The average 
percentage of patients across the three hospitals with Medicare or 
Medicare Advantage coverage was 69%, per the applicant. The applicant 
stated that raw data was provided from January 2020 through September 
2020, then annualized for 2020. Per the applicant, the average 
standardized charges were calculated per MS-DRG by the hospital system 
that provided the data.
    As mentioned previously, the applicant stated that the technology 
would map to the following MS-DRGs: MS-DRG 061 (Ischemic Stroke, 
Precerebral Occlusion or Transient Ischemia with Thrombolytic Agent 
with MCC), 062 (Ischemic Stroke, Precerebral Occlusion or Transient 
Ischemia with Thrombolytic Agent with CC), 063 (Ischemic Stroke, 
Precerebral Occlusion or Transient Ischemia with Thrombolytic Agent 
without CC/MCC), 064 (Intracranial Hemorrhage Or Cerebral Infarction 
with MCC), 065 (Intracranial Hemorrhage or Cerebral Infarction with CC 
or TPA in 24 Hours), 066 (Intracranial Hemorrhage or Cerebral 
Infarction without CC/MCC), 067 (Nonspecific CVA And Precerebral 
Occlusion without Infarction with MCC), and 068 (Nonspecific CVA And 
Precerebral Occlusion Without Infarction Without MCC). The applicant's 
data included a total of 385 cases mapping to those MS-DRGs. The 
applicant did not submit claims data for two of the listed MS-DRGs, MS-
DRG 063 and 067, because the data source that the applicant used did 
not have any cases under those MS-DRGs for the time period that the 
sample data was collected. The applicant imputed 11 claims for two 
other MS-DRGs, 061 and 068, because there were fewer than 11 claims 
submitted for these MS-DRGs.
    The applicant stated that it compared the distribution of MS-DRGs 
in the hospital data to the distribution of MS-DRGs in the FY 2022 New 
Technology Add-On Payment thresholds, which includes the number of 
cases per MS-DRG. The applicant asserted that because the MS-DRG 
distributions were highly similar, the data sample obtained from the 
hospital system was representative of the distribution of MS-DRGs 
nationally.
    The applicant did not remove charges for a prior technology 
because, as the applicant noted, ISC-REST is not replacing any other 
technology. The applicant then applied the one-year charge inflation 
factor of 1.06353 included in the FY 2021 IPPS/LTCH PPS proposed rule 
(85 FR 59039) to inflate the charges from FY 2020 to FY 2021. To add 
charges for the new technology, the applicant multiplied the cost of 
ISC-REST by the cost-to-charge ratio for acute care hospitals found in 
the FY 2020 IPPS/LTCH PPS final rule. The applicant explained that the 
urban and rural hospital cost-to-charge ratios were combined to yield a 
national average of 0.3095. However, we note that the applicant appears 
to have used the cost-to-charge ratios in Table 8A, which lists the 
statewide average operating cost-to-charge ratios for acute care 
hospitals.
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $87,842 which exceeds the average case-
weighted threshold amount, $57,110. The applicant contended that ISC-
REST meets the cost criterion based on these analyses.
    We have the following concerns regarding the cost criterion. It is 
not clear whether the applicant's use of private data from three 
hospitals is representative of the Medicare population. While the 
applicant states that the average Medicare and Medicare Advantage 
percentage of patients across the 3 hospitals was 69%, CMS is unsure 
whether the claims under the MS-DRGs the applicant provided are for 
Medicare patients, or private insurance patients in those hospitals. 
Similarly, because the applicant annualized data from the months of 
January to September 2020, it is not clear whether the portion of time 
selected by the applicant is representative of the entire year. 
Additionally, while the applicant points to the fact that the sample of 
claims data from the 3 hospitals had similar MS-DRG distributions as 
the FY 2022 New Technology Add-on Payment Thresholds, it is not clear 
whether this would indicate that the charging practices of the 
hospitals or their patient costs are similar to Medicare claims data 
nationally. It is also not clear whether the applicant's cost analysis 
is representative of the cost of the technology as the applicant did 
not use the applicable cost-to-charge ratio of 0.107 for laboratory 
services as provided in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58601). Finally, we note that it is not possible for CMS to verify the 
claims data submitted, as the applicant used hospital claims data that 
is not publicly available and did not identify the source. We are 
inviting public comments on whether ISC-REST meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that ISC-REST represents a substantial clinical 
improvement over existing technologies for several reasons. First, the 
applicant asserts that ISC-REST has the ability to stratify ischemic 
stroke patients early in the diagnosis process to reduce the number of 
cryptogenic stroke diagnoses, which leads to appropriate medical 
management that can better reduce the risk of a recurrent stroke. 
Second, the applicant asserts that ISC-REST will lead to appropriate 
utilization of subsequent diagnostic testing, or decrease the necessary 
use of subsequent diagnostic testing, to determine stroke etiology, 
including: Implantable cardiac monitoring, hypercoagulation panels, 
magnetic resonance angiography, and other commonly used tests for 
ischemic stroke. Third, the applicant asserts that use of ISC-REST will 
lead to a reduction in at least one clinically significant adverse 
event, a recurrent stroke, including a reduction in mortality or a 
clinically significant complication. Fourth, the applicant further 
asserts that use of ISC-REST will result in a decreased use of, or more 
appropriate utilization of, therapeutic intervention, in cases where 
patients are medically managed for a comorbidity and a stroke occurs. 
Fifth, the applicant asserts that use of ISC-REST will result in a 
decreased number of future hospitalizations by reducing recurrent 
stroke risk and physician visits, as in some cases ISC-REST will result 
in a diagnosis pathway that will not require surgical or invasive 
procedures. Additionally, once ISC-REST identifies the cause of the 
stroke, the applicant asserts that the opportunity to manage a chronic 
population may include telemedicine approach, rather than in-person 
physician visits. Finally, the applicant asserts that ISC-REST will 
result in improved quality of life by helping avoid a recurrent stroke.
    The applicant submitted five information sources to address the 
substantial clinical improvement criterion, as well as supplementary 
information in the application itself and additional narrative 
responses. First, the applicant submitted a poster presentation by 
Jauch E.C., on the results and methodology of a Biomarkers of Acute 
Stroke Etiology (BASE) study to determine whether RNA expression can 
accurately differentiate LA stroke from CE stroke in the acute 
setting.\301\ Similarly, the applicant submitted an unpublished 
manuscript detailing another BASE study on stroke biomarkers to 
determine

[[Page 25270]]

if the etiology of acute ischemic stroke could be objectively 
determined by RNA expression using BASE blood samples.\302\ Third, the 
applicant submitted a published study methodology paper by Jauch et 
al., on the methodology of an ongoing (at the time of publication) BASE 
study to identify serum markers defining the etiology of acute ischemic 
stroke.\303\ The fourth information source, by Jickling et al., was a 
published article from 2010 on a study to design genetic probes for 
ischemic stroke. The fifth and final information source submitted was a 
2016 journal article by Jeffrey L. Saver, with background information 
on etiologies of stroke.\304\
---------------------------------------------------------------------------

    \301\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
    \302\ Peacock, W.F. and Edward Jauch., ``Cardioembolic vs Large 
Artery Atherosclerotic Stroke: Can we answer Hobson's question?'', 
pre-publication manuscript.
    \303\ Jauch, Edward C., et al. ``Biomarkers of Acute Stroke 
Etiology (BASE) Study Methodology,'' May 5, 2017.
    \304\ Saver, Jeffrey L., ``Cryptogenic Stroke,'' N Engl J Med, 
May 26, 2016.
---------------------------------------------------------------------------

    The first three information sources all describe the BASE trial 
(NCT02014896), a prospective, multicenter, observational, convenience, 
sample cohort study of patients presenting to the hospital within 24 
hours of stroke onset, which looked to determine if the etiology of 
acute ischemic stroke can be objectively determined by RNA expression 
from patient blood samples.305 306 307 The primary objective 
of the BASE study was to confirm the diagnostic accuracy of the ISCDx 
test to identify stroke subtypes in patients with acute ischemic 
stroke. According to the BASE Study Methodology paper by Jauch et al., 
while enrollment for this multisite study was ongoing at the time of 
publication, it was expected to hit 1000 patients by March 2017.\308\ 
The Base Study Methodology paper explains that blood samples were first 
collected from patients presenting to the hospital within 24 hours of 
stroke onset, and then again collected 24 hours and 48 hours 
later.\309\ The tubes were kept at room temperature for up to 24 hours 
and then frozen -20 [deg]C until shipped to the Ischemia Care CLIA 
laboratory where the ISCDx testing was performed. From these blood 
samples, RNA gene expression was utilized to identify stroke etiology 
marker candidates. Patients who met the inclusion criteria: (1) Had 
experienced a suspected acute ischemic stroke within 24(+/-6) hours of 
symptom onset; (2) had a normal baseline CT, without hemorrhage or 
alternate explanation for symptoms; (3) were older than 18 years old; 
and (4) gave informed consent. Control samples consisted of 100 non-
stroke Emergency Department patients matched on clinical risk factors 
of age, race, gender, smoking history, diabetes, hypertension, atrial 
fibrillation, and hyperlipidemia. We note that there are changes from 
the previously stated study methodology in the two sources the 
applicant included with BASE study results.310 311 For 
example, while the study methodology as described in the Jauch et al. 
paper stated that the blood samples were kept at room temperature for 
up to 24 hours and then frozen,\312\ in the poster presentation by 
Jauch, E.C., the samples were frozen within 72 hours of 
collection.\313\
---------------------------------------------------------------------------

    \305\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
    \306\ Peacock, W.F. and Edward Jauch., ``Cardioembolic vs Large 
Artery Atherosclerotic Stroke: Can we answer Hobson's question?'', 
pre- publication manuscript.
    \307\ Jauch, Edward C., et al. ``Biomarkers of Acute Stroke 
Etiology (BASE) Study Methodology,'' May 5, 2017.
    \308\ Jauch, Edward C., et al. ``Biomarkers of Acute Stroke 
Etiology (BASE) Study Methodology,'' May 5, 2017.
    \309\ Ibid.
    \310\ Peacock, W.F. and Edward Jauch., ``Cardioembolic vs Large 
Artery Atherosclerotic Stroke: Can we answer Hobson's question?'', 
pre- publication manuscript.
    \311\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
    \312\ Jauch, Edward C., et al. ``Biomarkers of Acute Stroke 
Etiology (BASE) Study Methodology,'' May 5, 2017.
    \313\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
---------------------------------------------------------------------------

    The applicant describes a set of study results, which are detailed 
in the unpublished manuscript by Peacock et al. and the poster 
presentation by Jauch, E.C.314 315 These analyses used 
adjudicated stroke diagnoses, classified as CE and LA, and determined 
by two board-certified neurologists blinded to each other's diagnosis 
and biomarker results. The 218 patients enrolled were randomly assigned 
to a derivation cohort (70%) or validation cohort (30%). Using the 
derivation set gene expression levels, a signature was created to 
distinguish between CE and LA ischemic stroke, with the derived model 
then applied to the validation cohort. 59% of the participants in the 
study were male with a median age of 70.7 years. The median time from 
symptom onset to blood collection was 1200 minutes (ranging from 448 to 
1568 minutes). The applicant explains that, of the 218 patients 
enrolled with an NIHSS>5, 149 were adjudicated as CE and 69 were 
adjudicated as LA. Additionally, sample analysis of the derivation 
cohort resulted in 9,513 unique gene-level probe-sets for signature 
inclusion, with the best set containing 45 genes. The diagnostic gene 
signature results in the early validation cohort distinguished CE 
stroke from LA stroke with a C-statistic of 0.78 (0.50-1.0, 95% CI), 
sensitivity of 0.90 and specificity of 0.70. The study concluded that 
RNA expression accurately identifies stroke etiology.
---------------------------------------------------------------------------

    \314\ Peacock, W.F. and Edward Jauch., ``Cardioembolic vs Large 
Artery Atherosclerotic Stroke: Can we answer Hobson's question?'', 
pre- publication manuscript.
    \315\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
---------------------------------------------------------------------------

    The applicant also provided the following supplemental information 
to support that combining three tests in the ISC-REST kit improves 
patient outcomes over performing the lab tests separately. Though the 
applicant noted that there is no direct evidence currently available 
regarding the impact of using the ISC-REST kit, they explain that, in 
their experience, clinical supporters of the ISC-REST kit claim that 
they would order ISC-REST kit testing 100% of the time versus ordering 
three separate tests. The applicant claims that there is a convenience, 
cost effectiveness, and time savings associated with ISC-REST during a 
time when hospital resources are limited. Second, the applicant states 
that because the QIAstat-Dx Respiratory SARS-CoV-2 Panel tests for 
COVID-19 as well as 12 other common respiratory illnesses, in testing 
for several respiratory illnesses, ISC-REST may inform care decisions. 
Third, the applicant states that collecting the samples for each test 
together and testing them in the same laboratory will ensure high 
levels of quality control. The applicant also claims that using the 
ISC-REST test kit has investigative benefits, including the ability to 
help track and study how long the COVID-19 antibodies last in a chronic 
population based upon consistent measurement of the index events 
(stroke and COVID-19). Finally, the applicant states that the ISC-REST 
kit and adoption of guideline-directed appropriate care will result in 
prevention of recurrent strokes because it will impact clinician choice 
of therapeutics.
    After a review of the information provided by the applicant, we 
have the

[[Page 25271]]

following concerns with regard to the substantial clinical improvement 
criterion.
    We note that all of the BASE study results that the applicant 
submitted provide information on the ISCDx test on its own rather than 
the ISC-REST test kit, for which the applicant has submitted an 
application for new technology add-on payment 
consideration.316 317 As stated in the BASE Study 
methodology paper by Jauch, et al., the primary objective of the BASE 
study is to confirm the diagnostic accuracy of the ISCDx test to 
identify stroke subtypes in patients with acute ischemic stroke.\318\ 
No data were provided with regard to the complete ISC-REST kit, the 
other components individually, or any combination. We are therefore 
unclear as to whether it is possible to draw conclusions about 
substantial clinical improvement for the ISC-REST kit using the limited 
data provided on the ISCDx test and without any data or studies on the 
ISC-REST kit. Specifically, the applicant did not submit data or 
studies on how treatment decisions are impacted after the ISC-REST kit 
is used or if there is any impact on patient outcomes as a result of 
using the technology. While the applicant has made claims regarding 
reducing downstream diagnostic tests and avoiding inappropriate medical 
intervention by using the ISC-REST kit, it did not provide any studies 
or data regarding these claims. The applicant also made claims as to 
how the individual parts of the test impact care decisions, but 
similarly did not provide data to demonstrate this. For example, the 
applicant claimed that, in testing for several respiratory illnesses, 
the QIAstat-Dx Respiratory SARS-CoV-2 Panel will inform care decisions, 
but did not submit any evidence that this is the case. We also note 
that, because the applicant has not submitted evidence to demonstrate 
the utility of the ISC-REST kit, it seems that the additional tests 
outside of the ISCDx test could result in clinical burden and 
additional cost without demonstrated benefits.
---------------------------------------------------------------------------

    \316\ Ibid.
    \317\ Peacock, W.F. and Edward Jauch., ``Cardioembolic vs Large 
Artery Atherosclerotic Stroke: Can we answer Hobson's question?'', 
pre- publication manuscript.
    \318\ Jauch, Edward C., et al. ``Biomarkers of Acute Stroke 
Etiology (BASE) Study Methodology,'' May 5, 2017.
---------------------------------------------------------------------------

    With regard to the studies submitted on ISCDx, we are unsure 
whether they demonstrate or examine the impacts of using the test on 
patient care and clinical outcomes. The applicant did not submit 
evidence to demonstrate that a recurrent stroke did not happen, that 
the use of more invasive investigational or further diagnostic tools 
was avoided, or that there was an increase in appropriate treatment and 
recurrent stroke prevention protocols after using the test. In the 
study methodology paper by Jauch et al., the applicant did not include 
full survey results because they were not available at the time the 
application was submitted. Additionally, we are unsure how to interpret 
the results from the small BASE study for ISCDx because there are 
variations between the study methodology as explained in the Jauch, 
E.C. et al. paper and the way the studies were actually conducted. For 
example, while the study methodology as described in the Jauch et al., 
paper stated that the blood samples were kept at room temperature for 
up to 24 hours and then frozen,\319\ in the poster presentation by 
Jauch, E.C., the samples were frozen within 72 hours of 
collection.\320\ We also have concerns regarding the testing accuracy 
of the ISCDx test. In the BASE study results that were submitted on the 
ISCDx test, the sensitivity was 0.90 and specificity was 0.70 for a 
sample size of 218 survey subjects.\321\ Due to these figures, we 
question whether ISC-REST would alter the standard care ischemic stroke 
patients receive. Further, we note that the only trials submitted on 
the ISCDx test included patients whose cause of stroke was already 
determined. While the applicant claims that ISC-REST has the ability to 
stratify ischemic stroke patients early in the diagnosis process to 
reduce the number of cryptogenic stroke diagnoses and more 
appropriately manage stroke to reduce secondary recurrence, we question 
if there is sufficient evidence to evaluate this claim because the 
cause of stroke had already been determined in the study results the 
applicant submitted.
---------------------------------------------------------------------------

    \319\ Ibid.
    \320\ Jauch, Edward C., on behalf of BASE clinical trial 
principal investigators, ``RNA Expression for Diagnosis of Stroke 
Etiology Differentiating Large Artery and Cardioembolic Stroke: 
Analytical Validation of Testing From the BASE Clinical Trial,'' 
2020 AHA International Stroke Conference.
    \321\ Ibid.
---------------------------------------------------------------------------

    The applicant stated that there is no guideline standard of care 
pathway to determine cause of stroke, and uses this assertion as an 
underlying assumption for its claims in support of substantial clinical 
improvement. CMS notes that while there is room for clinicians to order 
certain additional tests over others depending on a patient's 
circumstances, there are algorithms developed by professional societies 
for the diagnosis and treatment of ischemic stroke.\322\ These best 
practices are updated frequently to reflect current clinical research, 
and detail prehospital care, urgent and emergency evaluation and 
treatment, and in-hospital management, including early secondary 
prevention measures. CMS notes that by assuming that there is no 
guideline standard of care to determine the cause of stroke, the 
applicant has not presented information to compare the technology 
against a standard of care or other technology to allow for an 
assessment of whether the technology is a substantial clinical 
improvement over existing technologies to diagnose the cause of stroke.
---------------------------------------------------------------------------

    \322\ Power, William J. ``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 Dec; 50:e344 
https://doi.org/10.1161/STR.0000000000000211.
---------------------------------------------------------------------------

    We are also unsure whether the way the ISC-REST test kit is used 
will limit its ability to impact any care decisions and prevent 
hospital use. Specifically, we question if the extended 30-hour window 
for obtaining the patient samples, as well as the added element of 
shipping the ISC-REST kit to a single laboratory, is in line with 
stroke protocols, which focus on diagnosing a stroke as quickly as 
possible to maximize patient outcomes. There has been extensive 
research regarding the time-outcome relationship for stroke; because 
brain cells die rapidly after the event of the stroke, effective 
treatment must start as early as possible.\323\ Since every minute 
matters in stroke treatment and secondary prevention, we believe that 
clinicians may order further diagnostic tests and begin a treatment 
plan before the ISC-REST kit results become available, which may limit 
the utility of the technology and its ability to impact care decisions. 
In other words, CMS questions whether ISC-REST would improve or alter 
the standard course of treatment for ischemic stroke due to the delay 
in receiving test results. We further note that sending the ISC-REST 
test kit to an external lab may cause a delay in COVID-19 test results 
as well. Therefore, we remain unclear as to the clinical benefit of 
combining these tests and are unsure how this potential for delay in 
results affects the technology's ability to impact care decisions.
---------------------------------------------------------------------------

    \323\ Harpaz, Dorin., et al., ``Point-of-Care-Testing in Acute 
Stroke Management: An Unmet Need Ripe for Technological Harvest,'' 
Biosensors (Basel), 2017 Sep; 7(3): 30. Published online 2017 Aug 3. 
DOI: 10.3390/bios7030030.

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

[[Page 25272]]

    The applicant also submitted various narrative responses claiming 
that testing for COVID-19 at the same time as testing for the cause of 
the ischemic stroke constitutes substantial clinical improvement over 
existing technologies. Regarding the applicant's claims that the ISC-
REST test kit is convenient for clinicians, CMS is unsure whether there 
is currently a need to order testing for COVID-19 along with the ISCDx 
test because, during the COVID-19 public health emergency, many 
hospitals automatically test for COVID-19 upon hospital admission to 
ensure proper treatment and containment. Further, CMS is unsure whether 
convenience for clinicians is evidence of substantial clinical 
improvement. With regard to the applicant's claim that, in its 
experience, clinical supporters of the ISC-REST kit claim that they 
would order ISC-REST kit testing 100% of the time versus ordering three 
separate tests, it is unclear whether clinical supporters of the ISC-
REST kit are representative of all providers, including those 
participating in Medicare. Similarly, the applicant did not provide 
evidence to support its claim that ISC-REST will help gather data on 
any connection between COVID-19 and stroke, including a tracking 
mechanism for how long COVID-19 antibodies last, such as how ISC-REST 
would be better at gathering data on COVID-19 and stroke than other 
COVID-19 diagnostics.
    Regarding the applicant's claims that knowing the results of all 
three tests in the ISC-REST kit, including COVID-19 status, impacts 
clinicians' choice of therapeutics for secondary stroke prevention or 
other treatment decisions, we are not sure that this conclusion can be 
reached as the connection between COVID-19 and stroke has not been 
established. As evidence of the connection between COVID-19 and stroke, 
the applicant claims that the cryptogenic rate is higher for stroke 
patients with COVID-19 than stroke patients without COVID-19 and 
references a study of one hospital, where 32 patients hospitalized for 
COVID-19 or positive for COVID-19 experienced an ischemic stroke during 
a one-month period of time in the spring of 2020. Other studies have 
been conducted researching the possible link between COVID-19 and 
stroke, including one study with a larger sample size, analyzing over 
27,000 participants across 54 health care facilities, that suggests 
that stroke in COVID-19 patients is infrequent, and is associated with 
typical stroke risk factors.\324\ Another study, analyzing data from 
close to 25,000 discharges from a large New York-based health care 
system from January to April 2020, did not identify a positive 
association between ischemic stroke and COVID-19.\325\ Based on the 
information that the applicant submitted, it is also unclear whether 
stroke treatment for an ischemic stroke patient, who is also COVID-19 
positive, would be different than for an ischemic stroke patient who is 
COVID-19 negative. For example, it is unclear whether a stroke patient 
would not receive antiplatelet or anticoagulative treatment due to a 
COVID-19 diagnosis. Because the connection between stroke and COVID-19 
is unclear and is still in the preliminary stages of research, we are 
unsure whether testing for the type of ischemic stroke as well as 
COVID-19 status is a substantial clinical improvement over existing 
technologies. As stated previously, the applicant did not submit 
studies or data on how using the ISC-REST kit has an impact on 
downstream treatment decisions or patient outcomes to determine whether 
knowing a patient's COVID-19 status and the type of ischemic stroke 
they experienced is a substantial clinical improvement over existing 
technologies. Furthermore, as there is research that casts doubt on the 
connection between COVID-19 and stroke,326 327 we question 
whether placing an emphasis on COVID-19 status and stroke may 
discourage a clinician from continuing to investigate the cause or 
treat an underlying predisposing condition for stroke, once the patient 
has recovered from COVID-19, and whether this could potentially lead to 
negative patient outcomes.
---------------------------------------------------------------------------

    \324\ Qureshi, et al. ``Acute Ischemic Stroke and COVID-19: An 
Analysis of 27,676 Patients,'' Stroke, 4 Feb 2021, https://www.ahajournals.org/doi/abs/10.1161/STROKEAHA.120.031786.
    \325\ Bekelis, et al. Ischemic Stroke Occurs Less Frequently in 
Patients With COVID-19: A Multicenter Cross-Sectional Study, Stroke, 
51(12):3570-3476, 27 Oct 2020, https://pubmed.ncbi.nlm.nih.gov/33106109/#affiliation-1.
    \326\ Qureshi, et al. ``Acute Ischemic Stroke and COVID-19: An 
Analysis of 27,676 Patients,'' Stroke, 4 Feb 2021, https://www.ahajournals.org/doi/abs/10.1161/STROKEAHA.120.031786. Qureshi, 
et al., 2021, Ibid.
    \327\ Bekelis, et al. Ischemic Stroke Occurs Less Frequently in 
Patients With COVID-19: A Multicenter Cross-Sectional Study, Stroke, 
51(12):3570-3476, 27 Oct 2020, https://pubmed.ncbi.nlm.nih.gov/33106109/#affiliation-1. Bekelis, et al., 2020, Ibid.
---------------------------------------------------------------------------

    We are inviting public comments on whether ISC-REST meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for ISC-REST.
j. Lifileucel
    Iovance Biotherapeutics submitted an application for new technology 
add-on payments for lifileucel for FY 2022. According to the applicant, 
lifileucel is a proprietary, one-time autologous Tumor Infiltrating 
Lymphocytes (TIL) cell-based therapy being studied for effectiveness in 
solid tumors. TIL cell therapy with lifileucel involves the adoptive 
cell transfer (ACT) of autologous T-cells directly isolated from the 
tumor tissue and expanded ex vivo without any prior selection or 
genetic modification. Tumor antigen-specific T-cells are located within 
tumor lesions, where a dysfunctional state and low numbers prevent them 
from effectively eradicating the tumor. By isolating autologous TIL 
from the tumor microenvironment and expanding them, the lifileucel 
manufacturing process produces large numbers of reinvigorated T-cells. 
Following the infusion of lifileucel, the TIL migrate back into the 
tumor, including metastases, where they trigger specific tumor cell 
killing upon recognition of tumor antigens.
    According to the applicant, relapsed and refractory metastatic 
melanoma presents a high unmet medical need with low survival rates and 
limited durable treatment options.\328\ Despite the advances in 
available treatments, responses in patients with metastatic melanoma 
are at times inadequate, with many patients either not responding (40% 
to 65%) 329 330 or displaying primary or acquired resistance 
(>70%) and the disease progresses.331 332 333 334 335 The 
applicant

[[Page 25273]]

stated there are currently no approved agents for the treatment of 
patients with metastatic melanoma who fail available standard-of-care 
therapies, which include immune checkpoint inhibitors (ICI) and BRAF/
MEK inhibitors. According to the applicant, the only commonly used 
available therapy for these patients post progression is chemotherapy. 
The applicant stated that as demonstrated in the literature referenced 
previously, retreatment with chemotherapy 336 337 338 or 
experimental combined ICIs \339\ offers a poor Objective Response Rate 
(ORR) \340\ of 4%-10%,341 342 a median PFS of 2.7-3.7 months 
343 344 345 and a median OS of ~7-8 
months.346 347
---------------------------------------------------------------------------

    \328\ Sarnaik A, et al. Safety and efficacy of lifileucel (LN-
144) tumor infiltrating lymphocyte therapy in metastatic melanoma 
patients after progression on multiple therapies--independent review 
committee data update. Poster presented at SITC 2019. Poster Number: 
P865 and abstract; Journal: J Immunotherapy Cancer 2020;8:A12.
    \329\ Mooradian MJ and Sullivan RJ. What to do when anti-PD-1 
therapy fails in patients with melanoma. Oncology (Williston Park) 
2019;33:141-8.
    \330\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
    \331\ Luke JJ, et al. Targeted agents and immunotherapies: 
Optimizing outcomes in melanoma. Nature Reviews Clinical Oncology. 
Doi:10.1038/ncrclinonc.2017.43. Published online April 4, 2017.
    \332\ Mooradian MJ and Sullivan RJ. What to do when anti-PD-1 
therapy fails in patients with melanoma. Oncology (Williston Park) 
2019;33:141-8.
    \333\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
    \334\ Schachter J, et al. Pembrolizumab versus ipilimumab for 
advanced melanoma: Final overall survival results of a multicenter, 
randomized, open-label phase 3 study (KEYNOTE-006). Lancet 2017; 
390:1853-62.
    \335\ Ugurel S, et al. Survival of patients with advanced 
metastatic melanoma: The impact of novel therapies-update 2017. Eur 
J Cancer 2017; 83:247-257.
    \336\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
    \337\ Larkin J, et al. Overall survival in patients with 
advanced melanoma who received nivolumab versus investigator's 
Choice chemotherapy in CheckMate 037: A randomized, controlled, 
open-label Phase III trial. J Clin Oncol 2018;36:383-90.
    \338\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol. 2015; 16(8): 
908-18.
    \339\ Kirchberger MC, et al. Combined low-dose ipilimumab and 
pembrolizumab after sequential ipilimumab and pembrolizumab failure 
in advanced melanoma. Eur J Cancer. 2016;65:182-184. doi:10.1016/
j.ejca. 2016.07.003.
    \340\ As used by the applicant and the studies provided, 
Objective Response Rate (ORR) is the combination of Complete and 
Partial Responses.
    \341\ Larkin J, et al. Overall survival in patients with 
advanced melanoma who received nivolumab versus investigator's 
Choice chemotherapy in CheckMate 037: A randomized, controlled, 
open-label Phase III trial. J Clin Oncol 2018;36:383-90.
    \342\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol. 2015; 16(8): 
908-18.
    \343\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
    \344\ Larkin J, et al. Overall survival in patients with 
advanced melanoma who received nivolumab versus investigator's 
Choice chemotherapy in CheckMate 037: A randomized, controlled, 
open-label Phase III trial. J Clin Oncol 2018;36:383-90.
    \345\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol. 2015; 16(8): 
908-18.
    \346\ Kirchberger MC, et al. Combined low-dose ipilimumab and 
pembrolizumab after sequential ipilimumab and pembrolizumab failure 
in advanced melanoma. Eur J Cancer. 2016;65:182-184. doi:10.1016/
j.ejca. 2016.07.003.
    \347\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that 
they are currently awaiting FDA approval of the Biologics License 
Application (BLA) for lifileucel as an autologous TIL immunotherapy 
indicated for the treatment of patients with unresectable or metastatic 
melanoma who have been previously treated with at least one systemic 
therapy, including a PD-1 blocking antibody and, if BRAF V600 mutation 
positive, a BRAF inhibitor or BRAF inhibitor with MEK inhibitor. The 
applicant stated that currently, there are no ICD-10-PCS procedure 
codes to uniquely identify procedures involving lifileucel. We note 
that the applicant has submitted a request for approval for a unique 
ICD-10-PCS code for the administration of lifileucel beginning in FY 
2022.
    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 lifileucel is not the same or similar to the 
mechanism of action of currently available products used in the 
treatment of advanced melanoma. According to the applicant, prior to 
2011, the most common first-line treatment for patients with Stage III 
unresectable or Stage IV unresectable metastatic melanoma was single-
agent therapy using dacarbazine (DTIC) or another alkylating agent, or 
combination chemotherapy using DTIC together with a platinum-based drug 
such as carboplatin and/or a microtubule inhibitor such as 
paclitaxel.348 349 350 IL-2 therapy has also been used as 
part of a biochemotherapy (BCT) antineoplastic regimen. The applicant 
asserted that since 2011, treatment options for advanced-stage melanoma 
have included kinase inhibitors such as BRAF and MEK inhibitors, 
cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed 
cell-death protein 1 (PD-1) blocking antibodies. According to the 
applicant, the currently available first and second line treatments for 
advanced melanoma include kinase inhibitors (BRAF and MEK inhibitors) 
and ICIs (anti-CTLA-4 antibody and anti-PD1 antibody).\351\ The 
applicant asserts that there are no approved treatment options for 
patients with metastatic melanoma that have progressed after two lines 
of therapy.
---------------------------------------------------------------------------

    \348\ Gogas HD, et al. The role of taxanes in the treatment of 
metastatic melanoma. Melanoma Res. 2004;14(5): 415-420.
    \349\ Yang AS and Chapman PB. The history and future of 
chemotherapy for melanoma. Hematol Oncol Clin North Am. 2009;23(3): 
583-597.
    \350\ Yushak M, et al. Advances in the systemic treatment of 
metastatic melanoma. Oncology (Williston Park). 2013; 27(5).
    \351\ Luke JJ, et al. Targeted agents and immunotherapies: 
Optimizing outcomes in melanoma. Nature Reviews Clinical Oncology. 
Doi:10.1038/ncrclinonc.2017.43. Published online April 4, 2017.
---------------------------------------------------------------------------

    According to the applicant, TIL cell therapy with lifileucel uses a 
novel and distinct mechanism of action which delivers a highly 
customized, personalized, and targeted treatment for unresectable or 
metastatic melanoma. Lifileucel TIL cell therapy involves the ACT of 
autologous T-cells directly isolated from the patient's tumor tissue 
and expanded ex vivo. Following the infusion of lifileucel, the TIL 
migrates back into the patient's tumor deposits, including metastases, 
where they trigger specific tumor cell killing upon recognition of 
tumor antigens. According to the applicant, after approval, lifileucel 
will be the only personalized, cellular therapy indicated for the 
treatment of unresectable or metastatic melanoma.
    The applicant asserted TIL cell therapy with lifileucel is also 
highly differentiated from currently approved chimeric antigen receptor 
(CAR) T-cell therapies which treat liquid tumors: YESCARTA[supreg] 
(axicabtagene ciloleucel) and KYMRIAH[supreg] (tisagenlecleucel), both 
approved for the treatment of large B-cell lymphoma in adults, and 
recently approved TECARTUSTM (brexucabtagene autoleucel) 
indicated for the treatment of relapsed/refractory mantle cell lymphoma 
(MCL). According to the applicant, CAR T-cell therapies mainly target 
only single/surface tumor antigens, versus TIL cell therapy which 
targets multiple tumor antigens. The applicant stated that there are no 
examples of successful utility of CAR T-cell therapy in solid tumors. 
The applicant further stated that the TIL mechanism of action does not 
rely on genetically engineered receptors, but maintains some 
physiologic control and therefore avoids hyperactivation that may be 
responsible for complications from CAR T-cell therapy such as cytokine 
release syndrome (CRS) or neurotoxicity.\352\ Per the applicant,

[[Page 25274]]

there have been no off-tissue effects found to date following treatment 
with TIL cell therapy, and TIL therefore offers a differentiated safety 
profile compared to CAR T-cell products or ICIs and confirms the 
mechanism of action differentiation discussed previously.
---------------------------------------------------------------------------

    \352\ Fardis M, et al. Current and future directions for tumor 
infiltrating lymphocyte therapy for the treatment of solid tumors. 
Cell and Gene Therapy Insights, 2020; 6(6), 855-863.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or different MS-DRG, the applicant stated that CMS has not 
yet determined the MS-DRG mapping for cellular therapies such as 
lifileucel. The applicant asserted that while TIL cell therapy is 
different from CAR T-cell therapy mechanistically, from tumor (solid 
vs. liquid) activity, and from a safety perspective, there are other 
similarities that support grouping the two technologies into a common 
MS-DRG for autologous T-cell immunotherapy. The applicant asserted that 
both CAR T-cell and TIL require collection of a patient's lymphocyte 
cells which are the core component of a complicated and lengthy 
manufacturing process to produce a patient-specific therapeutic dose. 
The applicant added that both are primarily administered in a hospital 
inpatient setting because of the risk of significant but treatable 
adverse events. Lastly, the applicant stated because of the complex 
process required to develop a personalized treatment and the total cost 
of caring for patients who have received TIL cell therapy that is 
similar to CAR T-cell therapy, these cases are expected to be 
comparably resource intensive.
    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 with FDA approval, lifileucel will be the only FDA-approved 
cellular treatment for patients with unresectable or metastatic 
melanoma who have been previously treated with at least one systemic 
therapy.
    Based on the information provided by the applicant, we have several 
questions with regard to the newness criterion. With respect to the 
first criterion for substantial similarity, we note 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. The applicant asserted that CAR T-cell therapies and TIL 
therapies can be differentiated by multiple criteria as listed 
previously. We are seeking public comment on whether the mechanism of 
action for lifileucel is different from existing therapies, in 
particular whether the distinguishing criteria identified by the 
applicant are sufficient to differentiate the mechanism of action of 
TIL from CAR T-cell therapies.
    We are inviting public comments on whether lifileucel is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    With regard to the cost criterion, the applicant provided the 
following analysis to demonstrate the technology meets the cost 
criterion. The applicant conducted multiple analyses to include a 
primary cohort, a cohort with a principle or admitting ICD-10 diagnosis 
of melanoma and metastasis and a cohort with any ICD-10 diagnosis of 
melanoma and metastasis. The ICD-10 codes and MS-DRGs identified by the 
applicant (for the primary cohort) are listed in the following tables.
[GRAPHIC] [TIFF OMITTED] TP10MY21.156

    To conduct the primary analysis, the applicant identified a cohort 
of patients that would be eligible for lifileucel that met the criteria 
of having any ICD-10 diagnosis of melanoma from the following table, 
and any ICD-10 diagnosis of metastasis from the following table, and 
any ICD-10 procedure code indicating administration of IL-2 or other 
chemotherapy via central or peripheral vein from the following table.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TP10MY21.157


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[GRAPHIC] [TIFF OMITTED] TP10MY21.158


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[GRAPHIC] [TIFF OMITTED] TP10MY21.160

[GRAPHIC] [TIFF OMITTED] TP10MY21.161

BILLING CODE 4120-01-C
    The applicant used the FY 2019 MedPAR file dataset with the FY 2019 
Final Rule with Correction Notice IPPS Impact File and the FY 2022 New 
Technology Thresholds to perform their cost analyses. Using the FY 2019 
MedPAR file dataset, the applicant's search resulted in the 
identification of 20 MS-DRGs to which cases in the primary cohort 
mapped, as previously listed. The applicant provided two sensitivity 
cohorts: (1) A principal or admitting ICD-10 diagnosis of melanoma and 
metastasis; and (2) any ICD-10 diagnosis of melanoma and metastasis. 
The applicant stated that the analysis was limited to Medicare 
discharges from facilities paid under the IPPS by only including 
hospitals listed in the FY 2019 Final Rule IPPS Impact File. The 
previously discussed criteria resulted in 220 claims from 20 MS-DRGs in 
the primary cohort, 1,052 claims from 79 MS-DRGs in the sensitivity 
cohort 1, and 6,988 claims from 369 MS-DRGs in sensitivity cohort 2. 
The applicant imputed a case count of 11 for those MS-DRGs with fewer 
than 11 cases, which per the applicant resulted in a significantly 
higher case count than if it used the actual case counts. The applicant 
stated that imputing the cases did not change the results of the charge 
threshold analyses presented below, and the final inflated average 
case-weighted standardized charge per case exceeded the case-weighted 
threshold in all scenarios regardless of whether the actual case count 
or minimimum case count of 11 is used. For each cohort, the applicant 
provided multiple analyses, by first using the threshold from each MS-
DRG included, second using the MS-DRG 018 threshold for all included 
MS-DRGs and the national pharmacy CCR (0.187) to calculate charges, and 
lastly using the MS-DRG 018 threshold for all included MS-DRGs and the 
applicant-calculated CAR T-cell CCR (0.314) to calculate charges. For 
example, in the first analysis, the applicant used a threshold amount 
of $62,724 for MS-DRG 838 but in second and third analyses the 
applicant used a threshold of $1,251,126 for MS-DRG 838 (the same 
threshold for MS-DRG 018). The applicant first calculated a case 
weighted threshold of $70,220, $72,889, and $67,947 for the primary, 
sensitivity one, and sensitivity two cohorts respectively based on a 
case-weighted average of the threshold amounts for the MS-DRGs to which 
the cases identified based on the claims data search mapped. The 
applicant calculated a case weighted threshold of $1,251,126 for all 
secondary calculations where the MS-DRG 018 threshold was applied for 
all MS-DRGs identified. We note, in section II.D. of this proposed 
rule, we are proposing to assign other immunotherapies MS-DRG 018 (for 
example Introduction of lifileucel immunotherapy into peripheral vein, 
percutaneous approach, new technology group 7), in addition to CAR T-
cell therapies. Therefore, it seems the appropriate threshold for 
comparison is that of MS-DRG 018, with an average case-weighted 
threshold amount of $1,251,126.
    For the analyses using the MS-DRG 018 thresholds, to calculate the 
average charge per case, the applicant used the cases identified based 
on the claims data search and mapped them to the MS-DRG 018 threshold. 
To determine the charges for lifileucel, the applicant converted cost 
to charges by dividing by the FY 2021 IPPS/LTCH PPS final rule national 
average pharmacy CCR of 0.187, and in secondary analyses, by a CAR T-
cell CCR of 0.314 calculated by the applicant. To estimate the CAR T-
cell CCR, the applicant obtained the MS-DRG 018 arithmetic mean charge 
in the AOR/BOR FY2021 Proposed Rule File released by CMS ($1,387,946). 
The applicant subtracted publicly reported non-drug charges for 
TECARTUS of $201,610 from the total arithmetic mean charge to estimate 
CAR T-cell charges (approximately $1,186,336). The applicant then 
divided a CAR T-cell wholesale acquisition cost of $373,000 (WAC for 
those CAR T-cell products approved as of FY 2019) by the estimated CAR 
T-cell charges, to estimate a CAR T-cell CCR of 0.314 (CCR = 373,000/
1,186,336).
    The applicant stated no charges were removed for the prior 
technology because previous treatments will continue to be reflected in 
cases where

[[Page 25279]]

lifileucel is administered. Next the applicant calculated the average 
standardized charge per case using the FY 2019 IPPS/LTCH PPS final rule 
Impact file. The 2-year inflation factor of 13.2% (1.13218) was 
obtained from the FY 2021 IPPS/LTCH PPS final rule and applied to the 
average standardized charge per case.
    The applicant calculated the final inflated average case-weighted 
standardized charge per case by adding the estimated charges for the 
technology to the inflated average standardized charge per case. The 
applicant determined a final inflated average case-weighted 
standardized charge per case of $2,188,043 and $1,355,334 from the 
primary cohort, pharmacy and CAR T-cell CCR analyses with CAR T-cell 
thresholds respectively, which both exceed the average case-weighted 
threshold amount of $1,251,126.
    The applicant determined a final inflated average case-weighted 
standardized charge per case of $2,134,830 and $1,302,121 from the 
sensitivity cohort one using the pharmacy and CAR T-cell CCR analyses 
with CAR T-cell thresholds respectively, which both exceed the average 
case-weighted threshold amount of $1,251,126.
    The applicant determined a final inflated average case-weighted 
standardized charge per case of $2,131,524 and $1,298,815 from the 
sensitivity cohort two using the pharmacy and CAR T-cell CCR analyses 
with CAR T-cell thresholds respectively, which both exceed the average 
case-weighted threshold amount of $1,251,126. Because the final 
inflated average case-weighted standardized charge per case for all the 
analyses exceeded the average case-weighted threshold amount, the 
applicant maintained that the technology meets the cost criterion.
    Based on the information provided by the applicant, we have the 
following concerns regarding the cost analysis.
    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 are 
uncertain how representative this data is for use in the applicant's 
cost analyses given this potential for variability.
    The applicant also uses both ICD-10 diagnosis code categories and 
subcategories which are not valid diagnosis codes and therefore, not 
appropriate to include for purposes of the cost analysis. There is a 
potential that inappropriately including ICD-10 diagnosis code 
categories and subcategories may alter the number of cases identified 
for inclusion in the cost analysis. We are seeking public comment on 
whether this issue may affect the cost analysis.
    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 invite public comments on whether 
lifileucel meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that lifileucel represents a substantial clinical 
improvement over existing technologies. In support of this assertion, 
the applicant provided data from two cohorts of the C-144-01 study, an 
ongoing phase 2, multicenter study (NCT02360579) consisting of four 
cohorts:
     Cohort 1 (n=30 generation 1 non-cryopreserved TIL 
product), not included for review as part of the applicant's new 
technology add-on payment application.
     Cohort 2 (n=60 generation 2 cryopreserved TIL product), 
included for review as part of the applicant's new technology add-on 
payment application.
     Cohort 3 (a sub-sample of n=10 from cohorts 1, 2, and 4), 
not included for review as part of the applicant's new technology add-
on payment application.
     Cohort 4 (n=75 generation 2 cryopreserved TIL product), 
included for review as part of the applicant's new technology add-on 
payment application and also provided to the FDA as part of the 
applicant's BLA application.
    The applicant stated that C-144-01 (NCT02360579) is a multi-cohort, 
Phase 2 clinical trial evaluating the safety and efficacy of lifileucel 
in patients that have been diagnosed with unresectable or metastatic 
Stage IIIc or IV melanoma. In addition to what the applicant previously 
described, the authors stated that in a sub-group analysis of 42 
patients who were primary refractory to anti-PD-1, the ORR was 40.5% 
comparable to the overall cohort.
    According to the applicant, the primary objective of this study was 
to evaluate the efficacy of lifileucel in patients with unresectable or 
metastatic melanoma using the objective response rate (ORR), as 
assessed by the independent review committee (IRC) per Response 
Evaluation Criteria in Solid Tumors (RECIST) version 1.1.\353\ The 
applicant added that secondary objectives were to: (1) Evaluate the 
efficacy endpoints of duration of response (DOR), disease control rate 
(DCR), and progression free survival (PFS); (2) further evaluate the 
efficacy of lifileucel in patients with unresectable or metatstatic 
melanoma by assessing ORR, DOR, DCR, and PFS; (3) to evaluate overall 
survival (OS); and (4) to characterize the safety profile of 
lifileucel. For cohort 2, 60 patients were determined to allow 
estimation of the ORR using the maximum half width of the two-sided 95% 
confidence limit of less than 13.2% when ORR is expected to range from 
20-50%. For cohort 4, approximately 75 patients were planned to be 
infused based on the null hypothesis of 10% ORR (based on historical 
control) which resulted in over 90% power to demonstrate superiority to 
this control. Patients included in this study were 18 years or older, 
had an ECOG (Eastern Cooperative Oncology Group) performance status of 
0 or 1 upon entry, an estimated life expectancy of less than or equal 
to 3 months, and had unresectable or metastatic melanoma (stage IIIC or 
IV) treated with at least one prior systemic therapy including an anti-
PD-1 antibody and a BRAF/MEK inhibitor. Patients were required to have 
a washout period of at least 28 days from prior anticancer therapy(ies) 
to the start of the planned nonmyeloablative lymphodeletion (NMA-LD) 
preconditioning regimen. The applicant explained that prior to the 
infusion of lifileucel, the patient receives NMA-LD with 
cyclophosphamide (60 mg/kg) intravenously daily for 2 days followed by 
fludarabine (25 mg/m\2\) intravenously for 5 days to eliminate 
potentially suppressive immune cells which support the tumor and to 
maximize engraftment and potency of the lifileucel therapy through 
homeostatic proliferation.\354\
---------------------------------------------------------------------------

    \353\ Eisenhauer EA, et al. New response evaluation criteria in 
solid tumours: Revised RECIST guideline (version 1.1). European 
Journal of Cancer. 45 (2009) 228-247.
    \354\ Rosenberg, SA and Restifo, N. Adoptive cell transfer as 
personalized immunotherapy for human cancer, Science. 2015;348 
(6230):62-68.
---------------------------------------------------------------------------

    The applicant stated that the patients in this study had a high 
tumor burden at baseline and had received a mean of 3.3 lines (range, 
1-9) of prior therapies. Twenty-eight patients (42%) had liver and/or 
brain lesions at baseline. Each prior line of therapy was defined as 
any

[[Page 25280]]

concomitant therapy given to the patient even if more than one target 
for each treatment was involved.\355\ The applicant added that 77% of 
patients had progressed on prior anti-CTLA-4 blockade therapy, 99% had 
progressed on prior anti-PD-1/PD-L1 therapy, and 23% had received BRAF/
MEK inhibitors. All patients had received PD on their prior therapy 
before study entry.
---------------------------------------------------------------------------

    \355\ Ghate S, et al. Patterns of treatment and BRAF testing 
with immune checkpoint inhibitors and targeted therapy in patients 
with metastatic melanoma presumed to be BRAF positive. Melanoma Res 
2019;29:301-10.
---------------------------------------------------------------------------

    As justification for the null hypothesis of ORR less than or equal 
to 10%, the applicant stated that according to the NCCN guideline for 
metastatic melanoma, the only approved treatment is dacarbazine (DTIC) 
whereas other agents such as carboplatin, paclitaxel, docetaxel, nab-
paclitaxel, and temozolomide are not approved by the FDA and are not 
appropriate as comparators. The applicant next presented the results 
from four studies which had at least one treatment arm receiving DTIC: 
(1) An abstract of a sample with metastatic melanoma previously treated 
with post-anti-PD-1 (no prior BRAF/MEK, metastatic melanoma) which 
resulted in a 10% ORR in the DTIC arm; \356\ (2) a sample with advanced 
melanoma previously treated with post-ipilimumab (+/- BRAF inhibitor) 
which resulted in a 10.6% ORR in the DTIC arm, (3) a sample of 
treatment-na[iuml]ve patients with unresectable stage IIIc or IV 
melanoma which resulted in a 9.8% ORR in the DTIC arm,\357\ and (4) a 
sample of chemo-na[iuml]ve patients with metastatic melanoma of which 
9% had received prior therapy for metastatic disease which resulted in 
an 11% ORR in the DTIC arm.\358\ The applicant stated that the 
historical control ORR of 10% for advanced melanoma was used for two 
reasons. First, the results from the first study (post-anti-PD-1) \359\ 
most closely represent patients in the C-144-01 study because they 
received prior anti-PD-1 treatment while the other studies did not. 
Second, the applicant stated that response rates to chemotherapy, 
including DTIC, in recent phase 3 melanoma trials ranged from 4% to 
10%.\360\ \361\ Also included in the application is a summary of 
results from six studies in patients treated with a DTIC monotherapy in 
advanced or metastatic melanoma prior to checkpoint inhibitor FDA 
approval which showed ORRs ranging from 5%-20%.
---------------------------------------------------------------------------

    \356\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
    \357\ Ribas A, et al. Phase III randomized clinical trial 
comparing tremelimumab with standard-of-care chemotherapy in 
patients with advanced melanoma. J Clin Oncol. 2013;31(5):616-622.
    \358\ Hersh EM, et al. A randomized, controlled phase III trial 
of nab-Paclitaxel versus dacarbazine in chemotherapynaive patients 
with metastatic melanoma. Ann Oncol. 2015;26(11):2267-2274.
    \359\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
    \360\ NCCN Clinical Guidelines in Oncology (NCCN Guidelines. 
Cutaneous Melanoma. Versions 2018 and 2019. https://www.nccn.org/professionals/physician_gls/#site.
    \361\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol. 2015; 16(8): 
908-18.
---------------------------------------------------------------------------

    Next, the applicant discussed the efficacy results from the C-144-
01 study. The applicant stated that regardless of location of tumor 
resected and BRAF mutational status, and across ages (20-79), patients 
responded to lifileucel therapy. Among patients in cohort 2 (n=66) 
there was an ORR of 36% (95% CI 25, 49) and a DCR of 80% (95% CI 69, 
89). When considering best overall response, two patients (3%) achieved 
complete response (CR), 22 patients (33%) achieved partial response 
(PR), 29 patients (44%) achieved stable disease, 9 patients (14%) had 
progressive disease, and 4 patients (6%) were non-evaluable. The 
applicant highlighted that the ORR (36.5% for those less than 65 years 
and 35.7% for those 65 and older) and DCR (71.2% for those less than 65 
years and 78.6% for those 65 and older) were consistent across age 
groups. The applicant contends that these results following the one-
time, single infusion of lifileucel represent a substantial improvement 
over chemotherapy which offers poor ORR of 4%-10%.\362\ \363\
---------------------------------------------------------------------------

    \362\ Larkin J, et al. Overall survival in patients with 
advanced melanoma who received nivolumab versus investigator's 
Choice chemotherapy in CheckMate 037: a randomized, controlled, 
open-label Phase III trial. J Clin Oncol 2018;36:383-90.
    \363\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol. 2015; 16(8): 
908-18.
---------------------------------------------------------------------------

    Next, the applicant asserted that, because the median duration of 
response (DOR) had not been reached at a median follow-up of 18.7 
months, the treatment effect will be durable and provide long-term 
benefit to those treated with lifileucel. The applicant stated that at 
the median follow-up, 50% (n=12) of responders showed ongoing response 
to lifileucel. The applicant added that the median DOR for treatment 
with DTIC is 5 to 6 months \364\ \365\ and that retreatment with an 
immune checkpoint inhibitor or chemotherapy has demonstrated a median 
overall survival of around 7-8 months.\366\ \367\
---------------------------------------------------------------------------

    \364\ Gogas HJ, et al. Chemotherapy for metastatic melanoma: 
Time for a change? Cancer 2007;109:455-64.
    \365\ Serrone L, et al. Dacarbazine-based chemotherapy for 
metastatic melanoma: Thirty-year experience overview. J Exp Clin 
Cancer Res 2000;19: 21-34.
    \366\ Kirchberger MC, et al. Combined low-dose ipilimumab and 
pembrolizumab after sequential ipilimumab and pembrolizumab failure 
in advanced melanoma. Eur J Cancer. 2016;65: 182-184. doi:10.1016/
j.ejca. 2016.07.003.
    \367\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 2018;36:e21588-e.
---------------------------------------------------------------------------

    Lastly, the applicant stated that the safety profile of lifileucel 
was consistent with the underlying advanced disease and the known 
toxicities associated with the single course of lymphodepleting 
preconditioning regimen and IL-2. The applicant stated that all 
patients experienced at least one treatment-emergent adverse event 
(TAEA) during the course of the study with the most common adverse 
event of any grade being hematologic along with chills, pyrexia, 
fatigue, tachycardia, and hypotension.\368\ The applicant added that 
the most common grade \3/4\ TEAEs included thrombocytopenia (82%), 
anemia (56%), febrile neutropenia (55%), neutropenia (39%), 
hypophosphatemia (35%), leukopenia (35%), and lymphopenia (32%),\369\ 
which were consistent with the lymphodepletion regimen and known 
profile of IL-2.\370\ \371\ \372\ One patient died due to intra-
abdominal hemorrhage reported as possibly related to TIL and one due to 
acute respiratory failure

[[Page 25281]]

assessed as not related to TIL.\373\ The applicant stated that there 
was no difference in the incidence of TEAEs (for example any grade, 
among grades 3 to 4, and among grade 5) in patients 65 or older as 
compared to those younger than 65. Furthermore, the applicant stated 
that AEs occurred and generally resolved within the first 14 days 
following TIL infusion and IL-2 administration, during which time 
patients typically remained in the inpatient setting.
---------------------------------------------------------------------------

    \368\ Sarnaik A, et al. Long-term follow up of lifileucel (LN-
144) cryopreserved autologous tumor infiltrating lymphocyte therapy 
in patients with advance melanoma progressed on multiple prior 
therapies. Oral presentation at ASCO2020. Abstract Number: 10006; 
Journal: J Clin Oncol 38:2020.
    \369\ Sarnaik A, et al. Long-term follow up of lifileucel (LN-
144) cryopreserved autologous tumor infiltrating lymphocyte therapy 
in patients with advance melanoma progressed on multiple prior 
therapies. Oral presentation at ASCO2020. Abstract Number: 10006; 
Journal: J Clin Oncol 38:2020.
    \370\ Rosenberg SA, et al. Durable complete responses in heavily 
pretreated patients with metastatic melanoma using Tcell transfer 
Immunotherapy. Clinical Cancer Research. 2011; 17(13):4550-4557. 
doi:10.1158/1078-0432.CCR-11-0116. 2,75,101
    \371\ Goff SL, et al. Randomized, prospective evaluation 
comparing intensity of lymphodepletion before adoptive transfer of 
tumor-infiltrating lymphocytes for patients with metastatic 
melanoma. J Clin Oncol. 2016 Jul 10;34(20):2389-97. PubMed PMID: 
27217459. Pubmed Central PMCID:PMC4981979.
    \372\ Dudley ME, et al. Adoptive cell therapy for patients with 
metastatic melanoma: Evaluation of intensive myeloablative 
chemoradiation preparative regimens. J Clin Oncol. 2008; 26(32): 
5233-5239.
    \373\ Sarnaik A, et al. Long-term follow up of lifileucel (LN-
144) cryopreserved autologous tumor infiltrating lymphocyte therapy 
in patients with advance melanoma progressed on multiple prior 
therapies. Oral presentation at ASCO2020. Abstract Number: 10006; 
Journal: J Clin Oncol 38:2020.
---------------------------------------------------------------------------

    In support of its claims regarding substantial clinical 
improvement, the applicant submitted four additional pieces of 
evidence.\374\ \375\ \376\ \377\ First is an article which describes 
the tumor-infiltrating lymphocytes (TIL) manufacturing process, the 
mechanism of action of these products, what the authors identify as 
clear advantages of TIL in the treatment of solid tumors, and lastly 
the results of C-144-01.\378\ The authors stated that this onetime 
autologous treatment involves a product individually derived for each 
patient, is not selected for the recognition of shared antigens that 
would be expressed in normal tissues, and is specific to the tumor 
neoantigens, reducing the risk for autoimmune toxicity. The authors 
also stated that the TIL mechanism of action does not rely on 
engineered receptors but maintains some physiologic control and avoids 
hyperactivation, which therefore suggests that TIL offers a different 
safety profile compared to CAR T-cell products or ICIs.
---------------------------------------------------------------------------

    \374\ Fardis M, et al. Current and future directions for tumor 
infiltrating lymphocyte therapy for the treatment of solid tumors. 
Cell and Gene Therapy Insights, 2020; 6(6), 855-863.
    \375\ Sarnaik A, et al. Long-term follow up of lifileucel (LN-
144) cryopreserved autologous tumor infiltrating lymphocyte therapy 
in patients with advance melanoma progressed on multiple prior 
therapies. Oral presentation at ASCO2020. Abstract Number: 10006; 
Journal: J Clin Oncol 38:2020.
    \376\ Sarnaik A, et al. Safety and efficacy of lifileucel (LN-
144) tumor infiltrating lymphocyte therapy in metastatic melanoma 
patients after progression on multiple therapies--independent review 
committee data update. Poster presented at SITC 2019. Poster Number: 
P865 and abstract; Journal: J Immunotherapy Cancer 2020;8:A12. 
Sarnaik, et al. SITC 2019
    \377\ Sarnaik A, et al. Lifileucel therapy leads to durable 
response in heavily pretreated, refractory, advanced melanoma. 
Poster presented at SMR 2019. Pending publication; online access: 
Advanced Melanoma, Practice Update, March 11, 2020.
    \378\ Fardis M, et al. Current and future directions for tumor 
infiltrating lymphocyte therapy for the treatment of solid tumors. 
Cell and Gene Therapy Insights, 2020; 6(6), 855-863.
---------------------------------------------------------------------------

    The second piece of evidence provided by the applicant is a 
presentation given at the 2020 ASCO annual meeting \379\ which, per the 
applicant, focused on the C-144-01 study design, overview, patient 
procedures, TIL manufacturing, and patient characteristics of cohort 2. 
The presentation asserts, as the applicant has previously, that there 
are currently no approved agents for patients with metastatic melanoma 
whose disease progressed after ICIs and BRAF/MEK inhibitors. The 
presentation repeats study design, patient characteristics of cohort 2, 
safety outcomes, and efficacy outcomes, as previously described by the 
applicant. The presentation states that the adverse event profile was 
consistent with the underlying advanced disease and the safety profile 
of the lymphodepletion and IL-2 regimens and adds that the median 
number of IL-2 doses administered was six. The author concluded that 
lifileucel had demonstrated potential efficacy and durability of 
response for patients with metastatic melanoma and that it represented 
a viable therapeutic option warranting further investigation (that is, 
pivotal Cohort 4).
---------------------------------------------------------------------------

    \379\ Sarnaik A, et al. Long-term follow up of lifileucel (LN-
144) cryopreserved autologous tumor infiltrating lymphocyte therapy 
in patients with advance melanoma progressed on multiple prior 
therapies. Oral presentation at ASCO2020. Abstract Number: 10006; 
Journal: J Clin Oncol 38:2020.
---------------------------------------------------------------------------

    The applicant next submitted an abstract from a poster presentation 
\380\ that discusses the TIL manufacturing process and the previously 
discussed study C-144-01. The presentation adds that tumors resected at 
local institutions were processed in central Good Manufacturing 
Practice (GMP) facilities for TIL production in a 22-day process. Final 
TIL infusion product was cryopreserved and shipped to sites. Patients 
received one week of cyclophosphamide/fludarabine preconditioning 
lymphodepletion, a single lifileucel infusion, followed by up to 6 
doses of IL-2. The authors conclude by stating that response per IRC 
assessment and concordance between investigator read ORR and IRC will 
be reported.
---------------------------------------------------------------------------

    \380\ Sarnaik A, et al. Safety and efficacy of lifileucel (LN-
144) tumor infiltrating lymphocyte therapy in metastatic melanoma 
patients after progression on multiple therapies--independent review 
committee data update. Poster presented at SITC 2019. Poster Number: 
P865 and abstract; Journal: J Immunotherapy Cancer 2020;8:A12.
---------------------------------------------------------------------------

    Lastly, the applicant submitted a peer-reviewed and published post 
summary presented at the Society for Melanoma Research 2019 annual 
meeting \381\ that discusses the results of the C-144-01 study as 
previously discussed by the applicant and other presentations. The 
author added that TIL therapy uses a patient's own immune cells to 
attack cancer. Tumor-infiltrating lymphocyte cells are extracted from a 
patient's own tumor tissue, expanded through a proprietary process, and 
infused back into the patient. After infusion, tumor-infiltrating 
lymphocytes reach tumor tissue, where they attack tumor cells. Lastly 
the author concluded that lifileucel treatment resulted in a 36.4% 
overall response rate with a median duration of response having not 
been reached after a median of one year in patients with heavily 
pretreated metastatic melanoma with high baseline disease burden who 
received prior anti-PD-1 and BRAF/MEK inhibitors.
---------------------------------------------------------------------------

    \381\ Sarnaik A, et al. Lifileucel therapy leads to durable 
response in heavily pretreated, refractory, advanced melanoma. 
Poster presented at SMR 2019. Pending publication; online access: 
Advanced Melanoma, Practice Update, March 11, 2020.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns concerning the substantial clinical improvement 
criterion. We note that results provided by the applicant are based on 
an ongoing phase two trial, C-144-01, and that these are potentially 
partial results from which we may not be able to draw end conclusions. 
We also note the potential for overestimating treatment effects when 
trials stop early or report interim results.\382\ \383\ \384\
---------------------------------------------------------------------------

    \382\ Pocock SJ. When (not) to stop a clinical trial for 
benefit. JAMA 2005; 294:2228e30.
    \383\ Pocock SJ, Hughes MD. Practical problems in interim 
analyses, with particular regard to estimation. Control Clin Trials 
1989; 10(4 Suppl): 209Se21S.
    \384\ 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.
---------------------------------------------------------------------------

    We question the selection of ORR as the primary outcome, which 
combines the results of complete and partial responders. Specifically, 
we question if the results experienced by those who are complete 
responders may substantially differ from those who are partial 
responders. We also question the appropriateness of combining these two 
groups together. Further, we note that the applicant used a surrogate 
endpoint (ORR) rather than overall survival or other measure. We 
believe that this measure may not be the most appropriate measure with 
which to evaluate substantial clinical improvement in this patient 
population because it may not capture patients' clinical experience as 
fully as a measure of overall survival at some later time point. We are 
seeking public comment on whether the ORR is an appropriate measure of 
efficacy of this and other treatments when considering substantial 
clinical improvement.

[[Page 25282]]

    Lastly, we note that a historical control is used for all of the 
studies provided and that the analyses using this historical control do 
not account for baseline differences between the groups being compared. 
This makes it difficult to determine if the results seen are due to the 
treatment, random occurrences, or bias. Further, we note that the 
patient sample or samples used to construct the historical control may 
not be representative of the C-144-01 cohort. We are unable to verify 
the appropriateness of this historical control because the evidence 
describing the historical control takes the form of abstracts or was 
not provided.
    We are inviting public comments on whether lifileucel meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
lifileucel.
k. Narsoplimab
    The Omeros Corporation submitted an application for new technology 
add-on payments for narsoplimab for FY 2022. Narsoplimab is a fully 
human monoclonal antibody for the treatment of HSCT-TMA, also known as 
transplant-associated thrombotic microangiopathy (TA-TMA), for which 
the applicant has submitted a Biologics License Application (BLA). 
According to the applicant, narsoplimab inhibits mannan-binding lectin 
serine protease 2 (MASP-2), the effector enzyme of the lectin pathway 
of the complement system, and activation of the lectin pathway that 
prevents complement-mediated inflammation and exhibits anticoagulant 
effects while leaving intact the respective functions of the classical 
and alternative pathways of innate immunity. According to the 
applicant, there are currently no FDA-approved products indicated for 
the treatment of hematopoietic stem cell transplantation-associated 
thrombotic microangiopathy (HSCT-TMA).
    According to the applicant, HSCT-TMA is a lethal complication of 
hematopoietic stem cell transplantation (HSCT) that results in 
thrombosis in the small blood vessels, leading to organ failure.\385\ 
\386\ \387\ According to the applicant, clinical guidelines for the 
treatment of HSCT-TMA are being developed by members of the American 
Society for Transplant and Cellular Therapy (ASTCT) and are expected to 
be published in 2021. The applicant stated that current management of 
HSCT-TMA includes modification or cessation of any immune-suppressive 
regimen, appropriate treatment of infections and/or graft-versus-host 
disease (GvHD) if present, aggressive control of hypertension, and 
other supportive therapy as deemed appropriate by the treating 
physician.\388\ However, according to the applicant, the withdrawal of 
immunosuppressive therapies and ongoing monitoring for resolution of 
TMA symptoms has been determined to be ineffective.\389\ The applicant 
stated that there are multiple off-label treatments for HSCT-TMA which 
have either not been reviewed by the FDA or have been reviewed and not 
deemed adequate for registration purposes; these unapproved treatments 
include therapeutic plasma exchange (TPE), eculizumab, defibrotide 
sodium, rituximab, and vincristine sulfate. The applicant asserted that 
available evidence for agents used off-label to treat HSCT-TMA is 
derived from observational studies and case series with mixed results, 
and none of the agents have been evaluated for efficacy or safety in a 
robust clinical trial in patients with HSCT-TMA.\390\ In summary, the 
applicant stated with regard to these unapproved therapies that: (1) 
The use of TPE is based on the extrapolation of its effectiveness for 
thrombocytopenic purpura with poor outcomes leading the Blood and 
Marrow Transplant Clinical Trials Network Toxicity Committee in 2005 to 
recommend that TPE not be considered as a standard of care for HSCT-
TMA; \391\ (2) eculizumab is a C5 inhibitor that blocks activation of 
the terminal cascade of complement \392\ of which the use is 
constrained by lack of efficacy and safety evaluations by the FDA \393\ 
and associated increased susceptibility to infections; \394\ \395\ (3) 
defibrotide (Defitelio[supreg]), an oligonucleotide mixture with 
profibrinolytic properties whose mechanism of action has not been fully 
elucidated \396\ is not approved by the FDA for the treatment of HSCT-
TMA nor considered a standard of care; (4) rituximab (Rituxan[supreg]), 
a monoclonal antibody that targets the CD20 antigen expressed on the 
surface of pre-B and mature B-lymphocytes,\397\ is not approved by the 
FDA for the treatment of HSCT-TMA; and (5) Vincristine sulfate, a vinca 
alkaloid isolated as a 1:1 sulfate salt from the periwinkle plant is 
not approved by the FDA for the treatment of HSCT-TMA.\398\
---------------------------------------------------------------------------

    \385\ Gavriilaki, E et al. Transplant-associated thrombotic 
microangiopathy: Opening Pandora's box. Bone Marrow Transplantation 
(2017) 52, 1355-1360.
    \386\ Jodele, S et al (2016). New approaches in the diagnosis, 
pathophysiology, and treatment of pediatric hematopoietic stem cell 
transplantation-associated thrombotic microangiopathy. Transfus 
Apher Sci. 2016 April; 54(2): 181-190.
    \387\ Rosenthal, J Hematopoietic cell transplantation-associated 
thrombotic microangiopathy: A review of pathophysiology, diagnosis, 
and treatment. Journal of Blood Medicine 2016:7 181-186.
    \388\ Khosla J et al. Hematopoietic stem cell transplant-
associated thrombotic microangiopathy: Current paradigm and novel 
therapies. Bone Marrow Transplant. 2018; 53(2):129-137.
    \389\ Li A et al. Transplant-associated thrombotic 
microangiopathy is a multifactorial disease unresponsive to 
immunosuppressant withdrawal. Biol Blood Marrow Transplant. 2019; 
25(3):570-576.
    \390\ Li A et al. Transplant-associated thrombotic 
microangiopathy is a multifactorial disease unresponsive to 
immunosuppressant withdrawal. Biol Blood Marrow Transplant. 2019; 
25(3):570-576.
    \391\ Schwatz, J et al. Guidelines on the Use of Therapeutic 
Apheresis in Clinical Practice-- Evidence-Based Approach from the 
Writing Committee of the American Society for Apheresis: The Seventh 
Special Issue. Journal of Clinical Apheresis 31:149-338 (2016).
    \392\ FDA. (2019, june). Soliris Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/125166s431lbl.pdf.
    \393\ Li A et al. Transplant-associated thrombotic 
microangiopathy is a multifactorial disease unresponsive to 
immunosuppressant withdrawal. Biol Blood Marrow Transplant. 
2019;25(3):570-576.
    \394\ Bohl SR, Kuchenbauer F, von Harsdorf S, Kloevekorn N, 
Schonsteiner SS, Rouhi A, et al. Thrombotic Microangiopathy after 
Allogeneic Stem Cell Transplantation: A Comparison of Eculizumab 
Therapy and Conventional Therapy. Biol Blood Marrow Transplant. 
2017; 23(12):2172-7.
    \395\ Khosla J et al. Hematopoietic stem cell transplant-
associated thrombotic microangiopathy: Current paradigm and novel 
therapies. Bone Marrow Transplant. 2018; 53(2):129-137.
    \396\ FDA. (2016, march). Defitelio Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/208114lbl.pdf 
Defitelio PI. 3/2016.
    \397\ FDA. (2019, september). Rituxan Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/103705s5450lbl.pdf 
Rituxan PI. 9/2019.
    \398\ FDA. (2020, july). Vincristine Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/202497s011lbl.pdf 
Vincristine PI. 7/2020.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated in its 
application that it is in the process of completing a rolling 
submission of a Biologics License Application (BLA) to the FDA for 
narsoplimab for the treatment of HSCT-TMA. According to the applicant, 
narsoplimab has received Orphan Drug designation and Breakthrough 
Therapy Designation from FDA for the treatment of patients with HSCT-
TMA who have persistent thrombotic microangiopathy despite modification 
of immunosuppressive therapy. The applicant submitted a request for 
approval for a unique ICD-10-CM code for HSCT-TMA and an

[[Page 25283]]

ICD-10-PCS code for the administration of narsoplimab; there are 
currently no ICD-10-CM codes that describe HSCT-TMA or ICD-10-PCS codes 
that describe narsoplimab.
    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 narsoplimab has a unique mechanism of action as 
it is the first therapeutic to target mannan-binding lectin serine 
protease 2 (MASP-2) and the first to inhibit the lectin pathway of the 
complement system. The applicant stated that MASP-2 inhibition 
specifically blocks the lectin pathway of complement but does not 
inhibit the classical and alternative pathways, leaving the complement 
system's effector function in adaptive immunity intact, which is 
important for fighting infection.\399\ \400\ According to the 
applicant, the mechanism of action of narsoplimab not only results in 
inhibition of lectin pathway-mediated activation of complement, but 
also blocks the MASP-2 mediated procoagulant activities in the 
coagulation cascade. The procoagulant effects of MASP-2, independent of 
its role in the complement system, include the conversion of 
prothrombin to thrombin as well as the activation of Factor XII to 
XIIa.\401\ \402\ \403\ In addition, MASP-2 is activated by fibrin and 
activated platelets, further augmenting a procoagulant state.\404\ The 
applicant asserted that by inhibiting these procoagulant activities of 
MASP-2, narsoplimab provides important anticoagulant benefits, without 
affecting bleeding parameters (that is, prothrombin time, activated 
partial thromboplastin time, international normalized ratio, or 
bleeding time). According to the applicant, narsoplimab is the only 
drug that addresses all the components of HSCT-TMA and is the only 
product that inhibits complement activation and has anticoagulant 
activity. Therefore, the applicant asserts that the mechanism of action 
of narsoplimab differs from that of the products occasionally used off 
label: eculizumab, defibrotide sodium, rituximab, and vincristine.
---------------------------------------------------------------------------

    \399\ Rambaldi, A et al. Improved survival following OMS721 
treatment following hematopoietic stem cell transplant-associated 
thrombotic microangiopathy (HCTTMA). European Hematology Society. 
Stockholm, June 15, 2018. Abstract PF724.
    \400\ Elhadad, S et al 2020. MASP2 levels are elevated in 
thrombotic microangiopathies: association with microvascular 
endothelial cell injury and suppression by anti-MASP2 antibody 
narsoplimab. Clinical and Experimental Immunology, 0: 2-9.
    \401\ Demopulos, Gregory, A. Dudler, Thomas, Nilsson, Bo. 
Compositions and methods of inhibiting MASP-2 for the treatment of 
various thrombotic diseases and disorders. WO2019246367 
(US20200140570A1). World International Property Organization. 26 
December 2019.
    \402\ Krarup, A et al. Simultaneous Activation of Complement and 
Coagulation by MBLAssociated Serine Protease 2. 2007. PLoS ONE 2(7): 
e623.
    \403\ Gulla, KC et al. Activation of mannan-binding lectin-
associated serine proteases leads to generation of a fibrin clot. 
Immunology, 2009. 129, 482-495.
    \404\ Kozarcanin, H et al. The lectin complement pathway serine 
proteases (MASPs) represent a possible crossroad between the 
coagulation and complement systems in thromboinflammation. Journal 
of Thrombosis and Haemostasis, 2016. 14: 531-545.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or different MS-DRG, the applicant stated that patients who 
receive narsoplimab will be assigned to the same DRGs as patients who 
are diagnosed with HSCT-TMA/transplant-associated thrombotic 
microangiopathy (TA-TMA) regardless of the treatment.
    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 narsoplimab treats a different disease than existing 
technologies. According to the applicant, when treating HSCT-TMA, 
clinicians may rely on approaches that have limited efficacy \405\ such 
as to reduce or discontinue anti-GVHD therapies (for example, 
calcineurin inhibitors), initiate therapeutic plasma exchange (TPE), 
and/or administer anti-CD20 antibody therapies, terminal complement 
inhibitors and/or oligonucleotide therapies.\406\ \407\ \408\ The 
applicant stated that narsoplimab will be the first technology 
specifically indicated to treat HSCT-TMA.
---------------------------------------------------------------------------

    \405\ Li A et al. Transplant-associated thrombotic 
microangiopathy is a multifactorial disease unresponsive to 
immunosuppressant withdrawal. Biol Blood Marrow Transplant. 2019; 
25(3):570-576.
    \406\ Dhakal P et al. Is complement blockade an acceptable 
therapeutic strategy for hematopoietic cell transplant-associated 
thrombotic microangiopathy? Bone Marrow Transplant. 2017; 52(3):352-
356.
    \407\ Khosla J et al. Hematopoietic stem cell transplant-
associated thrombotic microangiopathy: current paradigm and novel 
therapies. Bone Marrow Transplant. 2018; 53(2):129-137.
    \408\ Li A et al. Transplant-associated thrombotic 
microangiopathy is a multifactorial disease unresponsive to 
immunosuppressant withdrawal. Biol Blood Marrow Transplant. 2019; 
25(3):570-576.
---------------------------------------------------------------------------

    According to the applicant, existing products that are currently 
used off-label to treat HSCT-TMA patients are indicated for the 
treatment of other distinct diseases. Eculizumab is indicated for: (1) 
The treatment of patients with paroxysmal nocturnal hemoglobinuria 
(PNH) to reduce hemolysis; (2) the treatment of patients with atypical 
hemolytic uremic syndrome (aHUS) to inhibit complement-mediated 
thrombotic microangiopathy; (3) the treatment of anti-acetylcholine 
antibody-positive generalized myasthenia gravis; and (4) the treatment 
of anti-aquaporin-4 (AQP4) antibody-positive neuromyelitis optica 
spectrum disorder (NMOSD).\409\ Defibrotide sodium is indicated for the 
treatment of adult and pediatric patients with hepatic veno-occlusive 
disease (VOD) with renal or pulmonary dysfunction following HSCT.\410\ 
The applicant further asserted that HSCT-TMA is different from aHUS due 
to varying underlying causes (that is, Shiga toxin infection, genetic 
mutation),\411\ its association with receipt of a stem cell transplant 
and associated endothelial cell injury,\412\ and aHUS resulting from 
mutations and/or polymorphisms in complement genes rather than having 
received an HSCT.\413\ \414\ In regard to VOD, the applicant asserts 
that while this patient population is similar to HSCT-TMA patients with 
regard to both having received HSCT, VOD is a separate disease 
affecting only the liver whereas HSCT-TMA is a multi-factorial disease 
impacting many organ systems, such as the kidneys, the lungs, the CNS 
and the gastrointestinal tract.\415\
---------------------------------------------------------------------------

    \409\ FDA. (2019, june). Soliris Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/125166s431lbl.pdf 
Soliris PI. 6/2019.
    \410\ FDA. (2016, march). Defitelio Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/208114lbl.pdf 
Defitelio PI. 3/2016.
    \411\ Lee, H et al. Consensus regarding diagnosis and management 
of atypical hemolytic uremic syndrome. 2020. Korean J Intern Med 
2020; 35:25-40.
    \412\ Rosenthal, J Hematopoietic cell transplantation-associated 
thrombotic microangiopathy: a review of pathophysiology, diagnosis, 
and treatment. Journal of Blood Medicine 2016:7 181-186.
    \413\ Rosenthal, J Hematopoietic cell transplantation-associated 
thrombotic microangiopathy: a review of pathophysiology, diagnosis, 
and treatment. Journal of Blood Medicine 2016:7 181-186.
    \414\ Masias, C et al. None of the above: thrombotic 
microangiopathy beyond TTP and HUS. Blood. 2017; 129(21):2857-2863.
    \415\ Bonifazi, F et al. Diagnosis and Treatment of VOD/SOS 
After Allogeneic Hematopoietic Stem Cell Transplantation. Front 
Immunol. 2020; 11: 489.
---------------------------------------------------------------------------

    Furthermore, the applicant summarized key distinctions between 
HSCT-TMA and the diseases for which

[[Page 25284]]

the other off-label therapeutics are indicated (eculizumab, defibrotide 
sodium, plasmapheresis with fresh frozen plasma and rituximab). 
According to the applicant, HSCT-TMA is associated with HSCT 
endothelial cell injury, has unique triggers such as immune 
dysregulation caused by infection, chemotherapy, and GVHD, and involves 
the initiation of the complement system including the lectin pathway. 
Atypical hemolytic uremic syndrome (aHUS), treated by eculizumab, is 
associated with unchecked abnormal activation of alternative complement 
system due to genetic mutations in complement factors or inhibitory 
autoantibodies to factor H and I and has an onset that is idiopathic or 
secondary to triggers such as infection, fever, pregnancy, malignant 
hypertension, transplant, and diarrheal illnesses. Veno-occlusive 
disease (VOD), treated by defibrotide sodium, is a complication 
observed after HSCT where sinusoidal endothelial cells and hepatocytes 
in zone 3 of the hepatic acinus are damaged by toxic metabolites 
generated during the conditioning regimen. Thrombocytopenic purpura 
(TTP), treated by plasmapheresis with fresh frozen plasma and 
rituximab, is characterized by an ADAMTS-13 deficiency that is not 
commonly seen in HSCT-TMA with decreased ADAMTS activity due to genetic 
alterations to the gene or presence of inhibitory autoantibodies.
    In summary, the applicant believes that narsoplimab is not 
substantially similar to other currently available therapies and/or 
technologies and meets the ``newness'' criterion. We note that the 
applicant asserts that there are no FDA-approved products indicated for 
the treatment of HSCT-TMA and we are inviting public comment on whether 
narsoplimab therefore has a unique mechanism of action. In addition, we 
note that although the cause or triggers of thrombotic microangiopathy 
may be different between HSCT and for example HUS or TTP, the resulting 
disease may be similar. We welcome public comments on whether HSCT-TMA 
is a similar disease to other forms of TMA.
    We are inviting public comments on whether narsoplimab is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    With regard to the cost criterion, the applicant provided the 
following analysis to demonstrate the technology meets the cost 
criterion. The applicant stated that due to what it described as a lack 
of sufficient coding in the HSCT-TMA space, the applicant provided 
multiple scenarios to show that narsoplimab meets the cost criterion. 
The applicant stated they are not requesting that narsoplimab map to a 
new or different MS-DRG.
    The applicant used the full calendar year 2019 National Medicare 
100% inpatient Limited Dataset to identify patients with a combined 
diagnosis of history of stem cell transplantation (SCT, ICD-10 code 
Z94.84) OR complications of stem cell transplant (ICD-10 code T86.5) 
AND thrombotic microangiopathy (TMA, ICD-10 code M31.1) OR hemolytic-
uremic syndrome (HUS, ICD-10 code D59.3). Claims from PPS-exempt 
hospitals were excluded. In the base case analysis where all MS-DRGs 
were included, a total of 83 cases across 38 MS-DRGs were identified. 
The applicant imputed a case count of 11 for those MS-DRGs with fewer 
than 11 cases, which increased the number of claims from 83 to 396 
because all MS-DRGs had fewer than 11 claims. The applicant then varied 
this initial analysis in two ways. First, sensitivity analyses one and 
two varied the reduction for the charges related to the prior 
technology to 25 percent and 50 percent of prior related therapy 
charges, respectively, which are possibly tied to decreased length of 
stay and/or decreased ICU utilization. Second, the applicant provided 
four scenarios which varied the price of narsoplimab from zero to three 
greater values.
    The applicant first calculated a case weighted threshold of $96,810 
for all scenarios based upon the dollar threshold for each MS-DRG 
grouping and the proportion of cases in each MS-DRG. The applicant then 
calculated the average charge per case. The applicant stated that 
because narsoplimab is an adjunctive therapy, no charges for a prior 
technology or a technology being replaced were removed. In the base 
case analysis, no charges related to the prior technology were removed 
because narsoplimab is not anticipated to offset standard of care 
costs. However, according to the applicant, because of a reduction in 
complications leading to mortality and other clinically significant 
complications, narsoplimab is anticipated to decrease the rate of 
hospitalization and length of stay. Therefore, two sensitivity analyses 
were included which removed 25 percent and 50 percent of prior related 
therapy charges which could potentially be related to a decrease in 
length of stay and/or decrease in ICU utilization in sensitivity 
analyses one and two, respectively. The applicant stated the 50% charge 
reduction analysis was performed as an extreme analysis to examine the 
unlikely possibility that narsoplimab offsets a considerable amount of 
costs associated with treating TMA. Because of the reduction in 
complications leading to mortality and other clinically significant 
complications, the applicant asserted that for many with long-term 
sequelae, narsoplimab is anticipated to decrease the rate of 
hospitalization and length of stay. Next the applicant calculated the 
average standardized charge per case using the FY 2021 IPPS/LTCH PPS 
final rule Impact file. The 2-year inflation factor of 13.2% (1.13218) 
was obtained from the FY 2021 IPPS/LTCH PPS final rule and applied to 
the average standardized charge per case.
    To determine the charges for narsoplimab, the applicant converted 
cost to charges by dividing by the FY 2021 IPPS/LTCH PPS final rule 
national average drug CCR of 0.187. No charges related to the use of 
the technology were added by the applicant because utilization of 
narsoplimab is not anticipated to result in incremental costs. The 
applicant calculated the final inflated average case-weighted 
standardized charge per case by adding the charges for the technology 
to the inflated average standardized charge per case. In the base 
analysis where a technology related price of $0 was used, the applicant 
determined a final inflated average case-weighted standardized charge 
per case of $363,815, which exceeds the average case-weighted threshold 
amount of $96,810. In the same base analysis, the applicant determined 
a final inflated average case-weighted standardized charge per case of 
$272,861 in scenario one of the sensitivity analyses, which exceeds the 
average case-weighted threshold amount of $96,810. Lastly, in the same 
base analysis, the applicant determined a final inflated average case-
weighted standardized charge per case of $181,908 in scenario two of 
the sensitivity analyses, which exceeds the average case-weighted 
threshold amount of $96,810. The applicant then provided a secondary 
cost analysis where the price of narsoplimab was the average of the 
three greater values used as the charges for the technology, and 
identified a final inflated average case-weighted standardized charge 
per case of $898,574, $807,621, and $716,667 in the base, 25 percent 
sensitivity, and 50 percent sensitivity analyses respectively.
    We note that in its application, the applicant only provided, in 
Excel format, the primary base analysis without sensitivity scenarios. 
We are therefore unable to verify all other analyses, to include the 
sensitivity

[[Page 25285]]

analyses, discussed in this section and in the application. The 
applicant includes many MS-DRGs which are defined by other factors 
which may or may not be related to the intended indication for 
narsoplimab. For instance, the applicant identified MS-DRG 193 (Simple 
Pneumonia and Pleurisy with MCC) for inclusion in the cost analysis. 
Therefore, we are uncertain if the cases identified in the preceding 
cost analysis adequately identify potential cases eligible for 
narsoplimab. We are seeking public comment with regard to whether the 
MS-DRGs used in these cost analyses are appropriately representative of 
the cases that would be eligible for use of the technology. We invite 
public comments on whether narsoplimab meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that narsoplimab represents a substantial clinical 
improvement over existing technologies. According to the applicant, 
compared to the current recommendation of cessation of 
immunosuppressive therapies, narsoplimab demonstrates a substantial 
clinical improvement for the treatment of HSCT-TMA because it fulfills 
an unmet need for patients, demonstrated a statistically significant 
complete response rate in the pivotal clinical trial, provides a 
reduction in clinically significant adverse events, resulted in higher 
100-day survival rates, decreases the rate of subsequent therapeutic 
interventions, and is anticipated to decrease the rate of 
hospitalizations and length of stay.
    The applicant asserts that narsoplimab offers a treatment option 
for a patient population unresponsive to current available treatments. 
According to the applicant, the FDA awarded narsoplimab Breakthrough 
Therapy designation after reviewing literature for patients similar to 
those in the applicant's pivotal trial. The applicant states that if 
approved by the FDA, narsoplimab will be the only drug or biological 
approved for the treatment of HSCT-TMA.
    In support of the assertion that narsoplimab offers a treatment 
option for patients unresponsive to currently available treatments, the 
applicant provided an abstract of their pivotal trial, a single-arm 
trial of 28 adult HSCT-TMA patients.\416\ The abstract states that 
patients who had not responded to immunosuppression modification and 
who had thrombocytopenia, evidence of microangiopathic hemolytic 
anemia, and increased creatinine were included in the study. The 
applicant adds that patients with mild disease were excluded from the 
study. Patients received narsoplimab intravenously once weekly for four 
or eight weeks with a 6-week follow up period. The primary endpoint was 
a response-based composite measure requiring improvement both in 
laboratory TMA markers (platelet count and Lactate Dehydrogenase (LDH)) 
and in clinical status (that is organ function). Secondary endpoints 
were surivival and changes in laboratory TMA markers. The applicant 
asserts that a complete response rate of 15% was identified in 
conjunction with the FDA as the threshold to demonstrate efficacy for 
narsoplimab. The applicant states that narsoplimab resulted in a 61% 
complete response rate (CRR) in patients with HSCT-TMA who received at 
least one dose of the drug; the per protocol analysis (that is, 
patients who received at least the per-protocol-specified 4 weeks of 
treatment) resulted in a 74% complete response rate. The applicant 
states that these complete response rates are higher than the expected 
response of 10% to 15% in the absence of narsoplimab.
---------------------------------------------------------------------------

    \416\ Rambaldi, A et al. Narsoplimab for the treatment of Adult 
Hematopoietic Stem Cell Transplant-Associated Thrombotic 
Microangiopathy European Hematology Society. Abstract S262. 2020.
---------------------------------------------------------------------------

    In applying for Breakthrough Therapy designation, the applicant 
states that a literature review was conducted to identify studies in a 
patient population similar to that in the pivotal trial. Searching in 
PubMed using pre-identified search terms (transplant-associated 
thrombotic microangiopathy; thrombotic microangiopathy stem cell; and 
cancer-associated thrombotic microangiopathy), the applicant identified 
nine references that met inclusion criteria and excluded an unknown 
number of articles because the patient data was not included in the 
publication. Studies were included if they were published in the year 
2000 or later and included: (1) Survival data for patients; (2) 
documentation that immunosuppression was modified; and (3) 
documentation of patient response to immunosuppression 
modification.\417\
---------------------------------------------------------------------------

    \417\ Rambaldi, A et al. Improved survival following OMS721 
treatment following hematopoietic stem cell transplant-associated 
thrombotic microangiopathy (HCTTMA). European Hematology Society. 
Stockholm, June 15, 2018. Abstract PF724.
---------------------------------------------------------------------------

    Of the nine studies included, there was a mean sample size of 7.4 
ranging from 1-17 totaling 67 participants. The applicant identified a 
median overall survival of 21 days (95% CI 15-29) which ranged from 7 
to 43 days. The applicant compared these results to those of the 
pivotal trial, where 16 of 28 patients died with a median overall 
survival of 274 days (p < 0.0001) compared via a log-rank test to that 
identified in the literature review. The applicant stated that a one-
hundred-day survival post HSCT-TMA diagnosis was observed in 68% (n=28) 
of the full analysis set, 83% (n=23) in the patients treated per the 
protocol, and 94% (n=17) of complete responders.
    The applicant asserted that in a high-risk study population, 
narsoplimab demonstrated substantial clinical improvement compared to 
current treatment approaches, meaningfully decreasing the rates of 
clinically significant complications, including mortality, and reducing 
the need for subsequent interventions; as a result, narsoplimab is 
anticipated to decrease the rate of hospitalization and length of stay. 
The applicant stated that the primary objectives in the pivotal study 
for narsoplimab were to evaluate safety, tolerability, and response-
based efficacy requiring improvement in TMA laboratory markers of 
platelet count and LDH and improvement in clinical status on the basis 
of transfusions, renal, pulmonary, gastrointestinal, and neurological 
symptoms. The applicant stated that platelet count on average increased 
from baseline over time, LDH decreased from baseline, haptoglobin 
steadily increased from baseline, and hemoglobin increased over time 
with the use of narsoplimab. The applicant reported that overall 48% 
and 55% of patients had freedom from red blood cell and platelet 
transfusions, respectively. The applicant asserted that due to the 
decreased rate of complications, narsoplimab has the potential to lead 
to decreased hospital length of stay as well as decreased intensive 
care usage.
    Lastly, the applicant asserted that narsoplimab is well tolerated 
with no treatment related complications. The applicant stated that the 
most common adverse events in the pivotal trial were nausea, vomiting, 
diarrhea, hypokalemia, neutropenia, and fever, which are comparable to 
those typically seen in the post-transplant population. Six deaths 
(21%) occurred, collectively, from sepsis, AML progression, and graft-
versus host disease, which according to the applicant are causes of 
death common in patients with HSCT.
    In addition to the previously discussed pivotal trial abstract, the 
applicant submitted four additional citations (three case studies and 
one case series) in support of the substantial clinical improvement of 
narsoplimab. The first citation is described by the

[[Page 25286]]

applicant as a case study of an 18-year-old patient with biopsy-proven 
HSCT-TMA of the gastrointestinal tract which required transfusions. The 
applicant states that the patient received narsoplimab which led to the 
resolution of TMA and all transfusions were discontinued. The applicant 
submitted an educational agenda in support of this citation which does 
not provide any additional information.\418\
---------------------------------------------------------------------------

    \418\ Rafael Duarte, Diagnosis and treatment options for 
transplant-associated microangiopathy. European Society for Blood 
and Marrow Transplantation (EBMT). Abstract 2019.
---------------------------------------------------------------------------

    The second citation concerns the results of a case study of a 14 
year-old patient who did not tolerate eculizumab for the treatment of 
HSCT-TMA and was treated successfully with OMS721 (i.e., narsoplimab). 
The applicant submitted the abstract which states that after receiving 
allogeneic HSCT, the patient began to show progressive 
deterioration.\419\ The patient was treated twice with eculizumab at 
months seven and eleven both resulting in pulmonary edema. The patient 
next received narsoplimab after which he began to improve and did not 
experience any adverse events.
---------------------------------------------------------------------------

    \419\ Zecca, et al. Resolution of acute kidney injury secondary 
to HSCT-TMA by the anti-MASP-2 monoclonal antibody OMS721 in 
pediatric HSCT recipient. European Society for Blood and Marrow 
Transplantation (EBMT). Abstract 2017.
---------------------------------------------------------------------------

    The third citation is a presentation given at the European Society 
for Blood and Marrow Transplantation in 2017 \420\ which discusses a 
46-year-old patient with T-acute lymphoblastic leukemia who received 
HSCT. The applicant states this case study is about a patient with 
HSCT-TMA and late-onset acute GI GVHD who was treated with narsoplimab 
which resulted in the resolution of melena and hemolysis, increased 
platelets, and neurologic improvements over 354 days.
---------------------------------------------------------------------------

    \420\ Caprioli, et al. Effective treatment of GVHD-associated 
transplant-associated microangiopathy Transplant Complications 
Working Party. Crash course on diagnosis and treatment of non-
infectious complications after HCT. 19-20 October 2017 in Granada, 
Spain in conjunction with the European Society for Blood and Marrow 
Transplantation (EBMT). Abstract 2017.
---------------------------------------------------------------------------

    Lastly, the applicant submitted a presentation which discusses the 
results of a case series.\421\ The applicant states that laboratory 
marker and clinical improvement were seen following narsoplimab 
treatment in severely ill, complex patients with HSCT-TMA. The case 
series included results from 2 patients (age 19 and age 48), both of 
whom underwent HSCT, the latter of which was HIV positive. The 19-year-
old patient received 18 doses of narsoplimab showing favorable response 
with resolution of gastrointestinal bleeding and microangiopathic 
hemolytic anemia. The 48-year-old patient received eight doses of 
narsoplimab, but despite partial improvement remained on transfusions 
and dialysis until sudden death on day 31.
---------------------------------------------------------------------------

    \421\ Duarte, et al. Treatment of severe hematopoietic stem cell 
transplant-associated thrombotic microangiopathy (HSCT-TMA) with the 
MASP-2 inhibitor narsoplimab (OMS721). European Society for Blood 
and Marrow Transplantation (EBMT). Abstract 2020.
---------------------------------------------------------------------------

    After review of the provided information and citations we have 
concerns with regard to the substantial clinical improvement criterion. 
Firstly, the sample from which the applicant draws conclusions is small 
(sample size of pivotal trial 28, plus five case studies). Furthermore, 
we are unable to verify the methods, results, and conclusions of these 
studies as the applicant only provided evidence in the form of 
abstracts and presentations. For example, one citation provided by the 
applicant in the form of a non-peer-reviewed conference poster details 
interim results from what appear to be the pivotal trial.
    With regard to methodological concerns, first, we note the 
potential for overestimating treatment effects when trials stop early 
or report interim results.\422\ \423\ \424\ Second, the authors pool 
data from an historical cohort of patients drawn from published 
literature to calculate survival rates in patients with HSCT-TMA and 
then retrospectively compare these rates to the survival in their 
treated cohort. We are unable to evaluate the appropriateness of this 
historical comparison cohort based on the evidence provided in the form 
of two citations, an abstract \425\ and a poster.\426\ This analysis 
may not adequately account for baseline differences between the 
patients treated with narsoplimab and the patients across the articles 
from which a historical control was developed. In addition, we note 
that we may lack the ability to evaluate whether this literature review 
to obtain the historical control effectively identified the historical 
control, as the applicant only provided general details on how the 
search was performed.
---------------------------------------------------------------------------

    \422\ Pocock SJ. When (not) to stop a clinical trial for 
benefit. JAMA 2005; 294:2228e30.
    \423\ Pocock SJ, Hughes MD. Practical problems in interim 
analyses, with particular regard to estimation. Control Clin Trials 
1989; 10(4 Suppl): 209Se21S.
    \424\ 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.
    \425\ Rambaldi, A et al. Improved survival following OMS721 
treatment following hematopoietic stem cell transplant-associated 
thrombotic microangiopathy (HCTTMA). European Hematology Society. 
Stockholm, June 15, 2018. Abstract PF724.
    \426\ Rambaldi, A et al. Improved survival following oms721 
treatment of hematopoietic stem cell transplant-associated 
thrombotic microangiopathy (hct-tma). European Hematology 
Association (poster). Stockholm, June 15, 2018. Abstract PF724.
---------------------------------------------------------------------------

    We further note that the study design described in the pivotal 
trial, upon which the applicant bases its claims for substantial 
clinical improvement, was not appropriately designed to test for 
comparisons with another treatment such as an historical control. 
Furthermore, the methods utilized in the pivotal trial do not lend 
themselves to making statistical inferences based on the provided 
protocol (for example, no power assessment performed, no assessment for 
multiple comparisons, no pre-identified alpha).
    We are inviting public comments on whether narsoplimab meets the 
substantial clinical improvement criterion.
    We received one written comment in response to the New Technology 
Town Hall meeting notice published in the Federal Register. The 
commenter stated that they are enthusiastic about the results of the 
single arm open-label trial OMS721-TMA-001 evaluating narsoplimab for 
the treatment of HSCT-TMA. The commenter added that narsoplimab offers 
a treatment option for these high-risk patients that appears to 
markedly increase complete response rates with a substantial reduction 
in clinically significant complications including mortality. The 
commenter stated that the approval of the application for new 
technology add-on payments will help ensure appropriate patients will 
get the benefit of narsoplimab for treatment of HSCT-TMA.
    Response: We appreciate the commenter's input and will take this 
comment into consideration when deciding whether to approve new 
technology add-on payments for narsoplimab for FY 2022.
l. NexoBridTM
    Vericel Corporation submitted an application for 
NexoBridTM for new technology add-on payments for FY 2022. 
According to the applicant, NexoBridTM is a novel, non-
surgical option for eschar removal (debridement). Eschar is the dead 
tissue and dried secretions from a skin wound following a burn, and 
removal is essential for wound healing. According to the applicant, 
NexoBridTM is a mixture of proteolytic enzymes (enriched in 
bromelain) and has been developed for patients with deep partial 
thickness (DPT) and/or full thickness

[[Page 25287]]

(FT) thermal burns. According to the applicant, NexoBridTM 
has not yet received approval from FDA. The applicant further noted 
that NexoBridTM was approved by the European Medicines 
Agency (EMA) in 2012 and is currently commercially available in many 
countries.
    The applicant stated that timely, rapid debridement of eschar in 
burn patients is necessary for assessing the burn injury, initiating 
the wound healing process, and preventing further complications, such 
as local infection, sepsis and extension of the burn 
injury.427 428 429 The applicant stated that 
NexoBridTM has been identified by the Biomedical Advanced 
Research and Development Authority (BARDA) as a critical medical 
countermeasure to address the public health emergency need for a 
debridement product for the treatment of burns in adults, especially 
for mass casualty events, where surgical capacity is limited, and rapid 
assessment of burn severity and intervention are imperative.\430\
---------------------------------------------------------------------------

    \427\ Edmondson, S. J., Jumabhoy, I. A., & Murray, A. (2018). 
Time to start putting down the knife: A systematic review of burns 
excision tools of randomised and non-randomised trials. Burns, 
44(7), 1721-1737.
    \428\ Gibran, N. S., et al. (2013). Summary of the 2012 ABA burn 
quality consensus conference. Journal of Burn Care & Research, 
34(4), 361-385.
    \429\ Xiao-Wu, et al. (2002). Effects of delayed wound excision 
and grafting in severely burned children. Archives of surgery, 
137(9), 1049-1054.
    \430\ BARDA Initiates the Procurement of NexoBrid for Emergency 
Response. http://ir.mediwound.com/newsreleases/news-release-details/barda-initiates-procurement-nexobrid-emergency-response.
---------------------------------------------------------------------------

    The applicant stated that the current standard of care for burn 
debridement includes surgical and non-surgical approaches. The 
applicant stated that the surgical approach relies primarily on 
surgical tangential excision through use of sharp instruments such as 
scalpels and dermatomes.431 432 The applicant stated that 
surgical procedures include minor excision, avulsion, hydrosurgery (for 
example, VERSAJETTM), scraping, brushing, dermabrasion, and 
excisions.\433\ The applicant stated that non-surgical standard of care 
treatments include enzymatic debridement such as clostridial 
collagenase ointment (example, SANTYL[supreg]), antimicrobial agents 
such as silver sulfadiazine (example, SILVADENE[supreg]), or various 
hydrogels.434 435 436 437 438 439
---------------------------------------------------------------------------

    \431\ Edmondson, S. J., et al. (2018). Time to start putting 
down the knife: A systematic review of burns excision tools of 
randomised and non-randomised trials. Burns, 44(7), 1721-1737.
    \432\ Hindocha, S., et al. (2013). Burn eschar debridement: a 
review. J. Wound. Technol. July, 12-14.
    \433\ Legemate, C. M., et al. ``Application of hydrosurgery for 
burn wound debridement: an 8-year cohort analysis.'' Burns 45.1 
(2019): 88-96.
    \434\ Loo, Y. L., Goh, B. K., & Jeffery, S. (2018). An overview 
of the use of bromelain-based enzymatic debridement 
(NexoBrid[supreg]) in deep partial and full thickness burns: 
appraising the evidence. Journal of Burn Care & Research, 39(6), 
932-938.
    \435\ Pham, C. H., et al. (2019). The role of collagenase 
ointment in acute burns: a systematic review and meta-analysis. 
Journal of wound care, 28(Sup2), S9-S15.
    \436\ Cancio, L. C., Barillo, D. J., Kearns, R. D., Holmes IV, 
J. H., Conlon, K. M., Matherly, A. F., . . . & Palmieri, T. (2017). 
Guidelines for burn care under austere conditions: surgical and 
nonsurgical wound management. Journal of Burn Care & Research, 
38(4), 203-214.
    \437\ Hansbrough, J. F., et al (1995). Wound healing in partial-
thickness burn wounds treated with collagenase ointment versus 
silver sulfadiazine cream. The Journal of burn care & 
rehabilitation, 16(suppl_3_pt_1), 241-247.,
    \438\ Klasen, H. J. (2000). A historical review of the use of 
silver in the treatment of burns. II. Renewed interest for silver. 
Burns, 26(2), 131-138.,
    \439\ Soroff, H. S., & Sasvary, D. H. (1994). Collagenase 
ointment and polymyxin B sulfate/bacitracin spray versus silver 
sulfadiazine cream in partial-thickness burns: A pilot study. The 
Journal of burn care & rehabilitation, 15(1), 13-17.
---------------------------------------------------------------------------

    According to the applicant, NexoBridTM is a botanical 
and biologic product for topical use and is comprised of two 
components: The NexoBridTM powder that contains the active 
pharmaceutical ingredient (API) and a Gel Vehicle. The 
NexoBridTM API is a concentrate of proteolytic enzymes 
enriched in bromelain extracted from pineapple stems. The applicant 
stated that the mechanism of action of NexoBridTM is 
mediated by the proteolytic activity of its enzymes and is associated 
with selective debridement of eschar and denatured collagen while 
sparing healthy tissue.
    The applicant stated that according to the American Hospital 
Association (AHA) Coding Clinic, ``Non-excisional debridement is coded 
with root operation `extraction' ''.\440\ The applicant added that 
NexoBridTM could be identified with ICD-10-PCS code series 
0HD Extraction of Skin or 0JD Extraction of subcutaneous tissue and 
fascia. The applicant stated that it has not requested that its 
technology map to a new or different MS-DRG.
---------------------------------------------------------------------------

    \440\ American Hospital Association (AHA) Coding Clinic, Volume 
2, number 1, 2015, pg 23
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated they 
have not yet received FDA approval. The applicant submitted a Biologic 
License Application (BLA) for NexoBridTM for FDA approval on 
June 30, 2020 on the basis of two pivotal Phase 3 clinical trials. In 
September 2020, the FDA accepted the application and communicated a 
PDUFA date of June 29, 2021.
    The applicant indicated that the ICD-10-PCS code series for non-
excisional debridement, 0HD (Extraction of Skin) or 0JD (Extraction of 
subcutaneous tissue and fascia) could be used to identify 
NexoBridTM use. The applicant indicated that 
NexoBridTM is not separately identified with a unique ICD-
10-PCS code. The applicant submitted a request for an ICD-10-PCS code 
to uniquely identify the use of NexoBridTM beginning in FY 
2022.
    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, therefore, 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 stated that NexoBridTM is unique due to the 
bromelain active ingredient, which is extracted from pineapple stems. 
The applicant claimed that a search of the FDA website for the key 
words ``bromelain'' and ``pineapple'' did not yield any approved 
applications under section 505(b)(1) of the Federal Food, Drug, and 
Cosmetic (FD&C Act) or section 351(a) of the Public Health Service 
(PHS) Act.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant did not address the 
question directly, but stated that no existing technology used now or 
previously is similar to NexoBridTM that would be captured 
under burn MS-DRGs as identified in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.162


[[Page 25288]]


    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 NexoBridTM 
does treat the same patient population as existing approaches to eschar 
removal. The applicant further stated that the ability to use 
NexoBridTM at the bedside offers an effective option for 
rapid eschar removal that avoids the operating room, and that the 
ability to use NexoBridTM in delicate areas offers 
particular value in burn treatment.
    We have the following concerns regarding whether the technology 
meets the substantial similarity criteria and whether it should be 
considered new. While the applicant discussed the differences between 
NexoBridTM and products made by other manufacturers, we note 
the applicant does not provide enough information regarding the 
composition of the proteolytic enzymes used within the 
NexoBridTM active pharmaceutical ingredient, its mechanism 
of action, and how the ingredient(s) differs from other enzymatic 
debridement products on the market. Specifically, it is not clear 
whether the proteolytic enzyme is a type of collagenase similar to 
existing collagenase based enzymatic debridement products, since the 
applicant claimed that NexoBridTM debrides denatured 
collagen in the wound. In addition, the applicant states that 
NexoBridTM uses a new ingredient but does not explain how 
this represents a new mechanism of action. We also note that, while the 
applicant did not state so directly, we believe that patients treated 
using NexoBridTM would be assigned to the same MS-DRGs as 
those patients who were treated with competitive products or services 
used for burns. We further note that the applicant did not suggest that 
NexoBridTM was used to treat a different population from 
existing treatments.
    We are inviting public comments on whether NexoBridTM is 
substantially similar to other currently available therapies and/or 
technologies, and whether NexoBridTM meets the newness 
criterion.
    With regard to the cost criterion, the applicant provided two 
scenarios: Scenario 1: without grafting, which excluded cases with an 
ICD-10-PCS code for replacement of skin, and Scenario 2: with grafting, 
which required at least one ICD-10-PCS code for replacement of skin. 
Under the first scenario, the applicant searched the FY 2019 MedPAR 
dataset for cases reporting ICD-10-CM diagnosis codes for second- or 
third-degree burns as a primary diagnosis, and an ICD-10-PCS code(s) 
for excision or extraction of skin or subcutaneous tissue and fascia; 
these criteria resulted in the identification of 347 cases mapping to 
three unique MS-DRGs. Under the second scenario, the applicant again 
searched the FY 2019 MedPAR dataset for the same ICD-10 codes but with 
an additional ICD-10-PCS code for replacement of skin. Under the second 
scenario, the applicant identified 1,283 cases mapping to five unique 
MS-DRGs. In the following tables the applicant lists the MS-DRGs to 
which cases are assigned in each scenario:
[GRAPHIC] [TIFF OMITTED] TP10MY21.163

[GRAPHIC] [TIFF OMITTED] TP10MY21.164

    With respect to the MS-DRGs identified based on the claims search 
and included in the cost analysis, particularly MS-DRG 003, the 
applicant confirmed that this MS-DRG was appropriately representative 
of potential NexoBridTM patients.
    The applicant used the FY 2019 MedPAR LDS file with the FY 2022 New 
Technology thresholds to calculate the case-weighted thresholds, and 
the FY 2019 FR IPPS/LTCH PPS standardizing file to standardize charges. 
The applicant then removed 100 percent of the operating room charges 
and 24.5 percent of the blood charges from the identified cases to 
conservatively estimate the charges that potentially may be avoided 
through the use of NexoBridTM. After standardizing the 
charges, the applicant applied what it indicated was 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 was 13.2 percent (1.13218) for FY 2021 (85 FR 59039), 
which would have resulted in higher inflated charges. To calculate the 
charges for the technology, the applicant divided the cost of the 
technology by the national average CCR for the Drugs cost center of 
0.187 from the FY 2021 IPPS/LTCH PPS final rule.
    Under scenario one, the applicant calculated a final inflated case-
weighted average standardized charge per case of $95,828, which 
exceeded the average case-weighted threshold amount of $55,536. Under 
scenario two, the final inflated average case-weighted standardized 
charge per case of $334,405 exceeded the average case-weighted 
threshold amount of $168,985. The applicant stated that because the 
final inflated average case-weighted standardized charge per case 
exceeded the average case-weighted threshold amount for both scenarios, 
the technology meets the cost criterion.

[[Page 25289]]

    According to the applicant, NexoBridTM is indicated for 
the treatment of thermal burns. The cost analysis performed by the 
applicant includes MS-DRG 003 (ECMO or Tracheostomy w MV >96 Hours or 
Principal Diagnosis Except Face, Mouth and Neck w Major O.R. 
Procedures), which per the applicant is appropriately representative of 
potential NexoBridTM patients. However, MS-DRG 003 does not 
appear to be representative of the target patient population for 
NexoBridTM. We are seeking public comment on whether the use 
of this MS-DRG and others for the cost analysis appropriately reflects 
the potential cases treated by the technology.
    We are inviting public comment on whether NexoBrid[supreg] meets 
the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that NexoBridTM can be used in a patient 
population that is unresponsive to, or ineligible for currently 
available treatments because NexoBridTM can be used at the 
bedside and is therefore an effective eschar removal option for 
patients for whom surgery or general anesthesia may be contraindicated. 
The applicant asserted that NexoBridTM allows for the 
diagnosis of a medical condition in a manner different from existing 
technology because it allows for depth-of-burn diagnoses of 
indeterminant depth and/or mixed depth wounds. The applicant also 
asserted that NexoBridTM represents a substantial clinical 
improvement due to significantly improved clinical outcomes in the 
following ways: (1) Reduction in clinically significant adverse events 
by reducing the surgical burden associated with surgical excision, 
reducing donor site morbidity due to reduced autografting, reducing 
blood loss due to adoption of a non-surgical approach, and reduced 
usage of surgical escharotomies; (2) decreased rate in a subsequent 
diagnostic or therapeutic intervention by reducing the need for 
surgical excision and reducing the need for autografts; (3) improved 
quality of life due to reduced scarring associated with reduction in 
autografting; and (4) NexoBridTM is aligned with key 
benefits to elderly burn patients who may be too unwell for surgical 
excision.
    The applicant asserted that because NexoBridTM can be 
used at the bedside, it provides a unique non-surgical option for 
rapid, consistent eschar removal in patients for whom surgery or 
general anesthesia may be contraindicated. The applicant claimed that 
currently available non-surgical eschar removal procedures are 
generally considered inefficient, can result in a lengthy sloughing 
period, and have the potential for development of granulation tissue 
and increased infection and scarring.441 442 443
---------------------------------------------------------------------------

    \441\ Hansbrough, J. F., et al. (1995). Wound healing in 
partial-thickness burn wounds treated with collagenase ointment 
versus silver sulfadiazine cream. The Journal of burn care & 
rehabilitation, 16(suppl_3_pt_1), 241-247.
    \442\ Klasen, H. J. (2000). A historical review of the use of 
silver in the treatment of burns. II. Renewed interest for silver. 
Burns, 26(2), 131-138.
    \443\ Soroff, H. S., & Sasvary, D. H. (1994). Collagenase 
ointment and polymyxin B sulfate/bacitracin spray versus silver 
sulfadiazine cream in partial-thickness burns: a pilot study. The 
Journal of burn care & rehabilitation, 15(1), 13-17.
---------------------------------------------------------------------------

    The applicant submitted two pivotal Phase 3 clinical trials to 
primarily support its claims of substantial clinical improvement. The 
DETECT study (NCT02148705) is a multi-center, multi-national, assessor 
blinded, randomized, 3:3:1 controlled, three-arm study from which data 
is not yet publicly available. Per the applicant, this study aimed to 
demonstrate superiority of NexoBridTM treatment over Gel 
Vehicle (placebo) control and standard of care treatment, in 
hospitalized adult subjects with DPT and/or FT thermal burn of 3-30% 
total body surface area (TBSA) and total burn wounds of no more than 
30% TBSA. A total of 175 subjects were randomized in to the DETECT 
study with 169 subjects being treated with NexoBrid, SOC consisting of 
surgical and/or nonsurgical treatment as per the investigators' 
discretion, or placebo.\444\ NCT00324311 is an earlier multi-center, 
open-label, randomized, controlled clinical trial including 156 
patients aged 4-55 years with deep partial and full thickness burns 
covering 5-30% TBSA. Patients were randomly assigned to burn 
debridement with NexoBridTM or standard of care, which 
included surgical excisional or non-surgical debridement.\445\
---------------------------------------------------------------------------

    \444\ NexoBrid Draft Labeling Text
    \445\ Rosenberg, L., et al, A novel rapid and selective 
enzymatic debridement agent for burn wound management: A multi-
center RCT. Burns 2014, Vol 40(3): 466-474.
---------------------------------------------------------------------------

    The applicant asserted that in patients with indeterminant partial-
thickness and/or mixed depth burns, NexoBridTM debridement 
allows for a more accurate assessment of burn depth. The applicant 
stated, ``each additional non-autografted NexoBridTM-treated 
patient (relative to standard of care eschar removal) has an 
indeterminate superficial partial thickness wound that would otherwise 
have been incorrectly diagnosed as a deep partial thickness wound.'' 
The applicant suggested that deep partial thickness wounds require 
autografting. The applicant noted that the Phase 3 clinical trial 
NCT00324311 of patients with DPT and FT thickness had burns ranging 
from 5-30%TBSA.\446\ The applicant claimed that it can be estimated 
that approximately 16.2% of NexoBridTM treated wounds (34.1% 
autograft rate in standard of care group minus 17.9% autograft rate in 
the NexoBridTM treated group) would have been autografted 
had other standard of care methods for burn debridement been used.
---------------------------------------------------------------------------

    \446\ Ibid. Rosenberg, L., et al, A novel rapid and selective 
enzymatic debridement agent for burn wound management: A multi-
center RCT. Burns 2014, Vol 40(3): 466-474.
---------------------------------------------------------------------------

    The applicant asserted that the use of NexoBridTM as a 
non-surgical option for treatment reduces potential adverse events that 
may be associated with surgery or general anesthesia such as blood 
loss. The applicant noted that in the DETECT trial, median blood loss 
during eschar removal was significantly higher in the standard of care 
arm compared with NexoBridTM. It also noted that the 
NCT00324311 trial demonstrated smaller reductions in hemoglobin and 
hematocrit values before and after treatment in the 
NexoBridTM arm compared to the standard of care arm.
    The applicant asserted that the use of NexoBridTM may 
reduce instances of surgical escharotomies which may be needed when a 
circumferential eschar produces a tourniquet effect that compromises 
circulation or movement.447 448 449 According to the 
applicant, this requires an emergency escharotomy involving incising 
through areas of burnt skin to release the eschar and its constrictive 
effects, restore distal circulation, and allow adequate ventilation. 
The applicant claimed that reducing the need for an escharotomy also 
reduces the need for subsequent surgical reconstruction of the 
escharotomy wound, and potential complications, including uncontrolled 
bleeding, incomplete release, damage to deep structures, functional 
deficits, and scarring.
---------------------------------------------------------------------------

    \447\ Kreiger et al, Efficacy of enzymatic debridement of deeply 
burned hands. Burns 2012, Vol 38: 108-112.
    \448\ Giudice et al, Cost Analysis of a Novel Enzymatic 
Debriding Agent for Management of Burn Wounds. Biomed Res Int 2017, 
Vol 2017.
    \449\ Palao et al, Use of a selective enzymatic debridement 
agent (NexoBrid[supreg]) for wound management: Learning curve. World 
J of Dermatology 2017, Vol 6(2): 32-41.
---------------------------------------------------------------------------

    To support the claim that NexoBridTM reduces the time to 
eschar removal, the applicant asserted that NexoBridTM has 
been shown in the two phase 3 multi-center, randomized-controlled 
trials to have a lower average time of eschar removal compared to the 
standard of

[[Page 25290]]

care, with the DETECT study demonstrating 1.0 day eschar removal versus 
3.8 days and NCT00324311 demonstrating 2.2 days versus 8.7 days 
(p<0.0001) for treated and control groups respectively.\450\
---------------------------------------------------------------------------

    \450\ Rosenberg, L., et al, A novel rapid and selective 
enzymatic debridement agent for burn wound management: A multi-
center RCT. Burns 2014, Vol 40(3): 466-474.
---------------------------------------------------------------------------

    The applicant also included a systematic review and meta-analysis 
of clostridial collagenase ointment (CCO) studies by Pham, C. H., et 
al. to support its claim of decreased eschar removal time as compared 
to existing non-surgical therapies.\451\ Per the study, the reported 
average time to clean wound bed (complete eschar removal) for CCO 
ranged from 6 days to 9.3 days with daily dressing changes among the 
prospective studies included in the systematic review. We note that the 
literature review was limited to the efficacy and use of CCO in burn 
patients and did not discuss other standard of care therapies.
---------------------------------------------------------------------------

    \451\ [Insert cite]
---------------------------------------------------------------------------

    The applicant asserted that the use of NexoBridTM can 
lead to decreased need for surgical excision. The applicant stated that 
in a pooled analysis of both Phase 3 clinical trials, 
NexoBridTM exhibited lower incidence of surgical excision to 
complete eschar removal (26.9% vs 70.6%), lower mean percent wound area 
surgically excised (11.5% vs 55.1%), and a higher rate of complete 
eschar removal without rescue surgical excision (90.5% vs 70.1%) 
compared to standard of care. The applicant cited these results as 
proof of the tissue-sparing effects compared with standard of care. The 
applicant further stated that the NCT00324311 study \452\ showed that 
among patients with wounds comprised entirely of deep partial thickness 
(DPT) burns in this study, the incidence of excision or dermabrasion 
after debridement was statistically significantly lower with 
NexoBridTM compared with standard of care (15.1% vs 65.5%, 
p<0.0001), and that the mean percent wound area excised was also 
statistically significantly lower with NexoBridTM, 14.6% 
versus 44.5% in standard of care group (p <0.0001). The applicant 
stated that in the DETECT study, the incidence of complete eschar 
removal in the NexoBridTM group was 93.35% (70 of 75 
patients) versus 100% in the standard of care group (which included 
both surgical and non-surgical debridement) versus 4.0% in the gel 
vehicle placebo group. The applicant stated that the incidence of 
excision to complete eschar removal was statistically significantly 
lower with NexoBridTM, 4.0% versus 72% for the standard of 
care group (p<0.0001).
---------------------------------------------------------------------------

    \452\ Rosenberg, L., et al, A novel rapid and selective 
enzymatic debridement agent for burn wound management: A multi-
center RCT. Burns 2014, Vol 40(3): 466-474.
---------------------------------------------------------------------------

    The applicant asserted that the shorter time to complete eschar 
removal for patients treated with NexoBridTM has been shown 
to be associated with effective prevention of the subsequent need for 
autografting. The applicant stated that in the first published Phase 3 
pivotal clinical trial NCT00324311,\453\ the autograft rate was 17.9% 
in the NexoBridTM treated arm vs. 34.1% in the standard of 
care treated group (p=0.009), and the percentage of wound autografted 
was lower in the NexoBridTM group, 8.4% vs. 21.5% in the 
standard of care group (p=0.0054). The applicant further stated that 
among patients with at least one wound that was entirely a DPT burn, 
significantly fewer wound autografts were performed in the 
NexoBridTM group, 17.9% (19/106 wounds) versus 34% (30/88 
wounds) in the standard of care group (p=0.0099), and the percent 
treated wound area autografted was also significantly lower in the 
NexoBridTM group, 8.4% versus 21.5% in the standard of care 
group (p=0.0054).
---------------------------------------------------------------------------

    \453\ Rosenberg, L., et al, A novel rapid and selective 
enzymatic debridement agent for burn wound management: A multi-
center RCT. Burns 2014, Vol 40(3): 466-474.
---------------------------------------------------------------------------

    The applicant also stated that a prospective single-arm study of 
NexoBridTM showed that 25 patients with partial thickness 
burns who were treated with NexoBridTM experienced a 
reduction in the need for autografting compared to patients treated 
with standard of care.\454\
---------------------------------------------------------------------------

    \454\ Palao, R., et al. (2017). Use of a selective enzymatic 
debridement agent (NexoBrid[supreg]) for wound management: Learning 
curve. World Journal of Dermatology, 6(2), 32-41.
---------------------------------------------------------------------------

    The applicant also cited studies comparing NexoBridTM to 
surgical debridement in hand and facial burns. The applicant stated 
that a single center controlled study of 40 hand burns demonstrated a 
reduced need for autografting with NexoBridTM, with 15% of 
patients receiving NexoBridTM compared to 95% of patients 
treated with the standard of care (excisional surgical debridement) 
requiring autografting (p=0.034).\455\ The single center controlled 
study of 26 face burns demonstrated a reduced need for autografting 
with NexoBrid[supreg], with 15% of patients receiving 
NexoBridTM compared to 77% of patients treated with the 
standard of care requiring autografting (p=-0.002).\456\
---------------------------------------------------------------------------

    \455\ Schulz, A., et al. (2017). Enzymatic versus traditional 
surgical debridement of severely burned hands: a comparison of 
selectivity, efficacy, healing time, and three-month scar quality. 
Journal of Burn Care & Research, 38(4), e745-e755.
    \456\ Schulz, A., et al. (2017). Enzymatic debridement of deeply 
burned faces: healing and early scarring based on tissue 
preservation compared to traditional surgical debridement. Burns, 
43(6), 1233-1243.
---------------------------------------------------------------------------

    The applicant asserted that because the use of 
NexoBridTM reduces areas that require autografting, this 
results in decreased donor site morbidity, which is particularly useful 
for patients with limited donor site area (example, high total body 
surface area burns), or risk factors for delayed wound healing 
(example, advanced age).457 458
---------------------------------------------------------------------------

    \457\ Holmes Iv, J. H., et al. (2018). A comparative study of 
the ReCell[supreg] device and autologous split-thickness meshed skin 
graft in the treatment of acute burn injuries. Journal of Burn Care 
& Research, 39(5), 694-702.
    \458\ Gould, L., et al. (2015). Chronic wound repair and healing 
in older adults: current status and future research. Wound Repair 
and Regeneration, 23(1), 1-13.
---------------------------------------------------------------------------

    Per the applicant, by selectively debriding only non-viable tissue, 
NexoBridTM reduces the area of burn that requires 
autografting compared to surgical excision and other non-surgical 
approaches of eschar debridement. Per the applicant, 
NexoBridTM's selective debridement of non-viable tissue is 
especially useful in delicate areas such as face,\459\ 
hands,460 461 feet, and genitals which are difficult areas 
to excise eschar surgically.462 463 The applicant also 
claimed that the use of NexoBridTM results in decreased 
scarring from the reduced need for autografting.
---------------------------------------------------------------------------

    \459\ Schulz, A., et al. (2017). Enzymatic debridement of deeply 
burned faces: healing and early scarring based on tissue 
preservation compared to traditional surgical debridement. Burns, 
43(6), 1233-1243.
    \459\ Rosenberg et al, A novel rapid and selective enzymatic 
debridement agent for burn wound management: A multi-center RCT. 
Burns 2014, Vol 40(3): 466-474.
    \460\ Schulz, A., et al. (2017). Enzymatic versus traditional 
surgical debridement of severely burned hands: a comparison of 
selectivity, efficacy, healing time, and three-month scar quality. 
Journal of Burn Care & Research, 38(4), e745-e755.
    \461\ Krieger, Y., et al. (2012). Efficacy of enzymatic 
debridement of deeply burned hands. Burns, 38(1), 108-112.
    \462\ Cordts, T., et al. (2016). Enzymatic debridement for the 
treatment of severely burned upper extremities-early single center 
experiences. BMC dermatology, 16(1), 1-7.
    \463\ Hirche, C., et al. (2020). Eschar removal by bromelain 
based enzymatic debridement (NexoBrid[supreg]) in burns: European 
consensus guidelines update. Burns.
---------------------------------------------------------------------------

    The applicant asserted that the two single-center controlled trials 
discussed in this section, one of patients with hand burns\464\ and one 
of patients with

[[Page 25291]]

facial burns,\465\ demonstrated that cosmesis of the healed wound using 
NexoBridTM was comparable if not better than traditional 
surgical debridement (standard of care arm). In addition, per the 
applicant, a single arm prospective study of 36 patients showed that 
only 11.1% of patients treated with NexoBridTM developed 
hypertrophic scars.\466\
---------------------------------------------------------------------------

    \464\ Schultz et al, Enzymatic Versus Traditional Surgical 
Debridement of Severely Burned Hands: A Comparison of Selectivity, 
Efficacy, Healing Time, and Three-Month Scar Quality. J Burn Care 
and Research 2016, Vol 38(4): 745-755.
    \465\ Schultz et al, Enzymatic debridement of deeply burned 
faces: Healing and early scarring based on tissue preservation 
compared to traditional surgical debridement. Burns 2017b, Vol 
43(2017): 1233-1243.
    \466\ Corrales-Benitez et al, Reduced need for grafting and low 
incidence of hypertrophic scarring in burns after enzymatic 
debridement. J. Plastic Surgery Latin America 2016, Vol 42(4).
---------------------------------------------------------------------------

    In further support of their statements suggesting that the use of 
NexoBridTM results in reduced time to complete debridement, 
reduced need for surgery, and reduced need for autografting, the 
applicant submitted a literature review that identified studies 
published between 2012 and 2017 involving the use of 
NexoBridTM in deep partial and full thickness burns.\467\ In 
this article, studies were evaluated for proposed benefits of 
NexoBridTM and categorized under supporting evidence, 
contradicting evidence, and anecdotal opinions. Seven prospective 
studies met the inclusion criteria including four randomized controlled 
trials. Six proposed benefits associated with the use of 
NexoBridTM were extracted from the studies including reduced 
time to complete debridement, need for surgery, area of burns excised, 
need for autograft, time to wound closure, and improved scar quality. 
The authors of the literature review stated that most of the proposed 
benefits had strong supporting evidence from controlled trials as well 
as some anecdotal data. The authors further stated that for the 
proposed benefits of scar quality improvement and reduced time to wound 
healing, three sources and one anecdotal study provided refuting 
evidence. Incidence of pain was also evaluated and was mainly 
anecdotal, lacking formal objective assessment or cohort study.\468\
---------------------------------------------------------------------------

    \467\ Loo, Y. L., Goh, B. K., & Jeffery, S. (2018). An overview 
of the use of bromelain-based enzymatic debridement 
(NexoBrid[supreg]) in deep partial and full thickness burns: 
appraising the evidence. Journal of Burn Care & Research, 39(6), 
932-938.
    \468\ Loo, Y. L., Goh, B. K., & Jeffery, S. (2018). An overview 
of the use of bromelain-based enzymatic debridement 
(NexoBrid[supreg]) in deep partial and full thickness burns: 
appraising the evidence. Journal of Burn Care & Research, 39(6), 
932-938.
---------------------------------------------------------------------------

    Regarding the substantial clinical improvement criterion, we have 
the following concerns. We note that the applicant's claims of 
superiority of NexoBridTM to standard of care debridement 
methods are non-specific because the studies cited were not designed to 
compare NexoBridTM to a specific non-surgical method or an 
enzymatic debridement product. In addition, we are unclear whether 
comparing NexoBridTM to a surgical treatment modality is the 
most appropriate comparator since mechanical means of debridement have 
different clinical indications, risks, and benefits compared to 
enzymatic debridement. We note that studies also did not demonstrate 
that NexoBridTM selectively debrides eschar and does not 
injure viable skin. In addition, it may be difficult to generalize 
across studies of NexoBridTM because the wound care and 
timing of the debridement and subsequent autografting varies across 
different burn centers and studies. We note that we are unable to 
verify the results of the DETECT study as it does not appear that this 
data has been published or provided by the applicant. Finally, we note 
that a review of seven studies of NexoBridTM \469\ observed 
that when compared to the standard of care, there were variable reports 
of the cosmetic outcome of NexoBridTM, prolonged wound 
closure, longer lengths of stay, and significant pain associated with 
NexoBridTM eschar debridement.
---------------------------------------------------------------------------

    \469\ Loo, Y.L., et al, An Overview of the Use of Bromelain-
Based Enzymatic Debridement (NexoBrid[supreg]) in Deep Partial and 
Full Thickness Burns: Appraising the Evidence. J Burn Care and 
Research 2018, Vol 39(6): 932-938.
---------------------------------------------------------------------------

    We invite public comment on whether NexoBridTM meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for the 
NexoBridTM.
m. 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.\470\
---------------------------------------------------------------------------

    \470\ 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.\471\ 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.472 473 474 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).\475\ The applicant noted that 
there are ongoing

[[Page 25292]]

studies to evaluate the impact of the antiviral host activity of 
Olumiant[supreg].
---------------------------------------------------------------------------

    \471\ 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.
    \472\ 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.
    \473\ 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.
    \474\ 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.
    \475\ 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].
    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 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 this 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 are specifically requesting 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.
    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.\476\ 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.
---------------------------------------------------------------------------

    \476\ 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 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 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, 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 this 
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.
    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 note 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

[[Page 25293]]

substance into lower G.I. via natural or artificial opening) could also 
be used to report use of Olumiant[supreg]. We note that as of January 
1, 2021, Olumiant[supreg] is 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.\477\ The applicant claims 
that the mechanism of action for both of these treatments differs from 
Olumiant[supreg], which works as a JAK inhibitor.
---------------------------------------------------------------------------

    \477\ 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, although there may not be 
any other JAK inhibitors for the treatment of COVID-19 assigned to the 
same MS-DRG as Olumiant[supreg], we note that Olumiant[supreg] may map 
to the same MS-DRG as other existing COVID-19 treatments. We also note 
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, we are requesting 
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 are also specifically requesting 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.
    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 are inviting public comment on whether Olumiant[supreg] meets 
the newness criterion.
    With respect to the cost criterion, the applicant performed four 
analyses. Two of these analyses were based on proxy COVID-19 cases 
using ICD-10-CM B97.29 with additional coding to identify 
manifestation. The applicant stated that these cases were then 
differentiated into proxy COVID-19 cases with supplemental oxygen and 
all proxy COVID-19 cases. The applicant stated that they also conducted 
two supplemental analyses to confirm that actual COVID-19 cases using 
Olumiant[supreg] would meet the cost threshold using linked 837 and 835 
inpatient Electronic Data Interchange (EDI) transaction sets that were 
processed during February through June of 2020. The applicant then 
identified COVID-19 cases with supplemental oxygen and all COVID-19 
cases.
    For the first analysis, the applicant searched the FY 2019 MedPAR 
LDS claims data file for potential cases representing patients who may 
be eligible for treatment using Olumiant[supreg]. The applicant 
identified proxy COVID-19 cases with supplemental oxygen by using ICD-
10-CM diagnosis code B97.29 with one of the following ICD-10-CM codes: 
J12.89, J20.8, J40, J22, J98.8, and J80. The applicant excluded ICD-10-
CM codes B34.2 and Z03.818. The applicant stated that this coding 
methodology was based on CDC guidance for coding COVID-19 cases prior 
to April 1, 2020. The applicant then limited the group to those cases 
that had ICD-10-PCS codes for supplemental oxygen. The ICD-10-PCS codes 
included ventilation (5A1935Z, 5A1945Z, 5A1955Z, 5A09357, 5A09358, 
5A09359, 5A0935B, 5A0935Z, 5A09457, 5A09458, 5A09459, 5A0945B, 5A0945Z, 
5A09557, 5A09558, 5A09559, 5A0955B, and 5A0955Z), extracorporeal 
membrane oxygenation (5A15223, 5A1522F, 5A1522G, 5A1522H, 5A15A2F, 
5A15A2G, and 5A15A2H), and ICD-10-CM code Z99.81. This resulted in 473 
cases mapping to the 11 MS-DRGs listed below.

[[Page 25294]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.165

    For the second analysis, the applicant identified all proxy COVID-
19 cases using the same ICD-10-CM codes that were previously described; 
however, the applicant did not include or exclude any cases based on 
the ICD-10-PCS codes listed in claims. This resulted in 1,726 cases 
mapping to the following 25 MS-DRGs.
[GRAPHIC] [TIFF OMITTED] TP10MY21.166

[GRAPHIC] [TIFF OMITTED] TP10MY21.167

    For the third analysis, the applicant used Inovalon provider-
sourced pre- and post-adjudicated claims data to identify CY 2020 
claims for COVID-19 cases that may be eligible for treatment involving 
Olumiant[supreg]. Specifically, the applicant used linked 837 and 835 
inpatient Electronic Data Interchange (EDI) transaction sets that were 
processed between February and June of 2020. For discharges prior to 
April 1, 2020, the applicant identified cases using ICD-10-CM diagnosis 
code B97.29 with one of the following ICD-10-CM codes: J12.89, J20.8, 
J40, J22, J98.8, and J80. The applicant excluded ICD-10-CM codes B34.2 
and Z03.818. For cases discharged on or after April 1, 2020, the 
applicant identified cases using ICD-10-CM code U07.1 and excluded 
codes B34.2 and Z03.818. The applicant then limited the group to those 
cases that had ICD-10-PCS codes for supplemental oxygen. The ICD-10-PCS 
codes included ventilation (5A1935Z, 5A1945Z, 5A1955Z, 5A09357, 
5A09358, 5A09359, 5A0935B, 5A0935Z, 5A09457, 5A09458, 5A09459, 5A0945B, 
5A0945Z, 5A09557, 5A09558, 5A09559, 5A0955B, and 5A0955Z) and 
extracorporeal membrane oxygenation (5A15223, 5A1522F, 5A1522G, 
5A1522H, 5A15A2F, 5A15A2G, and 5A15A2H), and ICD-10-CM code Z99.81 
Dependence on supplemental oxygen. This resulted in 966 cases, which 
were mapped to the following 7 MS-DRGs:

[[Page 25295]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.168

    For the fourth analysis, the applicant identified all COVID-19 
cases using the same ICD-10-CM diagnosis codes as previously described. 
For discharges prior to April 1, 2020, the applicant identified cases 
using ICD-10-CM diagnosis code B97.29 with one of the following ICD-10-
CM codes: J12.89, J20.8, J40, J22, J98.8, and J80. The applicant 
excluded ICD-10-CM codes B34.2 and Z03.818. For cases discharged on or 
after April 1, 2020, the applicant identified cases using ICD-10-CM 
code U07.1 and excluded codes B34.2 and Z03.818. The applicant did not 
include or exclude any cases based on the ICD-10-PCS codes listed in 
claims. Based on this analysis, the applicant found 3,826 cases, which 
map to 21 MS-DRGs listed below.
[GRAPHIC] [TIFF OMITTED] TP10MY21.169

    For each analysis, the applicant then removed 12.5 percent of the 
length of stay charges from the relevant cases to estimate the 
reduction in charges due to decrease in number of hospitalization days 
that may be avoided through use of baricitinib. The applicant 
determined this percentage based on findings from the ACTT-2 
trial,\478\ sponsored by the National Institute of Allergy and 
Infection Diseases (NIAID), which found an improved median time to 
recovery from 8 to 7 days (that is, a 12.5 percent improvement).
---------------------------------------------------------------------------

    \478\ Kalil, A.C., Patterson, T.F., Mehta, A.K., et al. 
Baricitinib plus remdesivir for adults with Covid-19. (2020). New 
England Journal of Medicine. DOI: 10.1056/NEJMoa2031994
---------------------------------------------------------------------------

    For the first two analyses, the applicant then standardized the 
charges and applied a 2-year inflation factor of 1.131096 that the 
applicant stated was used in the FY 2021 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges. We note that the 2-year inflation 
factor used in the FY 2021 IPPS/LTCH PPS final rule to calculate 
outlier threshold charges is 1.13218, which would have increased the 
inflated charges figure. For analysis three and four, the applicant 
standardized the charges and applied a one-year inflation factor of 6.4 
percent, the one-year inflation factor published in the FY 2021 IPPS/
LTCH PPS final rule.
    For each analysis, the applicant then calculated and added the 
charges for Olumiant[supreg] by taking the estimated per patient cost 
of the drug, and converting it to a charge by dividing the costs by the 
national average CCR (cost-to-charge ratio) of 0.187 for drugs from the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58601).
    In the first analysis, which included proxy COVID-19 with 
supplemental oxygen cases, the applicant computed a final inflated 
average case-weighted standardized charge per case of $88,728, which 
exceeded the average case-weighted threshold amount of $69,276.
    In the second analysis, which included all proxy COVID-19 cases, 
the applicant computed a final inflated average case-weighted 
standardized charge per case of $68,562, which exceeded the average 
case-weighted threshold amount of $56,643.
    In the third analysis, which included COVID-19 with supplemental 
oxygen cases, the applicant computed a final inflated average case-
weighted

[[Page 25296]]

standardized charge per case of $198,114, which exceeded the average 
case-weighted threshold amount of $123,238.
    In the fourth analysis, which included all COVID-19 cases, the 
applicant computed a final inflated average case-weighted standardized 
charge per case of $99,870, which exceeded the average case-weighted 
threshold amount of $75,891.
    Because the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount 
under both analyses described previously, the applicant asserted that 
the technology meets the cost criterion.
    We invite public comments on whether Olumiant[supreg] meets the 
cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that Olumiant[supreg] in combination with remdesivir 
represents a substantial clinical improvement over existing 
technologies because it improves time to recovery, improves the odds of 
improvement in clinical status at Day 15 after enrollment, and reduces 
mortality in the treatment of COVID-19 compared to remdesivir 
alone.\479\ The applicant also stated that the combination of 
Olumiant[supreg] and remdesivir has a favorable risk/benefit profile in 
comparison to remdesivir alone. The applicant also claimed that 
Olumiant[supreg] improves respiratory function in patients treated with 
corticosteroids for SARS-CoV-2 pneumonia when compared with 
corticosteroids alone.
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    \479\ Kalil, A.C., Patterson, T.F., Mehta, A.K., et al. 
Baricitinib plus remdesivir for adults with Covid-19. (2020). New 
England Journal of Medicine. DOI: 10.1056/NEJMoa2031994.
---------------------------------------------------------------------------

    In support of these claims, the applicant submitted the results of 
the Adaptive COVID-19 Treatment Trial (ACTT-2) \480\ which was a 
randomized, double-blind, placebo-controlled clinical trial sponsored 
by the National Institute of Allergy and Infectious Diseases (NIAID), 
part of the National Institutes of Health (NIH). The ACTT-2 trial 
included 1,033 hospitalized patients with COVID-19 and assessed whether 
the combination of Olumiant[supreg] plus remdesivir was superior to 
remdesivir + placebo. There were 515 patients randomized to the 
treatment group and 518 to the control group. Of those in the treatment 
group, 507 (98.4 percent) received treatment as assigned. Of those in 
the control group, 509 (98.3 percent) received treatment as assigned. A 
total of 498 patients in the treatment group and 495 in the control 
group completed the trial through day 29, recovered, or died. The mean 
age of the patients was 55.4 years, and 63.1 percent were male. An 
ordinal scale was used in the study that identified the patient's 
baseline disease severity at enrollment and ranged from 1 (not 
hospitalized, no limitations on activities) to 8 (death). This scale is 
displayed in the table below. The intention-to-treat population 
included 706 patients with moderate disease (ordinal score of 4 
[hospitalized, not requiring supplemental oxygen--requiring ongoing 
medical care] or 5 [hospitalized, requiring supplemental oxygen]) and 
327 with severe disease (ordinal score of 6 [hospitalized, on non-
invasive ventilation or high flow oxygen devices] or 7 [hospitalized, 
on mechanical ventilation or ECMO]). Patients received remdesivir 
intravenously as a 200-mg loading dose on day 1, followed by a 100-mg 
maintenance dose administered daily on days 2 through 10 or until 
hospital discharge or death. Baricitinib was administered as a 4-mg 
daily dose (either orally [two 2-mg tablets] or through a nasogastric 
tube) for 14 days or until hospital discharge.
---------------------------------------------------------------------------

    \480\ Ibid.
    [GRAPHIC] [TIFF OMITTED] TP10MY21.170
    
    In support of its claim that Olumiant[supreg] in combination with 
remdesivir improves time to recovery from COVID-19 compared to 
remdesivir alone, the applicant cited the primary outcome of the ACTT-2 
study, which showed that the median time to recovery for the 
Olumiant[supreg] plus remdesivir (treatment) group was 7 days and the 
median time to recovery for remdesivir plus placebo (control) group was 
8 days (rate ratio for recovery, 1.16 (1.01-1.32); p=0.03). Recovery 
was defined as the participant being well enough for hospital 
discharge, meaning the participant either no longer required 
supplemental oxygen or ongoing medical care in the hospital, or was no 
longer hospitalized at Day 29.
    The applicant also stated that the median time to recovery among 
patients receiving noninvasive ventilation or high-flow oxygen 
(baseline ordinal score of 6) was 10 days for the treatment group and 
18 days in the control group (rate ratio for recovery, 1.51; 95 percent 
CI, 1.10-2.08). The applicant stated that the median time to recovery 
was one day shorter among patients receiving supplemental oxygen 
(baseline ordinal score of 5) in the Olumiant[supreg] and remdesivir 
group (5 days vs. 6 days) rate ratio 1.17; CI, 0.98-1.39). The 
applicant noted that for those receiving mechanical ventilation or ECMO 
at enrollment (baseline ordinal score of 7), the rate ratio for 
recovery was 1.08 (95 percent CI, 0.59 to 1.97).
    The applicant asserted that the secondary outcome of the ACTT-2 
study supports its claim of improved odds of improvement in clinical 
status at Day 15 based on the eight-category ordinal scale. The 
applicant summarized the results of the study which showed that the 
odds of improvement in clinical status at Day 15 were greater in the 
Olumiant[supreg] group compared to the placebo group (odds ratio 1.3; 
95 percent CI, 1.0-1.6). The applicant also stated that the odds of

[[Page 25297]]

improvement in clinical status at Day 15 were greater for patients 
receiving noninvasive ventilation or high-flow oxygen (baseline ordinal 
score of 6) in the Olumiant[supreg] group versus the control group 
(odds ratio 2.2; 95 percent CI, 1.4-3.6).
    The applicant asserted that the study conducted by Kalil et al. 
(2020) supports its claim of reduced mortality in the Olumiant[supreg] 
and remdesivir group compared to the control group because the Kaplan-
Meier estimates of mortality at day 28 after randomization were 5.1 
percent (95 percent CI, 3.5-7.6) in the combination (Olumiant[supreg] 
and remdesivir) group and 7.8 percent (95 percent CI, 5.7 to 10.6) in 
the control group (hazard ratio for death, 0.65; 95 percent CI, 0.39 to 
1.09). The applicant also stated that the greatest numerical 
differences in mortality between patients in the combination group and 
those in the control group were observed among those with a baseline 
ordinal score of 5 (1.9 percent vs. 4.7 percent; hazard ratio, 0.40; 95 
percent CI, 0.14 to 1.14) or 6 (7.5 percent vs. 12.9 percent; hazard 
ratio, 0.55; 95 percent CI, 0.22 to 1.38). The applicant also cited the 
Kaplan-Meier estimates of mortality at 14 days after randomization, 
which were 1.6 percent in the combination group and 3.0 percent in the 
control group (hazard ratio, 0.54; 95 percent CI, 0.23 to 1.28).
    The applicant also asserted that the incidence of new use of oxygen 
was lower in patients treated with Olumiant[supreg] in combination with 
remdesivir compared to remdesivir alone (22.9 percent vs. 40.3 percent 
respectively; difference, -17.4 percentage points; 95 percent CI, -31.6 
to -2.1) and that the incidence of new use of mechanical ventilation or 
ECMO was lower in the combination group (10.0 percent vs. 15.2 percent; 
difference, -5.2 percentage points; 95 percent CI, -9.5 to -0.9) based 
on Kalil et al. (2020). The applicant also stated that there were fewer 
median days of receipt of mechanical ventilation or ECMO among the 128 
patients for which these interventions were started after enrollment or 
who died with no observed new use in the Olumiant[supreg] in 
combination with remdesivir group compared to the remdesivir group (16 
median days in the combination group and 27 median days in the control 
group (difference, -11.0; 95 percent CI, -18.3 to -3.7)). The applicant 
also stated that the incidence of progression to death or noninvasive 
or invasive ventilation was lower in the combination group than in the 
control group (22.5 percent vs. 28.4 percent; rate ratio, 0.77; 95 
percent CI, 0.60 to 0.98) and that the incidence of progression to 
death or invasive ventilation was also lower (12.2 percent vs. 17.2 
percent; rate ratio, 0.69; 95 percent CI, 0.50 to 0.95).
    The applicant asserted that the study conducted by Kalil et al. 
(2020) supports its claim that the combination of Olumiant[supreg] in 
combination with remdesivir has a favorable benefit/risk profile 
compared to remdesivir alone. The applicant states that serious adverse 
events occurred in 81 patients (16.0 percent) in the combination group 
(six of these were thought to be related to the trial product) and in 
107 patients (21.0 percent) in the control group (five of these were 
thought to be related to the trial product) and the between-group 
difference was -5.0 percentage points (95 percent CI, -9.8 to -0.3; P = 
0.03). The applicant also states that Grade 3 or 4 adverse events 
occurred in 207 patients (40.7 percent) in the combination group and 
238 (46.8 percent) in the control group.
    The applicant also cited an observational study \481\ to support 
the claim that there was greater improvement in pulmonary function in 
patients receiving lopinavir/ritonavir and hydroxychloroquine with 
Olumiant[supreg] and corticosteroids when compared to patients 
receiving lopinavir/ritonavir and hydroxychloroquine with 
corticosteroids alone. In this study, the primary end point was the 
change in oxygen saturation as measured by pulse oximetry (SpO2)/FiO2 
from hospitalization to discharge. The applicant stated that there was 
a greater improvement in SpO2/FiO2 from hospitalization to discharge 
observed in the Olumiant[supreg] in combination with corticosteriods 
versus the corticosteroids alone group (mean differences adjusted for 
IPSW, 49; 95 percent CI: 22, 77; p<0.001).
---------------------------------------------------------------------------

    \481\ Rodriguez, J.L., Sanchez-Niveas, G., Arevalo-Serrano, J., 
et al. (2020). Baricitinib improves respiratory function in patients 
treated with corticosteroids for SARS-CoV-2 pneumonia: An 
observational study. Rheumatology. 00:1-9.
---------------------------------------------------------------------------

    In our assessment of the applicant's claims in support of 
substantial clinical improvement, we have the following concerns. With 
regard to the ACTT-2 trial, we note that there were no statistically 
significant differences in time to recovery or odds of improvement in 
clinical status at Day 15 between the Olumiant[supreg]+remdesivir group 
compared to the remdesivir+placebo group for patients with a baseline 
ordinal score of 4, 5, or 7. We further note that although the 
applicant asserted that Olumiant[supreg]+remdesivir reduces mortality 
compared to remdesivir alone, the difference between the treatment and 
control groups was not statistically significant. We also note that the 
ACTT-2 study protocol prohibited the use of systemic corticosteroids 
for the treatment of COVID-19 but allowed systemic steroids for 
standard indications such as asthma exacerbation, acute respiratory 
distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), 
laryngeal edema, adrenal insufficiency and shock \482\ and we are 
therefore unsure if the use of corticosteroids among the patient 
population may be a confounding factor. With regard to the Rodriguez-
Garcia (2020) study, we note that this study did not involve the 
treatment of patients with Olumiant[supreg] in combination with 
remdesivir, which is the authorized use per its EUA, and the use of 
multiple treatments in this trial may make the effect of 
Olumiant[supreg] on greater improvement in pulmonary function unclear. 
Finally, we note that the current clinical guidelines from the 
Infectious Diseases Society of America (IDSA) recommend the use of 
Olumiant[supreg] with remdesivir rather than remdesivir alone among 
hospitalized patients with severe COVID-19 who cannot receive 
corticosteroids because of a contraindication.\483\ In addition, 
guidelines from the National Institutes of Health (NIH) state that 
there are insufficient data to recommend for or against the use of 
Olumiant[supreg] in combination with remdesivir, where corticosteroids 
can be used instead, and there is insufficient data to recommend for or 
against the use of Olumiant[supreg], in combination with 
corticosteroids.\484\ We are therefore interested in data regarding the 
use of Olumiant[supreg] in combination with remdesivir over 
corticosteroids.
---------------------------------------------------------------------------

    \482\ Ibid.
    \483\ Infectious Diseases Society of America. (2021, March 18). 
Recommendations 15-16: Baricitinib with remdesivir vs. remdesivir 
alone for hospitilized patients who cannot recieve corticosteriods 
due to contraindication. IDSA Guidelines on the Treatment and 
Management of Patients with COVID-19. Retrieved from https://www.idsociety.org/practice-guideline/covid-19-guideline-treatment-and-management/. * Severe patients defined as defined as patients 
with SpO2 <=94% on room air, including patients on 
supplemental oxygen, oxygen through a high-flow device, or non-
invasive ventilation.
    \484\ National Institutes of Health. (2021, February 11). Kinase 
Inhibitors: Baricitinib and Other Janus Kinase Inhibitors, and 
Bruton's Tyrosine Kinase Inhibitors., COVID-19 Treatment Guidelines. 
Retrieved from https://www.covid19treatmentguidelines.nih.gov/immunomodulators/kinase-inhibitors/.
---------------------------------------------------------------------------

    We welcome public comment on whether Olumiant[supreg] meets the 
substantial clinical improvement criterion.
    In this section, we summarize and respond to written public 
comments

[[Page 25298]]

received in response to the New Technology Town Hall meeting notice 
published in the Federal Register regarding the substantial clinical 
improvement criterion for Olumiant[supreg].
    Comment: The applicant responded to questions elicited by its 
presentation at the New Technology Town Hall Meeting held in December 
2020.
    The applicant was asked to elaborate on the efficacy of 
Olumiant[supreg] and remdesivir as monotherapies versus in combination 
and how to think about appropriate use. The applicant stated that the 
evidence generated in randomized controlled clinical trials designed to 
evaluate remdesivir, Olumiant[supreg], and the combination of 
Olumiant[supreg] and remdesivir has come primarily from the Adaptive 
Covid-19 Treatment Trial (ACTT) trials sponsored by NIAID. The 
applicant also stated that ACTT-1 was the first trial of the ACTT 
program and showed that remdesivir, when compared to placebo, is an 
effective treatment for hospitalized adult patients with coronavirus 
disease 2019 (Covid-19) pneumonia who were receiving standard of care 
as background treatment. The applicant stated that to address unmet 
medical needs still identified after the completion of ACTT-1 (namely 
morbidity and mortality due to Covid-19), ACTT-2 was designed to 
evaluate the combination of Olumiant[supreg] and remdesivir versus 
remdesivir in hospitalized adult patients with Covid-19 pneumonia who 
were receiving standard of care as background treatment. The applicant 
stated that the study did not evaluate Olumiant[supreg] alone; 
therefore, they do not have results generated by a RCT on the efficacy 
and safety profile of Olumiant[supreg] alone for the treatment of 
Covid-19 patients. The applicant stated that the ACTT-2 trial results 
show that the combination of Olumiant[supreg] was superior to 
remdesivir and placebo in reducing recovery time and accelerating 
improvement in clinical status among hospitalized patients with Covid-
19, notably among those receiving high-flow oxygen or noninvasive 
ventilation.
    The applicant was asked what the mechanism of action is for 
baricinitib's antiviral activity. The applicant stated that patients 
diagnosed with COVID-19 are at an elevated risk for excess morbidity 
and mortality due to the underlying severe acute respiratory syndrome 
coronavirus 2 (SARS-CoV-2) infection and subsequent cytokine 
activation. Management of COVID-19 is supportive; and respiratory 
failure from acute respiratory distress syndrome (ARDS) is the leading 
cause of mortality. The cause of respiratory failure in COVID-19 is a 
hyperinflammatory state characterized by upregulation of multiple 
cytokines. The applicant stated that in Wuhan, China, COVID-19-infected 
patients admitted to the ICU exhibited increased plasma concentrations 
of IL-2, IL-7, IL-10, GM-CSF, IP-10, MCP-1, MIP1-[alpha], and TNF-
[alpha], compared with the non-ICU patients. Elevated IL-6 and 
hyperferritinemia were predictors of death in these patients with 
COVID-19.485 486 487
---------------------------------------------------------------------------

    \485\ Huang C, Wang Y, Li X, et al. Clinical features of 
patients infected with 2019 novel coronavirus in Wuhan, China. 
Lancet. 2020; 395(10223):497-506. https://doi.org/10.1016/S0140-6736(20)30183-5.
    \486\ Ruan Q, Yang K, Wang W, et al. Clinical predictors of 
mortality due to COVID-19 based on an analysis of data of 150 
patients from Wuhan, China. Intensive Care Med. 2020; 46(5):846-848. 
https://doi.org/10.1007/s00134-020-05991-x.
    \487\ Zhou F, Yu T, Du R, et al. Clinical course and risk 
factors for mortality of adult inpatients with COVID-19 in Wuhan, 
China: A retrospective cohort study. Lancet. 2020;395(10229):1054-
1062. https://doi.org/10.1016/S0140-6736(20)30566-3.
---------------------------------------------------------------------------

    The applicant stated that Olumiant[supreg] may be a viable 
treatment in patients with COVID-19 requiring supplemental oxygen, 
invasive mechanical ventilation, or ECMO because of its anti-
inflammatory activity and ability to reverse dysregulated inflammatory 
markers in patients with COVID-19.488 489 Relevant to COVID-
19 and the potential role played by IL-6, the applicant stated that it 
is notable that treatment with Olumiant[supreg] 4 mg resulted in 
reduced plasma levels of IL-6 in hospitalized patients with COVID-19, a 
finding that was replicated after being observed in patients with 
RA.490 491 492
---------------------------------------------------------------------------

    \488\ 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.
    \489\ 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.
    \490\ 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.
    \491\ 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.
    \492\ 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.
---------------------------------------------------------------------------

    The applicant stated that the biochemical inhibitory effects of 
Olumiant[supreg] on human numb-associated kinase (NAK) members, 
responsible for SARS-CoV-2 viral propagation, measuring nanomolar 
affinities for AAK1, BIKE, and GAK were recently confirmed.\493\ In 
addition, the applicant noted that some plasma markers that were 
dysregulated in moderate to severe hospitalized patients with COVID-19, 
that represent myeloid dysregulation, endothelial and cardiovascular 
inflammation, along with reduced antigen presenting plasmacytoid 
dendritic cells, were normalized over time with Olumiant[supreg] 
treatment.\494\ The applicant stated that the impact of this antiviral 
host activity in patients with COVID-19 is being evaluated through 
collection of nasopharyngeal swabs, serum and whole blood for RNA, 
epigenetic analysis, and cellular phenotyping in the ongoing randomized 
Study KHAA.
---------------------------------------------------------------------------

    \493\ 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.
    \494\ 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.
---------------------------------------------------------------------------

    The applicant stated that previous studies of corticosteroids in 
other viral pneumonias, especially SARS and Middle East respiratory 
syndrome (MERS), found an association with delayed viral clearance, and 
reinforced concerns that corticosteroids may impair host response to 
SARS-CoV-2.495 496 In contrast, treatment with 
Olumiant[supreg] from 2 distinct clinical case series indicate that the 
adaptive immune response responsible to generate IgG antibodies against 
SARS-CoV-2-specific spike proteins remains intact after treatment with 
Olumiant[supreg].497 498 The applicant stated that the 
effects of corticosteroid treatment on adaptive immunity are

[[Page 25299]]

believed to occur through the non-canonical signaling pathways. The 
applicant asserted that the immunomodulatory pathway targeted by 
Olumiant[supreg], JAK1/JAK2 signaling, opposed to NFKB (nuclear factor 
kappa-B cells) signaling targeted by corticosteroids, may offer an 
explanation to these effects.
---------------------------------------------------------------------------

    \495\ Lee N, Allen Chan KC, Hui DS, et al. Effects of early 
corticosteroid treatment on plasma SARS associated coronavirus RNA 
concentrations in adult patients. J Clin Virol. 2004; 31(4):304-309. 
https://doi.org/10.1016/j.jcv.2004.07.006.
    \496\ Arabi YM, Mandourah Y, Al-Hameed F, et al; Saudi Critical 
Care Trial Group. Corticosteroid therapy for critically ill patients 
with Middle East Respiratory Syndrome. Am J Respir Crit Care Med. 
2018; 197(6):757-767. https://doi.org/10.1164/rccm.201706-1172OC.
    \497\ 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.
    \498\ 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.
---------------------------------------------------------------------------

    The applicant also noted differences between Olumiant[supreg] and 
dexamethasone. The applicant stated that drugs acting on glucocorticoid 
receptors, such as dexamethasone, have a broad pathway approach to 
reduce inflammation that is known to be associated with profound 
immunosuppression, secondary hospital-acquired infections, 
gastrointestinal bleeding, hyperglycemia, and post-hospital 
neuromuscular weakness. JAK inhibitors, such as Olumiant[supreg], act 
on several critical pathways to reduce inflammation while minimizing 
biological redundancy and have favorable PK properties and less 
immunosuppression.\499\
---------------------------------------------------------------------------

    \499\ 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.
---------------------------------------------------------------------------

    The applicant stated that the anti-inflammatory effects of 
Olumiant[supreg] have also been demonstrated by the reduction of serum 
levels of IFN-[gamma], IP-10, GM-CSF, and MCP-1 in pediatric patients 
with steroid-dependent chronic inflammation, resulting in control of 
disease activity and the ability to wean or taper steroids.\500\ The 
applicant went on to state that, furthermore, dose[hyphen]dependent 
decreases in IFN biomarkers confirmed an in vivo effect of 
Olumiant[supreg] on type[hyphen]1 IFN signaling in pediatric patients 
suffering from CANDLE and SAVI.\501\
---------------------------------------------------------------------------

    \500\ Sanchez GAM, Reinhardt A, Ramsey S, et al. JAK1/2 
inhibition with baricitinib in the treatment of autoinflammatory 
interferonopathies. J Clin Invest. 2018; 128(7):3041-3052. https://doi.org/10.1172/JCI98814.
    \501\ Kim H, Brooks KM, Tang CC, et al. Pharmacokinetics, 
pharmacodynamics, and proposed dosing of the oral JAK1 and JAK2 
inhibitor baricitinib in pediatric and young adult CANDLE and SAVI 
patients. Clin Pharmacol Ther. 2018; 104(2):364-373. https://doi.org/10.1002/cpt.936.
---------------------------------------------------------------------------

    The applicant was asked if the adverse events were higher or 
unchanged among at risk subgroup populations over 65 years with 
comorbidities such as diabetes or chronic lung or renal disease in 
patients with COVID-19 and treated with Olumiant[supreg]. The applicant 
responded that there were 71 and 78 patients in the remdesivir+placebo 
groups and Olumiant[supreg]+remdesivir groups, respectively, who were 
over 65 years of age and had diabetes, chronic lung disease or renal 
disease in ACTT-2. The applicant stated that treatment emergent adverse 
events were reported in 62.0 percent of remdesivir+placebo and 57.7 
percent of Olumiant[supreg]+remdesivir patients. Serious adverse events 
were reported in 33.8 percent of remdesivir+placebo and 28.2 percent of 
Olumiant[supreg]+remdesivir patients. The applicant stated that these 
findings are consistent with that in the overall population; fewer 
events in the Olumiant[supreg]+remdesivir group compared to remdesivir 
and placebo group.
    Lastly, the applicant was asked to explain the difference in median 
time to recovery between patients who did not receive oxygen, which was 
5 days in the Olumiant[supreg] and remdesivir group, and 4 days in the 
remdesivir and placebo group. For patients that did receive 
supplemental O2 and other respiratory interventions, the median time to 
recovery was shorter in those patients who received Olumiant[supreg] 
and remdesivir compared to the remdesivir and placebo group. The 
applicant replied that across all outcome measures, a more pronounced 
treatment effect was observed in patients with more severe disease at 
baseline. These data did not show additional benefit of adding 
Olumiant[supreg] to remdesivir for patients in the milder disease 
status. The applicant also stated that the ACTT-2 trial was not 
designed or powered to evaluate efficacy in each subgroup of patients 
per baseline ordinal scale. The applicant stated that these data led 
the applicant to request Emergency Use Authorization for 
Olumiant[supreg] and FDA authorized the use of Olumiant[supreg] in 
combination with remdesivir, for treatment of suspected or laboratory 
confirmed COVID-19 in hospitalized adults and pediatric patients 2 
years of age or older, requiring supplemental oxygen, invasive 
mechanical ventilation, or extracorporeal membrane oxygenation (ECMO).
    Response: We appreciate the applicant's comment. We will take the 
responses into consideration when deciding whether to approve new 
technology add-on payments for Olumiant[supreg].
n. 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 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

[[Page 25300]]

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.502 503 Unknown abdominal pain, infection, and 
foreign body removal were also cited by the applicant as being common 
indications for an inpatient colonoscopy.
---------------------------------------------------------------------------

    \502\ 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.
    \503\ 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 prepared for colonoscopies, leading 
to one extra day in the hospital compared to patients that were 
adequately prepared.\504\ 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.\505\ 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.506 507 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.\508\
---------------------------------------------------------------------------

    \504\ 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.
    \505\ 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.
    \506\ 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.
    \507\ 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.
    \508\ 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.

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

[[Page 25301]]

    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.\509\ The 
applicant used the Boston Bowel Preparation Scale (BBPS), developed by 
Lai E. et al,\510\ 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.
---------------------------------------------------------------------------

    \509\ 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.
    \510\ 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.511 512 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.\513\ 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.\514\ 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.
---------------------------------------------------------------------------

    \511\ 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.
    \512\ 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.
    \513\ 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.
    \514\ Ibid. 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.
---------------------------------------------------------------------------

    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.
    Currently, there are no ICD-10-PCS procedure codes to uniquely 
identify procedures involving the Pure-Vu[supreg] System. We note that 
the applicant has submitted a request for approval for a unique ICD-10-
PCS code for the use of the Pure-Vu[supreg] System beginning FY 2022.
    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 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

[[Page 25302]]

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.\515\ 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.
---------------------------------------------------------------------------

    \515\ 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.
    After reviewing the information submitted by the applicant, we are 
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, we are unsure if the limited availability noted by 
the applicant would allow the technology to be considered commercially 
available. We are also unclear what the applicant means regarding the 
ClearPath system being not fully brought to the U.S. market. If the 
ClearPath system and/or earlier versions of the Pure-Vu 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. If the current version of Pure-Vu is 
substantially similar to ClearPath and/or previous versions, then it 
appears that the current Pure-Vu system may no longer be within the 
newness period. We further note 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 are 
therefore uncertain as to whether these features of the Pure-Vu[supreg] 
System result in a new mechanism of action. We invite public comment on 
whether the Pure-Vu[supreg] System has a new mechanism of action 
compared to these predicate devices.
    We are inviting public comments on whether the Pure-Vu[supreg] 
System is substantially similar to existing technologies and whether it 
meets the newness criterion.
    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._ 516 (malignant neoplasm of colon). The 
ICD-10-PCS procedure codes listed in the following table were used to 
identify claims involving colonoscopy procedures.
---------------------------------------------------------------------------

    \516\ Fourth character is required to describe specific location 
of neoplasm.
[GRAPHIC] [TIFF OMITTED] TP10MY21.171

    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

[[Page 25303]]

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 note 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 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 question whether all cases identified by 
the applicant appropriately represent potential cases eligible for the 
Pure-Vu[supreg] System. We invite public comment on whether the Pure-
Vu[supreg] System meets the cost criterion.
    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.\517\ 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.
---------------------------------------------------------------------------

    \517\ 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.\518\ 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 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.
---------------------------------------------------------------------------

    \518\ 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.\519\ 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]).
---------------------------------------------------------------------------

    \519\ 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 7.5 oz Magnesium Citrate (MgC) each 
taken with 19.5 oz of clear liquid (``Mag Citrate 15 oz arm''), and 18 
patients

[[Page 25304]]

ingested 2 doses of 5 oz MgC taken with 16 oz of clear liquid (``Mag 
Citrate 10 oz 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 15 oz arm, the mean BBPS score improved from 3.62 
to 8.95. For the Mag Citrate 10 oz 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 have the following concerns. 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 note 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 note 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 note 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 also note 
that the Helmut, et al. study noted one procedure related perforation 
which required surgical repair and we invite public comments regarding 
the concern of procedure related perforation.
    We are inviting public comments on whether the Pure-Vu[supreg] 
System meets the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for the Pure-
Vu[supreg] System.
o. 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

[[Page 25305]]

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. 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.\520\ 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.\521\
---------------------------------------------------------------------------

    \520\ Ovbiagele B, et al. Stroke Epidemiology: Advancing Our 
Understanding of Disease Mechanism and Therapy Neurotherapeutics. 
(2011) 8:319-329.
    \521\ 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,\522\ 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.\523\
---------------------------------------------------------------------------

    \522\ Rapid ASPECTS 510(k) clearance letter from FDA: https://www.accessdata.fda.gov/cdrh_docs/pdf20/K200760.pdf.
    \523\ 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 beginning 
FY 2022. 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 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 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

[[Page 25306]]

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 invite 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.
    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.

[[Page 25307]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.172


[[Page 25308]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.173

    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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.174

    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.

[[Page 25309]]

    The applicant then added charges for the technology. The applicant 
stated that it estimated the cost per case of Rapid ASPECTS using 
historical 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 note the following concerns 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 would like to understand why these 
MS-DRGs and their assigned cases were included in the baseline 
analysis. 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.
    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 note 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 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 invite public comment on whether Rapid ASPECTS meets the cost 
criterion.
    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.\524\ 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.\525\ 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:
---------------------------------------------------------------------------

    \524\ 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.
    \525\ 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.\526\
---------------------------------------------------------------------------

    \526\ 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 above-recommended guidelines from 
the

[[Page 25310]]

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.\527\ 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).\528\ 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.\529\
---------------------------------------------------------------------------

    \527\ 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.
    \528\ 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.
    \529\ 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 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 safe 
to give tPA if the early infarct signs were confined to less than one-
third of the middle cerebral artery territory.\530\
---------------------------------------------------------------------------

    \530\ 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).\531\ 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.\532\
---------------------------------------------------------------------------

    \531\ 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):1670-4.
    \532\ 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.533 534 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.\535\ 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 above, require an ASPECT score greater than or 
equal to six 6 for a patient to qualify for thrombectomy in the early 
treatment window.\536\
---------------------------------------------------------------------------

    \533\ Goyal M, Menon BK, et al for the HERMES collaborators. 
Endovascular thrombectomy after large-vessel ischaemic stroke: A 
meta[hyphen]analysis of individual patient data from five randomised 
trials. Lancet 2016; 387: 1723-31.
    \534\ 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.
    \535\ 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.
    \536\ 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

[[Page 25311]]

agreement, even among experts.537 538 539 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.\540\ 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.\541\ 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.
---------------------------------------------------------------------------

    \537\ 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.
    \538\ 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.
    \539\ 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[hyphen]12.
    \540\ 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[hyphen]12.
    \541\ 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.\542\ 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.
---------------------------------------------------------------------------

    \542\ 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 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.\543\ 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.
---------------------------------------------------------------------------

    \543\ Goyal M, Menon BK, et al for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: a meta-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.544 545
---------------------------------------------------------------------------

    \544\ 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.
    \545\ 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.\546\
---------------------------------------------------------------------------

    \546\ 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.\547\ 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).\548\
---------------------------------------------------------------------------

    \547\ 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.
    \548\ 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.

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[[Page 25312]]

    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.\549\
---------------------------------------------------------------------------

    \549\ 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.\550\
---------------------------------------------------------------------------

    \550\ 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 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).\551\
---------------------------------------------------------------------------

    \551\ 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.\552\
---------------------------------------------------------------------------

    \552\ 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.553 554 555 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.\556\ 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.\557\ 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.
---------------------------------------------------------------------------

    \553\ 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.
    \554\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
    \555\ 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.
    \556\ 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.
    \557\ 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 have 
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 note 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 are also unclear whether a 
mean ASPECT score, identified from radiologists whom

[[Page 25313]]

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 question 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 note 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, 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 note that the applicant stated that inter-rater disagreement 
with ASPECT scores leads to erroneous triage and treatment of Medicare 
patients. It is 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 
observe 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 are uncertain 
whether Rapid ASPECTS represents a substantial clinical improvement.
    Lastly, we note 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. 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 are unsure how it demonstrates 
a substantial clinical improvement in how Rapid ASPECTS supports the 
urgency of stroke care.
    We are inviting public comments on whether Rapid ASPECTS meets the 
substantial clinical improvement criterion.
    In this section, we summarize and respond to written public 
comments received in response to the New Technology Town Hall meeting 
notice published in the Federal Register regarding the substantial 
clinical improvement criterion for Rapid ASPECTS.
    Comment: Several commenters, some of whom participated in one of 
the retrospective studies assessing Rapid ASPECTS, asserted that Rapid 
ASPECTS offers a substantial clinical improvement over the current 
standard of care for evaluation and treatment of patients diagnosed 
with LVO. They cited the studies summarized in this section and their 
clinical experience with Rapid ASPECTS and stated that Rapid ASPECTS 
improves treatment decisions by improving the accuracy of the 
assessment of candidates eligible for thrombectomy as well as reducing 
the time to appropriate treatment, which leads to better outcomes.
    Response: We thank the commenters for their input and will take 
this information into consideration when deciding whether to approve 
new technology add-on payments for Rapid ASPECTS.
    Comment: The applicant responded to the questions received at the 
New Technology Town Hall Meeting held in December 2020.
    First, the applicant was asked if an ROC analysis had been 
performed with Rapid ASPECTS. The applicant stated that an ROC analysis 
had been performed for one of the retrospective studies assessing Rapid 
ASPECTS (Delio et al., 2020, under review). According to the applicant, 
using the scores for the 500 ASPECT regions for all 8 readers shows the 
AUC improved from 0.78 without RAPID to 0.85 with RAPID-assisted reads. 
The applicant stated the reference standard was the read from three 
experienced neuroradiologists who were provided access to a follow-up 
MRI scan to help enhance the accurary of the reference standard. The 
applicant asserted that the difference of 0.06 between the AUCs is 
statistically significant (p=0.0049).
    Second, the applicant was asked if clinical benefits of RAPID 
Aspects were directly observed in prospective studies using the Rapid 
ASPECTS software. The applicant cited a recent retrospective study 
reporting a series of 176 patients from one hospital in Alexandria, 
Egypt diagnosed with Acute Ischemic Stroke (AIS) and subsequently 
treated with tPA between January 2018 and December 2019. Results were 
reported on 122 of these patients; 36 had their NCCT images analyzed by 
Rapid ASPECTS and 86 had their NCCT images analyzed by a remote 
neuroradiologist who received the image by the text messaging platform 
WhatsApp. The applicant asserted that Rapid ASPECTS had excellent 
agreement (k=0.80) with the neuroradiologist's read. The door-to-needle 
time for the 86 WhatsApp-read patients was 52.3 16 minutes 
and for the 36 Rapid ASPECTS patients was 36.8 11 minutes 
(p=0.001), representing a 14-minute reduction in the door-to-treatment 
time in Rapid ASPECTS group compared with the WhatsApp standard care 
group. According to the applicant, 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 also asserted that the use of 
Rapid ASPECTS was shown to be cost-effective in this study.\558\
---------------------------------------------------------------------------

    \558\ Mansour, Ossama Yassin, et al. ``Deciding Thrombolysis in 
AIS Based on Automated versus on WhatsApp Interpreted ASPECTS, a 
Reliability and Cost-Effectiveness Analysis in Developing System of 
Care.'' Frontiers in Neurology 11 (2020): 333.
---------------------------------------------------------------------------

    Response: We appreciate the applicant's responses to questions 
asked at the New Technology Town Hall Meeting. Regarding 
generalizability, we note that the study results from a small, non-
randomized sample generated from a single hospital in Alexandria, 
Egypt, may limit the ability to assert findings are generalizable 
across the variety of health care settings in the United States. We 
question whether the fact that the radiologists in this study received 
the images via WhatsApp is generalizable to the standard of care in the 
United States. We also note the study did not attempt to control for 
other variables such as the mix of patients in each group or time of 
day or other changes

[[Page 25314]]

in hospital practices over time. Additionally, since only patients with 
confirmed acute ischemic stroke were included in the study results, no 
information was given about the imaging and interpretation of other 
patients imaged. We note that the retrospective study had two 
neuroradiologists interpret the NCCT images at a later time and compare 
their ASPECT score to the Rapid ASPECTS-generated score reading the 
same scans. The study reported that in only one patient, the Rapid 
ASPECTS software underestimated the extent of early ischemic changes by 
providing an automated ASPECTS >6, while the score was <6 by agreement 
read (which would indicate that tPA treatment was not appropriate). We 
note that the clinical outcome of that patient was not reported.
    We appreciate the information provided by the applicant and will 
take these comments into consideration when deciding whether to approve 
new technology add-on payments for Rapid ASPECTS.
p. Steripath[supreg] MicroTM Blood Collection System
    Magnolia Medical Technologies, Inc. submitted an application for 
new technology add-on payments for the Steripath[supreg] 
MicroTM Blood Collection System, which is also referred to 
as the Steripath[supreg] MicroTM Initial Specimen Diversion 
Device (ISDD[supreg]), for FY 2022. The applicant described the 
Steripath[supreg] MicroTM 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] MicroTM 
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] 
MicroTM 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.
    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.\559\ The applicant stated that blood culture 
contamination creates clinical confusion which leads to a risk of 
inappropriate antibiotic therapy,560 561 562 563 extended 
length of stay of an average of 2.0 to 2.4 days,564 565 
Clostridium difficile (CDI) infection,566 567 multidrug 
resistance organism (MDRO) infections, Acute Kidney Injury (AKI),\568\ 
hospital-acquired infection (HAI) or hospital-acquired condition 
(HAC),\569\ 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.\570\
---------------------------------------------------------------------------

    \559\ 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.
    \560\ Rupp M, et al. Reduction in Blood Culture Contamination 
Through Use of Initial Specimen Diversion Device. Clinical 
Infectious Diseases. 2017; 65(2):201-205.
    \561\ 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.
    \562\ 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.
    \563\ 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).
    \564\ 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.
    \565\ 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.
    \566\ 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.
    \567\ 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.
    \568\ Khalili H, et al. ``Antibiotics induced acute kidney 
injury: Incidence, risk factors, onset time and outcome.'' Acta 
Medica Iranica (2013): 51(12): 871-878.
    \569\ 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.
    \570\ 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.

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[[Page 25315]]

    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.\571\
---------------------------------------------------------------------------

    \571\ 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.\572\ 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.
---------------------------------------------------------------------------

    \572\ 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.
---------------------------------------------------------------------------

    According to the applicant, there are currently no ICD-10-PCS 
procedure codes to distinctly identify the use of the Steripath[supreg] 
Micro\TM\ ISDD[supreg]. The applicant submitted a request for a new 
ICD-10-PCS procedure code for implementation on October 1, 2021.
    As discussed above, 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 patients 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 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.
    We have the following concerns regarding whether the technology 
meets

[[Page 25316]]

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 note 
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 note 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 therefore 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 note 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 are 
inviting public comment on whether there are other FDA-cleared products 
designed to reduce blood culture contamination.
    We are inviting 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.
    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] TP10MY21.175


[[Page 25317]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.176

[GRAPHIC] [TIFF OMITTED] TP10MY21.177

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.573 574 575 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 above in one of the first two 
diagnosis code positions on the claim to include in the cost analysis.
---------------------------------------------------------------------------

    \573\ Sou, V., et al. A clinical pathway for the management of 
difficult venous access. BMC Nursing 16, 64 (2017).
    \574\ 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.
    \575\ 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] Micro\TM\ ISDD[supreg]. The 
applicant stated that these diagnoses rely on technologies not relevant 
to Steripath[supreg] Micro\TM\ 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.\576\ 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.
---------------------------------------------------------------------------

    \576\ 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] Micro\TM\ ISDD[supreg] is used, the 
applicant applied three percent of the savings described above 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 average case-

[[Page 25318]]

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 note the 
following concerns with regard to the cost criterion. In its analysis, 
the applicant stated it randomly selected 33% of claims that included 
one of the ICD-10 codes listed above 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 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 are seeking 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. 
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 are not certain that the 
patient population and the resulting conclusions from the 
aforementioned study \577\ 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 
are 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 are 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 are 
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 question whether it accurately reflects the experiences 
of providers and Medicare beneficiaries.
    We invite public comment on whether Steripath[supreg] Micro\TM\ 
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 technologies. 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.\578\
---------------------------------------------------------------------------

    \578\ 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.\579\ 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.
---------------------------------------------------------------------------

    \579\ 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,\580\ 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.
---------------------------------------------------------------------------

    \580\ 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.\581\ 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.
---------------------------------------------------------------------------

    \581\ Blakeney J, et al. ``Reduction of Blood Culture 
Contamination Using Initial Specimen Diversion Device''Poster 
presented at: American Society for Microbiology Annual Meeting 
(2018).

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

[[Page 25319]]

    The applicant submitted the Church K, et al.\582\ 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.
---------------------------------------------------------------------------

    \582\ 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.\583\ 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.
---------------------------------------------------------------------------

    \583\ 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.,\584\ with 
preliminary data and a paper, Huss, J, et al.,\585\ 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.
---------------------------------------------------------------------------

    \584\ 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).
    \585\ 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.\586\ paper, which is a 
12-month, 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.
---------------------------------------------------------------------------

    \586\ 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.\587\ 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.
---------------------------------------------------------------------------

    \587\ 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.\588\ 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.
---------------------------------------------------------------------------

    \588\ 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.\589\ 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].
---------------------------------------------------------------------------

    \589\ 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.\590\ 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).
---------------------------------------------------------------------------

    \590\ 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.\591\ 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.
---------------------------------------------------------------------------

    \591\ 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.\592\ paper (a 
randomized clinical trial) and the Binkhamis K and Forward K \593\ 
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.
---------------------------------------------------------------------------

    \592\ 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.
    \593\ 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 \594\ 
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].
---------------------------------------------------------------------------

    \594\ Patton R and Schmitt T. Innovation for reducing blood 
culture contamination: initial specimen diversion technique. Journal 
of Clinical Microbiology 48.12 (2010): 4501-4503.

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

[[Page 25320]]

    The applicant also submitted the Syed S, et al.\595\ 
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.
---------------------------------------------------------------------------

    \595\ 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.\596\ 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.,\597\ 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.
---------------------------------------------------------------------------

    \596\ 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.
    \597\ 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.\598\ decision tree health care 
economic model paper showed that investigators found that overall, each 
false positive blood culture was on average associated 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.
---------------------------------------------------------------------------

    \598\ 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.\599\ 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.
---------------------------------------------------------------------------

    \599\ 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.\600\ 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.\601\ 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,\602\ 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.
---------------------------------------------------------------------------

    \600\ 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.
    \601\ 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.
    \602\ Bates D, et al. Contaminant blood cultures and resource 
utilization: the true consequences of false-positive results. JAMA 
265.3 (1991): 365-369
---------------------------------------------------------------------------

    We have the following concerns regarding the substantial clinical 
improvement criterion. We note that much of the evidence submitted by 
the applicant to support that Steripath[supreg] Micro\TM\ represents a 
substantial clinical improvement over existing technologies speaks to 
the overall clinical value of reducing blood contamination, or the 
benefit of manual diversion over no diversion, but does not directly 
link the Steripath[supreg] Micro\TM\ to improved clinical endpoints. We 
note 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, 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 note 
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 note 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 are interested in any 
clinical data that directly links the Steripath[supreg] Micro\TM\ to 
these outcomes.
    Finally, we note 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

[[Page 25321]]

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 are interested 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 are inviting public comments on whether the Steripath[supreg] 
Micro\TM\ ISDD[supreg] meets the substantial clinical improvement 
criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
Steripath[supreg] Micro\TM\ ISDD[supreg].
q. 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] \603\ 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.
---------------------------------------------------------------------------

    \603\ 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 
of burn injury and accounts for approximately 86 percent of burn 
cases.\604\ 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).605 606 The applicant also noted the 
percentage of total body surface area (TBSA) determines burn severity 
and directly correlates with mortality.\607\
---------------------------------------------------------------------------

    \604\ 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//.
    \605\ 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.
    \606\ 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.
    \607\ 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.608 609 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.\610\ 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).\611\ The applicant also stated that unintentional fire or 
burn injuries was the 8th leading cause of death in those 65 years or 
older.\612\
---------------------------------------------------------------------------

    \608\ 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
    \609\ HCUPnet, Healthcare Cost and Utilization Project. Agency 
for Healthcare Research and Quality, Rockville, MD. https://hcupnet.ahrq.gov/. Accessed June 5, 2019.
    \610\ 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.
    \611\ 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.
    \612\ 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.\613\ 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.\614\ 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.\615\
---------------------------------------------------------------------------

    \613\ 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.
    \614\ 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.
    \615\ 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. 616 617 618 The 
applicant noted that common surgical interventions for burn injury 
include: escharotomy, debridement, excision, and skin grafting.\619\ 
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

[[Page 25322]]

problems of infection and rejection when using allografts or 
xenografts.\620\
---------------------------------------------------------------------------

    \616\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464.
    \617\ 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.
    \618\ Ibid.
    \619\ 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.
    \620\ 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.\621\ 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.\622\
---------------------------------------------------------------------------

    \621\ 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.
    \622\ 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.623 624 625 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.626 627 628 The applicant stated that while STBs 
require surgical debridement and grafting, superficial first-degree 
burns do not; \629\ however, in the acute phase of the burn injury, the 
clinical presentation of the severely injured burn patient usually 
involves a range of burn depths from a superficial burn to a FT 
burn.\630\
---------------------------------------------------------------------------

    \623\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464.
    \624\ 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
    \625\ Id.
    \626\ Deitch EA, Wheelahan TM, Rose MP, Clothier J, Cotter J. 
Hypertrophic burn scars: analysis of variables. J Trauma. 
1983;23(10):895-898.
    \627\ 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.
    \628\ 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.
    \629\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464.
    \630\ 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.\631\ The applicant also noted 
that donor-site pain is typically more painful than that in the 
treatment (burned) site and may become chronic.632 633 In 
patients with burns of 50-60 percent TBSA, autograft is limited by 
donor-site availability.\634\ 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.\635\
---------------------------------------------------------------------------

    \631\ 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.
    \632\ Birchall MA, Varma S, Milward TM. The Moriarty sign: an 
appraisal. Br J Plast Surg. 1991;44(2):149-150.
    \633\ 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.
    \634\ 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.
    \635\ 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.\636\ The applicant explained that because patients in 
these populations have thinner dermis and epidermis than non-elderly 
adults,637 638 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.\639\ 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.\640\
---------------------------------------------------------------------------

    \636\ 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.
    \637\ 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.
    \638\ Wainwright DJ, Bury SB. Acellular dermal matrix in the 
management of the burn patient. Aesthet Surg J. 2011;31(7 
Suppl):13S-23S.
    \639\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114
    \640\ 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.\641\ 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.\642\ 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.\643\
---------------------------------------------------------------------------

    \641\ American Burn Association. National Burn Repository 2019 
update. 2019.
    \642\ 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.
    \643\ Ibid.
---------------------------------------------------------------------------

    The applicant stated that there is currently no skin replacement 
product approved or available that leads to durable wound closure while

[[Page 25323]]

eliminating the need for harvesting an autograft.644 645
---------------------------------------------------------------------------

    \644\ 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.
    \645\ 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,\646\ and to provide the protective 
barrier function until definitive closure of the skin.\647\ The 
applicant noted that synthetic skin substitutes need to be removed or 
undergo biodegradation or resorption so the skin can heal and 
regenerate.\648\ 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.\649\
---------------------------------------------------------------------------

    \646\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020.
    \647\ MacNeil S. Progress and opportunities for tissue-
engineered skin. Nature 2007;445(7130)874-880.
    \648\ Halim A, Khoo T, Shah JY. Biologic and synthetic skin 
substitutes: An overview. Indian J. Plast. Surg. 2010;43(3)23
    \649\ 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.650 651 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.\652\ 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.
---------------------------------------------------------------------------

    \650\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020.
    \651\ Leon-Villapalos J. Skin autografting. UpToDate. https://www.uptodate.com/contents/skin-autografting. Literature review 
current through September 2020. Accessed October 1, 2020.
    \652\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020. Accessed September 25, 2020.
    \653\ Kumar P. Classification of skin substitutes. Burns. 
2008;34(1):148-149.
[GRAPHIC] [TIFF OMITTED] TP10MY21.178

    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.\654\ 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

[[Page 25324]]

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. Currently, there are no ICD-10-
PCS procedure codes to uniquely identify procedures involving 
StratagraftTM. We note that the applicant submitted a 
request for approval for a unique ICD-10-PCS code for the use of 
StratagraftTM beginning FY 2022.
---------------------------------------------------------------------------

    \654\ 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 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.\655\ 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.\656\ 
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.\657\ 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.
---------------------------------------------------------------------------

    \655\ 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.
    \656\ 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
    \657\ 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.\658\ 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.
---------------------------------------------------------------------------

    \658\ 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.\659\
---------------------------------------------------------------------------

    \659\ 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.660 661 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.
---------------------------------------------------------------------------

    \660\ Proposed prescribing information. for Stratagraft\TM\ skin 
tissue;. Submitted to FDA, April 2020.
    \661\ 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.\662\
---------------------------------------------------------------------------

    \662\ 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.\663\ The applicant also stated that autografting is especially

[[Page 25325]]

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.\664\ The applicant explained that these patients are 
disproportionately affected and are at increased risk for death due to 
the skin loss and its complications.\665\ 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.
---------------------------------------------------------------------------

    \663\ 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.
    \664\ 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.
    \665\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
---------------------------------------------------------------------------

    With respect to the first criterion, we note that there may be 
other biologic dressings that use some combination of keratinocytes, 
collagen, 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 are 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, StrataGraft\TM\ may treat the 
same or similar patient population as the standard of care or existing 
technologies to treat STB. While we agree that in patients with burns 
of 50-60 percent of the TBSA, donor-site availability is more limited, 
we observe that neither of the two pivotal studies included patients 
with burns of 50 percent or greater of the TBSA.\666\ We are unclear 
whether this suggests StratagraftTM is intended for 
treatment of patients with burns of less than 50 percent TBSA. We also 
question whether vulnerable patients, such as the elderly, are a new 
population as they are currently treated using standard of care or 
other technologies.
---------------------------------------------------------------------------

    \666\ 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 are inviting public comments on whether StratagraftTM 
is substantially similar to other technologies and whether 
StratagraftTM meets the newness criterion.
    With regard to the cost criterion, the applicant stated 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 appliant'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 25326]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.179

    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); 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.

[[Page 25327]]

    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 invite public comment on whether 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.\667\ The applicant stated that 
by significantly reducing or eliminating the need for autograft,\668\ 
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.\669\ The applicant explained that 
aging and environmental factors can influence the severity of burns in 
vulnerable skin.670 671 The applicant stated that geriatric 
skin also exhibits slower wound healing and is at increased risk of 
excessive scarring.672 673 674 675 676 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.\677\
---------------------------------------------------------------------------

    \667\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \668\ 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.
    \669\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114
    \670\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \671\ Landau M. Exogenous factors in skin aging. Curr Probl 
Dermatol. 2007;35:1-13.
    \672\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \673\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \674\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \675\ Ibid.
    \676\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \677\ 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,\678\ and may also lead to 
anxiety and depression due to scarring and body image concerns.\679\ 
Lastly, the applicant stated that use of StrataGraft\TM\ skin tissue 
reduces pain while offering a comparable scar quality to 
autograft.\680\
---------------------------------------------------------------------------

    \678\ Summer GJ, Puntillo KA, Miaskowski C, et al. Burn Injury 
Pain: The Continuing Challenge. J. Pain 2007;8(7)533-548.
    \679\ 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.
    \680\ 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) 681 682 was a 12-
month, open-

[[Page 25328]]

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) 683 684 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.
    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).\685\ We note that the applicant 
did not provide detailed information regarding the measurement 
methodology.
---------------------------------------------------------------------------

    \681\ 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.
    \682\ 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.
    \683\ 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.
    \684\ 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.
    \685\ 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.\686\ 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.\687\
---------------------------------------------------------------------------

    \686\ Ibid.
    \687\ 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) \688\ 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.\689\ 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.\690\
---------------------------------------------------------------------------

    \688\ Wong-Baker FACES Foundation. https://wongbakerfaces.org/. 
Accessed July 1, 2020.
    \689\ 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.
    \690\ 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) 691 692 
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.\693\ 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).\694\ The applicant explained that the 
STRATA2011 study showed that observer POSAS total scores from the 
StrataGraft\TM\ tissue treatment site and autograft were not 
significantly different throughout the study.\695\ 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.\696\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

[[Page 25329]]

studied in this context,\697\ while clinical studies for 
StrataGraft\TM\ skin tissue assessed wound closure as a pre-specified 
endpoint.698 699 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 StrataGraft.\700\
---------------------------------------------------------------------------

    \691\ 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.
    \692\ The Patient and Observer Scar Assessment Scale (POSAS). 
https://www.posas.nl/. Accessed July 1, 2020.
    \693\ 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.
    \694\ Ibid.
    \695\ 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.
    \696\ Ibid.
    \697\ 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.
    \698\ 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.
    \699\ 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.
    \700\ Hu MS, Maan ZN, Wu JC, et al. Tissue engineering and 
regenerative repair in wound healing. Ann Biomed Eng. 
2014;42(7):1494-1507.
---------------------------------------------------------------------------

    After reviewing the information provided by the applicant with 
regard to the substantial clinical improvement criterion, we note a 
lack of study data provided comparing StrataGraft\TM\ to other biologic 
dressings and we are 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 question whether 
the sample size of 30 is adequately generalizable to the larger 
Medicare population. In addition, we note 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 note 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 
question whether we can fully evaluate this claim because these 
patients were not assessed.
    We are inviting public comments on whether StrataGraftTM 
meets the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
StrataGraftTM skin tissue.
r. TecartusTM (brexucabtagene autoleucel)
    Kite Pharma submitted an application for new technology add-on 
payment for FY 2022 for Tecartus\TM\ (brexucabtagene autoleucel) 
(``Tecartus''). Tecartus 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 note 
that Kite Pharma previously submitted an application for new technology 
add-on payments for Tecartus for FY 2021, as summarized in the FY 2021 
IPPS/LTCH PPS proposed rule, under the name KTE-X19 (85 FR 32634).
    Tecartus 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 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 is different from other previously 
approved technologies because it has a distinct cellular product that 
requires a unique manufacturing process.
    According to the applicant, MCL is a rare and aggressive subtype of 
non-Hodgkin lymphoma (NHL) with distinct 
characteristics701 702 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).703 704 705
---------------------------------------------------------------------------

    \701\ Fakhri B, Kahl B. Current and emerging treatment options 
for mantle cell lymphoma. Ther Adv Hematol. 2017;8(8):223-34.
    \702\ 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.
    \703\ 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.
    \704\ Zhou Y, et al. Incidence trends of mantle cell lymphoma in 
the United States between 1992 and 2004. Cancer. 2008;113(4):791-
798.
    \705\ Teras LR, et al. 2016 US lymphoid malignancy statistics by 
World Health Organization subtypes CA Cancer J Clin. 2016;6:443-459.
---------------------------------------------------------------------------

    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.\706\ 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 r/r 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.\707\ 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.\708\ 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.709 710 711
---------------------------------------------------------------------------

    \706\ 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.
    \707\ Cheah CY, et al. Mantle cell lymphoma. J Clin Oncol. 
2016;34:1256-1269.
    \708\ 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.
    \709\ 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.
    \710\ 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.
    \711\ 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.\712\ 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:

[[Page 25330]]

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.
---------------------------------------------------------------------------

    \712\ Campo E, Rule S. Mantle cell lymphoma: evolving management 
strategies. Blood. 2015;125(1):48-55.
---------------------------------------------------------------------------

    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.
    With respect to the newness criterion, the applicant indicated that 
the FDA approved the Tecartus 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 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: 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).
    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 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 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 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 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 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's mechanism of 
action and other available therapies for r/r MCL, the applicant stated 
that Tecartus 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 as having a different 
mechanism of action from existing r/r MCL therapies.
    The applicant stated that Tecartus 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 has a different mechanism of action as 
compared to YESCARTA[supreg] given that the European Medicines Agency 
(EMA) deemed Tecartus 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 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 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 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 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. 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 treats a different subtype of NHL, r/r MCL, 
as compared to other FDA approved CAR T-cell therapies. However, we 
note that the applicant recognized in its application that MCL and 
DLBCL patients share

[[Page 25331]]

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 which are 
inherent to the disease 713 714 or due to peripheral 
mobilization of tumor cells induced by BTK inhibitor therapy.\715\ 
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.\716\
---------------------------------------------------------------------------

    \713\ Argatoff LH, et al. Mantle cell lymphoma: a 
clinicopathologic study of 80 cases. Blood. 1997;89 (6):2067-78
    \714\ 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.
    \715\ 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.
    \716\ 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 would provide a new treatment option for adult patients with 
r/r MCL and therefore is not substantially similar to any existing 
technologies. We note 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 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 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 32636-32637), we are 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 note, in their review, 
the FDA identified many similarities between Tecartus 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.'' \717\ 
Further, as Tecartus is also a CD19-directed T-cell immunotherapy for 
the treatment of patients with an aggressive subtype of NHL, we 
continue to question whether the differences identified by the 
applicant would mean that Tecartus does not have a similar mechanism of 
action to existing CD19-directed CAR T-cell therapies. We are seeking 
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.
---------------------------------------------------------------------------

    \717\ 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 question whether this therapy may involve the treatment of a 
similar type of disease when compared to existing CAR T-cell therapies.
    We are inviting public comments on whether Tecartus is 
substantially similar to other technologies and whether Tecartus meets 
the newness criterion.
    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.
    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.

[[Page 25332]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.180

    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 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 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 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).
    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

[[Page 25333]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.181


[[Page 25334]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.182


[[Page 25335]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.183

BILLING CODE 4120-01-C
    The applicant then removed charges for prior technology. The 
applicant stated that the cases representing patients who had received 
chemotherapy, as reflected by the Medicare claims data, would generally 
not receive both chemotherapy and Tecartus as an inpatient because 
conditioning chemotherapy would be administered in the outpatient 
setting before the patient would be admitted for Tecartus infusion and 
monitoring. Otherwise, the applicant asserted that patients receiving 
Tecartus 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 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 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 are uncertain how 
representative this data is for use in the applicant's cost analyses 
given this potential for variability.
    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 invite public comment on whether Tecartus meets the cost 
criterion based on this proposal.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that Tecartus 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 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 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

[[Page 25336]]

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% \718\ and 32% \719\ for use as their 
comparator.
---------------------------------------------------------------------------

    \718\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \719\ 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).\720\
---------------------------------------------------------------------------

    \720\ 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. \721\ 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%).
---------------------------------------------------------------------------

    \721\ 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 ORR of 29%, CR 
rate of 14%, and PR rate of 15%.722 723 724 725
---------------------------------------------------------------------------

    \722\ 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.
    \723\ 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.
    \724\ 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.
    \725\ 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, 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.\726\
---------------------------------------------------------------------------

    \726\ 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 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 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 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. 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 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 727 728 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.729 730 In registrational trials, the 
ORR and CRR were 66% and 17%, respectively for ibrutinib, and 81% and 
40%, respectively, for acalabrutinib.731 732 The

[[Page 25337]]

applicant contended that primary and secondary resistance to BTK 
inhibitors \733\ is common, and subsequent therapies currently 
available are minimally effective.734 735 736
---------------------------------------------------------------------------

    \727\ Campo E, Rule S. Mantle cell lymphoma: Evolving management 
strategies. Blood. 2015;125(1):48-55.
    \728\ Vose JM. Mantle cell lymphoma: 2017 update on diagnosis, 
risk-stratification, and clinical management. Am J Hematol. 
2017;92(8):806-813.
    \729\ Kantar Health. CancerMPact[supreg] United States. 
September 2018, v1.2.
    \730\ Vose JM. Mantle cell lymphoma: 2017 update on diagnosis, 
risk-stratification, and clinical management. Am J Hematol. 
2017;92(8):806-813.
    \731\ Ibrutinib USPI. Available from: https://www.imbruvica.com/docs/librariesprovider7/default-document-library/prescribing_information.pdf.
    \732\ Acalabrutinib USPI. Available from: https://www.azpicentral.com/calquence/calquence.pdf#page=1.
    \733\ 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.
    \734\ 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.
    \735\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \736\ 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 (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 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 be followed to month 12, 90% remained in CR at month 12. 
The applicant contended that this statistic showcased that early 
responses to Tecartus are likely indicative of long-term remission 
after the single infusion of Tecartus. Furthermore, the applicant 
suggested that a substantial number of patients with r/r MCL treated 
with Tecartus will achieve a CR, and that this suggests these patients 
will likely experience a long-term remission after a single infusion of 
Tecartus. 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.737 738 739 740
---------------------------------------------------------------------------

    \737\ 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.
    \738\ 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.
    \739\ 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.
    \740\ 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, the applicant argued that 
the ZUMA-2 study demonstrated a positive benefit-risk of Tecartus over 
the current therapy options for patients with r/r MCL. The applicant 
stated that the toxicity profile that is associated with Tecartus 
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 therapy 
are certified so that all who prescribe, dispense, or administer 
Tecartus 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 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.

[[Page 25338]]

    In response to CMS's concern as discussed in the FY 2021 IPPS/LTCH 
PPS proposed rule (85 FR 32646-32647) 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 73.741 742 
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.\743\ 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 and 12 deaths 
occurred >=3 months after infusion of Tecartus. 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).
---------------------------------------------------------------------------

    \741\ 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.
    \742\ 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
    \743\ 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 have 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 question 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 offers 
a treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments, we question whether the 
sample size and research presented in this application support 
extrapolating these results across the Medicare population.
    Relatedly, we have 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 was successfully manufactured for 71 (96%) and 
administered for 68 (92%).\744\ 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 note 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 have 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 745 746 747 and 
that formal stopping rules do not reduce this bias, particularly in 
samples less than 500 events or cases.\748\ Given the lack of 
confidence intervals around the ORR among all 74 patients and the 
potential for the overestimation of treatment effects, it is unclear 
whether there is sufficient information to determine a substantial 
clinical improvement.
---------------------------------------------------------------------------

    \744\ 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.
    \745\ Pocock SJ. When (not) to stop a clinical trial for 
benefit. JAMA 2005;294:2228e30.
    \746\ Pocock SJ, Hughes MD. Practical problems in interim 
analyses, with particular regard to estimation. Control Clin Trials 
1989;10(4 Suppl): 209Se21S.
    \747\ 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.
    \748\ 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 has not 
been a direct study completed comparing outcomes of patients with r/r 
MCL treatment with Tecartus and BTK inhibitors. According to the 
applicant, ZUMA-2 remains the only study to evaluate patient outcomes 
after receiving Tecartus for the treatment of r/r MCL, but this study 
does 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.\749\
---------------------------------------------------------------------------

    \749\ 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% \750\ and 32% \751\ respectively), it is 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 to BTK 
inhibitors, we are uncertain whether it would support a determination 
of substantial clinical improvement.
---------------------------------------------------------------------------

    \750\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \751\ 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.
---------------------------------------------------------------------------

    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 note 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 remain concerned that further 
analysis may be needed to evaluate the safety of Tecartus and the 
longer term effects of the CRS and neurological events associated with 
the Tecartus therapy.
    We are inviting public comments on whether Tecartus meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New

[[Page 25339]]

Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for Tecartus.
s. TERLIVAZ[supreg] (Terlipressin)
    Mallinckrodt Pharmaceuticals submitted an application for new 
technology add-on payments for TERLIVAZ[supreg] (terlipressin) for FY 
2022. Per the applicant, TERLIVAZ[supreg] is for intravenous use in the 
treatment of adults with hepatorenal syndrome type 1 (HRS-1). The 
applicant stated that TERLIVAZ[supreg] (N[alpha]-tryglycl-8-lysine-
vasopressin) is a pro-drug for the endogenous/natural porcine hormone 
[Lys8]-vasopressin and a synthetic vasopressin analog derived from the 
natural/endogenous human hormone [Arg8]-vasopressin.\752\ According to 
the applicant, TERLIVAZ[supreg] has greater selectivity for the 
vasopressin receptors (V1) versus vasopressin receptors (V2) and 
inhibits portal hypertension with simultaneous reduction of blood 
circulation in portal vessels.\753\ The applicant stated that the V1 
receptor mediated vasoconstrictor activity of TERLIVAZ[supreg], 
particularly in the splanchnic area, results in an increase in 
effective arterial volume, an increase in mean arterial pressure (MAP), 
and normalization of endogenous vasoconstrictor systems (renin-
angiotensin-aldosterone and sympathetic nervous system) resulting in 
increased renal blood flow.\754\
---------------------------------------------------------------------------

    \752\ Jamil K, Pappas SC, Devarakonda KR. In vitro binding and 
receptor-mediated activity of terlipressin at vasopressin receptors 
V1 and V2. J Exp Pharmacol. 2017;10:1-7.
    \753\ Wong F. Recent advances in our understanding of 
hepatorenal syndrome. Nat Rev Gastroenterol Hepatol. 2012;9(7):382-
391.
    \754\ Ibid.
---------------------------------------------------------------------------

    The applicant described HRS-1 as a serious, life-threatening 
condition characterized by development of acute or sub-acute renal 
failure in patients with advanced chronic liver disease (CLD). The 
applicant stated that HRS-1 is estimated to affect between 30,000 and 
40,000 patients in the U.S. annually 755 756 and is the 
leading cause of hospitalizations among all patients with advanced 
CLD.\757\ The applicant asserted that the high mortality and 
significant rates of HRS-1-related readmissions support the need for 
better disease awareness and more effective treatment 
options.758 759 760 The applicant asserted that there are 
currently no FDA-approved medications available in the US indicated 
specifically for the treatment of HRS-1,\761\ but several agents are 
used off-label. The applicant stated that in the U.S., the standard of 
care and initial treatment for HRS-1 is a combination of midodrine and 
octreotide, which are used off-label.762 763 According to 
the applicant, this combination is concomitantly administered with 
albumin. The applicant also stated that in patients who are admitted to 
the ICU, initial treatment with norepinephrine, also used off-label, in 
combination with albumin is recommended.\764\ The applicant stated that 
the ideal therapy for HRS-1 is improvement of liver function from 
either recovery of alcoholic hepatitis, treatment of decompensated 
hepatitis B with effective antiviral therapy, recovery from acute 
hepatic failure, or liver transplantation.\765\ According to the 
applicant, TERLIVAZ[supreg] is approved as the first-line treatment for 
HRS-1 in European and Asian countries under appropriate marketing 
authorizations in those countries.\766\
---------------------------------------------------------------------------

    \755\ Pant C, Jani BS, Desai M, et al. Hepatorenal syndrome in 
hospitalized patients with chronic liver disease: results from the 
Nationwide Inpatient Sample 2002-2012. J Investig Med. 
2016;64(1):33-38.
    \756\ Quick Facts. The United States Census Bureau. https://www.census.gov/quickfacts/fact/table/US/PST045218. Accessed January 
24, 2021.
    \757\ Allegretti AS, Ortiz G, Wenger J, et al. Prognosis of 
Acute Kidney Injury and Hepatorenal Syndrome in Patients with 
Cirrhosis: A Prospective Cohort Study. Int J Nephrol. 
2015;2015:108139.
    \758\ Rice JB, White AG, Galebach P, et al. The burden of 
hepatorenal syndrome among commercially insured and Medicare 
patients in the United States. Curr Med Res Opin. 2017;33(8):1473-
1480.
    \759\ Low G, Alexander GJ, Lomas DJ. Hepatorenal syndrome: 
Aetiology, diagnosis, and treatment. Gastroenterol Res Pract. 
2015;2015:207012.
    \760\ Angeli P, Bernardi M, Villanueva C, et al. EASL Clinical 
Practice Guidelines for the management of patients with 
decompensated cirrhosis. J Hepatol. 2018;69(2):406-460.
    \761\ Jamil K, Huang X, Lovelace B, Pham AT, Lodaya K, Wan G. 
The burden of illness of hepatorenal syndrome (HRS) in the United 
States: A retrospective analysis of electronic health records. J Med 
Econ. 2019;22(5):421-429.
    \762\ Mindikoglu AL, Pappas SC. New Developments in Hepatorenal 
Syndrome [published correction appears in Clin Gastroenterol 
Hepatol. 2018 Jun;16(6):988]. Clin Gastroenterol Hepatol. 
2018;16(2):162-177.e1.
    \763\ Runyon BA. Hepatorenal syndrome. UpToDate.com. https://www.uptodate.com/contents/hepatorenal-syndrome. Updated April 13, 
2020. Accessed January 26, 2020.
    \764\ Ibid.
    \765\ Runyon BA. Hepatorenal syndrome. UpToDate.com. https://www.uptodate.com/contents/hepatorenal-syndrome. Updated April 13, 
2020. Accessed January 26, 2020.
    \766\ Sarin S, Sharma P. Terlipressin: An Asset for 
Hepatologists! Hepatology. 2011;54(2):724-728.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that in 
2005, a New Drug Application (NDA) filing for TERLIVAZ[supreg] was 
granted Fast Track designation by the FDA and was considered under 
Priority Review in May 2008, but a Complete Response Letter (CRL) was 
issued by the FDA in November 2009. A CRL indicates that the review 
cycle for an application is complete and that the application is not 
ready for approval (73 FR 39588). The applicant also stated that in 
2016, Mallinckrodt Pharmaceuticals and the FDA reached agreement on 
their trial protocol design and data analysis under the agency's 
special protocol assessment (SPA) process. In April 2020, the applicant 
submitted the current NDA application with FDA as a Class 2 
resubmission of the original NDA. On July 15, 2020, the Cardiovascular 
and Renal Drugs Advisory Committee of the FDA voted to recommend 
approval of the investigational agent TERLIVAZ[supreg] to treat adults 
with HRS-1, but on September 14, 2020, Mallinckrodt received a CRL from 
the FDA for this NDA. At the time of the development of this proposed 
rule, TERLIVAZ[supreg] had not received FDA marketing authorization. 
The applicant submitted a request for a unique ICD-10-PCS code to 
identify the intravenous infusion of TERLIVAZ[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 similar mechanism of action to achieve a therapeutic outcome, 
according to the applicant, there are currently no FDA-approved 
treatments for HRS-1 that have a mechanism of action of selectivity for 
vasopressin V1 receptors. The applicant also stated that 
TERLIVAZ[supreg] represents a different compound type, vasoconstrictor 
class, and mechanism of action than those of currently available off-
label treatments for HRS-1. The applicant submitted the following table 
that compares the mechanism of action for TERLIVAZ[supreg] to the 
mechanism of action for existing technologies used off-label to treat 
HRS-1 including midodrine, octreotide, and norepinephrine.

[[Page 25340]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.184

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that 
TERLIVAZ[supreg] may be assigned to the same MS-DRG as existing 
technologies currently used to treat HRS-1. In particular, the 
applicant stated that cases involving the use of Terlivaz[supreg] may 
map to the three MS-DRGs included in Major Diagnostic Category (MDC) 7 
(Diseases & Disorders of the Hepatobiliary System & Pancreas); MS-DRG 
441--Disorders of Liver Except Malignancy, Cirrhosis or Alcoholic 
Hepatitis with CC; MS-DRG 442--Disorders of Liver Except Malignancy, 
Cirrhosis or Alcoholic Hepatitis with CC; and MS-DRG 443--Disorders of 
Liver Except Malignancy, Cirrhosis or Alcoholic Hepatitis without CC/
MCC. The applicant stated that although TERLIVAZ[supreg] may be 
assigned to the same MS-DRG when compared with an existing technology, 
this does not mean that TERLIVAZ[supreg] is not new for the purposes of 
new technology add-on payments because, according to the applicant, the 
existing technologies are not specifically indicated for the treatment 
of HRS-1. The applicant stated that none of the current standard-of-
care drugs used to treat HRS-1, namely midodrine, octreotide, and 
norepinephrine are FDA-approved for the treatment of this disease. The 
applicant referenced the discussion in the FY 2016 IPPS/LTCH PPS final 
rule (80 FR 49445) of BLINCYTO[supreg], as an example of another 
technology that was the only FDA-approved product available on the U.S. 
market to treat the relevant indication, and stated that CMS agreed 
that eligible cases involving the BLINCYTO technology would map to a 
different MS-DRG than cases treated with similar technologies. The 
applicant also stated that the MS-DRG system does not differentiate 
between patients with HRS and non-HRS conditions that are assigned to 
the three MS-DRGs included in Major Diagnostic Category (MDC) 7 
(Diseases & Disorders of the Hepatobiliary System & Pancreas) and 
further that the current MS-DRGs do not differentiate between HRS type 
1 and type 2. The applicant states that because of this, both 
TERLIVAZ[supreg] and an existing technology used to treat non-HRS 
conditions of HRS type 2 may be assigned to MS-DRGs 441, 442, and 443.
---------------------------------------------------------------------------

    \767\ Midodrine. Drugs.com. https://www.drugs.com/pro/midodrine.html. Updated August 1, 2020. Accessed January 25, 2021.
    \768\ Compound Summary of Octreotide acetate. U.S. National 
Library of Medicine.
    \769\ Norepinephrine. Drugs.com. https://www.drugs.com/ppa/norepinephrine.html. Updated June 15, 2020. Accessed January 4, 
2021.
    \770\ Cavallin M, Kamath PS, Merli M, et al. Terlipressin plus 
albumin versus midodrine and octreotide plus albumin in the 
treatment of hepatorenal syndrome: a randomized trial. Hepatology. 
2015;62:567-574.
---------------------------------------------------------------------------

    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, TERLIVAZ[supreg] will treat the same type of disease but 
will not treat the same or similar population when compared to existing 
technologies currently treating HRS-1 in the U.S. The applicant stated 
that TERLIVAZ[supreg] will offer treatment to a new patient population 
that is a subset of the larger patient population for which 
TERLIVAZ[supreg] will receive an FDA label, if approved, and that this 
subset includes patients for which existing technologies offer a lower 
rate of recovery of renal function compared to TERLIVAZ[supreg]. The 
applicant states that while the FDA label for TERLIVAZ[supreg] will not 
be reserved for a subset of the patient population that has been 
diagnosed with HRS-1 and has failed to respond to standard-of-care 
treatment options, it does not logically follow that because of this 
label, TERLIVAZ[supreg] will not offer a treatment option to a new 
patient population.
    Based on the applicant's statements as summarized above, the 
applicant believes that TERLIVAZ[supreg] is not substantially similar 
to other currently available therapies and/or technologies and meets 
the ``newness'' criterion. We note that while TERLIVAZ[supreg] may 
address an unmet need because it will be the first treatment indicated 
specifically for the treatment of HRS-1, the applicant's assertion that 
TERLIVAZ[supreg] involves the treatment of a different patient 
population on the basis that there is a lower rate of renal function 
recovery using standard of care treatments does not necessarily support 
the unmet need for HRS-1 treatment. We are inviting public comments on 
whether TERLIVAZ[supreg] is substantially similar to other technologies 
and whether TERLIVAZ[supreg] meets the newness criterion.
    With respect to the cost criterion, the applicant searched the FY 
2018 MedPAR dataset for cases reporting the ICD-10-CM code K76.7--
Hepatorenal syndrome. The applicant stated that average covered charges 
were obtained at the provider level and case counts for provider 
instances with fewer than 11

[[Page 25341]]

discharges at the MS-DRG level were redacted and replaced with the 
number 1. The applicant initially identified 2,592 providers and 35,806 
cases. The applicant excluded 315 providers and 1,149 cases that were 
not listed in the Impact File FY 2021 Proposed Rule, as the average 
charges for these cases/providers could not be standardized. The 
applicant further stated that there were initially 255 MS-DRGs in the 
data set. However, three MS-DRGs were not found in FY 2022 New 
Technology Thresholds file posted with the FY 2021 IPPS final rule and 
correction notice, and an additional three MS-DRGs were excluded 
because providers were not listed in the Impact File FY 2021 Proposed 
Rule. The exclusion of those 6 MS-DRGs resulted in an additional 6 
excluded cases. Thus, the final data set for analysis included 34,651 
cases spanning across a total of 249 MS-DRGs.
    The applicant then presented six analyses with defined cohorts. The 
applicant considered the following factors in defining the cohorts:
     The applicant explained that, because HRS is not always 
the primary or admitting diagnosis in cases where ICD-10-CM code K76.7 
is present, and that K76.7 is commonly coded to cases such as sepsis, 
they included cases where HRS is the primary and/or admitting diagnosis 
code in cohorts 1, 3, and 5 and cases where HRS can be the primary, the 
admitting, or any secondary diagnosis in cohorts 2, 4, and 6.
     The applicant stated that it filtered out cases without a 
2-day minimum length of inpatient stay. Per the applicant, the ICD-10-
CM diagnosis code K76.7 covers type 1 and type 2 HRS. The applicant 
stated that HRS type 1 and type 2 have clinical differentiators that 
make HRS-1 the condition requiring greater hospital resource 
utilization to treat. The applicant stated that, to produce a cost 
threshold calculation for an indication of HRS-1, HRS-2 cases must be 
redacted from any inpatient case population used to ensure charge 
averages are not dampened by lower costs to treat cases not described 
by an HRS-1 indication. The applicant explained that HRS-1 is diagnosed 
by the exclusion of other causes of acute kidney injury in cirrhotic 
patients, and that no response to 2 consecutive days of diuretic 
withdrawal and volume expansion with albumin is one of the diagnostic 
criteria in patients with cirrhosis. Accordingly, per the applicant, 
patients who do not fulfill this criterion within 48 hours cannot be 
considered HRS-1 cases and were excluded from the analysis.
     The applicant also stated that the clinical presentation 
of HRS-1 means the more serious cases requiring stabilization will be 
treated in the ICU and other cases will be treated in the general 
medical ward. The applicant included cases with an ICU indicator for 
Cohorts 1 and 2, representing serious cases where the patient needed 
stabilization procedures and/or conditions needing immediate attention. 
The applicant stated that these could be conditions related to, caused 
by, or leading to the HRS diagnosis or having no relationship to HRS 
other than a concurrent presence. The applicant also included cases 
without an ICU indicator for cohorts 3 and 4 and included all cases 
without differentiation in ICU utilization for cohorts 5 and 6.
[GRAPHIC] [TIFF OMITTED] TP10MY21.185

    The applicant then removed the charges for the technology being 
replaced. For analyses 1 and 2, the applicant removed the estimated 
cost of generic norepinephrine based on HRS-1 dosing regimens from each 
case, which was $1,699 (AnalySource 2018 U.S. Pricing). For analyses 3 
and 4, the applicant removed the estimated cost of midodrine plus 
octreotide based on HRS-1 dosing regimens from each case, which was 
$3,391 (AnalySource 2018 U.S. Pricing). For analyses 5 and 6, the 
applicant removed the estimated cost of generic norepinephrine ($1,699) 
from ICU cases and the estimated cost of midodrine plus octreotide 
($3,391) from non-ICU cases.
    Across all analyses, the applicant standardized the charges and 
applied a 2-year inflation factor of 13.1 percent that the applicant 
stated was used in the FY 2021 IPPS/LTCH PPS final rule to calculate 
outlier threshold charges. We note that the 2-year inflation factor 
used in the FY 2021 IPPS/LTCH PPS final rule to calculate outlier 
threshold charges is 1.13218, which would have increased the inflated 
charges. The applicant stated that it did not add any charges for and 
related to the new technology or any charges related to the prior 
technologies.
    In the first analysis, (Cohort 1), the applicant computed a final 
inflated average case-weighted standardized charge per case of 
$135,189, which exceeded the average case-weighted threshold amount of 
$70,629.
    In the second analysis, (Cohort 2), the applicant computed a final 
inflated average case-weighted standardized charge per case of 
$181,617, which exceeded the average case-weighted threshold amount of 
$88,445.
    In the third analysis, (Cohort 3), the applicant computed a final 
inflated average case-weighted standardized charge per case of $59,184, 
which exceeded the average case-weighted threshold amount of $56,994.
    In the fourth analysis, (Cohort 4), the applicant computed a final 
inflated average case-weighted standardized

[[Page 25342]]

charge per case of $66,974, which exceeded the average case-weighted 
threshold amount of $63,976.
    In the fifth analysis, (Cohort 5), the applicant computed a final 
inflated average case-weighted standardized charge per case of $96,783, 
which exceeded the average case-weighted threshold amount of $63,738.
    In the sixth analysis, (Cohort 6), the applicant computed a final 
inflated average case-weighted standardized charge per case of 
$132,324, which exceeded the average case-weighted threshold amount of 
$78,101.
    Because the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount 
under all analyses, the applicant asserted that the technology meets 
the cost criterion. However, based on the information provided by the 
applicant, we have the following concerns regarding the cost criterion. 
We question whether the analyses conducted by applicant may include MS-
DRGs that are defined by other factors and which may or may not be 
related to the intended indication for TERLIVAZ[supreg]. Per the 
applicant, on average, MS-DRGs 441 and 442, used for disorders of the 
liver, covered 83.41 percent of cases included in cohorts where HRS is 
the primary and/or admitting diagnosis code, and may therefore be a 
more refined representation of current reimbursement for cases of HRS-
1. We also note that the applicant identified cases using the FY 2018 
MedPAR dataset instead of the FY 2019 MedPAR dataset. We invite public 
comments on whether TERLIVAZ[supreg] meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserts that TERLIVAZ[supreg] represents a substantial 
clinical improvement over existing technologies because the use of 
TERLIVAZ[supreg] is associated with a more rapid resolution of the HRS-
1 disease process and a reduced rate of mortality compared to placebo, 
midodrine and octreotide, and norepinephrine. The applicant also stated 
that the use of TERLIVAZ[supreg] is associated with a decreased rate of 
several subsequent diagnostic or therapeutic interventions, compared 
with placebo and the overall benefit-risk profile of TERLIVAZ[supreg] 
as a treatment for HRS-1 is favorable.
    In support of the claim that the use of TERLIVAZ[supreg] is 
associated with a more rapid resolution of the HRS-1 disease process 
and a reduced rate of mortality compared to placebo, the applicant 
submitted a PowerPoint presentation that discussed the results of the 
CONFIRM study. The CONFIRM study \771\ was a randomized (2:1), double-
blind, placebo-controlled study comparing TERLIVAZ[supreg] to placebo 
in 300 adult patients, 18 years of age or older with HRS-1 (defined as 
rapidly progressive worsening in renal function to a serum creatinine 
(SCr) >=2.25 mg/dL and meeting a trajectory for SCr to double over 2 
weeks). TERLIVAZ[supreg] or placebo were administered as a 1 mg IV 
bolus injection every 6 hours for a maximum of 14 days.
---------------------------------------------------------------------------

    \771\ U.S. Food and Drug Administration. Terlipressin Briefing 
Document. NDA # 022231. Cardiovascular and Renal Drugs Advisory 
Committee, July 15, 2020. https://www.fda.gov/media/139963/download. 
Accessed February 17, 2021.
---------------------------------------------------------------------------

    The primary objective of the study was to confirm the efficacy and 
safety of TERLIVAZ[supreg] versus placebo in the treatment of adult 
subjects with HRS-1 receiving standard of care albumin therapy. The 
primary endpoint was the incidence of verified HRS reversal, defined as 
2 consecutive serum creatinine values <=1.5 mg/dL at least 2 hours 
apart, while on treatment by Day 14 or discharge, whichever came first 
(on treatment defined as up to 24 hours after the final dose of study 
drug). In order to be counted in the primary endpoint, patients needed 
to be alive without renal replacement therapy (RRT) for at least 10 
days after achieving verified HRS reversal. RRT was defined as any 
procedure to replace nonendocrine kidney function and included 
intermittent hemodialysis, ultrafiltration, continuous hemofiltration 
and hemodialysis, peritoneal dialysis, and other dialysis and 
filtration techniques. The secondary endpoints and their definitions 
are listed in the following table. The statistical analysis plan also 
specified that the secondary endpoints were to be tested using the 
Hochberg procedure to control the overall type 1 error rate.\772\ A 
sample size calculation was conducted and found that a sample size of 
300 subjects would provide approximately 90% power with a two-sided 
type 1 error rate of 0.05 with a 2:1 randomization and assuming event 
rates of verified HRS reversal of approximately 28% and 12.5%.
---------------------------------------------------------------------------

    \772\ Ibid.
    [GRAPHIC] [TIFF OMITTED] TP10MY21.186
    

[[Page 25343]]


    The applicant \773\ stated that the incidence of verified HRS 
reversal was 29.1 percent (n=58) in the TERLIVAZ[supreg] (treatment) 
group and 15.8 percent (n=16) in the placebo (control) group 
(p=0.012).\774\ According to the applicant, the incidence of subjects 
with HRS-1 reversal was 36.2 percent (n=72) in the treatment group and 
16.8 percent (n=17) in the control group (p<0.001). The durability of 
HRS-1 reversal was 31.7 percent (n=63) in the treatment group and 15.8 
percent (n=16) in the control group (p=0.003). The incidence of HRS-1 
reversal in SIRS subgroup was 33.3 percent (n=28) in the treatment 
group and 6.3 percent (n=3) in the control group (p <0.001). According 
to the applicant, the incidence of verified HRS-1 reversal without HRS-
1 recurrence by Day 30 was 24.1 percent (n=48) in the treatment group 
and 15.8 percent (n=16) in the control group (p=0.092). The applicant 
also claimed that the overall survival up to Day 90 was higher in 
responders (subjects who achieved verified HRS reversal or HRS reversal 
while receiving treatment) than in non-responders (p<0.001) in both the 
treatment and control groups.\775\
---------------------------------------------------------------------------

    \773\ Ibid.
    \774\ Wong F, Curry MP, Reddy KR, et al, on behalf of the 
CONFIRM Study Investigators. The CONFIRM Study: A North American 
Randomized Controlled Trial (RCT) of Terlipressin plus Albumin for 
the Treatment of Hepatorenal Syndrome Type 1 (HRS-1). Presented at: 
The American Association for the Study of Liver Diseases (AASLD) 
meeting; November 8-12, 2019; Boston, MA.
    \775\ Jamil, K. Terlipressin, a New Investigational Drug for the 
Treatment of Hepatorenal Syndrome Type 1. Presented at: New 
Technology Town Hall Meeting; December 16, 2019; Centers for 
Medicare & Medicaid Services; Baltimore, MD.
---------------------------------------------------------------------------

    The applicant asserted that the study conducted by Arora et 
al.\776\ supports its claims that the use of TERLIVAZ[supreg] is 
associated with a more rapid resolution of the HRS-1 disease process 
and a reduced rate of mortality compared to norepinephrine. This study 
was an open-label, randomized controlled trial conducted as a single-
center study in India. The study compared a continuous infusion of 
TERLIVAZ[supreg] and albumin to a continuous infusion of norepinephrine 
and albumin in the management of HRS-acute kidney injury (AKI) in 
patients with a diagnosis of acute on chronic liver failure (ACLF). 
Patients were randomized to receive either TERLIVAZ[supreg] or 
norepinephrine in a 1:1 ratio.\777\
---------------------------------------------------------------------------

    \776\ Arora V, Maiwall R, Rajan V, et al. Terlipressin Is 
Superior to Noradrenaline in the Management of Acute Kidney Injury 
in Acute on Chronic Liver Failure. Hepatology. 2019;71(2):600-610.
    \777\ Ibid.
---------------------------------------------------------------------------

    ACLF is a distinct diagnosis where, because of severe acute hepatic 
injury, a rapid loss of liver function develops in a patient with 
previous chronic liver disease. In this study, ACLF was defined as an 
acute hepatic insult manifesting as jaundice (serum bilirubin >=5 mg/
dL) and coagulopathy (international normalized ratio [INR] >=1.5) 
complicated within 4 weeks by ascites and/or encephalopathy in a 
patient with previously diagnosed or undiagnosed chronic liver disease 
or cirrhosis. HRS-AKI was defined as ICA-AKI stage >=II when other 
causes of AKI were excluded and the patient was nonresponsive to volume 
expansion with intravenous albumin.
    A total of 120 patients were randomized and 60 patients were 
allocated to the intention to treat group for both the TERLIVAZ[supreg] 
and norepinephrine arms. Adverse events requiring discontinuation of 
the drug were reported in 9 of 60 (15%) patients in the 
TERLIVAZ[supreg] arm compared to 5 of 60 (8.3%) in the norepinephrine 
arm (P=0.39). These events included diarrhea, abdominal pain, atrial 
fibrillation, cyanosis, and chest pain in the TERLIVAZ[supreg] arm. In 
the norepinephrine arm, patients experienced the previously mentioned 
adverse events as well as ventricular premature complex (VPCs) and 
hypertension. The per protocol analysis included 51 patients in the 
TERLIVAZ[supreg] arm and 55 patients in the norepinephrine arm. A 
response rate of 56% for TERLIVAZ[supreg], a response rate of 43% for 
norepinephrine, and a 10% noninferiority margin was assumed. For an 
alpha level of 5 percent and power of 80 percent, it was determined 
that 57 patients were needed in each arm.
    According to the applicant, the results showed that a higher 
percentage of patients achieved HRS reversal at day 14 (primary 
endpoint) in the TERLIVAZ[supreg] group compared to the norepinephrine 
group in both the intention to treat analysis (ITT) and per-protocol 
analysis (PPA) (ITT 40 percent (n=24) vs. 16.7 percent (n=10); p=0.004; 
PPA 43.13 percent (n=22) vs. 16.3 percent (n=9); p=0.002). Complete 
response was defined as return of serum creatinine (SCr) to a value 
within 0.3 mg/dL of baseline.
    In support of its claims that TERLIVAZ[supreg] is associated with a 
more rapid resolution of the HRS-1 disease process and a reduced rate 
of mortality compared to midodrine and octreotide, the applicant 
summarized the results of the Cavallin et al. study,\778\ which 
compared TERLIVAZ[supreg] plus albumin versus midodrine and octreotide 
plus albumin in a multi-center randomized controlled trial. Patients in 
the study were from eight hospitals in Italy. The researchers 
hypothesized a response rate of 60 percent for TERLIVAZ[supreg] and of 
30 percent for midodrine plus octreotide (MID/OCT), with an alpha error 
of 5 percent and power of 80 percent. An interim analysis after 
enrollment of half the sample size set a stopping rule for the 
randomized clinical trial if the difference in recovery of renal 
function was significant at P<0.01. The study was terminated after 49 
patients were included according to the a priori determined stopping 
rule. The applicant stated that the results showed that improvement of 
renal function was significantly more frequent in patients randomized 
to the TERLIVAZ[supreg] group compared to patients randomized to the 
MID/OCT group; 70.4 percent of patients in the TERLIVAZ[supreg] group 
had a complete or partial response compared with 28.6 percent in the 
MID/OCT group (p=0.01); 55.5 percent of patients in the 
TERLIVAZ[supreg] group had a complete response compared with 4.8 
percent of the MID/OCT group (p<0.001). Complete response was defined 
as a decrease in serum creatinine to <=133 [mu]mol/L (<=1.5 mg/dL). 
Partial response was defined as a >=50% serum creatinine decrease from 
baseline to a final value >133 [micro]mol/L (>1.5 mg/dL). No response 
was defined as a serum creatinine decrease of <50% from baseline.
---------------------------------------------------------------------------

    \778\ Cavallin M, Kamath PS, Merli M, et al. Terlipressin plus 
albumin versus midodrine and octreotide plus albumin in the 
treatment of hepatorenal syndrome: a randomized trial. Hepatology. 
2015;62:567-574.
---------------------------------------------------------------------------

    In this study, some nonresponders to the assigned treatment 
received a rescue treatment according to the treating physician's 
decision. Seven of 12 (58.3 percent) nonresponders in the MID/OCT group 
received a rescue treatment: Six received TERLIVAZ[supreg] plus 
albumin, and one received dialysis. An improvement of renal function 
was observed in five of six patients (83.3 percent) who received 
TERLIVAZ[supreg] plus albumin. Four patients had a complete response 
and one patient had a partial response.
    In support of its claim that TERLIVAZ[supreg] is associated with a 
decreased rate of subsequent diagnostic or therapeutic interventions, 
compared with placebo, the applicant cited the results of the CONFIRM 
trial. The applicant noted that there was a lower incidence of renal 
replacement therapy through the treatment period (14 days) in patients 
receiving TERLIVAZ[supreg] (23.1 percent (n=46)) versus the placebo 
(34.7 percent (n=35)). The applicant also stated that there was a 
decreased incidence of renal replacement therapy (RRT) after liver 
transplant in patients treated with TERLIVAZ[supreg] (19.6 percent

[[Page 25344]]

(n=46)) versus 44.8 percent (n=29) in the placebo group (p=0.04). The 
applicant stated that the need for RRT post-transplant is predictive of 
poor graft function and survival.\779\ The applicant also claimed that 
patients receiving TERLIVAZ[supreg] stayed an average of 6.4 days in 
the ICU versus 13.2 days in the placebo group.
---------------------------------------------------------------------------

    \779\ Watt KDS, Pedersen RA, Kremers WK, et al. Evolution of 
Causes and Risk Factors for Mortality Post-Liver Transplant: Results 
of the NIDDK Long-Term Follow-Up Study. Am. J. Transplant. 
2010;10(6)1420-1427.
---------------------------------------------------------------------------

    In support of its assertion that the overall benefit-risk profile 
of TERLIVAZ[supreg] as a treatment for HRS-1 is favorable, the 
applicant cited the results of the CONFIRM trial. The applicant noted 
that the overall incidence of adverse events (AEs) and serious adverse 
events (SAEs) were similar between patients receiving TERLIVAZ[supreg] 
(n=200) and those receiving placebo (n=99). Further, the applicant 
stated that 88.0 percent (n=176) of patients receiving TERLIVAZ[supreg] 
reported AEs versus 88.9 percent (n=88) in the placebo group and that 
65.0 percent (n=130) of patients receiving TERLIVAZ[supreg] reported 
SAEs versus 60.6 percent (n=60) in the placebo group. The applicant 
also claimed that the majority of AEs associated with TERLIVAZ[supreg] 
are predictable, recognizable, and generally manageable in the hospital 
setting where HRS-1 patients are treated.
    Finally, the applicant asserted that TERLIVAZ[supreg] represents a 
substantial clinical improvement because the totality of the 
circumstances otherwise demonstrates that TERLIVAZ[supreg] 
substantially improves, relative to technologies previously available, 
the treatment of Medicare beneficiaries. The applicant stated that HRS-
1 is a serious, life-threatening condition characterized by development 
of acute or sub-acute renal failure in patients with advanced CLD. The 
applicant further emphasized that HRS-1 is the leading cause of 
hospitalizations among all patients with advanced CLD; therefore, 
inpatient care management of patients with HRS-1 is time and resource 
intensive, representing a significant cost to hospitals.\780\ Finally, 
the applicant reiterated that upon FDA approval, TERLIVAZ[supreg] will 
be the only FDA-approved drug for the HRS-1 indication that aligns with 
the European Association for the Study of the Liver (EASL) treatment 
guidelines for HRS-1: ``Terlipressin plus albumin should be considered 
as the first-line therapeutic option for the treatment of HRS-AKI.'' 
\781\
---------------------------------------------------------------------------

    \780\ Jamil K, Huang X, Lovelace B, et al. The Burden of Illness 
of Hepatorenal Syndrome (HRS) in the United States: A Retrospective 
Analysis of Electronic Health Records. Journal of Medical Economics. 
2019;22(5):421-430.
    \781\ Angeli P, Bernardi M, Villanueva C, et al. EASL Clinical 
Practice Guidelines for the management of patients with 
decompensated cirrhosis. Journal of Hepatology. 2018;69(2):406-460.
---------------------------------------------------------------------------

    In our assessment of the applicant's claims in support of 
substantial clinical improvement, we have the following concerns. 
Regarding the CONFIRM trial, we note that at the time of development of 
this proposed rule, this study has not been published and we would 
appreciate access to additional or more robust materials to facilitate 
further review of the CONFIRM trial results. We note that the 
proportion of patients with verified HRS reversal without HRS 
recurrence by Day 30 was numerically greater in the TERLIVAZ[supreg] 
arm, but the difference between groups was not statistically 
significant (24 percent vs 16 percent, p=0.09) \782\ and we note that 
the potential for HRS-1 recurrence among patients treated with 
TERLIVAZ[supreg] after 30 days is unclear. We also note that, though 
the applicant claimed a reduction in mortality with the use of 
TERLIVAZ[supreg], the mortality rate at Day 90 was higher in the 
TERLIVAZ[supreg] group vs the placebo group (51 percent vs 44.4 
percent).\783\ We further note that the applicant states that survival 
was not defined as a primary or secondary analysis in the CONFIRM trial 
and that no overall survival benefit was observed in the CONFIRM trial 
because survival is confounded by multiple co-morbidities in patients 
with HRS-1.\784\ We note that the primary endpoint of the CONFIRM trial 
used a surrogate endpoint of serum creatinine as an indicator of HRS 
reversal, and we question whether this correlates to improvements in 
clinical outcomes such as mortality and time to transplant. With regard 
to the applicant's claims regarding a similar incidence of adverse 
events and serious adverse events between groups in the CONFIRM trial, 
we note that the results show that the TERLIVAZ[supreg] arm had a 
higher incidence of SAEs up to 30 days post-treatment related to 
respiratory failure, serious infections such as sepsis and septic 
shock, GI bleeding, and abdominal pain. Additionally, 61 percent (\17/
28\) of respiratory events in the treatment arm were fatal versus 20% 
(\1/5\) in the placebo arm.\785\ Regarding the study conducted by Arora 
et al., we note that this study had an open-label design and included 
patients with a diagnosis of ACLF as well as HRS-AKI which may have 
contributed to the differences observed between the TERLIVAZ[supreg] 
arm and the norepinephrine arm in this study.\786\ Finally, we note 
that the results of the Cavallin et al study submitted by the applicant 
in support of a substantial clinical improvement over midodrine and 
octreotide show that there was no survival benefit for the 
TERLIVAZ[supreg] group at months one and three.\787\
---------------------------------------------------------------------------

    \782\ Wong F, Curry MP, Reddy KR, et al, on behalf of the 
CONFIRM Study Investigators. The CONFIRM Study: A North American 
Randomized Controlled Trial (RCT) of Terlipressin plus Albumin for 
the Treatment of Hepatorenal Syndrome Type 1 (HRS-1). Presented at: 
The American Association for the Study of Liver Diseases (AASLD) 
meeting; November 8-12, 2019; Boston, MA.
    \783\ U.S. Food and Drug Administration. Terlipressin Briefing 
Document. NDA #022231. Cardiovascular and Renal Drugs Advisory 
Committee, July 15, 2020. https://www.fda.gov/media/139963/download. 
Accessed February 17, 2021.
    \784\ Mallinckrodt Pharmaceuticals. Terlipressin Briefing 
Document. NDA #022231. Cardiovascular and Renal Drugs Advisory 
Committee, July 15, 2020. U.S. Food and Drug Administration. https://www.fda.gov/media/139965/download. Accessed February 18, 2021.
    \785\ U.S. Food and Drug Administration. Terlipressin Briefing 
Document. NDA #022231. Cardiovascular and Renal Drugs Advisory 
Committee, July 15, 2020. https://www.fda.gov/media/139963/download. 
Accessed February 17, 2021.
    \786\ Israelsen M, Krag A, Allegretti AS, et al. Terlipressin 
versus other vasoactive drugs for hepatorenal syndrome. Cochrane 
Database Syst Rev [internet] 2017 [cited 2019 Nov 5]; 2017(9). 
Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483765/.
    \787\ Cavallin M, Kamath PS, Merli M, et al. Terlipressin plus 
albumin versus midodrine and octreotide plus albumin in the 
treatment of hepatorenal syndrome: A randomized trial. Hepatology. 
2015;62:567-574.
---------------------------------------------------------------------------

    We welcome public comment on whether TERLIVAZ[supreg] meets the 
substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
TERLIVAZ[supreg].
s. 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

[[Page 25345]]

individuals. The applicant asserted viral incubation averages 3-7 days 
and can occur for up to 2 weeks.\788\ According to the applicant, once 
infected, approximately 81% of COVID-19 patients experience mild 
disease, 14% experience severe disease, and 5% experience critical 
disease.\789\ 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+.\790\ The applicant asserted that other risk factors 
for severity include underlying comorbidities but severe illness can 
occur in otherwise healthy individuals at any age.\791\
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    \788\ 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/.
    \789\ 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.
    \790\ 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.
    \791\ 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.\792\ 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.\793\
---------------------------------------------------------------------------

    \792\ Ibid.
    \793\ 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.
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    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.\794\ 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.795 796 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.\797\ 
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.798 799
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    \794\ 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.
    \795\ VEKLURY[supreg] NDA approval: https://www.accessdata.fda.gov/drugsatfda_docs/appletter/2020/214787Orig1s000ltr.pdf; https://www.fda.gov/media/143189/download.
    \796\ FDA. Fact Sheet for Health Care Providers Emergency Use 
Authorization (EUA) of VEKLURY[supreg] (remdesivir): https://www.fda.gov/media/137566/download.
    \797\ 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.
    \798\ VEKLURY[supreg] EUA: https://www.fda.gov/media/137564/download.
    \799\ 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 
into an agreement with the U.S. Government to allocate and distribute 
commercially-available VEKLURY[supreg] across the country.\800\ 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.
---------------------------------------------------------------------------

    \800\ 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-19.801 802 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.\803\ The 
applicant asserted this mechanism of action is different from 
VEKLURY[supreg] which works as a nucleotide analog to inhibit viral 
replication. We note 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.\804\
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    \801\ Convalescent plasma EUA: https://www.fda.gov/media/141477/download.
    \802\ 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.
    \803\ 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.
    \804\ 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.

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[[Page 25346]]

    We note 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).\805\ 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.\806\
---------------------------------------------------------------------------

    \805\ Olumiant[supreg] EUA: https://www.fda.gov/media/143822/download.
    \806\ 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.\807\ 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.\808\
---------------------------------------------------------------------------

    \807\ CDC. Severe Acute Respiratory Syndrome (SARS), updated 
December 6, 2017. https://www.cdc.gov/sars/index.html.
    \808\ 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. We note 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 note 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 
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 would not be eligible for new technology 
add-on payment, if VEKLURY[supreg] is approved for new technology add-
on payment for the patient population indicated in its FDA approval.
    We refer the reader to our comment solicitation in section II.F.7 
of the preamble of this 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.
    We also invite public comments on any implications of the 
distribution agreement described previously with regard to the market 
availability of VEKLURY[supreg] .

[[Page 25347]]

    We also refer the reader to our proposal in section II.F.8 of the 
preamble of this proposed rule 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 invite public comments on whether VEKLURY[supreg] meets the 
newness criterion.
    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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[GRAPHIC] [TIFF OMITTED] TP10MY21.193

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 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

[[Page 25351]]

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 invite public comment on whether 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 above, 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.\809\
---------------------------------------------------------------------------

    \809\ 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.\810\ 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.\811\
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    \810\ 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.
    \811\ 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).\812\
---------------------------------------------------------------------------

    \812\ Ibid.
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    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 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).\813\
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    \813\ 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.\814\
---------------------------------------------------------------------------

    \814\ 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.
---------------------------------------------------------------------------

    We note that the articles submitted by the applicant in support of 
substantial

[[Page 25352]]

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 are unclear whether this may 
suggest that VEKLURY[supreg] did not demonstrate superiority over the 
control. We also note 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.\815\ Furthermore, 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.
---------------------------------------------------------------------------

    \815\ 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 are inviting public comments on whether VEKLURY[supreg] meets 
the substantial clinical improvement criterion.
    In this section, we summarize and respond to written public 
comments received in response to the New Technology Town Hall meeting 
notice published in the Federal Register regarding the substantial 
clinical improvement criterion for VEKLURY[supreg].
    Comment: The applicant responded to questions elicited by its 
presentation at the New Technology Town Hall Meeting held in December 
2020.
    First, the applicant was asked to provide information on adverse 
events and readmissions specifically in patients over 65 years with co-
morbidities. The applicant stated that in the pivotal ACTT-1 study, the 
incidence of overall adverse events was similar among participants >=65 
years of age in both the VEKLURY[supreg] and placebo groups 
(VEKLURY[supreg] 65.6%; placebo: 69.7%).\816\ The applicant asserted 
that reported clinical experience has not identified differences in 
responses between patients over 65 years old and patients under 65 
years old and no dosage adjustment is required in patients over the age 
of 65 years. The applicant stated the NDA for VEKLURY[supreg] notes 
that ``appropriate caution should be exercised in the administration of 
Veklury and monitoring of elderly patients, reflecting the greater 
frequency of decreased hepatic, renal, or cardiac function, and of 
concomitant disease or other drug therapy.'' \817\ According to the 
applicant, subanalyses of readmission rates among participants who were 
at least 65 years of age with comorbidities have not been conducted 
because the overall rate of readmission is too low for any subanalyses 
to be meaningful. The applicant stated that in the ACTT-1 study 
overall, readmittance was reported in 26 participants (5%) in the 
VEKLURY[supreg] group and in 15 participants (3%) in the placebo group.
---------------------------------------------------------------------------

    \816\ Ibid. Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir 
for the Treatment of Covid-19--Final Report. N Engl J Med. 2020.
    \817\ VEKLURY[supreg] NDA approval (re-issued): https://www.fda.gov/media/143189/download.
---------------------------------------------------------------------------

    Second, the applicant was asked to comment on findings of the World 
Health Organization (WHO)-sponsored SOLIDARITY trial. According to the 
applicant, the SOLIDARITY trial is an ongoing, multi center, open-label 
global trial that was designed to (1) provide access to treatments that 
the WHO expert groups recommended for mortality studies and (2) collect 
in-hospital mortality data from a large number of participants without 
posing a significant burden on overstressed healthcare systems. The 
applicant stated that the trial prioritizes broad access to 
investigational treatments, particularly in countries where ongoing 
trials of these treatments were not available, resulting in significant 
heterogeneity in trial adoption, implementation, controls, and patient 
populations.
    According to the applicant, interim results from the WHO study were 
published in the New England Journal of Medicine (NEJM) on December 2, 
2020.\818\ The applicant stated that between March 22, 2020 and October 
4, 2020, 11,330 adult participants were enrolled at 405 hospitals in 30 
countries with vastly different healthcare systems. Of these, 2,743 
participants were treated with VEKLURY[supreg] and 2,708 were 
designated as the VEKLURY[supreg] control group (received local 
standard of care only without placebo). The primary endpoint of 
mortality at Day 28 was 12.5% in the VEKLURY[supreg] group and 12.7% in 
the standard of care group (Kaplan-Meier rate ratio: 0.95 [95% CI: 0.81 
to 1.11; p=0.50]). The authors also reported progression to ventilation 
and time to discharge as secondary endpoints. At the time of the 
interim analysis, 11.9% in the VEKLURY[supreg] group and 11.5% in the 
standard of care group had progressed to mechanical ventilation and 
there were no differences between the VEKLURY[supreg] and standard of 
care groups in time to discharge. None of the three drugs evaluated 
definitively reduced mortality (overall or in any subgroup), initiation 
of ventilation, or duration of hospitalization.
---------------------------------------------------------------------------

    \818\ WHO Solidarity Trial Consortium. Repurposed Antiviral 
Drugs for Covid-19--Interim WHO Solidarity Trial Results. NEJM. 
December 2, 2020. https://www.nejm.org/doi/full/10.1056/NEJMoa2023184.
---------------------------------------------------------------------------

    The applicant stated concerns that the data from WHO's open-label 
global trial has limitations in light of the trial design. According to 
the applicant, the variations in the clinical settings of some 
countries may result in heterogeneity in local standards of care, 
access to earlier care, or access to mechanical ventilation, which 
could account for the high observed mortality rate in ventilated 
patients in SOLIDARITY. Additionally, the applicant stated that lack of 
detail on the level of oxygen support (low versus high), duration of 
symptom onset prior to randomization, and the number of VEKLURY[supreg] 
doses administered precludes subanalyses that could elucidate 
subpopulations who derived benefit from VEKLURY[supreg] treatment. 
Consequently, according to the applicant, it is unclear what conclusive 
findings can be drawn from the study results at this time.
    The applicant stated that according to a perspective piece by 
Rubin, et al., the FDA approval for VEKLURY[supreg] was based on robust 
evidence from three pivotal studies, including the randomized, double-
blind, placebo-controlled ACTT-1 study. The applicant stated that in 
the opinion of Rubin, et al., the results of SOLIDARITY were not 
inconsistent with the results of ACTT-1 and any apparent 
inconsistencies arose from differences in the designs and purposes of 
the studies. The applicant asserted that the authors of the perspective 
piece stated that the effect of VEKLURY[supreg] appears to be on the 
course of hospitalization rather than on mortality.\819\
---------------------------------------------------------------------------

    \819\ Rubin D, Chan-Tack K, Farley J, Sherwat A. FDA approval of 
remdesivir--a step in the right direction. N Engl J Med. DOI: 
10.1056/NEJMp2032369.
---------------------------------------------------------------------------

    According to the applicant, an editorial by Harrington, et al. 
indicated that the authors consider it likely that the estimated 
treatment effects on mortality that were observed in SOLIDARITY are 
largely accurate given the size of the SOLIDARITY study; however, 
aspects of the study design that allowed for the rapid execution of the 
study undermine the ability of the

[[Page 25353]]

study to evaluate more subtle endpoints, such as time to recovery.\820\
---------------------------------------------------------------------------

    \820\ Harrington David P., Baden Lindsey R., Hogan Joseph W. 
(2020) A Large, Simple Trial Leading to Complex Questions. N Engl J 
Med DOI: 10.1056/NEJMe2034294.
---------------------------------------------------------------------------

    The applicant noted that treatment guidelines from the US National 
Institute of Health and the Infectious Disease Society of America, 
which have been updated since publication of the interim data from the 
SOLIDARITY study, continue to recommend treatment with VEKLURY[supreg] 
in hospitalized patients who require supplemental oxygen. Further, the 
applicant asserted, these efficacy and safety data have supported 
regulatory approvals or temporary authorizations to treat COVID-19 in 
approximately 50 countries worldwide.
    Third, the applicant was asked to provide more information on the 
evidence showing there was a trend towards lower mortality, notably in 
patients who received low flow oxygen. The applicant stated that in the 
overall ACTT-1 population, there was a numerical trend toward lower 
mortality in the VEKLURY[supreg] group (11.4%) compared to the placebo 
group (15.2%), which did not reach statistical significance 
(p=0.07).\821\ The applicant asserted that a post-hoc analysis of 
participants receiving low-flow supplemental oxygen (baseline ordinal 
scale score of 5), revealed that VEKLURY[supreg] reduced mortality by 
70% compared with placebo (4.0% vs. 12.7%; hazard ratio: 0.30 [95% CI: 
0.14 to 0.64]).
---------------------------------------------------------------------------

    \821\ Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the 
Treatment of Covid-19--Final Report. New England Journal of Medicine 
2020.
---------------------------------------------------------------------------

    Lastly, the applicant was asked to provide more information to 
justify the claim that all subgroups consistently improved with 
VEKLURY[supreg], given that Medicare patients are older and frequently 
have co-morbidities. According to the applicant, across the clinical 
spectrum, hospitalized patients with COVID-19 receiving VEKLURY[supreg] 
recovered 5 days faster, on average, than those receiving placebo (10 
days vs. 15 days; rate ratio: 1.29; 95% CI: 1.12-1.49; p<0.001), 
representing an increased recovery rate of 29%.\822\ The applicant 
stated that this clinically meaningful benefit is observed across 
subgroups, including among participants at least 65 years of age.
---------------------------------------------------------------------------

    \822\ Ibid.
---------------------------------------------------------------------------

    Response: We appreciate the applicant's responses to questions 
asked at the New Technology Town Hall Meeting and will take this 
information into consideration when deciding whether to approve new 
technology add-on payments for VEKLURY[supreg].
u. 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.\823\ The majority of 
SCLC treated patients show disease relapse and are eligible for second-
line therapy; however, few second-line treatment options exist.\824\
---------------------------------------------------------------------------

    \823\ 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.
    \824\ 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.\825\ 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 
826 827 828--doubling in cell number about every 30 days and 
spreading quickly to lymph nodes and other organs.\829\ 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.830 831 Many 
patients with SCLC have substantial comorbidities that may affect 
performance status and treatment options.\832\ A restrospective 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%).\833\ 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.\834\
---------------------------------------------------------------------------

    \825\ Tan WT, et al. Small Cell Lung Cancer (SCLC), Medscape, 
Oncology. Updated June 19, 2020. Emedicine.medscape.com.
    \826\ Ibid.
    \827\ 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.
    \828\ 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.
    \829\ 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.
    \830\ Ibid.
    \831\ 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].
    \832\ Kalemkerian GP. Small cell lung cancer. Semin Respir Crit 
Care Med. 2016;6(37):783-796.
    \833\ 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.
    \834\ 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.835 836 837 Once a 
patient

[[Page 25354]]

relapses, the likelihood of response is highly dependent on time from 
initial therapy to relapse,\838\ with survival based on the duration of 
remission.\839\ 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 
years.840 841 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.\842\ Despite best management, the 5-year 
overall survival (OS) of even limited-stage SCLC is still only 15% to 
25%.843 844
---------------------------------------------------------------------------

    \835\ 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.
    \836\ 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.
    \837\ 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.
    \838\ 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.
    \839\ Pietanza MC, et al. Small cell lung cancer: Will recent 
progress lead to improved outcomes? Clin Cancer Res. 
2015;21(10):2244-2255.
    \840\ Simos D, et al. Third-line chemotherapy in small-cell lung 
cancer: An international analysis. Clin Lung Cancer (2014) 15 (2): 
110-8.
    \841\ Pelayo AM, et al. Chemotherapy versus best supportive care 
for extensive small cell lung cancer. Cochrane Database Syst Rev 
(2013) 11: CD001990.
    \842\ 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.
    \843\ Simos D, et al. Third-line chemotherapy in small-cell lung 
cancer: An international analysis. Clin Lung Cancer (2014) 15 (2): 
110-8.
    \844\ 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.845 846 847 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.848 849 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,850 851 852 
progression free survival of 2.7 to 3.5 months,853 854 855 
and a median time to progression of 13.3 weeks.\856\ Furthermore, the 
applicant asserted that topotecan is associated with hematological 
toxicities such as anemia, neutropenia, thrombocytopenia, and febrile 
neutropenia.857 858 859
---------------------------------------------------------------------------

    \845\ 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.
    \846\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \847\ Horita N, et al. Topotecan for relapsed small-cell lung 
cancer: Systematic review and meta-analysis of 1347 patients. Sci 
Rep 2015;5: 15437.
    \848\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \849\ Wakuda K et al. Efficacy of second-line chemotherapy in 
patients with sensitive relapsed small-cell lung cancer. In vivo. 
33:2229-2234 (2019).
    \850\ 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 J TopotecanTopotecancyclophosphamidecyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent. J 
ClinVolVol 17, No 2, 1999: 658-667.
    \851\ 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.
    \852\ 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.
    \853\ 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).
    \854\ 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.
    \855\ 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).
    \856\ 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.
    \857\ vonvVon Pawel J.
    Evans 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).
    \858\ 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.
    \859\ 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

[[Page 25355]]

hospital setting.\860\ The applicant stated that there are no existing 
ICD-10-PCS codes that uniquely identify the administration of 
ZEPZELCATM. The applicant submitted a request for a unique 
ICD-10-PCS code to identify the technology beginning FY 2022.
---------------------------------------------------------------------------

    \860\ 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 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%).861 862 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.\863\ The applicant further states 
that ZEPZELCATM has been shown to induce immunogenic cell 
death,\864\ 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.\865\
---------------------------------------------------------------------------

    \861\ ZEPZELCA website, ZEPZELCATM prescribing 
information., Rev. 6/2020: https://www.zepzelcapro.com/.
    \862\ 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.
    \863\ 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.
    \864\ Xie W, et al. Lurbinectedin synergizes with immune 
checkpoint blockade to generate anticancer immunity. Oncoimmunology. 
2019;5;8(11):e1656502.
    \865\ 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.\866\ 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.867 868 869
---------------------------------------------------------------------------

    \866\ FDA website, Hycamtin (topotecan) prescribing 
information., Rev. 2/2014: https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/022453s002lbl.pdf.
    \867\ 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.
    \868\ 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.
    \869\ 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.\870\ 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.\871\ 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.\872\
---------------------------------------------------------------------------

    \870\ FDA website, Hycamtin (topotecan) prescribing 
information., Rev. 2/2014: https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/022453s002lbl.pdf.
    \871\ ZEPZELCA website, ZEPZELCATM prescribing 
information., Rev. 6/2020: https://www.zepzelcapro.com/.
    \872\ 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 are inviting public comments on whether ZEPZELCATM is 
substantially similar to an existing technology and whether it meets 
the newness criterion.
    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

[[Page 25356]]

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-10PCS 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 
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 note 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 note 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 are inviting public comment on whether 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

[[Page 25357]]

indicated for the treatment of adult 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.\873\ 
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.
---------------------------------------------------------------------------

    \873\ 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.\874\ Another 
analysis stated that most patients experience relapse of small cell 
lung cancer within 1 year of treatment.\875\ 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.\876\ 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.\877\
---------------------------------------------------------------------------

    \874\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \875\ 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.
    \876\ Horita N, et al. Topotecan for relapsed small-cell lung 
cancer: Systematic review and meta-analysis of 1347 patients. Sci 
Rep 2015;5:15437.
    \877\ 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.\878\ 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.\879\
---------------------------------------------------------------------------

    \878\ Tan WT, et al. Small Cell Lung Cancer (SCLC), Medscape, 
Oncology. Updated June 19, 2020. Emedicine.medscape.com.
    \879\ 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.\880\
---------------------------------------------------------------------------

    \880\ 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.\881\ 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.\882\ 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.\883\ 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.\884\
---------------------------------------------------------------------------

    \881\ 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.
    \882\ 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.
    \883\ 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.
    \884\ 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.\885\
---------------------------------------------------------------------------

    \885\ 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.\886\ 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%).\887\
---------------------------------------------------------------------------

    \886\ Simeone E, et al. Nivolumab for the treatment of small 
cell lung cancer. Exp Rev Resp Med. 2020;14(1):5-13.
    \887\ 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

[[Page 25358]]

neutropenia and febrile neutropenia were the most common with 5% of 
patients for each.\888\
---------------------------------------------------------------------------

    \888\ 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%.\889\
---------------------------------------------------------------------------

    \889\ 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%.\890\
---------------------------------------------------------------------------

    \890\ 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%.\891\
---------------------------------------------------------------------------

    \891\ 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.\892\
---------------------------------------------------------------------------

    \892\ 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.\893\
---------------------------------------------------------------------------

    \893\ 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.\894\ 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.\895\ 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.\896\ Fourth, the applicant submitted a commentary from 
Arrieta, et. al., and stated that ZEPZELCATM outperformed 
all previously reported results for topotecan.\897\
---------------------------------------------------------------------------

    \894\ Additional secondary endpoints are discussed with the 
overall survival claim.
    \895\ 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.
    \896\ 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.
    \897\ 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.\898\ 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

[[Page 25359]]

completion of the first-line treatment, patients randomized to the 
topotecan group demonstrated an ORR of 25%.\899\ Lastly, a randomized, 
multi-center phase 3 trial of 107 patients treated with topotecan 
reported an ORR of 24.3%.\900\
---------------------------------------------------------------------------

    \898\ 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.
    \899\ 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
    \900\ 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.\901\
---------------------------------------------------------------------------

    \901\ 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.\902\
---------------------------------------------------------------------------

    \902\ 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.\903\ 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.\904\ 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).\905\ 
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.\906\
---------------------------------------------------------------------------

    \903\ 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.
    \904\ 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.
    \905\ 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.
    \906\ 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.\907\ 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.908 909
---------------------------------------------------------------------------

    \907\ 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).
    \908\ 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.
    \909\ 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.\910\ 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.
---------------------------------------------------------------------------

    \910\ 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.\911\
---------------------------------------------------------------------------

    \911\ 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

[[Page 25360]]

treated with lurbinectedin had an ORR 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.912 913 The applicant 
also referenced Arrieta et. al., stating that ZEPZELCATM 
data outperformed less established treatment schemes including platinum 
rechallenge.\914\ 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.\915\ 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.\916\
---------------------------------------------------------------------------

    \912\ 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.
    \913\ 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.
    \914\ 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.
    \915\ NCCN Clinical Practice Guidelines in Oncology, Small Cell 
Lung Cancer. Version 4.2020, July 7, 2020. https://nccn.org.
    \916\ 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%.\917\
---------------------------------------------------------------------------

    \917\ 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.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns. The evidence submitted by the applicant in 
support of ZEPZELCATM's improvement in overall response and 
survival rates is 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 note that without 
a direct comparison arm it may be more difficult to draw definitive 
conclusions.918 919 920 921 We note 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 note 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.\922\ 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 differs from those used in the historical 
controls of topotecan studies, and we note 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 note 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 is unclear 
whether this may partially explain the poorer outcomes of patients in 
the historical control groups. We also note that, while the claim of 
improved hematological outcomes using ZEPZELCATM appears 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 believe 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 note 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 note that the 
subsetted analyses generated from the primary basket study have small 
sample sizes and the authors of these studies stated that further 
research on larger populations is required to draw firm 
conclusions.923 924
---------------------------------------------------------------------------

    \918\ 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.
    \919\ 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.
    \920\ 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.
    \921\ 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.
    \922\ 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.
    \923\ 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
    \924\ 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 invite public comments on whether ZEPZELCATM meets 
the substantial clinical improvement criterion.
    We did not receive any written comments in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
ZEPZELCATM.
6. Proposed 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

[[Page 25361]]

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. 
One applicant withdrew its application prior to the issuance of this 
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.
    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. 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 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 this proposed rule we are making a proposal to approve or 
disapprove each of these 16 applications for FY 2022 new technology 
add-on payments. Therefore, in this section of the preamble of this 
proposed rule, we provide background information on each alternative 
pathway application and propose whether or not each technology would be 
eligible for the new technology add-on payment for FY 2022. We refer 
readers to section II.H.8. of the preamble of 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. The applicant 
anticipates that the aprevoTM device will 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). 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, it appears that 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, would 
have a different newness date, depending on when marketing 
authorization is received for that indication. We note 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.
    According to the applicant, there are currently no unique ICD-10-
PCS codes describing the device. The applicant submitted a request to 
the ICD-10 Coordination and Maintenance Committee for approval of a 
code for FY

[[Page 25362]]

2022 to uniquely identify the technology.
    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] TP10MY21.194

    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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.195

    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.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY21.196


[[Page 25363]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.197


[[Page 25364]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.198

[GRAPHIC] [TIFF OMITTED] TP10MY21.199

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.\925\ 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.\926\ 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 bills 
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.
---------------------------------------------------------------------------

    \925\ Orthopedic Network News. ``2019 Spinal Surgery update.'' 
Volume 30, No. 4. October 2019.
    \926\ 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.
    We agree with the applicant that the aprevoTM 
Intervertebral Body Fusion meets the cost criterion and therefore are 
proposing 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 
this 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 note 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 are proposing 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

[[Page 25365]]

(that is 65 percent of the average cost of the technology).
    We are inviting 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.
(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. According to the applicant, 
there are currently no unique ICD-10-PCS codes describing the device. 
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.
    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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.200

    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 \927\ by the hospital-specific cost-to-charge ratio from the 
FY 2021

[[Page 25366]]

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).
---------------------------------------------------------------------------

    \927\ 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.
    We agree with the applicant that the aScopeTM Duodeno 
meets the cost criterion; and therefore, we are proposing 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 
this 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 believe 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 believe the operating cost of the aScopeTM 
Duodeno is $1,995.
    Based on the information available at the time of this proposed 
rule, it appears 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. As we are unable to separately identify these 
cases to apply two separate payment amounts for these technologies, we 
are 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 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 are 
inviting public comments on this 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 note 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 are proposing 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 are inviting 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 are further inviting public comments on the calculation of the 
maximum new technology add-on payment amount for the 
aScopeTM Duodeno.
(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 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. 
According to the applicant, there are currently no unique ICD-10-PCS 
codes describing the device. The applicant submitted a request to the 
ICD-10 Coordination and Maintenance Committee for a new code to 
uniquely identify the technology.
    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

[[Page 25367]]

(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.\928\ 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 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).
---------------------------------------------------------------------------

    \928\ Ward RP, Lee L, Ward TJ, Lang RM. Utilization and 
Appropriateness of Transthoracic Echocardiography in Response to the 
COVID-19 Pandemic. J Am Soc Echocardiogr. 2020 June;33(6):690-691. 
doi: 10.1016/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 agree with the applicant that, using the cost per case provided 
by the applicant, the Caption GuidanceTM system would meet 
the cost criterion and therefore are proposing to approve the Caption 
GuidanceTM system for new technology add-on payments for FY 
2022. However, as we note later in this section, because the cost per 
case can vary based on utilization of the technology, we would like 
further information on whether the Caption GuidanceTM system 
would still meet the cost criterion if, for instance, an increase in 
utilization resulted in a cost per case that is lower than the figure 
the applicant provided.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of the Caption GuidanceTM 
system is $2,874. We note 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 are 
proposing 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). However, we refer the reader to our discussion and request 
for comments regarding our concerns with respect to determining a cost 
per case for a technology that utilizes a subscription for its cost, 
and note that we may consider finalizing a different add-on payment 
amount after consideration of comments received.
    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 are interested in information 
about

[[Page 25368]]

whether 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 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 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 invite 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.
(4) CERAMENT[supreg] G
    BONESUPPORT Inc. submitted an application for new technology-add on 
payments for CERAMENT[supreg] G for FY 2022. Per the applicant, 
CERAMENT[supreg] G is an injectable bone-void filler made of calcium 
sulfate, hydroxyapatite, and gentamicin sulfate indicated for the 
surgical treatment of osteomyelitis. Per the applicant, this bone graft 
substitute fills gaps resulting from debridement of infected bone and 
prevents colonization of sensitive bacteria, promoting bone healing in 
two ways. The applicant stated that the primary mode of action is for 
CERAMENT[supreg] G to act as a resorbable ceramic bone-void filler 
intended to fill gaps and voids in the skeleton system created when 
infected bone is debrided. The applicant also stated that the secondary 
mode of action is to prevent the colonization of gentamicin-sensitive 
microorganisms in order to protect bone healing. Per the applicant, 
CERAMENT[supreg] G may eliminate the need to harvest autologous bone, 
avoiding pain and infection at the donor site.
    CERAMENT[supreg] G is designated as a Breakthrough Device for use 
as a bone-void filler as an adjunct to systemic antibiotic therapy and 
surgical debridement as part of the surgical treatment of 
osteomyelitis. It has not yet received FDA 510(k) clearance. According 
to the applicant, there are no available codes that adequately describe 
the product CERAMENT[supreg] G. The applicant submitted a request to 
the ICD-10 Coordination and Maintenance Committee for approval of a 
code to uniquely identify the technology.
    With respect to the cost criterion, 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 with 
CERAMENT[supreg] G would most likely map. The applicant identified the 
following seven relevant MS-DRGs:
[GRAPHIC] [TIFF OMITTED] TP10MY21.201

    The applicant conducted a review of ICD-10-PCS codes for procedures 
that would use CERAMENT[supreg] G. For each MS-DRG, the applicant 
searched for cases reporting a diagnosis code from the Osteomyelitis 
category in combination with one of the procedure codes listed in the 
table that follows.
BILLING CODE 4120-01-P

[[Page 25369]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.202


[[Page 25370]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.203


[[Page 25371]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.204


[[Page 25372]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.205

BILLING CODE 4120-01-C
    The applicant identified 7,994 cases across the seven MS-DRGs. The 
applicant then removed charges for prior technology that may be 
replaced by CERAMENT[supreg] G. The applicant conducted a market 
analysis that identified 3 types of prior technology devices: Poly 
(methyl methacrylate) (PMMA) manually mixed with antibiotics, PMMA pre-
loaded with antibiotics, and calcium sulfate (CaS) mixed with 
antibiotics. The applicant researched the average sales price (ASP) for 
major competitors for 5cc and 10cc of each device type and calculated a 
weighted average cost of $444 per 5cc and $727 per 10 cc.\929\ Then the 
applicant converted costs to charges by weighting the operating cost-
to-charge ratios for 3,315 hospitals in the FY 2021 IPPS/LTCH PPS final 
rule and correction notice impact file by each hospital's share of the 
9,235,824 submitted bills 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, or the 2-year inflation factor used 
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 multiplying the estimated 
average cost for 5cc and 10cc of CERAMENT[supreg] G by the 393 percent 
hospital charge markup.
---------------------------------------------------------------------------

    \929\ The applicant's analysis was informed by 2019 and 2020 
data for its competitors from three sources: an iData Market 
Research 2019 Sku Data Report, Global Data US Hospital Bone Grafts 
and Substitutes Q3 2019 Report, and feedback from sales 
representatives in the field.
---------------------------------------------------------------------------

    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $107,671 and an average case-weighted 
threshold of $76,791. 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 agree with the applicant that CERAMENT[supreg] G meets the cost 
criterion; and therefore, subject to the technology receiving FDA 
marketing authorization for use as a bone-void filler as an adjunct to 
systemic antibiotic therapy and surgical debridement as part of the 
surgical treatment of osteomyelitis by July 1, 2021, we are proposing 
to approve CERAMENT[supreg] G for new technology add-on payments for FY 
2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of CERAMENT[supreg] G is $6,020 per 
procedure. Per the applicant, the amount of CERAMENT[supreg] G used per 
patient depends on the location and size of the bone void. The 
applicant expects that a typical patient will require 5-10cc per 
procedure, with large and more complex cases requiring higher volumes. 
The applicant estimated that 70 percent of patients will receive 5cc 
and 30 percent of patients will receive 10 cc of CERAMENT[supreg] G, 
resulting in a weighted average cost of $6,020 per patient. We note 
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 are proposing that the 
maximum new technology add-on payment for a case involving the use of 
the product CERAMENT[supreg] G would be $3,913 for FY 2022 (that is 65 
percent of the average cost of the technology).

[[Page 25373]]

    We are inviting public comments on whether CERAMENT[supreg] G meets 
the cost criterion and our proposal to approve new technology add-on 
payments for CERAMENT[supreg] G for FY 2022, subject to 
CERAMENT[supreg] G receiving FDA marketing authorization for use as a 
bone-void filler as an adjunct to systemic antibiotic therapy and 
surgical debridement as part of the surgical treatment of osteomyelitis 
by July 1, 2021.
(5) EXALTTM Model D Single-Use Duodenoscope
    Boston Scientific Corporation submitted an application 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.
    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

[[Page 25374]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.206

BILLING CODE 4120-01-C
    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

[[Page 25375]]

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 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 note 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 we believe that the same CCR 
should apply for purposes of the cost analysis for EXALTTM 
Model D Single-Use Duodenoscope.
    We agree with the applicant that EXALTTM Model D Single-
Use Duodenoscope meets the cost criterion and therefore are proposing 
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 this proposed rule, it appears 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. Thus, as we are unable to 
separately identify these cases to apply two separate payment amounts 
for these technologies, we are 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 are inviting public 
comments on this 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 note 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 are proposing 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 are inviting 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 are further inviting public 
comments on our calculation of the maximum new technology add-on 
payment amount for the EXALTTM Model D.
(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 has not yet been granted FDA approval. According to the applicant, 
there are currently no unique ICD-10-PCS codes describing the system. 
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.
    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:
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TP10MY21.207


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[GRAPHIC] [TIFF OMITTED] TP10MY21.211

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.
    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. Based on preliminary information from 
the applicant, it appears that the costs of the FUJIFILM EP-7000X 
System do not include any operating costs. Therefore, even if the 
technology meets the cost criterion, it appears 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). However, we are inviting public comments on whether the 
FUJIFILM EP-7000X System has any operating costs. If the FUJIFILM EP-
7000X System does have operating costs, since it appears to meet the 
cost criterion as previously noted, we are proposing to approve new 
technology add-on payments for only the operating costs of the FUJIFILM 
EP-7000X System for FY 2022, 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.
(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

[[Page 25381]]

May 1, 2019, with the indication for the treatment of symptomatic 
severe pulmonary regurgitation in patients with a surgically-repaired 
right ventricular outflow tract. The applicant anticipates receiving 
510(k) clearance for Class III medical device by June 2021. 
Additionally, the applicant noted that the proposed indication for the 
pending FDA marketing authorization is more expansive than the 
indication for the FDA Breakthrough Device status, to include patients 
who have had a prior transcatheter intervention. We note 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 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.
    According to the applicant, there are currently no unique ICD-10-
PCS codes describing the HarmonyTM Transcatheter Pulmonary 
Valve (TPV). 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.
    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.
    We are concerned 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 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. 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 
this 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. It is not clear to us whether these costs reflect the 
use of capital equipment. We note 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, if both components of the HarmonyTM Transcatheter 
Pulmonary Valve (TPV) System are operating costs, we are 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 are inviting 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 replacement. We are also 
inviting public comment on whether the costs of the 
HarmonyTM TPV and HarmonyTM transcatheter 
pulmonary valve delivery and loading system reflect use of capital 
equipment.
(8) Neovasc ReducerTM
    Neovasc Inc. submitted an application for new technology-add on 
payments for the Neovasc ReducerTM System for FY 2022. The 
Neovasc ReducerTM System is a permanent implant inserted 
percutaneously into the coronary sinus and indicated for relief of 
angina symptoms in patients with refractory

[[Page 25382]]

angina. According to the applicant, the device creates a permanent and 
controlled narrowing of the coronary sinus to improve perfusion to 
ischemic myocardium with its hourglass shape. Per the applicant, the 
focal narrowing works to generate a pressure gradient and redistribute 
blood flow to ischemic areas of the heart.
    The Neovasc ReducerTM System was designated as a 
Breakthrough Device on October 10, 2018, indicated for use in patients 
with refractory angina pectoris despite guideline-directed medical 
therapy who are unsuitable for revascularization by coronary artery 
bypass grafting (CABG) or by percutaneous coronary intervention (PCI), 
and anticipates receiving Pre-Market Approval as a Class III medical 
device in the first half of 2021.
    According to the applicant, there are no unique ICD-10-PCS 
procedure codes to report the implantation of the device; however, the 
applicant noted that facilities could report the insertion of the 
ReducerTM System with ICD-10-PCS code 02H43DZ (Insertion of 
intraluminal device into coronary vein, percutaneous approach). 
Similarly, the applicant indicated that there are no unique ICD-10-CM 
diagnosis codes to report refractory angina; however, facilities might 
use ICD-10-CM diagnosis codes I20.8 `Other forms of angina pectoris' or 
I20.9 `Angina pectoris, unspecified' to report refractory angina. The 
applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval for a new ICD-10-PCS procedure code 
for the implantation of the device and a new ICD-10-CM diagnosis code 
for refractory angina for FY 2022 to identify the technology.
    With respect to the cost criterion, the applicant searched the FY 
2019 MedPAR dataset for claims with an ICD-10-PCS procedure code of 
02L73DK (Occlusion of left atrial appendage with intraluminal device, 
percutaneous approach) and 027034Z (Dilation of coronary artery, one 
artery with drug-eluting intraluminal device, percutaneous approach).
    The applicant explained that patients who may be eligible for the 
Neovasc Reducer would be those diagnosed with refractory angina. The 
applicant further explained that because there is by definition no 
treatment for refractory angina, cases admitted to an inpatient 
hospital with a diagnosis of refractory angina were almost exclusively 
assigned to medical MS-DRGs that do not resemble a cardiac procedure in 
terms of clinical or resource use.
    Per the applicant, Left Atrial Appendage (LAA) Occlusion is most 
closely related to the new technology, as it is a venous procedure 
using a permanent implant that is generally performed on a stable 
patient and requires a 1- to 2-day hospital stay. The applicant used 
the refractory angina cases to establish the eligible case count and 
the ratio between cases ``with complication and comorbidity (CC)'' and 
``with major complication and comorbidity (MCC)'' versus cases 
``without CC/MCC''. The applicant stated that it used this ratio to 
weight the MS-DRGs to which the LAA procedure cases mapped, as the 
refractory angina patient population differs in terms of comorbidities 
and severity of illness compared to the patient population receiving 
LAA.
    The applicant identified a total of 16,182 LAA cases mapping to MS-
DRGs 273 or 274. The applicant then removed the implantable device 
charges for the prior technology. The applicant also removed charges 
for cardiac catheterization, the operating room, and supplies and 
equipment. 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 (85 FR 89039), to update the charges from FY 2019 to FY 
2021. The applicant added charges for the new technology, which it 
calculated by dividing the cost of the Reducer device by the national 
cost-to-charge ratio for implantable devices (0.239). The applicant 
noted that the charges for the new technology were not inflated.
    As noted previously, the refractory angina patient population 
differs in terms of comorbidities and severity of illness compared to 
the patient population receiving LAA. Therefore, the applicant adjusted 
the volume weights for MS-DRGs 274/273 to reflect the refractory angina 
population. The applicant extracted cases with an ICD-10-CM diagnosis 
code I20.8 (Other forms of angina pectoris) and I20.9 (Angina pectoris, 
unspecified) from the FY 2019 MedPAR dataset. The applicant identified 
9,548 cases with a refractory angina diagnosis spread across 513 MS-
DRGs. The applicant divided cases into two groups--those mapping to an 
MS-DRG with a CC or MCC designation and those mapping to an MS-DRG 
without CC or MCC. The applicant found that the ratio of cases with CC/
MCC to cases without CC/MCC was 61/39. The applicant applied this ratio 
to the refractory angina cases assigned to MS-DRGs with no CC/MCC 
designation and filled in the volumes by MS-DRG (39 percent of 
refractory angina cases were assigned to MS-DRG 274 and 61 percent to 
MS-DRG 273).
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $141,304 and an average case-weighted 
threshold of $127,659. 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.
    We agree with the applicant that the Neovasc ReducerTM 
System meets the cost criterion and therefore are proposing to approve 
the Neovasc ReducerTM System for new technology add-on 
payments for FY 2022, subject to the technology receiving FDA marketing 
authorization for use in patients with refractory angina pectoris 
despite guideline-directed medical therapy who are unsuitable for 
revascularization by CABG or by PCI by July 1, 2021.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of the Neovasc ReducerTM System 
is $15,000. We note 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 are proposing that the 
maximum new technology add-on payment for a case involving the use of 
the Neovasc ReducerTM System would be $9,750 for FY 2022 
(that is 65 percent of the average cost of the technology).
    We are inviting public comments on whether the Neovasc 
ReducerTM System meets the cost criterion and our proposal 
to approve new technology add-on payments for Neovasc 
ReducerTM System for FY 2022, subject to the Neovasc 
ReducerTM receiving FDA marketing authorization by July 1, 
2021 for use in patients with refractory angina pectoris despite 
guideline-directed medical therapy who are unsuitable for 
revascularization by coronary artery bypass grafting (CABG) or by 
percutaneous coronary intervention (PCI).
(9) Phagenyx[supreg] System
    Phagenesis Ltd. submitted an application for new technology-add on 
payments for Phagenyx[supreg] System for FY 2022. The Phagenyx[supreg] 
system (Phagenyx[supreg]) is a neurostimulation device for the 
treatment of neurogenic dysphagia, which is often seen after

[[Page 25383]]

stroke, traumatic brain injury, or prolonged mechanical ventilation. 
Per the applicant, the system is comprised of a sterile single-use per 
patient catheter, introduced nasally and extending as far as the 
patient's stomach; and a base station, described as a touch screen user 
interface that facilitates the optimization of stimulation levels and 
stores patient and treatment information. Per the applicant, treatment 
involves the use of electric pulses to stimulate sensory nerves in the 
oropharynx.
    The Phagenyx[supreg] system received Breakthrough Device 
designation on December 4, 2019 and anticipates receiving De Novo FDA 
clearance by the second quarter of CY 2021. Per the applicant, the FDA 
granted Breakthrough Device designation for use in treating neurogenic 
dysphagia in adult tracheotomized patients weaned from ventilation. The 
applicant noted that their De Novo application to FDA has a broader 
proposed indication, which states that it is intended for the treatment 
of non-progressive neurogenic dysphagia in adult patients, and 
explained that there are current plans to request an expanded 
Breakthrough Designation to align with this broader labelling. We note 
that, under the eligibility criteria for approval under the alternative 
pathway for certain transformative new devices, only the use of the 
Phagenyx[supreg] system for the treatment of neurogenic dysphagia in 
adult tracheotomized patients weaned from ventilation, 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, unless an expanded Breakthrough Designation that aligns with FDA 
labelling is also granted by the FDA marketing authorization deadline.
    According to the applicant, there are currently no unique ICD-10-
PCS codes describing the Phagenyx[supreg] system. 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.
    With respect to the cost criterion, the applicant performed two 
analyses based on its Breakthrough Designation indication and the 
broader proposed indication. For both scenarios, the applicant used the 
FY 2019 MedPAR dataset to assess the MS-DRGs to which potential cases 
representing patients who may be eligible for the Phagenyx[supreg] 
System would most likely map. Under the first analysis based on the 
applicant's Breakthrough designation indication, the applicant searched 
for claims reporting an ICD-10-PCS procedure code for tracheostomy in 
combination with an ICD-10-CM diagnosis code for dysphagia.
[GRAPHIC] [TIFF OMITTED] TP10MY21.212

[GRAPHIC] [TIFF OMITTED] TP10MY21.213

    The applicant identified 8,181 cases spanning 170 MS-DRGs. Per the 
applicant, 69 percent of the discharges were in MS-DRGs 003 and 004, 
which is consistent with the applicant's assertion that cases involving 
tracheostomized patients typically map to these MS-DRGs.
    Under the second analysis, based on the applicant's proposed 
broader indication, the applicant searched for claims reporting an ICD-
10-CM diagnosis code for dysphagia, then excluded claims reporting an 
ICD-10-CM code for CNS disease. The applicant identified 390,328 cases 
spanning 722 MS-DRGs.

[[Page 25384]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.214

[GRAPHIC] [TIFF OMITTED] TP10MY21.215

    Under both analyses, the applicant did not remove any charges for 
prior technology. The applicant 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 89039), to update the charges from FY 2019 to FY 2021. The applicant 
then added charges for the Phagenyx[supreg] System by dividing the cost 
by the national cost-to-charge ratio for supplies and equipment of 
0.297 (85 FR 58601).
    Under the analysis based on the applicant's Breakthrough 
Designation indication, the applicant calculated a final inflated case-
weighted average standardized charge per case of $331,860 and an 
average case-weighted threshold of $276,624. Under the analysis based 
on the applicant's broader proposed indication, the applicant 
calculated a final inflated case-weighted average standardized charge 
per case of $104,346 and an average case-weighted threshold of $68,799. 
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.
    We agree with the applicant that Phagenyx[supreg] System meets the 
cost criterion and therefore are proposing to approve Phagenyx[supreg] 
System for new technology add-on payments for FY 2022, subject to the 
technology receiving FDA marketing authorization for the indication 
corresponding to the Breakthrough Device designation by July 1, 2021. 
As noted previously, only the use of the Phagenyx[supreg] System for 
the treatment of neurogenic dysphagia in adult tracheotomized patients 
weaned from ventilation, 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 
this proposed rule, the cost of the Phagenyx[supreg] System is $5,000. 
We note 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 are proposing that the 
maximum new technology add-on payment for a case involving the use of 
the Phagenyx[supreg] System would be $3,250 for FY 2022 (that is, 65 
percent of the average cost of the technology).
    We are inviting public comments on whether the Phagenyx[supreg] 
System meets the cost criterion and our proposal to approve new 
technology add-on payments for the Phagenyx[supreg] System for FY 2022 
for the indication corresponding to the Breakthrough Device 
designation, subject to the Phagenyx[supreg] System receiving FDA 
marketing authorization for that indication by July 1, 2021.
(10) PRCFC
    Cerus Corporation submitted an application for new technology-add 
on payments for FY 2022. PRCFC (pathogen reduced cryoprecipitated 
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.
    PRCFC 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 stated that the product will not be 
available for sale until the second quarter of CY 2021 due to 
manufacturing lead time for system components as well as validations 
and quality control analyses that must be completed by the 
manufacturing facilities. We note that, under the eligibility criteria 
for approval under the alternative pathway for certain

[[Page 25385]]

transformative new devices, only the use of PRCFC 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.
    According to the applicant, there are currently no unique ICD-10-
PCS codes that accurately identify the transfusion of this product. The 
applicant stated while there are many ICD-10-PCS codes to describe the 
transfusion of traditional nonautologous plasma cryoprecipitate, these 
codes do not apply to this product. 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.
    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] TP10MY21.216

    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, PRCFC 
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 PRCFC 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.\930\ 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 PRCFC.
---------------------------------------------------------------------------

    \930\ 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.
    We agree with the applicant that PRCFC meets the cost criterion and 
therefore are proposing to approve PRCFC 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 this proposed rule, the 
cost of PRCFC is $750 per gram x 5.2 grams for the amount of $3,900 per 
patient. We note 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 are proposing that the 
maximum new technology add-on payment for a case involving the use of 
PRCFC would be $2,535 per patient for FY 2022 (that is, 65 percent of 
the average cost of the technology).
    We are inviting public comments on whether PRCFC meets the cost 
criterion and our proposal to approve new technology add-on payments 
for PRCFC for FY 2022 when used for the control of massive bleeding 
associated with fibrinogen (Fg) deficiency.
(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

[[Page 25386]]

FDA \931\) 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. 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.
---------------------------------------------------------------------------

    \931\ https://www.fda.gov/regulatory-information/search-fda-guidance-documents/breakthrough-devices-program.
---------------------------------------------------------------------------

    With regard to the newness criterion, we believe that the beginning 
of the newness period for RECELL[supreg] commences from the date of 
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 do not believe 
that the device is eligible for new technology add on payments for FY 
2022. Accordingly, we are proposing to disapprove RECELL[supreg] 
Autologous Cell Harvesting Device for new technology add on payments 
for FY 2022. We are inviting 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.
    We also present the applicant's analysis of the cost criterion for 
this application. With regard to the cost criterion, the applicant 
searched the FY 2019 MedPAR dataset for cases representing patients who 
may be eligible for treatment with RECELL[supreg]. The applicant noted 
that the FY 2019 MedPAR dataset did not contain the ICD-10-PCS code 
0HR_X72 (Skin Replacement on the _____, Autologous Tissue Substitute, 
using Cell Suspension Technique) that identify RECELL[supreg] 
procedures because the code was first effective on October 1, 2019 
after the closing date for the FY 2019 file. For purposes of this 
application, the applicant searched for cases reporting ICD-10-PCS 
codes 0HR_X73 (Skin Replacement on the _____, Autologous Tissue 
Substitute, Full Thickness) and 0HR_X74 (Skin Replacement on the _____, 
Autologous Tissue Substitute, Partial Thickness) which describe skin 
graft procedures used to treat burn injuries. The applicant highlighted 
the potential codes in between using the following table:
[GRAPHIC] [TIFF OMITTED] TP10MY21.217


[[Page 25387]]


    Per the applicant, skin grafts for burn diagnoses, including 
RECELL[supreg] procedures, are assigned to MS-DRGs 927, 928, and 929 in 
Major Diagnostic Category (MDC) 22 (Burns). No other MS-DRGs or MDCs 
were considered because RECELL[supreg] is only indicated for acute 
thermal burns. The applicant presented four analyses based on patient 
cases with increasingly conservative inputs to demonstrate that 
RECELL[supreg] meets the cost criterion. The applicant indicated that 
it varied the combination of the 2-year inflation factor from the FY 
2021 IPPS/LTCH PPS final rule and charges for the new technology in 
each analysis.
    For all four scenarios, the applicant calculated the average charge 
per case for each MS-DRG and then standardized the charges. The 
applicant did not remove any charges for the technology being replaced, 
as the applicant asserted that RECELL[supreg] is not replacing a 
technology. However, the applicant removed charges to account for a 
reduced length of stay because of utilizing RECELL[supreg]. The 
applicant applied the 2-year outlier inflation factor of 13.2 percent 
from the FY 2021 IPPS/LTCH PPS final rule (85 FR 59039), to update the 
charges from FY 2019 to FY 2021 for two analyses. To provide a 
conservative calculation, the applicant submitted two additional 
analyses that did not apply an inflation factor to standardized 
charges.
    The applicant added charges for the new technology after dividing 
the cost of RECELL[supreg] by the national average cost-to-charge ratio 
for supplies and equipment (0.297). Per the applicant, the anticipated 
charges for RECELL[supreg] vary depending on the size and extent of the 
burn wound. The applicant noted that one RECELL[supreg] system covers 
up to 1,920 square centimeters of body surface area, which equals 
approximately 10 percent of the total body surface area (TBSA) of an 
average-sized adult. The applicant also noted the ICD-10-CM T21 
diagnosis code category (Burn and corrosion of trunk) to describe the 
extent of a burn wound in 10 percent TBSA increments and provide an 
objective, claims-based index for the approximate number of 
RECELL[supreg] systems needed per patient. Per the applicant, more than 
one RECELL[supreg] system may be required to provide full coverage of 
the patient's burn wounds as indicated by the T31 diagnosis code 
category (Burns classified according to extent of body surface 
involved).
[GRAPHIC] [TIFF OMITTED] TP10MY21.218

    Under the first analysis, which involved a case with a 27 percent 
TBSA burn injury requiring three RECELL[supreg] systems and a 13.2 
percent charge inflation factor, the applicant calculated a final 
inflated case-weighted average standardized charge per case of 
$268,119.
    Under the second analysis, which involved the same case with a 27 
percent TBSA burn injury requiring three RECELL[supreg] systems and no 
charge inflation factor, the applicant calculated a final inflated 
case-weighted average standardized charge per case of $245,824.
    Under the third analysis, which involved a case with a 9 percent 
TBSA injury requiring one RECELL[supreg] system and a 13.2 percent 
charge inflation factor, the applicant calculated a final inflated 
case-weighted average standardized charge per case of $217,614.
    Under the fourth analysis, which involved the same case with a 9 
percent TBSA burn injury requiring one RECELL[supreg] system and no 
charge inflation factor, the applicant calculated a final inflated 
case-weighted average standardized charge per case of $195,319.
    The applicant calculated a case-weighted threshold of $166,916 
under all four analyses.
    Because the final inflated case-weighted average standardized 
charge per case exceeded the average case-weighted threshold amount 
under all four analyses, the applicant asserted that the technology 
meets the cost criterion.
    We agree with the applicant that RECELL[supreg] meets the cost 
criterion. As stated previously, because the 3-year anniversary date of 
the entry of RECELL[supreg] onto the U.S. market (September 20, 2021) 
will occur in FY

[[Page 25388]]

2021, we do not believe that the device is eligible for new technology 
add-on payments for FY 2022. Therefore, we are proposing to disapprove 
RECELL[supreg] for new technology add-on payments for FY 2022. However, 
in the event we receive updated information to establish that 
RECELL[supreg] meets the newness criterion, we are providing the 
following information regarding the new technology add-on payment 
amount.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost per patient of RECELL[supreg] is $15,000 
or an estimated average cost of $7,500 per device multiplied by 2, 
which, per the applicant, is the average number of RECELL[supreg] units 
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. In the event we receive supplemental information to 
establish that the technology is still within the newness period, and 
we were to approve new technology add-on payments for RECELL[supreg] in 
the final rule, the maximum new technology add-on payment for 
RECELL[supreg] would be $9,570 for FY 2022 (that is, 65 percent of the 
average cost of the technology).
(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.
    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 stated that it anticipates 
receiving Pre-Market Approval as a Class III device from the FDA by 
March 2021 for the same proposed indication. The applicant stated that 
they expect to be shipping product within 1 month of FDA approval and 
state that they therefore estimate market availability by April 2021. 
According to the applicant, there are currently no unique ICD-10-PCS 
codes describing the device. The applicant has submitted a request to 
the ICD-10 Coordination and Maintenance Committee for approval of a 
unique code for FY 2022 to identify the technology.
    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:

[[Page 25389]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.219

    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 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.
    We agree with the applicant that Shockwave C2 Intravascular 
Lithotripsy (IVL) System meets the cost criterion and therefore are 
proposing 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 
this 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. We note 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 are proposing 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 are inviting 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.

[[Page 25390]]

(13) ThoraflexTM Hybrid Device
    Terumo Aortic submitted an application for new technology-add on 
payments for the ThoraflexTM Hybrid Device 
(ThoraflexTM) for FY 2022. Per the applicant, the device is 
a sterile single-use, gelatin sealed Frozen Elephant Trunk (FET) 
surgical medical device. The applicant explained that the device is 
deployed through an opened aortic arch and then positioned into the 
descending thoracic aorta. The applicant further explained that, once 
it is completely deployed, the collar is sutured to the aorta, and 
graft anastomoses are then performed in a manner depending upon the 
chosen product design (which the applicant specified as either the 
Plexus or the Ante-Flo). The device includes a proximal crimped 
polyester surgical graft, central polyester collar, and distal nitinol 
ring stents supported by thin-wall polyester fabric. The applicant also 
noted that the device has a unique gelatin sealant that acts as a seal, 
preventing blood loss through the polyester fabric product wall.
    ThoraflexTM Hybrid Device received Breakthrough Device 
designation on March 20, 2020 with an indication for the open surgical 
repair or replacement of damaged or diseased vessels of the aortic arch 
and descending aorta, with or without involvement of the ascending 
aorta, in cases of aneurysm and/or dissection. The applicant is seeking 
Pre-Market Approval for the device under a Class III device 
designation. The applicant stated there are currently no unique ICD-10-
PCS codes that describe the ThoraflexTM Hybrid Device, but 
the following codes may be currently utilized: 02RX08Z (Replacement of 
thoracic aorta, ascending/arch with zooplastic tissue, open approach); 
02RX0JZ (Replacement of thoracic aorta, ascending/arch with synthetic 
tissue, open approach); and 02RX0KZ (Replacement of thoracic aorta, 
ascending/arch with nonautologous tissue substitute, open approach). 
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.
    With regard to the cost criterion, the applicant conducted two 
analyses based on 100 percent of identified claims and 74 percent of 
identified claims. To identify potential cases where the 
ThoraflexTM Hybrid Device could be utilized, the applicant 
searched the FY 2019 MedPAR file for claims reporting the ICD-10-PCS 
codes for thoracic aortic replacement procedures noted previously. For 
the analysis using 100 percent of cases, the applicant identified 5,374 
cases mapping to 21 MS-DRGs. The applicant then removed charges for the 
technology being replaced. Per the applicant, the use of the 
ThoraflexTM Hybrid device is expected to replace a portion 
of prior technologies. The applicant explained that because an estimate 
of the percentage of these total charges that would be replaced could 
not be determined, it removed 100 percent of charges associated with 
medical/surgical supplies and devices (revenue centers 027x and 0624). 
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. As the average sales price 
of the ThoraflexTM has yet to be determined, the applicant 
did not add charges for the new technology. The applicant indicated 
that, once the price is determined, it will utilize the national cost-
to-charge ratio for implantable devices from the FY 2021 IPPS/LTCH PPS 
final rule (0.293) to calculate estimated average hospital charges 
associated with the device. Under this analysis, based on 100 percent 
of identified claims, the applicant calculated a final inflated case-
weighted average standardized charge per case of $298,047 and an 
average case-weighted threshold of $230,079.
    Under the analysis based on 74 percent of cases, the applicant used 
the same methodology, which identified 3,978 cases across MS-DRGs 219 
and 220. The applicant determined the average case-weighted threshold 
of $210,585 and a final inflated average standardized charge per case 
of $254,795. 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.
    We agree with the applicant that the ThoraflexTM Hybrid 
Device meets the cost criterion and therefore are proposing to approve 
the ThoraflexTM Hybrid Device for new technology add-on 
payments for FY 2022, subject to the technology receiving FDA marketing 
authorization for the open surgical repair or replacement of damaged or 
diseased vessels of the aortic arch and descending aorta, with or 
without involvement of the ascending aorta, in cases of aneurysm and/or 
dissection by July 1, 2021.
    The applicant has not provided an estimate for the cost of the 
ThoraflexTM Hybrid Device at the time of this proposed rule. 
We expect the applicant to submit cost information prior to the final 
rule, and we will provide an update regarding the new technology add-on 
payment amount for the technology, if approved, in the final rule. Any 
new technology add on payment for the ThoraflexTM Hybrid 
Device would be subject to our policy under Sec.  412.88(a)(2) where 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 are inviting public comments on whether the 
ThoraflexTM Hybrid Device meets the cost criterion and our 
proposal to approve new technology add-on payments for the 
ThoraflexTM Hybrid Device for FY 2022, subject to 
ThoraflexTM Hybrid Device receiving FDA marketing 
authorization by July 1, 2021 for the open surgical repair or 
replacement of damaged or diseased vessels of the aortic arch and 
descending aorta, with or without involvement of the ascending aorta, 
in cases of aneurysm and/or dissection.
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 plans to resubmit an NDA

[[Page 25391]]

after discussing next steps with the FDA and hopes 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). If CONTEPOTM 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. 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 CONTEPOTM for FY 
2021.
    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.
    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, 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.
    We agree with the applicant that CONTEPOTM (fosfomycin) 
meets the cost criterion.
    Therefore, if CONTEPOTM does not receive FDA approval by 
July 1, 2021 to

[[Page 25392]]

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 are proposing 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. If 
CONTEPOTM receives FDA marketing authorization prior to July 
1, 2021, we are 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 this proposed rule, the cost of CONTEPOTM 
administered over 12.5 days is $3,500. We note 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 are proposing 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 antiinfective into central vein, 
percutaneous approach, new technology group 5).
    We are inviting 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.
(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 FY2022 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.
    We agree with the applicant that FETROJA[supreg] (cefiderocol) 
meets the cost criterion and therefore are proposing to approve 
FETROJA[supreg] for new technology

[[Page 25393]]

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 XW03366 or XW04366.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of FETROJA[supreg] administered over an 
average of 10.4 days is $11,439.79. We note 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 are proposing 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 are inviting 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.
(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] TP10MY21.220

    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

[[Page 25394]]

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 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.
    We agree with the applicant that RECARBRIOTM meets the 
cost criterion and therefore are proposing 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 this proposed rule, the 
cost of RECARBRIOTM is $12,768.68 when used for the 
treatment of HABP and VABP. We note 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 are proposing 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 are inviting 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.
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.

[[Page 25395]]

    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 are seeking 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.
8. Proposal To Extend the New COVID-19 Treatments Add-On Payment 
(NCTAP) Through the End of the FY in Which the PHE Ends for Certain 
Products and Discontinue NCTAP for Products Approved for New Technology 
Add-on Payments in FY 2022
    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 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, if the PHE were to end in FY 2022, 
until September 30, 2022).\932\ At the same time, we also believe 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 
note 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.
---------------------------------------------------------------------------

    \932\ 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 are proposing 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 are also proposing 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 believe this 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 anticipate 
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, this proposal would allow discharges 
involving that product to continue to be eligible for the NCTAP through 
September 30, 2022 (the end of FY 2022). If that same product 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 invite 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.

[[Page 25396]]

III. Proposed 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 proposed FY 2022 hospital wage index based 
on the statistical areas appears under section III.A.2. of the preamble 
of this proposed 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 
proposed adjustment for FY 2022 is discussed in section II.B. of the 
Addendum to this proposed rule.
    As discussed in section III.I. of the preamble of this proposed 
rule, we also take into account the geographic reclassification of 
hospitals in 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 proposed budget neutrality adjustment for FY 2022 is discussed in 
section II.A.4.b. of the Addendum to this proposed 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 proposing to 
apply to the FY 2022 wage index appears under sections III.E. and F. of 
the preamble of this proposed rule.
2. Core-Based Statistical Areas (CBSAs) for the Proposed 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. Typically, interim OMB bulletins (those 
issued between decennial censuses) have only contained minor 
modifications to labor market delineations. However, the April 10, 2018 
OMB Bulletin No. 18-03 and the September 14, 2018 OMB Bulletin No. 18-
04 included more modifications to the labor market areas than are 
typical for OMB bulletins issued between decennial censuses, including 
some material modifications that had a number of downstream effects, 
such as reclassification changes. These bulletins established revised 
delineations for Metropolitan Statistical Areas, Micropolitan 
Statistical Areas, and

[[Page 25397]]

Combined Statistical Areas, and provided guidance on the use of the 
delineations of these statistical areas. 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, 2018, 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 updates from 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/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 proposing to adopt the updates set forth 
in OMB Bulletin No. 20-01 consistent with our longstanding 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 would continue 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 and 18-04.
    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 PHE, we also seek 
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 seek 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).
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 
crosswalking 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 crosswalking counties to CBSAs. For FY 2022, Tables 2 
and 3 associated with this proposed 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 Proposed FY 2022 Wage Index

    The proposed 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 proposed FY 2022 wage index includes all of the following 
categories of data associated with costs paid under the IPPS (as well 
as outpatient costs):

[[Page 25398]]

     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 
proposed 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 proposed 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.

C. Verification of Worksheet S-3 Wage Data

    The wage data for the proposed 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 
proposed final FY 2022 wage index includes FY 2018 data submitted to us 
as of February 5, 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 asked 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. 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 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.
    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 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 rule, 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. In summary, we calculated the 
proposed FY 2021 wage index using the Worksheet S-3, Parts II and III 
wage data of 3,159 hospitals.
    For the proposed 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 proposed FY 2022 
wage index associated with this proposed rule (available via the 
internet on the CMS website), includes separate wage data for the 
campuses of 16 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 25399]]

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[GRAPHIC] [TIFF OMITTED] TP10MY21.222

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

[[Page 25400]]

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.

D. Method for Computing the Proposed FY 2022 Unadjusted Wage Index

    The method used to compute the proposed 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 are not proposing 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 proposed 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 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 above 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

[[Page 25401]]

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 are not proposing 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.
    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 proposed 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 proposed 
rule for the policy regarding rural areas that do not have IPPS 
hospitals.
    Step 11.--Section 4410 of Pub. L. 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 
proposed 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 are not proposing 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 25402]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.223

    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, the proposed FY 
2022 unadjusted national average hourly wage is the following:
[GRAPHIC] [TIFF OMITTED] TP10MY21.224

E. Proposed 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 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

[[Page 25403]]

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
    For FY 2022, we are proposing 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 proposed 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 proposed rule (which is 
available via the internet on the CMS website), which contains the 
proposed 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 proposed 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 proposed FY 2022 wage index. For the proposed FY 2022 wage 
index, we are using 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 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 
proposed FY 2022 occupational mix adjusted national average hourly wage 
is the following:
[GRAPHIC] [TIFF OMITTED] TP10MY21.225

F. Analysis and Implementation of the Proposed Occupational Mix 
Adjustment and the Proposed FY 2022 Occupational Mix Adjusted Wage 
Index

    As discussed in section III.E. of the preamble of this proposed 
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] TP10MY21.226

    The proposed 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

[[Page 25404]]

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] TP10MY21.227

    We compared the proposed FY 2022 occupational mix adjusted wage 
indexes for each CBSA to the proposed unadjusted wage indexes for each 
CBSA. Applying the occupational mix adjustment to the wage data 
resulted in the following:
[GRAPHIC] [TIFF OMITTED] TP10MY21.228

    These results indicate that a smaller percentage of urban areas 
(54.9 percent) would benefit from the occupational mix adjustment than 
would rural areas (57.4 percent).
    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:

[[Page 25405]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.229

    These results indicate that the wage indexes of 49.3 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 (50.5 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 (40.4 
percent).

G. Application of the Rural Floor, Application of the State Frontier 
Floor, Continuation of the Low Wage Index Hospital Policy, and Proposed 
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 are 
not proposing 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 are not proposing any changes to this 
policy for FY 2022.
    Based on the FY 2022 wage index associated with this proposed 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 
287 hospitals would receive an increase in their FY 2022 proposed wage 
index due to the application of the rural floor.
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

[[Page 25406]]

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 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 are proposing 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 this 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 this 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-Payment/AcuteInpatientPPS/index, and an aggregate payment 
impact for the imputed floor in the Appendix to this 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.

[[Page 25407]]

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 
qualification in this 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 value. There is 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 in time, 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 this 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 are proposing 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 propose 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 are proposing 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 are proposing a conforming revision to Sec.  
412.64(e)(1)(ii) to refer to Sec.  412.64(h)(4)(vii) (proposed in this 
proposed rule) in the introductory phrase that excepts certain 
provisions from the budget neutrality requirement specified in 
paragraph (e)(1)(ii).
     We are proposing 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 are proposing 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 are proposing 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 are proposing to make the following revisions to Sec.  
412.64(h)(5). First, we are proposing 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 are proposing 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 are 
proposing 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.
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 this FY 2022 IPPS/
LTCH PPS proposed rule, we are not proposing any changes to the 
frontier floor policy for FY 2022. In this proposed rule, 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 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 
proposed FY 2022 wage index are identified in Table 2 associated with 
this proposed rule, which is available via the internet on the CMS 
website.
4. Continuation of the Low Wage Index Hospital Policy; Proposed 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

[[Page 25408]]

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 are proposing 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 
proposed 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 this proposed rule, the table below 
displays the 25th percentile wage index value across all hospitals for 
FY 2022.
[GRAPHIC] [TIFF OMITTED] TP10MY21.230

H. Proposed 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 proposed 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 proposed rule for a discussion of the wage index 
tables for FY 2022.

I. Proposed 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 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

[[Page 25409]]

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 this proposed rule and published elsewhere in this issue of the 
Federal Register implementing the court's decision in Bates Cnty. Mem'l 
Hosp.(``Bates'') v. Azar for further changes to the treatment of Sec.  
412.103 hospitals reclassifying under the MGCRB.
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 proposed rule was drafted, the MGCRB had 
completed its review of FY 2022 reclassification requests. Based on 
such reviews, there are 496 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 245 hospitals approved for wage index reclassifications in 
FY 2020 that will continue for FY 2022, and 317 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 this proposed 
rule, 1,058 hospitals are in a MGCRB reclassification status for FY 
2022 (with 161 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. Proposed 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's 
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 this proposed rule, we are proposing 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 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 are proposing to also provide for tolling of 
the 105 day timeframe at Sec.  412.278(f)(2)(ii). Specifically, we are 
proposing 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.
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

[[Page 25410]]

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. Proposed 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 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 are proposing to use them again for FY 2022, as we 
believe they continue to be appropriate. 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 
are not proposing 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).)
    Table 2 associated with this proposed 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 proposed 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 proposed 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

[[Page 25411]]

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 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. Proposed 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 (cancelation 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 cancelation 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

[[Page 25412]]

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 are proposing 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 cancelation until October 1, 2022. We are also proposing an 
additional modification to the effective date of these cancelation 
requests. Currently, all rural reclassification 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 cancelation 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 cancelation 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 cancelation 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 one-year minimum 
reclassification period proposal is finalized, the hospital could 
request cancelation on May 25th the following year. Since that date 
would be prior to 120 day cancelation 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 are 
proposing to eliminate the current rule at Sec.  412.103(g)(3) (that 
cancelation 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 are 
proposing to make cancellation requests effective for the Federal 
fiscal year that begins in the calendar year after the calendar year in 
which the cancelation request is submitted. For example, we are 
proposing that a cancelation 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 are proposing 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 cancelation request is submitted. We are also proposing 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 cancelation 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 
cancelation deadline to a sufficient number of days to ensure that 
hospitals could not time applications and cancelations 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.\933\ 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

[[Page 25413]]

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 are addressing in this proposed rule 
is 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 one year before cancelation 
can be requested, and the proposed policy to make rural 
reclassification cancelations effective beginning the Federal fiscal 
year that begins in the calendar year after the calendar year in which 
the cancelation request is submitted would 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 one-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.
---------------------------------------------------------------------------

    \933\ ``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).
---------------------------------------------------------------------------

3. Modification of Limitations on Redesignation by the Medicare 
Geographic Classification Review Board Interim Final Rule (CMS-1762-
IFC) to implement Bates Co. v. Azar Adverse Court Decision
    In the interim final rule with comment period (IFC) (CMS-1762-IFC) 
simultaneously submitted for public inspection with this proposed rule 
and publishing elsewhere in this issue of the Federal Register, CMS 
made regulatory changes in order to align our policy with the decision 
in Bates County Memorial Hospital v. Azar, 464 F. Supp. 3d 43 (D.D.C. 
2020). Specifically, the IFC revised the regulations at Sec.  412.230 
to allow hospitals with a rural redesignation under Section 
1886(d)(8)(E) 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 fiscal year 
(FY) 2023. 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.

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

[[Page 25414]]

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 made 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 are given the opportunity to examine Table 2 associated 
with this proposed rule, which is listed in section VI. of the Addendum 
to the proposed 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 
contains 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 note 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 plan to post the final wage index data PUFs in late April 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 can 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 believes that its wage or occupational mix data are incorrect 
due to a MAC or CMS error in the entry or tabulation of the final data, 
the hospital is given the opportunity to notify both its MAC and CMS 
regarding why the hospital believes an error exists and provide all 
supporting information, including relevant dates (for example, when it 
first became aware of the error). The hospital is required to send its 
request to CMS and to the MAC so that it is received no later than May 
28, 2021. May 28, 2021 is 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 do 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 
are 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 will be 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 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 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.

[[Page 25415]]

    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.
    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 proposed 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

[[Page 25416]]

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).

M. Proposed 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.
    As described in section IV. of the preamble of this proposed rule, 
effective beginning FY 2022, we are proposing to rebase and revise the 
IPPS market basket to reflect a 2018 base year. We also are proposing 
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 this proposed rule, we are proposing this 
rebased and revised labor -related share in a budget neutral manner. 
However, consistent with section 1886(d)(3)(E) of the Act, we would 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.
    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 this proposed rule, 
beginning with FY 2022, we are proposing 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 are proposing to use a labor-
related share of 67.6 percent for discharges occurring on or after 
October 1, 2021.
    As discussed in section V.B. of the preamble of this proposed 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

[[Page 25417]]

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 are not proposing a 
Puerto Rico-specific labor-related share percentage or a nonlabor-
related share percentage.
    Tables 1A and 1B, which are published in section VI. of the 
Addendum to this FY 2022 IPPS/LTCH PPS proposed rule and available via 
the internet on the CMS website, reflect the proposed 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 proposing to 
apply 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 proposing to apply the wage index to the proposed labor-related 
share of 67.6 percent of the national standardized amount.

IV. Proposed 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 this proposed rule, we are proposing 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 
this FY 2022 IPPS/LTCH PPS proposed rule, we are proposing 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 
rule. We are also proposing to rebase and revise the Capital Input 
Price Index (CIPI) as described in section IV.D. of the preamble of 
this proposed 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 this proposed rule, we are proposing 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 47387), 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 are proposing to rebase and revise the 
IPPS market basket from 2014 to 2018. We are inviting public comments 
on our proposed methodology.
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

[[Page 25418]]

and before October 1, 2018. We are proposing 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 are proposing 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 are proposing 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 rule), we propose 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 are proposing to calculate total Medicare-allowable 
operating costs for each hospital. We are proposing 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 are proposing 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 are now proposing 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 are proposing to first calculate total unadjusted wages and 
salaries costs as reported on Worksheet S-3, Part II, column 4, line 1. 
We are then proposing 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 are proposing 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).
    Specifically, we are proposing 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 are proposing to only include the 
proportion attributable to the Medicare-allowable cost centers. 
Specifically, we are proposing 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 are 
proposing 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.

[[Page 25419]]

(2) Employee Benefits Costs
    We are proposing 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 proposed 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 rule. We are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 
are proposing to use these more detailed lines; however, the expenses 
captured on these lines would 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 are 
no longer proposing to 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 are proposing 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

[[Page 25420]]

(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 are proposing 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 proposed 2018-based IPPS market basket for the given category.
    For the Home Office/Related Organization Contract Labor cost 
weight, we are proposing 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 proposed 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 
for this proposed rule.
[GRAPHIC] [TIFF OMITTED] TP10MY21.231

    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.
    As we did for the 2014-based IPPS market basket (82 FR 38162), we 
are proposing 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 are proposing 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

[[Page 25421]]

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] TP10MY21.232

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 are proposing 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.\934\ 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 are proposing 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 this 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).
---------------------------------------------------------------------------

    \934\ http://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------

    Using this methodology, we are proposing to derive 17 detailed cost 
categories 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 are proposing that these costs be 
included in the Electricity and Other Non-Fuel Utilities cost category.
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 are proposing 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

[[Page 25422]]

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 rule, we present a detailed explanation of the price 
proxies that we are proposing for each cost category weight. We note 
that many of the proxies that we are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing to create 
blended index of these expenses based on each NAICS' expenses as share 
of their sum. Therefore, we are proposing 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.
(4) Electricity and Other Non-Fuel Utilities
    We are proposing 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 
are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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

[[Page 25423]]

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 are 
proposing 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 are proposing 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.233

(10) Blood and Blood Products
    We are proposing 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 are proposing 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 
are proposing to use a blend of these two price proxies. To proxy the 
price changes associated with NAICS 339112, we propose using the PPI--
Commodity--Surgical and medical instruments (BLS series code 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 are 
proposing 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 are proposing 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] TP10MY21.234

(12) Rubber and Plastics
    We are proposing 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 are proposing 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 are proposing 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.

[[Page 25424]]

(15) Professional Fees: Labor-Related
    We are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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 are proposing 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.
    Table IV-05 sets forth the proposed 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.
BILLING CODE 4120-01-P

[[Page 25425]]

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[[Page 25426]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.236

    Table IV-06 compares both the historical and forecasted percent 
changes in the 2014-based IPPS market basket and the proposed 2018-
based IPPS market basket. The forecasted growth rates in Table IV-06 
are based on IHS Global Inc.'s (IGI's) fourth quarter 2020 forecast 
with historical data through third quarter 2020.

[[Page 25427]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.237

BILLING CODE 4120-01-C
    There is no difference between the average percent change in the 
2014-based and the proposed 2018-based IPPS market basket over the FY 
2017 through FY 2020 time period. For FY 2022, the increase is 
projected to be 2.5 percent for both the 2014-based and proposed 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 this FY 2022 
IPPS/LTCH PPS proposed rule, we are proposing 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 are proposing 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 are proposing 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. 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 are proposing 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 are proposing 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 
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 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 are proposing to apportion 4.1 percentage points of the 6.4 
percentage point figure into the

[[Page 25428]]

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 are 
proposing 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 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 
are proposing 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 are apportioning approximately 3.5 percentage 
points of the 5.9 percentage points figure into the Professional Fees: 
Labor-Related cost category and designating 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 proposed rule, the Wages and 
Salaries and Employee Benefits cost weights reflect contract labor 
costs.
[GRAPHIC] [TIFF OMITTED] TP10MY21.238

    Using the cost category weights from the proposed 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 weights 
to reflect 2012 Input-Output data.
    Therefore, we are proposing 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

[[Page 25429]]

labor-related share continues to be consistent with section 1886(d)(3) 
of the Act. We note that section 403 of Pub. L. 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.

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-
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 this FY 2022 
IPPS/LTCH PPS proposed rule, we are proposing 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 are 
proposing 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.

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 are proposing 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 are also proposing 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 
proposed rule. As with the 2014-based index, we are proposing 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 are proposing 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 are proposing to allocate lease costs across each of the 
remaining capital cost categories as was done in the 2014-based CIPI. 
We are proposing 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 are proposing 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 are assuming that approximately 1.3 percent (13.3 percent x 0.1) of 
total capital costs represent lease costs attributable to overhead, and 
we are proposing to add this 1.3 percent to the 4.7 percent Other cost 
category weight. We are then proposing 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

[[Page 25430]]

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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.239

    Finally, we are proposing to further divide the Depreciation and 
Interest cost categories. We are proposing to separate the Depreciation 
cost category into the following two categories: (1) Building and Fixed 
Equipment and (2) Movable Equipment. We also are proposing 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 are proposing 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 are proposing 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 provides a 
comparison of the 2014-based CIPI cost weights and the proposed 2018-
based CIPI cost weights.
    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 are proposing to apply the same price 
proxies as were used in the 2014-based CIPI, which are listed in Table 
IV-09. We also are proposing 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 are proposing 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 are proposing 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 are 
proposing 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 are proposing 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 are proposing 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

[[Page 25431]]

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 are proposing 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.240

    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 proposed 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 are proposing 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 are proposing 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 are 
proposing 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 are proposing 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

[[Page 25432]]

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 
weights, we are proposing 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 proposed rule. For the interest vintage 
weights, we are proposing 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 are 
proposing 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 are 
proposing 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 are proposing 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.
    The vintage weights for the proposed 2018-based CIPI and the 2014-
based CIPI are presented in Table IV-10.
BILLING CODE 4120-01-P

[[Page 25433]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.241

BILLING CODE 4120-01-C
    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.''
    Table IV-11 in this section of this rule compares both the 
historical and forecasted percent changes in the 2014-based CIPI and 
the proposed 2018-based CIPI.

[[Page 25434]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.242

    IHS Global, Inc. forecasts a 1.0 percent increase in the proposed 
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 proposed 2018-based 
CIPI are included in Table IV-12.
[GRAPHIC] [TIFF OMITTED] TP10MY21.243


[[Page 25435]]


    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. Proposed Changes in the Inpatient Hospital Update for FY 2022 (Sec.  
412.64(d))

1. Proposed 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 
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 
productivity (the multifactor productivity (MFP) 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 MFP 
adjustment may result in the applicable percentage increase being less 
than zero.
    We note, in compliance with section 404 of the MMA, in this 
proposed rule, we are proposing 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 are proposing 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 is estimated to be 2.5 percent. We 
also are proposing that if more recent data subsequently become 
available (for example, a more recent estimate of the market basket 
update and the MFP adjustment), we would use such data, if appropriate, 
to determine the FY 2022 market basket update and the MFP adjustment in 
the final rule.
    For FY 2022, we are proposing an MFP adjustment of 0.2 percentage 
point. Similar to the market basket update, for this proposed rule, we 
used IGI's fourth quarter 2020 forecast of MFP to compute the proposed 
FY 2022 MFP adjustment. As noted previously, we are proposing 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 
MFP adjustment for the final rule.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51689 through 
51692), we finalized our methodology for calculating and applying the 
MFP 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. As we discussed in the FY 2016 IPPS/LTCH 
PPS final rule (80 FR 49509), beginning with the FY 2016 rulemaking 
cycle, the MFP adjustment is calculated using the revised series 
developed by IGI to proxy the aggregate capital inputs. Specifically, 
in order to generate a forecast of MFP, IGI forecasts BLS aggregate 
capital inputs using a regression model. 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.
    For FY 2022, we are proposing an MFP adjustment of 0.2 percentage 
point. Similar to the market basket update, for this proposed rule, we 
used IGI's fourth quarter 2020 forecast of the MFP adjustment to 
compute the proposed FY 2022 MFP adjustment. As noted previously, we 
are proposing 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 MFP for the final rule.
    Based on these data, we have determined four proposed applicable 
percentage increases to the standardized amount for FY 2022, as 
specified in the following table:

[[Page 25436]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.244

    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 an MFP 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 are proposing 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 this proposed rule, we 
are using 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 MFP 
adjustment. We are proposing that if more recent data subsequently 
became available (for example, a more recent estimate of the market 
basket update and the MFP adjustment), we would use such data, if 
appropriate, to determine the update in the final rule.
2. Proposed 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 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

[[Page 25437]]

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 MFP 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 MFP 
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, for this FY 2022 proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, as discussed previously, for Puerto 
Rico hospitals we are proposing a market basket update of 2.5 percent 
and an MFP adjustment of 0.2 percent. Therefore, 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 have 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 are proposing 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 MFP 
adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we are proposing 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 MFP adjustment.
    As noted previously, we are proposing 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 MFP adjustment 
for the FY 2022 IPPS/LTCH PPS final rule.

B. Rural Referral Centers (RRCs) Proposed 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 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. Proposed 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 section I.F. of this proposed rule, 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 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 note that the CMI values calculated using the FY

[[Page 25438]]

2020 data are significantly different from the CMI values calculated 
using the FY 2019 data. As such, while we would normally propose to use 
data from FY 2020 to calculate CMI values for this FY 2022 proposed 
rule, we are instead proposing to use values that are based on 
discharges occurring during FY 2019 (October 1, 2018 through September 
30, 2019), and include bills posted to CMS' records through March 2020. 
We are making available for public comment the CMI values calculated 
using the FY 2020 data that we would ordinarily propose to use. We 
refer readers to the ``Alternatives Considered'' discussion in section 
I.O. of Appendix A for where these and other supplemental files may be 
found.
    Accordingly, we are proposing 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 are proposing 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 are also proposing 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.
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 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 this proposed rule and as 
previously noted with respect to the CMI calculation, 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 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 note 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 are instead proposing 
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 are making available for public comment the 
regional median discharges calculated using FY 2019 cost report data 
that we would ordinarily propose to use. We refer readers to the 
``Alternatives Considered'' discussion in section I.O. of Appendix A 
for where these and other supplemental files may be found.
    Accordingly, we are proposing 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.
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 
proposed amendment to provide for the use of the best available data 
rather than the use of the latest available data. The proposed national 
median CMI value for FY 2022 is based on the CMI values of all urban 
hospitals nationwide, and the proposed 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 proposed values are based on discharges occurring 
during FY 2019 (October 1, 2018 through September 30, 2019), and 
include bills posted to CMS' records through March 2020.
    In this FY 2022 IPPS/LTCH PPS proposed rule, we are proposing 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 are set forth in the table 
in this section of this rule. 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.

[[Page 25439]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.245

    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. 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 are proposing 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 are proposing 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 proposed number of discharges in the table set 
forth in this section of the rule.
[GRAPHIC] [TIFF OMITTED] TP10MY21.246

    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 proposed 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. Proposed 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,

[[Page 25440]]

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 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 Federal Register on April 26, 2018 (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 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

[[Page 25441]]

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).\935\ 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.
---------------------------------------------------------------------------

    \935\ We note that for FY 2021, we established a deadline of 
September 15, 2020 for receipt of a hospital's written request by 
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 are proposing 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 are proposing 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 note 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).\936\
---------------------------------------------------------------------------

    \936\ 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 
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.

D. Proposed 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.

E. Proposed 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

[[Page 25442]]

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 proposed 
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. 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

[[Page 25443]]

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 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 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 this FY 2022 IPPS/LTCH PPS proposed rule, we 
are proposing 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, consistent with 
our proposal discussed in section I.F of the preamble of this proposed 
rule. For a discussion of the inpatient Provider Specific File, we 
refer the reader to section II.A.4 of the Addendum of this proposed 
rule. In this FY 2022 IPPS/LTCH PPS proposed rule, we discuss 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 
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 are proposing 
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:

[[Page 25444]]

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. We refer the 
reader 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). The Model's Performance Year 5 
was extended to September 30, 2021.
     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 (Pub. L. 
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 Public Law 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 
Public Law 108-173 to extend the Rural Community Hospital Demonstration 
Program for an additional 5-year period. At the time of issuance of 
this proposed rule, we believe 27 hospitals may participate in the 
demonstration program at the start of 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.
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 proposed rule, we discuss the data sources and 
methodologies for computing each of these factors, our final policies 
for FYs 2014 through 2021, and our proposed policies for FY 2022.
a. Proposed 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.
    As we did for FY 2021, in this FY 2022 IPPS/LTCH PPS proposed rule, 
in order to determine Factor 1 in the uncompensated care payment 
formula for FY 2022, we are proposing to

[[Page 25445]]

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, these estimates will not be revised or 
updated subsequent to the publication of our final projections in the 
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 
proposed 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 
this 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 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 are 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 this 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, is 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, is approximately $3.524 
billion (or 25 percent of the total amount of estimated Medicare DSH 
payments for FY 2022). Under Sec.  412.l06(g)(1)(i) of the regulations, 
Factor 1 is the difference between these two OACT estimates . 
Therefore, in this proposed rule, we are proposing 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). We note that consistent 
with our approach in previous rulemakings, OACT intends to use more 
recent data that may become available for purposes of projecting the 
final Factor 1 estimates for the FY 2022 IPPS/LTCH PPS final 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 the final rule 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 expect that the Midsession Review will have updated 
economic assumptions and actuarial analysis, which would be used for 
the development of Factor 1 estimates in the final rule.
    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).
    In this proposed rule, we include information regarding the data 
sources, methods, and assumptions employed by the actuaries in 
determining OACT's estimate of Factor 1. In summary, we indicate the 
historical HCRIS data update OACT used to identify Medicare DSH 
payments, we explain that the most recent Medicare DSH payment 
adjustments provided in the IPPS Impact File were used, and we provide 
the components of all the 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 includes a description of the ``Other'' and 
``Discharges'' assumptions, and also provides additional information 
regarding how we address the Medicaid and CHIP expansion.
    The Office of the Actuary's estimates for FY 2022 for this proposed 
rule began

[[Page 25446]]

with a baseline of $13.931 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:
[GRAPHIC] [TIFF OMITTED] TP10MY21.247

    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 proposed 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 from the 
COVID-19 pandemic. We note that, based on the most recent available 
data, it is estimated that Medicaid enrollment increased by 2.9 percent 
in FY 2020 and will increase by an additional 1.2 percent in FY 2021.
    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. 
We note 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 25447]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.248

b. Calculation of Proposed 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 are proposing 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 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

[[Page 25448]]

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). 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 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/.
    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 this FY 2022 IPPS/LTCH proposed rule for further 
details on the methodology and assumptions that were used in the 
projection of the uninsurance rate.\937\
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    \937\ 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.
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(2) Proposed Factor 2 for FY 2022
    Using these data sources and the previously described 
methodologies, OACT estimates 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.
    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 are proposing to continue to apply the 
weighted average approach used in past fiscal years in order to 
estimate the rate of uninsurance for FY 2022.

[[Page 25449]]

    OACT has 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. 
We may 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. We note that any 
potential impacts from the American Rescue Plan Act are not reflected 
in the following estimates, due to the timing for the development and 
publication of the FY 2022 IPPS/LTCH proposed rule.
    The calculation of the proposed Factor 2 for FY 2022 is 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 are proposing that Factor 
2 for FY 2022 would be 72.14 percent.
    The proposed FY 2022 uncompensated care amount is 
$10,573,368,841.28* 0.7214 = $7,627,628,282.10.
[GRAPHIC] [TIFF OMITTED] TP10MY21.370

    We are inviting public comments on the proposed Factor 2 for FY 
2022.
c. Calculation of Proposed 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 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

[[Page 25450]]

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 
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

[[Page 25451]]

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 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

[[Page 25452]]

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).
    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,

[[Page 25453]]

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) Proposed 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 are now available, in time for the development of this 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, 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. We recognize that the FY 2017 reports 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), we have 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 are proposing to continue to use the low-income 
insured days proxy to calculate Factor 3 for these hospitals for one 
more year. 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. For purposes of this FY 2022 proposed rule, we 
have used a HCRIS extract updated through February 19, 2021. We note 
that we intend 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 may 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.
 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 propose to continue the 
policy first adopted in the FY 2018 rulemaking regarding the low-income 
patient proxy. Specifically, for FY 2022 we propose 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. 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.
 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.
    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 are proposing 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 are proposing 
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 are proposing 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

[[Page 25454]]

2017 IPPS/LTCH PPS final rule (81 FR 56953 through 56956).
(b) Methodology for Calculating Factor 3 for FY 2022
    For purposes of determining Factor 3 for FY 2022, we will apply 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 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.
 New Hospital for Purposes of Factor 3
    We will continue 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 where 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 
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, for FY 2022, the eligibility of a newly 
merged hospital to receive interim uncompensated care payments 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.
 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 will apply 
the following steps to determine the applicable CCR:
    Step 1: Remove Maryland hospitals. In addition, we will 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.

[[Page 25455]]

    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 this proposed 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
    After applying the CCR trim methodology, we note that 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.
    We note that 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 are proposing 
to apply a new trim specific to certain hospitals that do not have 
audited FY 2018 Worksheet S-10 data. We note 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 
are proposing 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 are proposing 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; 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 are proposing to apply this new trim in 
place of the existing UCC trim methodology. 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 propose that, for the hospitals that would be 
subject to this 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.
 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 would 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 are proposing 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 are 
proposing 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.

[[Page 25456]]

(c) Proposal Related to the 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 are proposing 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 believe computing a 3-year average with the FY 2020 discharge 
data would underestimate discharges, due to the decrease in discharges 
during the pandemic. Under this proposal, 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 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 this 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.
(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 proposed 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 would be subject 
to the proposed new trim, which is similar to the approach for new 
hospitals, which also do not have a Factor 3 published. At the time of 
development of this proposed rule, the FY 2019 SSI ratios were not 
available. Accordingly, 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. If more recent 
data become available, then we would use such data in the final rule.
    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 ten hospitals 
that would be subject to the proposed new trim, with a N/A in the 
Factor 3 column.
    Hospitals have 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). Comments 
raising issues that are specific to the information included in the 
table and supplemental data file can be submitted to the CMS inbox at 
[email protected]. All other comments submitted in response to 
our proposed policies for determining uncompensated care payments for 
FY 2022 must be submitted in one of three ways found in the ADDRESSES 
section of this proposed rule before the 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. We will 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

[[Page 25457]]

conjunction with the publication of the FY 2022 IPPS/LTCH PPS final 
rule.
    For FY 2022, we are again proposing that hospitals will 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. Any changes to Factor 3 would be 
posted on the CMS website and would be effective beginning October 1, 
2021. 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, we currently expect to use data from 
the March 2021 HCRIS extract for the FY 2022 final rule, which 
contributes to our increased confidence that hospitals would be able to 
comment on mergers and report any upload discrepancies during the 
comment period for this proposed rule. However, we also noted that we 
may 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.
    We are inviting 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.

F. Counting Days Associated With Section 1115 Demonstration Projects in 
the Medicaid Fraction

    Some States extend medical coverage benefits under a section 
1115(a) demonstration project (also referred to as a section 1115 
waiver) to populations that could not have been made eligible for 
medical assistance under the Medicaid State plan. These populations, 
commonly referred to as expansion populations or expansion waiver 
groups, are specific, finite populations defined in the waiver approval 
letters and special terms and conditions for each demonstration 
project.
    On January 20, 2000, we issued an interim final rule with comment 
period (65 FR 3136) (hereinafter, January 2000 interim final rule), 
followed by a final rule issued on August 1, 2000 (65 FR 47086 through 
47087), that changed the Secretary's policy on how to treat the patient 
days of all populations that receive medical coverage benefits under a 
section 1115 demonstration project in calculating the Medicare DSH 
adjustment. Previously, hospitals could include only the days for those 
populations receiving medical coverage benefits under a section 1115 
demonstration project who were, or could have been made, eligible for 
Medicaid under the State plan. Patient days of those expansion waiver 
groups who were not and could not be made eligible for medical 
assistance under the State plan were not to be included for purposes of 
determining Medicaid patient days in calculating the Medicare DSH 
patient percentage.
    Under the new policy adopted in the January 2000 interim final rule 
(65 FR 3137), hospitals could include in the numerator of the Medicaid 
fraction all patient days of populations eligible for Title XIX for 
which matching payment through a section 1115 expansion waiver 
demonstration project is made, whether or not those individuals were or 
could be made eligible for medical assistance under a State plan. This 
policy was effective for discharges occurring on or after January 20, 
2000. In the January 2000 interim final rule (65 FR 3137), we explained 
that allowing hospitals to include patient days for section 1115 
expansion populations in the Medicare DSH calculation is fully 
consistent with the Congressional goals of the Medicare DSH adjustment 
to recognize the higher costs to hospitals of treating low-income 
individuals covered under Medicaid.
    In the FY 2004 IPPS final rule (68 FR 45420 and 45421), we further 
revised our regulations in order to limit the types of section 1115 
waiver programs for which patient days could be counted in the 
numerator of the Medicaid fraction. We explained that in allowing 
hospitals to include patient days of section 1115 expansion waiver 
populations, our intention was to include patient days of those 
populations who, under a demonstration project, receive benefits, 
including inpatient hospital coverage benefits, that are similar to the 
benefits provided to traditional Medicaid beneficiaries. We had become 
aware, however, that certain section 1115 demonstration projects serve 
expansion populations with benefit packages so limited that the 
benefits are unlike the relatively expansive health care insurance 
coverage provided under a Medicaid State plan. We explained that these 
limited section 1115 demonstration projects extend coverage only for 
specific services and do not include insurance coverage for inpatient 
hospital care. We noted that due to the limited nature of the coverage 
provided under the section 1115 waiver, these expansion populations 
could have significantly higher incomes than traditional Medicaid 
beneficiaries. Because of the limited nature of the medical coverage 
benefits provided to expansion populations under these waivers, as 
compared to the benefits provided to the traditional Medicaid 
population under a State plan, and the possible difference in income 
levels between the expansion populations in limited benefit 
demonstrations and traditional Medicaid beneficiaries, we determined it 
was appropriate to exclude patient days of patients provided limited 
benefits under a section 1115 waiver from the determination of Medicaid 
days for purposes of the DSH calculation. Specifically, we revised the 
language of Sec.  412.106(b)(4)(i) to provide that for purposes of 
determining the Medicaid fraction, a patient is deemed eligible for 
Medicaid on a given day only if the patient is eligible for inpatient 
hospital services under an approved State Medicaid plan or under a 
section 1115 waiver. Thus, under our current regulations, hospitals are 
allowed to count patient days in the numerator of the Medicaid fraction 
only if they are days of patients eligible for inpatient hospital 
services under either a State Medicaid plan or section 1115 expansion 
waiver, who are not also entitled to benefits under Medicare Part A.
    In the FY 2004 IPPS final rule, we specifically discussed family 
planning benefits offered under a section 1115 waiver as an example of 
the kind of waiver program that should not be counted in the Medicaid 
fraction because the benefits granted to the expansion population are 
too limited and, therefore, might be offered to populations with 
significantly higher incomes. Our intention was to provide a concrete 
example of how the changes being made in the FY 2004 IPPS final rule 
would refine the Secretary's policy to allow only the days of those 
expansion waiver populations who are provided medical coverage 
benefits, and

[[Page 25458]]

specifically coverage of inpatient hospital care, like the health care 
coverage that traditional Medicaid beneficiaries receive under a State 
plan, to be included in the numerator of the Medicaid fraction of the 
Medicare DSH calculation. While we specifically discussed section 1115 
waiver family planning benefits, it was our intention that they would 
serve as an illustrative example of the kind of benefits offered 
through a section 1115 waiver program that are so limited that the 
patients receiving them should not be considered eligible for Medicaid 
for purposes of the DSH calculation.
    In 2005, the Ninth Circuit held that expansion populations receive 
care ``under the State plan'' and that, accordingly, our pre-2000 
practice of excluding them from the numerator of the Medicaid fraction 
was contrary to the plain language of the Act.\938\ Subsequently, the 
District Court for the District of Columbia reached the same 
conclusion, reasoning that if our policy of counting the days of 
expansion populations after 2000 was correct, then patients in 
expansion populations were necessarily ``eligible for medical 
assistance under a State plan'' (that is Medicaid) and the Act had 
always required their inclusion.\939\
---------------------------------------------------------------------------

    \938\ Portland Adventist Med. Ctr. v. Thompson, 399 F.3d 1091, 
1096 (9th Cir. 2005).
    \939\ Cookeville Reg'l Med. Ctr. v. Thompson, No. 04-1053, 2005 
WL 3276219, at *4-6 (D.D.C. Oct. 28, 2005).
---------------------------------------------------------------------------

    Shortly thereafter, in early 2006, Congress enacted the Deficit 
Reduction Act of 2005 (``the DRA''). Section 5002 of the DRA amended 
section 1886(d)(5)(F)(vi) of the Act to clarify our authority to 
include or exclude expansion populations from the DSH calculation, 
effectively overruling the earlier court decisions. Section 5002(a) of 
the DRA clarified that expansion populations receiving Medicaid 
benefits were not ``eligible for medical assistance under a State 
plan'' by referring to them as ``not so eligible.'' The statute made 
explicit that the Secretary nevertheless has the discretion to 
``regard'' certain expansion populations as being ``eligible for 
medical assistance under a State plan'' for the purpose of the DSH 
calculation, and to include them in the numerator of the Medicaid 
fraction ``to the extent and for the period the Secretary determines 
appropriate.'' Section 5002(b) of the DRA expressly ratified our pre-
2000 policy of not including expansion populations unless they could 
have been made eligible for Medicaid. As discussed, at the time the DRA 
was enacted, CMS ``regarded'' only a small subset of expansion 
populations as being eligible for Medicaid: Those who were eligible to 
receive inpatient hospital insurance benefits under the terms of the 
expansion waiver. In light of that history, we have not understood the 
DRA to grant CMS the authority to include in the DSH calculation any 
patient who in any way benefits from a section 1115 demonstration 
project. Rather, our authority under section 1886(d)(5)(F)(vi) of the 
Act remains limited to including expansion populations--that is, 
patients who can be ``regarded'' as ``eligible for medical assistance 
under a State plan approved under title XIX'' (that is, Medicaid) 
because they receive benefits through a section 1115 demonstration 
project that are comparable to traditional Medicaid benefits.
    More recently, section 1115 demonstration projects have been used 
to authorize the funding of uncompensated care pools that help to 
offset the burden that treating the uninsured places on hospitals. 
These pools do not extend Medicaid benefits to uninsured individuals. 
Unlike demonstration projects that expand the population of people who 
are entitled to Medicaid benefits, these pools do not provide inpatient 
health coverage directly to patients or, like insurance, make payments 
on behalf of specific, covered individuals, but rather directly benefit 
hospitals and other providers by making Medicaid funds available to 
compensate them for the otherwise uncompensated costs that they incur 
in providing medical care to the uninsured and under-insured. Making 
these funding pools available to hospitals and other providers to 
reduce their uncompensated costs advances the objective of the Medicaid 
program, as required by section 1115 of the Act, by making these 
entities more financially viable and able to continue to serve the 
Medicaid population. Indeed, these uncompensated care pools serve 
essentially the same function as Medicaid DSH payments under sections 
1902(a)(13)(A)(iv) and 1923 of the Act by indirectly subsidizing the 
cost of treating the uninsured, while not extending Medicaid benefits 
to additional populations.
    Consistent with our current policy of excluding patient days of 
individuals provided limited benefits (like family planning benefits) 
under a section 1115 expansion waiver from the numerator of the 
Medicaid fraction because the benefits they receive are too limited to 
be considered similar to Medicaid coverage, we believe it is also 
appropriate to exclude patient days for which hospitals receive payment 
from an uncompensated care pool or other similar funding source 
authorized by section 1115(a)(2). Uncompensated care pools and other 
funding streams provided to hospitals do not offer any medical coverage 
benefits directly to individuals, let alone benefits that are 
comparable to the panoply of benefits provided to traditional Medicaid 
beneficiaries under a State plan. As a result, we do not believe that 
the uninsured patients whose costs are partially offset by 
uncompensated care pools can be ``regarded'' as being eligible for 
Medicaid as required under section 1886(d)(5)(F)(vi) of the Act. 
Therefore, the patient days paid from such pools and other similar 
sources should not be included in the calculation of the Medicare DSH 
adjustment.
    Similarly, we believe the days of patients who, under a section 
1115 expansion waiver, receive premium assistance--that is, financial 
assistance that can be used to help with the purchase of health 
insurance from a private entity--should also be excluded from the DSH 
calculation. Like patients receiving only a family planning or other 
limited benefit from a demonstration project, premium assistance 
patients do not receive guaranteed health insurance coverage for 
inpatient hospital services. Rather, they receive money they can use to 
buy private health insurance that may not necessarily provide the same 
type of benefits traditional Medicaid beneficiaries receive. Moreover, 
premium assistance is usually offered on a sliding scale with 
relatively wealthy individuals receiving smaller subsidies and 
individuals with lower incomes receiving higher subsidies. As a result, 
individuals who receive premium assistance under an expansion waiver 
program may be significantly wealthier than traditional Medicaid 
beneficiaries. Because individuals receiving premium assistance as part 
of an expansion waiver do not directly receive health insurance for 
inpatient hospital services and may have higher incomes than 
traditional Medicaid beneficiaries, we do not believe the days of such 
patients are properly included in the numerator of the Medicaid 
fraction.
    Recently, however, courts have decided in a series of cases 
(Bethesda Health, Inc. v. Azar, 980 F.3d 121 (DC Cir. 2020); Forrest 
General Hospital v. Azar, 926 F.3d 221 (5th Cir. 2019); HealthAlliance 
Hosps., Inc. v. Azar, 346 F. Supp. 3d 43 (D.D.C. 2018)) that, based on 
the current language of the regulations, CMS is required to count in 
the numerator of the Medicaid fraction patient days for which hospitals 
have

[[Page 25459]]

received payment from an uncompensated care pool authorized by a 
section 1115 demonstration and the days of patients who receive premium 
assistance under a section 1115 demonstration program. These courts 
have concluded that if a hospital received payment for otherwise 
uncompensated inpatient hospital treatment of a patient, that patient 
is ``eligible for inpatient hospital services'' within the meaning of 
the current regulation. Likewise, the courts have concluded that 
patients who receive premium assistance to pay for private insurance 
that covers inpatient hospital services are ``eligible for inpatient 
hospital services'' within the meaning of the current regulation. As 
discussed previously, that was not our intent when we adopted the 
current language of the regulation, and we continue to believe that it 
is not appropriate to include patient days associated with these types 
of expansion programs in the Medicare DSH calculation because the 
benefits offered under these section 1115 demonstrations are not 
similar to traditional Medicaid benefits and may be provided to 
individuals with much higher incomes.
    In light of these court decisions, we believe it is appropriate to 
further revise our regulations to ensure that the only section 1115 
days that may be counted in the numerator of the Medicaid fraction are 
the days of patients for whom a section 1115 waiver provides inpatient 
hospital insurance coverage benefits directly to that patient on that 
day. Medicaid provides inpatient hospital insurance benefits directly 
to specific individuals. Patient days associated with a section 1115 
waiver program that does not similarly directly provide inpatient 
hospital insurance coverage to specific individuals are not comparable 
to the days of patients receiving traditional Medicaid benefits, and 
therefore, should not be counted in the numerator of the Medicaid 
fraction. Accordingly, we are proposing to revise the regulation at 
Sec.  412.106(b)(4)(i) to state explicitly that a patient is deemed 
eligible for Medicaid for the purposes of the DSH calculation on a 
given day, and the corresponding patient day is included in the 
numerator of the Medicaid fraction, only if the patient is eligible for 
inpatient hospital services under an approved State Medicaid plan that 
includes coverage for inpatient hospital care on that day or directly 
receives inpatient hospital insurance coverage on that day under a 
waiver authorized under section 1115(a)(2) of the Act. We also propose 
to remove Sec.  412.106(b)(4)(ii) in its entirety as this provision 
would no longer be needed.
    We invite comments on this proposal.

G. Hospital Readmissions Reduction Program: Proposed 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 proposed rule, we are proposing 
to update 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 from Hospital Compare to Care Compare.
3. Summary of Proposed Policies for the Hospital Readmissions Reduction 
Program
    In section V.G.5 of the preamble of this proposed rule, we are 
proposing 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. In section V.G.6 of the preamble of 
this proposed rule, we are proposing to suppress the Hospital 30-Day, 
All-Cause, Risk-Standardized Readmission Rate (RSRR) following 
Pneumonia Hospitalization measure (NQF #0506) and we provide 
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. In section V.G.8 of the preamble of this proposed rule, 
we are proposing to use the MedPAR data to determine aggregate payments 
that aligns with the applicable period for FY 2022. In section V.G.9 of 
the preamble of this proposed rule, we are proposing 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. In section 
V.G.13 of the preamble of this proposed rule, we are clarifying our 
Extraordinary Circumstances (ECE) Policy. In section V.G.14 of the 
preamble of this proposed rule, we request 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. We are also seeking 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.
    We discuss these proposals in greater detail in this proposed rule.

[[Page 25460]]

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 are proposing 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 section V.G.6 of this preamble. We are also providing 
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.
    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 this 
proposed rule, where we request 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 this proposed rule, where we request 
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. Proposed 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, 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, lower 
incentive payments in the Hospital Readmissions Reduction Program. We 
are concerned that regional and temporal differences in COVID-19 
prevalence during the FY 2022 Hospital Readmissions Reduction Program 
applicable period, which includes data collected during the PHE, have 
directly affected hospitals' readmissions measure performance for the 
FY 2022 program year. 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 are proposing 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 determine that circumstances caused 
by the COVID-19 PHE have affected those measures and the associated 
``excess readmissions'' calculations significantly. Under this proposed 
policy, if we determine that the suppression of a Hospital Readmissions 
Reduction Program measure is 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 0% in the 
program's scoring methodology until adjustments are made, the affected 
portion of the performance period for the measure is no longer 
applicable to program scoring, or the measure is

[[Page 25461]]

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 are made 
aware of the changes in performance rates that we have 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 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 believe 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 believe 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 believe 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 note 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 believe 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 a Hospital Readmissions Reduction 
Program measure for one or more program years that overlap with the PHE 
for COVID-19. We are proposing 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 believe that these Measure Suppression Factors will help us 
evaluate the Hospital Readmissions 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:
    1. 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.
    2. Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
    3. Rapid or unprecedented changes in:
    (i) Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    (ii) 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.
    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.
    We also considered alternatives to this 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 while 
those data are likely to have 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 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 and implementing it as previously specified. However, this 
alternative would mean assessing hospitals using quality measure data 
that has 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 view the measure suppression proposal as a necessity to ensure 
that the Hospital Readmissions Reduction Program does not reward or 
penalize hospitals based on factors that the Program's measures were 
not designed to accommodate. We intend for this proposed 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 invite 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 
this proposed policy.
    We are also inviting 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 request 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 request commenters' feedback on 
whether we should, rather

[[Page 25462]]

than suppress a measure completely by assigning it a 0 percent weight, 
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.
6. Proposals To 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, 
and January 7, 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 public health emergency 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 below, we have concluded that COVID-19 has severely 
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, given the ongoing status of the PHE and the impact of 
COVID-19 on this measure data, we are proposing to temporarily suppress 
this measure for the FY 2023 program year.
    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. Therefore, we are not proposing to suppress the 
five remaining condition/procedure-specific measures for the FY 2022 
program year but are updating their specifications instead. The 
measures are as follows:
     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, we are modifying 
these five condition/procedure-specific measures to exclude COVID-19 
patients from the measure denominators as technical updates to the 
measure specifications.
b. Proposal To Suppress 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 this proposed rule, we are proposing 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.\940\ Pneumonia has been 
identified as a typical characteristic of individuals infected with 
COVID-19,\941\ and our analysis based on data from CY 2020 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 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 high 
percentage of Medicare beneficiaries with a secondary diagnosis of 
COVID-19 in the measure cohort during CY 2020.
---------------------------------------------------------------------------

    \940\ CDC. ``How COVID-19 Spreads''. Available at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \941\ 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.
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    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.

[[Page 25463]]

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 are proposing 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.249

    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.
    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 note 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.\942\ We found that the suppression of the CMS 30-Day 
Pneumonia Readmission

[[Page 25464]]

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 note 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.
---------------------------------------------------------------------------

    \942\ 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 are seeking comments on our proposal to suppress the current CMS 
30-Day Pneumonia Readmission Measure (NQF #0506) for FY 2023.
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). Due to the impact of the COVID-19 PHE on the 
measures used in the Hospital Readmissions Reduction Program, as 
described previously, we are updating these five condition/procedure-
specific readmission measures to exclude COVID-19 diagnosed patients 
from the measure denominators. This technical update will modify these 
five condition/procedure-specific readmission measures to exclude 
certain ICD-10 Codes that represent patients with a 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 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). Readmissions Reduction Program are on the 
Resources web page of the QualityNet website (available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772412995).
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.\943\
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    \943\ 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.
---------------------------------------------------------------------------

    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. We remind readers that, 
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. We are not 
proposing any updates to this policy in this proposed rule.
8. Proposal To Identify 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

[[Page 25465]]

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 are 
proposing to continue to exclude admissions for patients enrolled in 
Medicare Advantage (MA), as identified in the Medicare Enrollment 
Database.
    In this proposed rule, for FY 2022, we are proposing 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.\944\ As we stated in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38232), we will determine the 
neutrality modifier using the most recently available full year of 
MedPAR data. However, we note that, for the purpose of modeling the 
proposed FY 2022 readmissions payment adjustment factors for this 
proposed rule, we are 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 2021 Hospital Readmissions Reduction Program applicable 
period (July 1, 2016 through June 30, 2019). 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).
---------------------------------------------------------------------------

    \944\ 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.
---------------------------------------------------------------------------

    In this proposed rule, we are proposing 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 are proposing 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 welcome public comment on this proposal to identify aggregate 
payments for each condition/procedure and all discharges for the FY 
2022 applicable period using corresponding MedPAR data.
9. Proposed 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 
proposed rule, we are proposing 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, we are proposing 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 propose 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 propose 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 welcome public comment on this proposal.
10. Calculation of Payment Adjustment Factors for FY 2022
    As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226),

[[Page 25466]]

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,\945\ 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.
---------------------------------------------------------------------------

    \945\ 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 are not proposing any changes to this 
payment adjustment calculation methodology for FY 2022 in this proposed 
rule.
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 are 
not proposing any changes to our calculation of payment methodology in 
this proposed rule.
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).
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 proposed 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

[[Page 25467]]

purchasing programs.\946\ 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.\947\ 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.
---------------------------------------------------------------------------

    \946\ 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.
    \947\ 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 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 will respond to those public comments in the 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/).\948\
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    \948\ We note that the QualityNet website (previously at 
QualityNet.org) has transitioned to a QualityNet.cms.gov.
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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 this 
proposed rule, we would like to clarify 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 depending on 
the type of measure, the ECE policy applies to both programs. 
Therefore, in this proposed rule 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, we are not proposing to waive the data 
submission requirements of a hospital for claims data. 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 reimbursement 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 would like to clarify that, although an 
approved ECE for the Hospital

[[Page 25468]]

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 this proposed rule, we clarify the impact of data which has 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 when 6 months 
of data are 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). 
Based on our analysis showing that there would be a minimal impact when 
6 months of data are removed from Hospital Readmissions Reduction 
Program calculations, we believe that these updates to payment 
adjustment factor components are nonsubstantive and do not 
substantially impact the Hospital Readmissions Reduction Program's 
previously finalized policies. Therefore, we would like to clarify that 
the impact of the two quarters of data that were excluded from the 
Hospital Readmissions Reduction Program due to the nationwide ECE that 
was granted in response to COVID-19 on payment adjustment factor 
components 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.\949\ As described in section IX.B of this proposed 
rule, 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,\950\ we have created 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

[[Page 25469]]

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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    \949\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \950\ 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 section IX.B.3 of this proposed rule, we are 
seeking 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 section IX.B.3 of 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.\951\ 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.
---------------------------------------------------------------------------

    \951\ 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.
---------------------------------------------------------------------------

    More specifically, we are seeking comment on expanding our efforts 
to provide hospital-level results of both the Within- and Across-
Hospital Disparity Methods, as described in section IX.B.3 of this 
proposed rule, 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.\952\ 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. Section IX.B.3 of this proposed rule also summarizes 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.\953\
---------------------------------------------------------------------------

    \952\ IOM. 2009. Race, Ethnicity, and Language Data: 
Standardization for Health Care Quality Improvement. Washington, DC: 
The National Academies Press.
    \953\ Although we are proposing to suppress the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506) in section V.G.6 of this 
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.
---------------------------------------------------------------------------

    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 section IX.B.3 of this 
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 invite 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) 
on possible 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.
15. Proposed Regulatory Updates (42 CFR 412.154)
    We are proposing to update the references to CMS resources in 
regulation text. 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 are proposing to revise our 
regulations for the Hospital Readmissions Reduction Program at 42 CFR 
412.154(f)(4) to reflect the new website name. We propose 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.'' \954\
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    \954\ 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 invite public comment on our proposal.

H. Hospital Value-Based Purchasing (VBP) Program: Proposed 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

[[Page 25470]]

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 412.167.
1. Proposed Flexibilities for the Hospital VBP Program in Response to 
the Public Health Emergency (PHE) Due to COVID-19
a. Proposed 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 are proposing 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. We are also proposing, as described 
more fully in section V.H.1.b. of this 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 are proposing to suppress, but would only calculate achievement and 
improvement scores for the measures in the Clinical Outcomes Domain, 
which we are not proposing to suppress. 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 note 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,\955\ 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.
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    \955\ 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 are proposing 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 are not proposing to adopt a special scoring and payment rule 
for that program year. Instead, the scoring and

[[Page 25471]]

payment rules we previously adopted at 42 CFR 412.160-412.165 would 
apply. The FY 2024 and FY 2025 program years also use CY 2020 data, but 
we are not proposing 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 this measure suppression proposal, 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. We believe 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 believe 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 believe 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 note 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 believe 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 are proposing 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 believe 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:
    5. 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.
    6. Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
    7. Rapid or unprecedented changes in:
    (iii) Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    (iv) 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.
    8. 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.
    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 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 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 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. We intend for this 
proposed 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 invite public comment on this proposal 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 this proposed 
policy.
    We are also inviting 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 request 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 request commenters' 
feedback on

[[Page 25472]]

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.
b. Proposals To Suppress 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 in this proposed rule. 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 are proposing to 
remove this measure from the Hospital VBP Program beginning with FY 
2023. Based on those analyses, which are discussed in more detail in 
this proposed rule, we are proposing 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 are additionally proposing 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 
proposed rule.
(2) Proposal To Suppress the Hospital Consumer Assessment of Healthcare 
Providers and Systems (HCAHPS) Survey Measure (NQF #0166) for the FY 
2022 Hospital VBP Program Year
    We are proposing 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. 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.\956\
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    \956\ 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:
    a. Official HCAHPS top-box scoring that adjusts for survey mode and 
patient mix.
    b. 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.
    c. 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.
    d. Comparisons of parallel quarters were used, for example Q1 to 
Q1, to neutralize any seasonal effects.
    Table V.H-1: Change in HCAHPS Top-Box scores in matched quarters, 
from Q1 2019 vs. Q1 2018, to Q3 2020 vs. Q3 2019.
    Each column compares data from the named quarter to data from the 
same hospitals one year earlier, thus accounting for seasonal effects 
and patient-mix adjustment.

[[Page 25473]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.250

    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 with sometimes 
>1 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 always lower than a year earlier, generally by 1-3 top-box 
points. 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 the preamble of 
this proposed rule, submission of CY 2020 Q1 and Q2 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 
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 TPSs 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 six 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 welcome public comment on our proposal to suppress the HCAHPS 
measure for the FY 2022 program year.
(3) Proposal To Suppress 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 
XX.H.1 of the preamble of this proposed rule, we are proposing 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. 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

[[Page 25474]]

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 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 welcome public comment on our proposal to suppress the MSPB 
measure for the FY 2022 program year.
(4) Proposal To Suppress the Five Healthcare-Associated Infection (HAI) 
Safety Measures for the FY 2022 Hospital VBP Program Year
    In this proposed rule, we are proposing 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 on them. 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'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 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

[[Page 25475]]

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 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 one 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 incur administrative costs on 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 are proposing to suppress all 
five HAI measures in the Safety domain for the entire FY 2022 program 
year.
    We welcome public comment on our proposal to suppress the five HAI 
measures for the FY 2022 program year.
(5) Proposal To Suppress 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 this proposed rule, we are proposing 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 SAR-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,\957\ 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.
    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

[[Page 25476]]

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 
are proposing 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.251

[GRAPHIC] [TIFF OMITTED] TP10MY21.252

    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

[[Page 25477]]

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.\958\ 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 are not proposing to make any changes to the FY 2023 scoring 
methodology as a result.
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    \958\ We note that this analysis did not include the MORT-30-
CABG measure because it is not included in the Hospital VBP Program 
until FY 2022 (81 FR 56996 through 56998).
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    We invite public comment on our proposal to suppress the MORT-30-PN 
measure for the FY 2023 program year.
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 the preamble of this proposed rule, we are proposing to 
suppress several measures in the Hospital VBP Program for the FY 2022 
Program Year. If these policies are finalized each hospital would 
receive the payment reduction for the Hospital VBP Program as required 
by statute, but every hospital would receive a value-based incentive 
payment amount that matches the payment reduction amount. However, if 
the policies in section V.H.1. of the preamble of this proposed rule 
are not finalized, the FY 2022 program year payment details would be as 
described in this section. 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. We intend to update this estimate for the FY 2022 
IPPS/LTCH PPS final rule using the March 2021 update of the FY 2020 
MedPAR file.
    As finalized in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53573 
through 53576), we would 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 would 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. Applying the 
current scoring methodology without any modifications reflecting the 
proposals in this proposed rule, we are publishing proxy value-based 
incentive payment adjustment factors in Table 16 associated with this 
proposed rule (which is available via the internet on the CMS website). 
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 PHE due to COVID-19 was declared. 
Actual TPSs for the FY 2022 program year may be more variable than the 
FY 2021 TPSs due to the impacts of the COVID-19 PHE on FY 2022 data. We 
refer readers to sections V.H.1. and V.H.6. of the preamble of this 
proposed rule for additional information on the impacts of the COVID-19 
PHE on the Hospital VBP Program. The slope of the linear exchange 
function used to calculate the proxy value-based incentive payment 
adjustment factors in Table 16 is 2.6527024687. This slope, along with 
the estimated amount

[[Page 25478]]

available for value-based incentive payments, is also published in 
Table 16.
    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 will not update Table 16 
as Table 16A in the final rule. However, if those proposals 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.
    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 will 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).
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 42 CFR 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 are not proposing any changes to these policies in this proposed 
rule.
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 are 
not proposing any changes to these policies in this proposed rule.
c. Proposed Removal of the CMS Patient Safety and Adverse Events 
Composite (CMS PSI 90) (NQF #0531) Beginning With the FY 2023 Program 
Year
    We are proposing 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. 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 maybe 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

[[Page 25479]]

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 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 are proposing 
to remove the CMS PSI 90 measure from the Hospital VBP Program 
beginning with the FY 2023 program year.
    We welcome public comment on this proposal to remove 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 the presence of a COVID-19 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. 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 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/

[[Page 25480]]

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).
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 are proposing to remove 
the CMS PSI 90 measure from the Hospital VBP Program beginning with the 
FY 2023 program year. We are also proposing 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 are not proposing to add new 
measures at this time. If these measure proposals are finalized as 
proposed, the Hospital VBP Program measure set for the FY 2022, FY 
2023, FY 2024 and FY 2025 program years would, as of now, contain the 
following measures:
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BILLING CODE 4120-01-C
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 sections V.H.3.c and 
V.H.1.b.(5). of the preamble of this proposed rule, we are proposing to 
remove the CMS PSI 90 measure and suppress the MORT-30-PN measure for 
the FY 2023 program year.
b. Proposal To Update the 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., 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 six 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 are proposing several updates to the 
baseline periods in this proposed rule for the FY 2024 program year. 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) Proposal To Update the 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 six 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 this measure (76 FR 2458). Therefore, we are proposing to 
use a baseline period of January 1, 2019 through December 31, 2019 so 
that we have a full year of data. 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 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 note 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 indicates 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 six months would result in fewer hospitals, 
especially smaller hospitals, being able to report 100 surveys for the 
performance period. We estimate 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) Proposal To Update the 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 six 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 are proposing 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. 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.
(4) Proposal To Update the 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

[[Page 25484]]

leave us with six 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 are proposing 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. 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 welcome 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.
c. Summary of Previously Adopted and Newly Proposed Baseline and 
Performance Periods for the FY 2023 Through FY 2027 Program Years
    The following tables summarize the baseline and performance periods 
that we have previously adopted and those that we are proposing to 
adopt.
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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 the preamble of this proposed rule, will not affect 
the performance standards for the FY 2022 or FY 2023 program year. 
However, as discussed in section X.H.6. of the preamble of this 
proposed rule, we are proposing 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 the

[[Page 25489]]

preamble of this proposed rule, we are proposing to remove the CMS PSI 
90 measure from the Hospital VBP Program beginning with the FY 2023 
program year. For this reason, we are not providing the estimated 
performance standards for this measure in this 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 the preamble of this proposed rule, we are proposing 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. If 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 note 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 we intend to update the 
numerical values in the FY 2022 IPPS/LTCH PPS final rule.
    The previously established and estimated 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 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 the

[[Page 25490]]

preamble of this proposed rule, we are proposing to update the FY 2024 
program year baseline period for the measure included in the Person and 
Community Engagement domain. If 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 the preamble of this proposed rule, we are proposing 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 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. 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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6. Proposed Scoring Methodology and Data Requirements
a. Proposed Scoring Methodology for the FY 2022 Program Year Due to the 
PHE for COVID-19
    As described in section V.H.1. of the preamble of this proposed 
rule, we are proposing 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 proposing that we would calculate measure 
rates for all measures in the FY 2022 program year. For measures that 
we propose to suppress, we would not use the measure rates to generate 
achievement and improvement points within the Hospitals VBP's current 
scoring methodology. We further propose 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 
propose 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., 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 are proposing 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 are proposing 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 invite public comment on these proposals.
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 are not proposing any changes to these domain weights in this 
proposed rule.
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 are not

[[Page 25494]]

proposing any changes to these domain weights in this proposed rule.
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 for the minimum numbers of 
measures for hospitals to receive domain scores. We are not proposing 
any changes to these policies in this proposed rule.
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 are not proposing any changes to these policies in 
this proposed rule.
(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] TP10MY21.266

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 are not proposing any changes to these policies in this 
proposed rule.
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

[[Page 25495]]

(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 (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 the preamble of this proposed 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.
(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.\959\ 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.\960\ 
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.
---------------------------------------------------------------------------

    \959\ 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.
    \960\ 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.
---------------------------------------------------------------------------

(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 will respond to those public comments in the FY 2022 IPPS/
LTCH PPS final rule.
8. Proposal To Revise Existing Code of Federal Regulations (CFR) 
Language by Replacing the Term ``System Administrator'' With the Term 
``Security Official''
    We are proposing 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 are proposing 
in section IX.A.8.c.(2). of this proposed rule 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 welcome public comment on this proposal to replace the term 
``QualityNet System Administrator'' with ``QualityNet security 
official'' in our regulation text.
9. Proposal 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, we are proposing to update 
regulation text to reflect changes made to CMS resources. Specifically, 
we are proposing 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.
    We welcome public comment on this proposal to update references to 
CMS resources in our regulation text.
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

[[Page 25496]]

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.202F; 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 the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41440 through 41472) for more information about how the Hospital VBP 
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 this proposed rule, 
where we request 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 
proposed rule, where we request 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 Conditions (HAC) Reduction Program: Proposed 
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 Proposed Updates to the HAC Reduction Program and 
Requests for Information
    In section IX.I.3.c. of this proposed rule, we propose to adopt a 
cross-program measure suppression policy and in section IX.I.3.d. we 
propose to suppress third and fourth quarter CY 2020 CMS PSI 90 and CDC 
NHSN HAI measure data from the HAC Reduction Program. In section 
IX.I.7. of this proposed rule, we clarify some aspects of the 
Extraordinary Circumstances Exception (ECE) policy. In section IX.I.9. 
of this proposed rule, we propose 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.
    We also refer readers to section IX.B. of this proposed rule, 
Closing the Health Equity Gap in CMS Quality Programs--A Request for 
Information, where we request 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. 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 this proposed rule where 
we request 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 25497]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.267

    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 this proposed rule, we are not proposing 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 this proposed rule, 
we are not proposing any measure removal and retention factor policy 
changes.
c. Proposed 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 and FY 2023 
performance periods, which include data collected during the PHE, may 
directly affect hospitals' HAC measure performance for the FY 2022 and 
FY 2023 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.
    Therefore, we are proposing 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. Under this proposed policy, if we 
determine that the suppression of a HAC Reduction Program measure is 
warranted for a

[[Page 25498]]

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 0% weight for any 
suppressed measures in the Total HAC Score calculation. We would also 
provide confidential feedback reports to hospitals on their FY 2022 and 
FY 2023 performance to ensure that they are made aware of the changes 
in performance rates that we have observed. We would also publicly 
report the FY 2022 and FY 2023 data with appropriate caveats noting the 
limitations of the data due to the PHE for COVID-19.
    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 believe 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 believe 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 believe 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 note 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 believe 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 are 
proposing 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 believe 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:
    1. 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.
    2. Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
    3. Rapid or unprecedented changes in:
    i. Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ii. 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.
    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.
    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, implementation of the FY 
2022 and FY 2023 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 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 intend for this proposed 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 HAC Reduction Program's measures.
    We invite 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 have developed for purposes of this 
proposed policy.
    We are also inviting 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 request comment on whether we should in future 
years consider adopting

[[Page 25499]]

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 request 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.
d. Proposal To Suppress Third and Fourth Quarter CY 2020 Data From the 
FY 2022 and FY 2023 HAC Reduction Program
    In section IX.I.3.c., we proposed to adopt a measure suppression 
policy. We are proposing 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.'' 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.
    As described in more detail in section IX.B.7.a., 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 
are therefore proposing 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 believe 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 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 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 and FY 2023 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.
    We believe using data from the proposed periods will provide 
sufficiently reliable data for evaluating hospital performance that we 
can use for FY 2022 and FY 2023 scoring. 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 50712). Further, as we have 
previously noted, NQF has 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

[[Page 25500]]

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 
note 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).
    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. However, 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. In addition, an analysis revealed that smaller and rural 
hospitals would be more negatively impacted by this approach.
    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 has 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 believe 
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 invite 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.
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 this proposed rule, we 
are not proposing 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 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] TP10MY21.268

    We are not proposing any changes to the policies regarding measure 
validation in this proposed rule.
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    \961\ 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

[[Page 25501]]

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.
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 proposed 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.\962\ 
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.\963\ In that memorandum, we stated that 
qualifying 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 calendar 
year (CY) 2019, first quarter CY 2020 and second quarter CY 2020.
---------------------------------------------------------------------------

    \962\ 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.
    \963\ 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 the COVID-19 
PHE
    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 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. We will respond to those public comments in 
the 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 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

[[Page 25502]]

QualityNet website (https://www.qualitynet.cms.gov/).\964\
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    \964\ 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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    In section IX.I.3.d., as previously mentioned, we propose to 
suppress third and fourth quarter CY 2020 data from FY 2022 and FY 2023 
Total HAC Scores using the measure suppression policy proposed in 
IX.I.3.c.
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 proposed 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 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 proposed 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 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. We are 
performing additional analyses as CY 2020 data becomes available, and 
we will provide updated analyses as necessary when it becomes 
available.
    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 nonsubstantive and do not substantially impact the HAC 
Reduction Program's previously finalized policies. 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. Proposed Regulatory Updates (42 CFR 412.172)
    We are proposing 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 are proposing to revise our 
regulations for the HAC Reduction Program at 42 CFR 412.172(f)(4) to 
reflect the new website name. We propose 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.'' \965\ We invite 
public comment on our proposal.
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    \965\ 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. Proposed 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

[[Page 25503]]

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 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 provide detailed proposals for 
implementing these three CAA provisions in this rule.
a. Distribution of Additional Residency Positions Under the Provisions 
of Section 126 of Division CC of the Consolidated Appropriations Act, 
2021 (CAA)
(1) Overview
    Section 126(a) of the CAA amended section 1886(h) of the Act by 
adding a new section 1886(h)(9) requiring the distribution of 
additional residency positions to qualifying hospitals. Section 
1886(h)(9)(A) requires that for FY 2023, and for each succeeding fiscal 
year until the aggregate number of full-time equivalent (FTE) residency 
positions distributed is equal to 1,000, the Secretary shall initiate 
separate rounds of applications from hospitals for these additional 
residency positions. The Secretary is required, subject to certain 
provisions in the law, to increase the otherwise applicable resident 
limit for each qualifying hospital that submits a timely application by 
the number of positions that may be approved by the Secretary for that 
hospital. The Secretary is required to notify hospitals of the number 
of positions distributed to them by January 31 of the fiscal year of 
the increase, and the increase is effective beginning July 1 of that 
fiscal year. Section 1886(h)(9)(A) also limits the aggregate number of 
such positions made available in a single fiscal year across all 
hospitals to no more than 200.
    In determining the qualifying hospitals for which an increase is 
provided, section 1886(h)(9)(B) of the Act requires the Secretary to 
take into account the demonstrated likelihood of the hospital filling 
the positions made available within the first five training years 
beginning after the date the increase would be effective, as determined 
by the Secretary.
    Section 1886(h)(9)(B) also requires a minimum distribution for 
certain categories of hospitals. Specifically, the Secretary is 
required to distribute at least 10 percent of the aggregate number of 
total residency positions available to each of four categories of 
hospitals. Stated briefly, and discussed in greater detail later in 
this proposed rule, the categories are as follows: (1) Hospitals 
located in rural areas or that are treated as being located in a rural 
area (pursuant to sections 1886(d)(2)(D) and 1886(d)(8)(E) of the Act); 
(2) hospitals in which the reference resident level of the hospital is 
greater than the otherwise applicable resident limit; (3) hospitals in 
states with new medical schools or additional locations and branches of 
existing medical schools; and (4) hospitals that serve areas designated 
as Health Professional Shortage Areas (HPSAs). Section 
1886(h)(9)(F)(ii) of the Act defines a qualifying hospital as a 
hospital in one of these four categories.
    Section 1886(h)(9)(C) of the Act places certain limitations on the 
distribution of the residency positions. First, a hospital may not 
receive more than 25 additional FTE residency positions. Second, no 
increase in the otherwise applicable resident limit of a hospital may 
be made unless the

[[Page 25504]]

hospital agrees to increase the total number of FTE residency positions 
under the approved medical residency training program of the hospital 
by the number of positions made available to that hospital.
(2) Determinations Required for the Distribution of Residency Positions
(a) Determination That a Hospital has a Demonstrated Likelihood of 
Filling the Positions
    Section 1886(h)(9)(B)(i) of the Act directs the Secretary to take 
into account the demonstrated likelihood of the hospital filling the 
positions made available within the first 5 training years beginning 
after the date the increase would be effective, as determined by the 
Secretary. Section 1886(h)(9)(A)(iii)(II) of the Act requires that the 
increase would be effective beginning July 1 of the fiscal year of the 
increase. For FY 2023, this means the additional positions would be 
effective July 1, 2023.
    As discussed later in this section, we are proposing that the 
application deadline for the additional positions available for a 
fiscal year be January 31 of the prior fiscal year. Accordingly, for FY 
2023, all references in section V.J.2.a of this proposed rule to the 
application deadline are references to the proposed application 
deadline of January 31, 2022. We are proposing that a hospital would 
show a demonstrated likelihood of filling the additional positions 
(sometimes equivalently referred to as slots) for which it applies by 
demonstrating that it does not have sufficient room under its current 
FTE resident cap(s) to accommodate a planned new program or expansion 
of an existing program.
    In order to demonstrate that it does not have sufficient room under 
its current FTE resident cap(s), we are proposing that a hospital 
submit copies of its most recently submitted Worksheets E, Part A and 
E-4 from the Medicare cost report CMS-Form-2552-10) as part of its 
application for an increase to its FTE resident cap.
    We are proposing that a hospital demonstrate and attest to a 
planned new program or expansion of an existing program by meeting at 
least one of the following two criterion:
     Demonstrated Likelihood Criterion 1 (New Residency 
Program). The hospital does not have sufficient room under its FTE 
resident cap, and the hospital intends to use the additional FTEs as 
part of a new residency program that it intends to establish on or 
after the date the increase would be effective (that is, a new program 
that begins training residents at any point within the hospital's first 
five training years beginning on or after the date the increase would 
be effective). Under Demonstrated Likelihood Criterion 1, the hospital 
would be required to check at least one of the following as part of its 
application:
    [ballot] Application for approval of the new residency program has 
been submitted to the ACGME or the American Board of Medical 
Specialties (ABMS) by the application deadline for that year.
    [ballot] The hospital has submitted an institutional review 
document or program information form concerning the new residency 
program in an application for approval of the new program by the 
application deadline for that year.
    [ballot] The hospital has received written correspondence by the 
application deadline for that year from the ACGME or ABMS acknowledging 
receipt of the application for the new residency program, or other 
types of communication from the accrediting bodies concerning the new 
program approval process (such as notification of site visit).
     Demonstrated Likelihood Criterion 2 (Expansion of an 
Existing Residency Program). The hospital does not have sufficient room 
under its FTE resident cap, and the hospital intends to use the 
additional FTEs to expand an existing residency training program within 
the hospital's first five training years beginning on or after the date 
the increase would be effective. Under Demonstrated Likelihood 
Criterion 2, the hospital would be required to check at least one of 
the following as part of its application:
    [ballot] The hospital has approval by the application deadline from 
an appropriate accrediting body (the ACGME or ABMS) to expand the 
number of FTE residents in the program.
    [squ] The hospital has submitted by the application deadline an 
institutional review document or program information form for the 
expansion of the existing residency training program.Under Demonstrated 
Likelihood Criterion 2, the hospital would be applying for an increase 
in its FTE resident cap because it is expanding an existing residency 
program. We are proposing this means that as of the application 
deadline the hospital is either already training residents in this 
program, or, if the program exists at another hospital as of that date, 
the residents begin to rotate at the applying hospital on or after the 
effective date of the increase.We note that section 1886(h)(9)(C)(ii) 
of the Act requires that if a hospital is awarded positions, that 
hospital must increase the number of its residency positions by the 
amount the hospital's FTE resident caps are increased based on the 
newly awarded positions under section 126 of CAA. We are proposing that 
a hospital must, as part of its application, attest to increase the 
number of its residency positions by the amount the hospital's FTE 
resident caps are increased based on any newly awarded positions.
(b) Determination of Hospitals That Are Located in a Rural Area or Are 
Treated as Being Located in a Rural Area (Category One)
    Section 1886(h)(9)(B)(ii) of the Act requires the Secretary to 
distribute not less than 10 percent of resident positions available for 
distribution to each of four categories of hospitals. Under section 
1886(h)(9)(B)(ii)(I) of the Act, the first of these categories consists 
of hospitals that are located in a rural area (as defined in section 
1886(d)(2)(D) of the Act) or are treated as being located in a rural 
area pursuant to section 1886(d)(8)(E) of the Act. We refer to this 
category as Category One.
    Section 1886(d)(2)(D)(ii) of the Act defines a rural area as any 
area outside a Metropolitan Statistical Area (MSA). Under the existing 
regulations at Sec.  412.64(b)(1)(ii), an ``urban area'' means an MSA 
or a Metropolitan Division (in the case where a Metropolitan 
Statistical Area is divided into Metropolitan Divisions), as defined by 
the Executive Office of Management and Budget. Under existing Sec.  
412.64(b)(1)(ii)(C), a ``rural area'' means any area outside an urban 
area. Since FY 2005, we no longer use the term MSA, but instead use the 
term Core-Based Statistical Area (CBSA). Certain CBSAs are designated 
as urban, while those not designated as urban are considered rural. For 
purposes of Section 1886(h)(9)(B)(ii), we are proposing that a hospital 
with its main campus located in an area outside of an urban CBSA is a 
rural hospital. We note that this definition of ``rural area'' is 
consistent with our policy concerning designation of rural areas for 
wage index purposes.
    Similar to our historical wage index policy of crosswalking 
counties to CBSAs as discussed in section III.A.4. of this proposed 
rule, CMS is proposing to use the County to CBSA Crosswalk and Urban 
CBSAs and Constituent Counties for Acute Care Hospitals File, or 
successor files containing similar information, from the most recent FY 
IPPS final rule (or correction notice if applicable) to determine if a 
hospital is a rural hospital. (This file would be available on the CMS 
website in

[[Page 25505]]

approximately August of the year prior to the year of the application 
deadline. Under the file's current format, blank cells in Columns F and 
G indicate an area outside of a CBSA.)
    Under section 1886(d)(8)(E) of the Act, a subsection (d) hospital 
(that is, generally, an IPPS hospital) that is physically located in an 
urban area is treated as being located in a rural area for purposes of 
payment under the IPPS if it meets criteria specified in section 
1886(d)(8)(E)(ii) of the Act, as implemented in the regulations at 
Sec.  412.103. Under these regulations, a hospital may apply to CMS to 
be treated as located in a rural area for purposes of payment under the 
IPPS.Given the fixed number of available residency positions, it is 
necessary to establish a deadline by which a hospital must be treated 
as being located in a rural area for purposes of Category One. We are 
proposing to use Table 2, or a successor table containing similar 
information, posted with the most recent IPPS final rule (or correction 
notice if applicable) to determine whether a hospital is reclassified 
to rural under Sec.  412.103. If a hospital is not listed as 
reclassified to rural on Table 2, but has been subsequently approved by 
the CMS Regional Office to be treated as being located in a rural area 
for purposes of payment under the IPPS as of the application deadline 
for additional positions for the fiscal year, we are proposing that the 
hospital must submit its approval letter with its application in order 
to be treated as being located in a rural area for purposes of Category 
One.
(c) Determination of Hospitals for Which the Reference Resident Level 
of the Hospital Is Greater Than the Otherwise Applicable Resident Limit 
(Category Two)
    Under section 1886(h)(9)(B)(ii)(II), the second category consists 
of hospitals in which the reference resident level of the hospital (as 
specified in section 1886(h)(9)(F)(iii)) is greater than the otherwise 
applicable resident limit. We refer to this category as Category Two.
    Under section 1886(h)(9)(F)(iii), the term `reference resident 
level' means, with respect to a hospital, the resident level for the 
most recent cost reporting period of the hospital ending on or before 
the date of enactment of section 1886(h)(9), December 27, 2020, for 
which a cost report has been settled (or, if not, submitted (subject to 
audit)), as discussed in this proposed rule.
    Under section 1886(h)(9)(F)(iii), the term `resident level' has the 
meaning given such term in paragraph (7)(C)(i). That section defines 
``resident level'' as with respect to a hospital, the total number of 
full-time equivalent residents, before the application of weighting 
factors (as determined under paragraph (4)), in the fields of 
allopathic and osteopathic medicine for the hospital.
    Under section 1886(h)(9)(F)(i), the term `otherwise applicable 
resident limit' means, with respect to a hospital, the limit otherwise 
applicable under subparagraphs (F)(i) and (H) of paragraph (4) on the 
resident level for the hospital determined without regard to the 
changes made by this provision of CAA 2021, but taking into account 
section 1886(h)(7)(A), (7)(B), (8)(A), and (8)(B) of the Act. These 
paragraphs all address the distribution of positions and redistribution 
of unused positions.
    In the CY 2011 OPPS final rule, we previously interpreted these 
terms when we implemented section 5503 of the Affordable Care Act. 
Under section 1886(h)(8)(H)(i) (as interpreted in the CY 2011 OPPS 
final rule (75 FR 46391)), the ``reference resident level'' generally 
refers to the number of unweighted allopathic and osteopathic FTE 
residents who are training at a hospital in a given cost reporting 
period. That is, the ``reference resident level'' refers to a 
hospital's allopathic and osteopathic FTE resident count for a specific 
period. The definition can vary based on what calculation is being 
performed to determine the correct allopathic and osteopathic FTE 
resident count (see, for example, 42 CFR 413.79(c)(1)(ii)). As noted 
previously, section 126 of the CAA, under new section 
1886(h)(9)(F)(iii) defines the ``reference resident level'' as coming 
from the most recent cost reporting period of the hospital ending on or 
before the date of enactment of the CAA (that is, December 27, 2020).
    Under new section 1886(h)(9)(F)(i), the term ``otherwise applicable 
resident limit'' is defined as ``the limit otherwise applicable under 
subparagraphs (F)(i) and (H) of paragraph (4) on the resident level for 
the hospital determined without regard to this paragraph but taking 
into account paragraphs (7)(A), (7)(B), (8)(A), and (8)(B).'' We 
propose to define this as the hospital's 1996 cap during its reference 
year, adjusted for the following: New programs as defined at Sec.  
413.79(e); participation in a Medicare GME affiliation agreement as 
defined at Sec. Sec.  413.75(b) and 413.79(f); participation in an 
Emergency Medicare GME affiliation agreement as defined at Sec.  
413.79(f); participation in a hospital merger; whether an urban 
hospital has a separately accredited rural training track program as 
defined at Sec.  413.79(k); applicable decreases or increases under 
section 422 of the MMA, applicable decreases or increases under section 
5503 of the Affordable Care Act, and applicable increases under section 
5506 of the Affordable Care Act.
    Regarding the term `resident level', in the CY 2011 OPPS final rule 
(75 FR 46391) we indicated that we generally refer to a hospital's 
number of unweighted allopathic and osteopathic FTE residents in a 
particular period as the hospital's resident level, which we propose to 
define consistently with the definition in section 126 of the CAA; that 
is, the ``resident level'' under section 1886(h)(7)(c)(i), which is 
defined as the total number of full-time equivalent residents, before 
the application of weighting factors (as determined under paragraph 
(4)), in the fields of allopathic and osteopathic medicine for the 
hospital.
    For the purposes of section 126 of the CAA we are proposing that 
the definitions of the terms ``otherwise applicable resident level,'' 
``reference resident level,'' and ``resident level'' be as similar as 
possible to the definitions those terms have in the regulations at 
Sec.  413.79(c) as developed in the CY 2011 OPPS rulemaking.
(d) Determination of Hospitals Located in States With New Medical 
Schools, or Additional Locations and Branch Campuses (Category Three)
    The third category specified in section 1886(h)(9)(B)(ii) of the 
Act, as added by section 126 of CAA, consists of hospitals located in 
States with new medical schools that received `Candidate School' status 
from the Liaison Committee on Medical Education (LCME) or that received 
`Pre-Accreditation' status from the American Osteopathic Association 
(AOA) Commission on Osteopathic College Accreditation (the COCA) on or 
after January 1, 2000, and that have achieved or continue to progress 
toward `Full Accreditation' status (as such term is defined by the LCME 
or toward `Accreditation' status (as such term is defined by the COCA); 
or additional locations and branch campuses established on or after 
January 1, 2000, by medical schools with `Full Accreditation' status 
(as such term is defined by LCME) or `Accreditation' status (as such 
term is defined by the COCA). We note that the statutory language is 
specific with respect to these definitions. We refer to this category 
as Category Three.
    Based on research and assistance received from LCME and the COCA, 
we understand that each accrediting body administers a multi-step 
processes for applicant medical schools to progress to

[[Page 25506]]

fully accredited status within the first few years after they are 
established and begin training students. LCME grants candidate status 
to an applicant medical education program after it reviews and approves 
the medical school's data collection instrument and planning self-
study; at this point, it determines that the school is ready for a 
survey visit, and the preliminary accreditation survey visit is 
scheduled. After that visit, LCME reviews the survey team's preliminary 
survey report and determines whether or not sufficient progress toward 
compliance with accreditation standards has been made and satisfactory 
plans for the medical education program have been developed.
    If LCME grants preliminary accreditation status, the school may 
begin accepting applications for enrollment. During the second year of 
the school's charter class, a school with preliminary accreditation 
status may submit information and receive a survey site visit to 
determine whether it meets criteria for provisional accreditation 
status. Finally, LCME grants full accreditation status to schools with 
provisional accreditation status, typically in the fourth teaching 
year, after determining the school is in compliance with or has made 
significant progress toward attaining compliance with all full 
accreditation standards.
    LCME defines a regional campus, comparable to ``additional 
locations and branch campuses'' in Section 1886(h)(9)(B)(ii)(III)(bb) 
of the Act, as a site distinct from the main campus of the medical 
school where students spend at least one full year of the curriculum. 
Regional campuses of a medical education program receive accreditation 
status through the main campus of the program and are not separately 
accredited.
    The COCA may grant pre-accreditation status to a proposed college 
of osteopathic medicine (COM) that has achieved candidate status and 
meets the standards of pre-accreditation status. The pre-accreditation 
process starts with the submission of a pre-accreditation self-study by 
a proposed COM; COCA staff then reviews the submission and conducts a 
site visit to examine the proposed COM's compliance with accreditation 
standards. Following the site visit, the COCA reviews the site visit 
report and other submitted information and grants pre-accreditation 
status to a proposed COM that meets the pre-accreditation standards. 
Once a proposed COM receives pre-accreditation status, it may begin to 
recruit, accept applications from, and admit prospective students. We 
note that prior to 2017, the COCA used the term ``provisional status'' 
instead of ``pre-accreditation status.''
    The COCA may grant accreditation status to a COM that has achieved 
pre-accreditation status and meets the standards for accreditation. 
These accreditation statuses include accreditation with exceptional 
outcome, accreditation, accreditation with heightened monitoring, 
accreditation with warning, and accreditation with probation. Any 
accreditation status constitutes full accreditation, in contrast to 
pre-accreditation status or candidate status, which do not constitute 
full accreditation status.
    The COCA defines a branch campus as a geographically separate 
location apart from the COM's main campus that is: Permanent in nature; 
offers courses in educational programming leading to a doctorate in 
osteopathic medicine; has its own faculty and administrative or 
supervisory organization; and maintains its own budgetary and hiring 
authority. A COM that establishes a branch location must apply for and 
receive separate approval from the COCA; the application process has 
four steps: A written application and branch campus self-study, a 
progress report, a revised branch campus self-study and site visit, and 
a final, pre-operational site visit.
    The COCA defines an additional location as a location that is 
geographically separate from the main campus of a COM, but unlike a 
branch location, shares administration, faculty, curriculum, and 
budgetary authority with the main campus. Additional locations receive 
accreditation through the main campus of the COM following the review 
of documents and a survey site visit, after which a COM may enroll 
students in the additional location.
    Based on information gathered from LCME and the COCA about new 
medical schools, additional locations and branch campuses, we are 
proposing that hospitals located in the following 35 states and one 
territory, referred to as Category Three states, are Category Three 
hospitals: Alabama, Arizona, Arkansas, California, Colorado, 
Connecticut, Delaware, Florida, Georgia, Idaho, Illinois, Indiana, 
Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Mississippi, 
Missouri, Nevada, New Jersey, New Mexico, New York, North Carolina, 
Ohio, Oklahoma, Pennsylvania, Puerto Rico, South Carolina, Tennessee, 
Texas, Utah, Virginia, Washington, West Virginia, and Wisconsin. If a 
hospital is located in a State not listed here, but believes the State 
in which it is located should be on this list, the hospital may submit 
a formal comment on this proposed rule to make a change to this list, 
or must provide documentation with submission of its application to CMS 
that the State in which it is located has a medical school or 
additional location or branch campus of a medical school established on 
or after January 1, 2000. Pursuant to the statutory language, all 
hospitals in such states are eligible for consideration; the hospitals, 
themselves, do not need to meet the conditions of section 
1886(h)(9)(B)(ii)(III)(aa) or (bb) of the Act in order to be 
considered.
(e) Determination of Hospitals That Serve Areas Designated as Health 
Professional Shortage Areas Under Section 332(a)(1)(A) of the Public 
Health Service Act (Category Four)
    The fourth category specified in the law consists of hospitals that 
serve areas designated as health professional shortage areas under 
section 332(a)(1)(A) of the Public Health Service Act (PHSA), as 
determined by the Secretary. We refer to this category as Category 
Four.The Health Resources and Services Administration (HRSA) designates 
certain areas as health professional shortage areas (HPSAs). Section 
332(a)(1)(A) of the Public Health Service Act (PHSA), states that a 
``health professional shortage area'' is an area in an urban or rural 
area (which need not conform to the geographic boundaries of a 
political subdivision and which is a rational area for the delivery of 
health services) which the Secretary determines lacks sufficient health 
care providers to meet the health care needs of that area's population. 
HRSA designates HPSAs for primary care, mental health, and dental 
health.
    A geographic area may be designated as a HPSA under section 
332(a)(1)(A) of the PHSA only on the basis of a shortage of services 
for the entire population within that area (a ``geographic HPSA''). 
Subsequent clauses of 332(a)(1) refer to other types of HPSAs, to which 
we will return later in this proposed rulemaking. The geographic area 
to which a geographic HPSA is assigned may be a single county, multiple 
counties, a county subdivision, or a census tract.
    Section 126 of the CAA does not explicitly address the question of 
how HPSAs for different medical specialties should factor into 
determining which hospitals serve areas designated as HPSAs. In our 
consideration of this question, we began by examining the use of HPSAs 
in the HPSA Physician Bonus Program authorized under section 1833(m) of 
the Act. This program is relevant to our belief, because Congress 
established the program as an incentive to attract new

[[Page 25507]]

physicians to medically underserved communities and to encourage 
physicians in those areas to remain there (69 FR 47517 through 47518).
    The HPSA Physician Bonus Program was created by Section 4043 of the 
Omnibus Budget Reconciliation Act (OBRA) of 1987, which added section 
1833(m) to the Act. It provides incentive payments to physicians who 
furnish services to an individual in an area that is designated as a 
HPSA. Originally, under section 1833(m) of the Act, a 5 percent payment 
was added, beginning January 1, 1989, to the amounts otherwise payable 
to physicians who furnish services to Medicare patients in designated 
HPSAs. Section 6102 of OBRA 1989 further amended section 1833(m) of the 
Act to raise the amount of this incentive payment from 5 percent to 10 
percent for services furnished after December 31, 1990. The OBRA 1989 
amendment also expanded eligible service areas to include both rural 
and urban HPSAs.
    We first examined the role of primary care geographic HPSAs in the 
HPSA Physician Bonus program. Physicians furnishing services in a 
primary care geographic HPSA are eligible to receive the bonus payments 
and the payments apply to all physicians who perform covered services 
within a primary care geographic HPSA, regardless of specialty. 
Similarly, section 126 of the CAA does not explicitly distinguish 
between physician specialties for purposes of allocating the additional 
residency positions. Therefore, we are proposing that primary care 
geographic HPSAs be considered in determining what hospitals qualify 
under Category Four and that hospitals that have main campuses or 
provider-based facilities in these HPSAs may apply for additional 
residency positions for any specialty. We also note CMS used primary 
care HPSAs for the allocation of residency positions for purposes of 
section 5503 of the ACA (75 FR 72147).
    We next considered the use under the HPSA Physician Bonus Program 
of areas that are solely mental health geographic HPSAs and not also 
primary care geographic HPSAs. We will refer to these areas as mental 
health only geographic HPSAs. The HPSA Physician Bonus Program provides 
incentive payments for services provided in mental health only 
geographic HPSAs, but only for services provided by psychiatry provider 
specialties. The distinction between primary care geographic HPSAs, in 
which all physician provider specialties, including psychiatry provider 
specialties, receive the incentive payments, and mental health only 
geographic HPSAs, in which only psychiatry provider specialties receive 
the incentive payments, is relevant to the question of how mental 
health geographic HPSAs should factor into determining hospitals that 
serve areas designated as HPSAs for purposes of section 126 of the CAA. 
We believe that it is appropriate to incorporate this feature of the 
HPSA Physician Bonus Program as well, and propose to use mental health 
only geographic HPSAs for mental health providers accordingly in the 
determination of hospitals that serve areas designated as HPSAs. Thus, 
we are proposing that hospitals that only have main campuses or 
provided-based facilities in mental health only geographic HPSAs may 
only apply for residency positions for psychiatry residency programs.
    We next considered dental geographic HPSAs. 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 allopathic 
and osteopathic 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 the same cost reporting period is applied effective for 
discharges occurring on or after October 1, 1997. Given that dental 
residents are not included in this statutory cap and that section 126 
of the CAA distributes additional residency positions in the context of 
the statutory cap, we are not proposing that dental geographic HPSAs 
factor into the determination of whether a hospital serves a HPSA for 
purposes of section 126.
    In summary, we are proposing to consider geographic HPSAs for 
primary care and mental health providers for purposes of determining 
hospitals that serve areas designated as HPSAs. We are proposing that 
hospitals that only have campuses or provider-based facilities in 
mental health only geographic HPSAs may only apply for positions for 
psychiatry residency programs. We are not proposing to consider dental 
HPSAs as dental FTE residents are not subject to a hospital's IME and 
direct GME caps.
    We next considered what hospitals serving areas designated as 
primary care or mental health HPSAs means for purposes of Category 
Four. As with the question regarding the role of primary care, mental 
health, and dental HPSAs, section 126 of the CAA does not explicitly 
address this question.
    There are many possible interpretations of what hospitals that 
serve areas designated as primary care or mental health HPSAs means for 
purposes of Category Four. The most expansive interpretation might be 
that this refers to the universe of hospitals where each hospital 
provides care to at least one patient that resides in a HPSA without 
regard to the location of the main campus of the hospital or of its 
other patient care locations. This interpretation could be made less 
expansive by developing a relative or absolute threshold for the number 
of patients of the hospital that reside in HPSAs. It could also be made 
less expansive by considering whether the physical location of the main 
campus of the hospital and/or its other patient care locations are 
inside of or proximate to a HPSA.
    In considering this issue, we prioritized objective factors that 
would maximize distribution of GME positions to residency programs 
serving underserved populations. See section V.J.2.a.4. for a further 
discussion of prioritizing care to underserved populations.) To this 
end, we propose that a hospital is qualified under Category Four if it 
has its main campus or a provider-based facility (under 42 CFR 413.65) 
physically located in a primary care or mental health geographic HPSA. 
Additionally, as part of the qualification requirements under Category 
Four, in the residency program for which the hospital is applying, at 
least 50 percent of the residents training time over the duration of 
the program must occur at those locations in the HPSA. We believe it is 
important to avoid the possibility that a hospital with provider-based 
facilities in multiple locations, some of which may not be located in a 
HPSA, uses an additional residency position mostly or entirely to serve 
populations that face no health service shortage.
    A Category Four hospital must submit an attestation, signed and 
dated by an officer or administrator of the hospital who signs the 
hospital's Medicare cost report that it has its main campus or a 
provider-based facility (under 42 CFR 413.65) physically located in a 
primary care or mental health geographic HPSA, and in the program for 
which the hospital is applying, at least 50 percent of the residents' 
training time over the duration of the program occurs at those 
locations in the HPSA.
    For example, Hospital A applies under Category Four for a 
psychiatry residency program. Its main campus is located in a non-HPSA 
area and it has one provider-based facility located in a mental health 
only geographic HPSA. Hospital A must attest that residents training in 
the psychiatry residency

[[Page 25508]]

program spend at least 50 percent of the duration of their training in 
the program at its provider-based facility located in the mental health 
only geographic HPSA. As another example, Hospital B applies for a 
residency program. Its main campus is located in a primary care 
geographic HPSA and it has two provider-based facilities, one in the 
same geographic HPSA as the main campus and one in a non-HPSA area. 
Hospital B must attest that residents training in the program will 
spend at least 50 percent of the duration of their training in the 
program on the main campus or at the provider-based facility located in 
the geographic HPSA, combined (for example, 30 percent of the time on 
the main campus and 20 percent at the provider-based facility).
(f) Determination of Qualifying Hospitals
    Section 1886(h)(9)(F)(ii) defines a qualifying hospital as a 
hospital described in any of the subclauses (I) through (IV) of 
subparagraph (B)(ii). In other words, a qualifying hospital is a 
Category One, Category Two, Category Three, or Category Four hospital, 
or one that meets the definitions of more than one of these categories.
(3) Number of Residency Positions Made Available to Hospitals and 
Limitation on Individual Hospitals
(a) Number of Residency Positions Made Available to Hospitals
    Section 1886(h)(9)(A)(ii)(II) limits the aggregate number of total 
residency positions made available in a single fiscal year across all 
hospitals to no more than 200. In order to provide these additional 
residency positions to hospitals as quickly as possible, we are 
proposing to make 200 residency positions available for FY 2023 and 
each subsequent year.
(b) Limitation on Individual Hospitals
    We expect the demand from hospitals for the aggregate number of 
total residency positions made available for each fiscal year to 
significantly exceed the 200 maximum. For example, there are currently 
over 300 teaching hospitals that have their main campus located in a 
primary care or mental health HPSA. We expect the majority of these 
hospitals would apply for additional residency positions because they 
would qualify under our proposed Category Four. Even if we were to 
exclusively allocate the maximum 200 positions permitted under the 
statute each year to these hospitals, which are only a subset of 
Category Four hospitals and Category Four itself is only one of four 
categories, it would still be insufficient to award even 1.0 FTE to 
each hospital each year. Therefore, in order to make additional 
residency positions available to more hospitals each year, we are 
proposing to limit the increase in the number of residency positions 
made available to each individual hospital to no more than 1.0 FTE each 
year. We note that this is not 1.0 FTE for each program at a hospital 
each year, it is 1.0 FTE for each hospital each year.
    As noted earlier, section 1886(h)(9)(C) places certain limitations 
on the distribution of the residency positions, one of which is that a 
hospital may not receive more than 25 additional FTE residency 
positions. Under our proposed 1.0 FTE limitation, no hospital would 
receive more than 25 additional FTE residency positions.
(4) Prioritization of Applications From Hospitals for Residency 
Programs That Serve Underserved Populations
(a) Use of Geographic HPSAs and Population HPSAs
    The Executive Order on ``Ensuring an Equitable Pandemic Response 
and Recovery'' noted that the COVID-19 pandemic has exposed and 
exacerbated severe and pervasive health and social inequities in 
America (see https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/21/executive-order-ensuring-an-equitable-pandemic-response-and-recovery/.)
    In order to help address these exposed health inequities longer 
term, we believe that it would be appropriate to prioritize the 
applications from hospitals that will use the additional residency 
positions under section 126 of the CAA in residency programs serving 
underserved populations.This prioritization is already partially 
reflected in our proposed Category Four, where we discussed maximizing 
the number of GME positions distributed to residency programs serving 
underserved populations in geographic HPSAs designated by HRSA under 
PHSA section 332(a)(1)(A). However, under PHSA section 332(a)(1)(B), 
HRSA also designates HPSAs on the basis of a shortage of services for a 
specific subset of the population (``population HPSAs'') rather than 
the entire population in an area as is the case in geographic HPSAs. 
These population subsets include, but are not limited to: Low-income 
populations, Medicaid-eligible population, Native American populations, 
homeless populations, and migrant farmworker populations. (For 
information on the location and types of population HPSAs see https://data.hrsa.gov/tools/shortage-area/hpsa-find).
    In order to more fully address health inequities for underserved 
populations, we believe that it also would be appropriate to prioritize 
the applications from hospitals that serve the specific designated 
underserved population of a population HPSA.
    We have already discussed our proposed definition in Category Four 
of hospitals that serve the populations of geographic HPSAs. Similar to 
that approach, we propose that a hospital serves a population HPSA if 
it has its main campus or a provider-based facility (under 42 CFR 
413.65) physically located in a primary care or mental health 
population HPSA, and any such locations serve the designated 
underserved population of that HPSA. Additionally, as part of the 
qualification requirements under Category Four, in the residency 
program for which the hospital is applying, at least 50 percent of the 
residents' training time over the duration of the program must occur at 
those locations in the HPSA. As with geographic HPSAs, we believe it is 
important to avoid the possibility that a hospital with provider-based 
facilities in multiple locations, some of which may not be located in a 
population HPSA or serve the designated population of that HPSA, uses 
an additional residency position mostly or entirely to serve 
populations that face no health service shortage.
    Also similar to our proposed use of geographic HPSAs, we are 
proposing that hospitals that only have main campuses or provider-based 
facilities in mental health only population HPSAs may only apply for 
position for a psychiatry residency programs.Under our proposal, a 
hospital must submit an attestation, signed and dated by an officer or 
administrator of the hospital who signs the hospital's Medicare cost 
report that it has its main campus or a provider-based facility (under 
42 CFR 413.65) physically located in a primary care or mental health 
population HPSA, any such locations serve the designated underserved 
population of that HPSA, and in the program for which the hospital is 
applying at least 50 percent of the residents' training time over the 
duration of the program occurs at those locations in the HPSA.
    We recognize that our proposed approach for population-based HPSAs 
means that we potentially would be awarding a residency position for 
the provision of care that is not exclusively provided to the 
designated underserved population for which the shortage exists. 
However, in the context of our proposal discussed in this proposed rule

[[Page 25509]]

to use HPSA scores to prioritize applications by the severity of the 
shortages, our proposal to limit the number of additional residency 
positions awarded to 1.0 FTE per hospital each year, and our proposal 
that at least 50 percent of the training time over the duration of the 
program occur at locations in the HPSA that serve the designated 
underserved population of that HPSA, we believe it is sufficient for 
the residents in a program to provide care to the designated 
underserved population of that HPSA, and it is not necessary for 
residents to provide care exclusively to that population.
    We note that HRSA also designates certain facilities as HPSAs, 
either through an application process or on the basis of regulation or 
statute, under PHSA section 223(a)(1)(C). The process for facility HPSA 
designation is dissimilar from that for geographic and population 
HPSAs. Further, a HPSA score for a facility does not reflect on the 
adequacy of the health care workforce outside that facility in a 
geographic area, and so it is not comparable to geographic or 
population HPSAs. Therefore, we are not proposing to use facility HPSA 
designations for the purposes of this rulemaking.
    We also note that there are teaching hospitals that may not have 
facilities in areas designated as geographic or population HPSAs, but 
that under its Medicare provider agreement operate one or more 
facilities that serve areas for which there exists a shortage of 
providers. If this is the case, we recommend that a hospital interested 
in applying for FTE resident cap positions under this section contact 
its State or territorial Primary Care Office (PCO). HRSA maintains 
cooperative agreements with the 54 State and territorial PCOs, which 
conduct needs assessments and submit applications to HRSA to designate 
areas as HPSAs. We refer interested parties to 42 CFR part 5 and 57 FR 
2473 for information on procedures for HPSA designation for primary 
care and mental health HPSAs, respectively.
    In summary, we propose to prioritize applications from qualifying 
hospitals (that is, hospitals that qualify under categories One through 
Four, as previously described), for residency programs that serve 
underserved populations in geographic HPSAs or population HPSAs. In the 
next section we discuss our proposed use of HPSA scores for this 
purpose.
(b) Use of HPSA Scores for Prioritization
    HRSA assigns HPSA scores on a scale of 0 to 25 as a measure of the 
severity of a primary care or mental health provider shortage in a 
geographic area, with higher scores indicating a more severe health 
professional shortage. Using HPSA scores to differentiate applications 
from hospitals that qualify under categories One through Four would 
allow us to optimize the use of the limited number of additional 
residency positions under section 126 of the CAA and best address 
health inequities by focusing those residency positions on underserved 
populations with the most need.
    In preparing its application for an additional residency position 
for a program, hospitals should refer to HRSA's HPSA Find Tool (https://data.hrsa.gov/tools/shortage-area/hpsa-find) to obtain the HPSA score 
of the HPSA served by the program and include this score in its 
application. A HPSA is served by a program if that program meets the 
requirements discussed earlier. Given our proposal to limit the 
additional positions awarded to individual hospitals to 1.0 FTE for any 
given year, we are proposing that a hospital may not submit more than 
one application in any fiscal year. Given the limited number of 
residency positions available and the number of hospitals we expect to 
apply, we expect that a hospital would choose to apply for a program 
that serves the HPSA with the highest score among its programs, but a 
hospital is not required to do so.
    We would allocate 1.0 FTE to each hospital with the highest HPSA 
score, prorating only in the event that the number of hospitals with 
the highest score exceeds the number of residency positions available. 
If the number of hospitals with the highest score is less than the 
number of residency positions available, each hospital with the next 
highest score would receive 1.0 FTE, with proration again occurring 
only in the event that the number of hospitals with this score exceeds 
the number of positions remaining. We would continue in this manner, 
moving on to hospitals with the next highest score until all available 
positions are distributed. We note that hospitals applying for 
residency positions for programs that do not serve HPSAs are not 
categorically excluded, but those applications would have the lowest 
priority.
    As an illustrative example, assume the following hospitals apply, 
Hospitals A through HV. Assume there are 200 additional residency 
positions available. We propose that Hospitals A through ET would each 
get 1.0 FTE, while Hospitals EU through HV would each get a prorated 
FTE award of 0.625, as follows:
[GRAPHIC] [TIFF OMITTED] TP10MY21.269

    In summary, under our proposal, additional residency positions 
under section 126 of the CAA will be distributed to hospitals that 
qualify under categories One through Four based on the HPSA score of 
the HPSA served by the residency program for which each hospital is 
applying, with programs serving higher HPSA scores receiving higher 
prioritization. Hospitals applying for residency positions for programs 
that do not serve HPSAs are not categorically excluded, but those 
applications would have the lowest priority.
(5) Alternative Considered for Prioritization
    As alterative to our proposed prioritization approach, we 
considered a simpler prioritization approach for FY 2023 that would 
allow additional time to work with stakeholders to develop a more 
refined approach for future years. Under this alternative approach, CMS

[[Page 25510]]

would distribute 200 additional residency positions for FY 2023 among 
hospitals that qualify in Category One, Category Two, Category Three, 
and/or Category Four, with higher priority given to applications from 
hospitals that qualify in more categories. Hospitals that qualify under 
all four categories would receive top priority, hospitals that qualify 
under any three of the four categories would receive the next highest 
priority, then any two of the four categories, and finally hospitals 
that qualify under only one category. We would distribute 1.0 FTE to 
each hospital that qualified under all four categories, prorating only 
in the event that the number of hospitals that qualified under all four 
categories exceeds 200. If the number of hospitals that qualified under 
all four categories is less than 200, each hospital that qualified 
under three out of four categories would receive 1.0 FTE, with 
proration again occurring only in the event that the number of 
hospitals that qualified under three out of four categories exceeds the 
number of positions remaining. We would continue in this manner, moving 
on to hospitals that qualified under two out of four and one out of 
four categories until all 200 positions are distributed.
    We seek comment on this alternative prioritization approach 
considered to allow for additional time to work with stakeholders to 
develop a more refined approach for future years.
(6) Distributing At Least 10 Percent of Positions to Each of the Four 
Categories
    Section 1886(h)(9)(B)(ii) of the Act requires the Secretary to 
distribute at least 10 percent of the aggregate number of total 
residency positions available to each of the following categories of 
hospitals discussed earlier: Category One, Category Two, Category 
Three, and Category Four.
    We believe that because it is possible for a hospital to be 
eligible for distribution of additional residency positions via more 
than one of the four categories, Category One, Two, Three or Four, 
there is a strong likelihood that by prioritizing applications by HPSA 
score the result will be that 10 percent or more of the additional 
residency positions will be distributed to hospitals in each of the 
four categories. We propose to collect information regarding 
qualification for all four categories in applications to allow us to 
track progress in meeting all statutory requirements, and evaluate the 
need to modify the distribution methodology in future rulemaking.
(7) Hospital Attestation to National CLAS Standards
    In order to ensure that the residents are educated and trained in 
culturally and linguistically appropriate policies and practices, we 
propose that all applicant hospitals would be required to attest that 
they meet the National Standards for Culturally and Linguistically 
Appropriate Services in Health and Health Care (the National CLAS 
Standards). By requiring attestation by hospitals that training 
programs meet CLAS standards, CMS would ensure the section 126 
additional residency position allocation broadens the availability of 
quality care and services to all individuals, regardless of preferred 
language, cultures, and health beliefs. (For more information on the 
CLAS standards, please refer to https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=2&lvlid=53).
(8) Payment for and Aggregation of Additional FTE Residency Positions 
Awarded Under Section 126 of the CAA
    Section 1886(h)(9)(D) requires that CMS pay a hospital for 
additional positions awarded under this paragraph using the hospital's 
existing direct GME PRAs for primary care and OB/GYN programs and non-
primary care programs consistent with the regulations at Sec.  413.77. 
However, similar to our implementation of section 5503 in the CY 2011 
OPPS final rule (75 FR 72192) with respect to the application of direct 
GME PRAs for primary care and nonprimary care residents, for the 
implementation of section 126 of the CAA, we are proposing that a 
hospital that receives additional positions under section 126 would be 
paid for FTE residents counted under those positions using the same 
primary care and nonprimary PRAs for which payment is made for FTE 
residents subject to the 1996 FTE cap. We are expecting to revise 
Worksheet E-4 to add a line on which hospitals would report the number 
of FTEs by which the hospital's FTE caps were increased for direct GME 
positions received under section 126.
(9) Conforming Regulation Amendments for 42 CFR 412.105 and 42 CFR 
413.79
    Section 126 of the CAA, under clause (b), amends section 
1886(d)(5)(B) of the Act to provide for increases in FTE resident 
positions for IME payment purposes as well. Specifically, a new section 
1886(d)(5)(B)(xii) is added to state that for discharges occurring on 
or after July 1, 2023, if additional payment is made for FTE resident 
positions distributed to a hospital for direct GME purposes under 
section 1886(h)(9), the hospital will receive appropriate IME payment 
based on the additional residency positions awarded using the same IME 
adjustment factor used for the hospital's other FTE residents. We are 
proposing conforming amendments to the IME regulations at 42 CFR 
412.105 to specify that effective for portions of cost reporting 
periods beginning on or after July 1, 2023, a hospital may qualify to 
receive an increase in its otherwise applicable FTE resident cap if the 
criteria specified in 42 CFR 413.79(p) are met.
    We are also proposing to amend our regulations at 42 CFR 413.79 to 
codify our proposal to specify that--(1) for portions of cost reporting 
periods beginning on or after July 1, 2023, a hospital may receive an 
increase in its otherwise applicable FTE resident cap (as determined by 
CMS) if the hospital meets the requirements and qualifying criteria 
under section 1886(h)(9) of the Act and if the hospital submits an 
application to CMS within the timeframe specified by CMS; and (2) FTE 
resident cap positions added under section 126 of Public Law 116-260 
may be used in a Medicare GME affiliation agreement beginning in the 
5th year after the effective date of those FTE resident cap positions.
(10) Prohibition on Administrative and Judicial Review
    Section 126 of the CAA, under clause (c), prohibits review of 
section 1886(h)(9) of the Act. Specifically, it amends section 
1886(h)(7)(E) of the Act by inserting ``paragraph (9),'' after 
``paragraph (8),''. Therefore, we are proposing that the determinations 
and distribution of residency positions under sections section 
1886(d)(5)(B)(xii) and 1886(h)(9) of the Act are final without 
administrative or judicial review.
(11) Report by the Comptroller General
    We note here for reference that section 126(d) of the CAA requires 
the Comptroller General of the United States to conduct a study and 
submit to Congress two reports on section 126 of the CAA, after the 5-
year period of implementation is complete.
(12) Application Process for Receiving Increases in FTE Resident Caps
    In order for hospitals to be considered for increases in their FTE 
resident caps, each qualifying hospital must submit a timely 
application. We are proposing that an application be considered timely 
for additional residency positions effective July 1 of fiscal year if 
it is completely submitted by January 31 of

[[Page 25511]]

the prior fiscal year. The following information must be submitted on 
an application to be considered completely submitted:
     The name and Medicare provider number of the hospital.
     The name of the Medicare contractor to which the hospital 
submits its Medicare cost report.
     The residency program for which the hospital is applying 
to receive an additional position.
     FTE resident counts for direct GME and IME and FTE 
resident caps for direct GME and IME reported by the hospital in the 
most recent as-filed cost report. (Including copies of Worksheets E, 
Part A, and E-4).
     If the hospital qualifies under Demonstrated Likelihood 
Criterion 1 (New Residency Program), which of the following applies:
    [ballot] Application for approval of the new residency program has 
been submitted to the ACGME or the American Board of Medical 
Specialties (ABMS) by the application deadline for that year.
    [ballot] The hospital has submitted an institutional review 
document or program information form concerning the new residency 
program in an application for approval of the new program by the 
application deadline for that year.
    [ballot] The hospital has received written correspondence by the 
application deadline for that year from the ACGME or ABMS acknowledging 
receipt of the application for the new residency program, or other 
types of communication from the accrediting bodies concerning the new 
program approval process (such as notification of site visit).
     If the hospital qualifies under Demonstrated Likelihood 
Criterion 2 (Expansion of an Existing Residency Program), which of the 
following applies:
    [ballot] The hospital has approval by the application deadline from 
an appropriate accrediting body (the ACGME or ABMS) to expand the 
number of FTE residents in the program.
    [ballot] The hospital has submitted by the application deadline an 
institutional review document or program information form for the 
expansion of the existing residency training program.
     Identification of the category that describes the hospital 
under section 126 of Division CC of the Consolidated Appropriations 
Act, 2021 (per section 1886(h)(9)(F)(ii) of the Social Security Act):
    [ballot] (I) The hospital is located in a rural area (as defined in 
section 1886(d)(2)(D) of the Social Security Act) or are treated as 
being located in a rural area pursuant to section 1886(d)(8)(E) of the 
Social Security Act.
    [ballot] (II) The reference resident level of the hospital (as 
specified in section 1886(h)(9)(F)(iii) of the Social Security Act) is 
greater than the otherwise applicable resident limit.
    [ballot] (III) The hospital is located in a State with a new 
medical school (as specified in section 1886(h)(9)(B)(ii)(III)(aa) of 
the Act), or with additional locations and branch campuses established 
by medical schools (as specified in section 1886(h)(9)(B)(ii)(III)(bb) 
of the Act) on or after January 1, 2000.
    [ballot] (IV) The hospital serves areas designated as health 
professional shortage areas (HPSAs) under section 332(a)(1)(A) of the 
Public Health Service Act, as determined by the Secretary.
     The HPSA (if any) served by the residency program for 
which the hospital is applying and the HPSA score for that HPSA.
     An attestation, signed and dated by an officer or 
administrator of the hospital who signs the hospital's Medicare cost 
report, of the following:
    ``I hereby certify that the hospital is a Qualifying Hospital under 
section 126 of Division CC of the Consolidated Appropriations Act, 2021 
(per section 1886(h)(9)(F)(ii) of the Social Security Act).
    ``I hereby certify the demonstrated likelihood that the hospital 
will fill the position made available under section 126 of Division CC 
of the Consolidated Appropriations Act, 2021 within the first 5 
training years beginning after the date the increase would be 
effective, as determined by the Secretary (per section 1886(h)(9)(B)(i) 
of the Social Security Act).
    ``I hereby certify that the hospital agrees to increase the number 
of its residency positions by the amount the hospital's FTE resident 
caps are increased under section 126 of Division CC of the Consolidated 
Appropriations Act, 2021, if awarded positions (per section 
1886(h)(9)(C)(ii) of the Social Security Act).
    ``I hereby certify that if the residency program for which the 
hospital is applying serves a geographic or population Health 
Professional Shortage Area (HPSA), that the hospital has its main 
campus or a provider-based facility (under 42 CFR 413.65) physically 
located in that HPSA, any such locations serve the designated 
underserved population of that HPSA in the case of a population HPSA, 
and in the residency program for which the hospital is applying, at 
least 50 percent of the residents training time over the duration of 
the program occurs at those locations in the HPSA.
    ``I hereby certify that the hospital meets the National Standards 
for Culturally and Linguistically Appropriate Services in Health and 
Health Care (the National CLAS Standards).
    ``I hereby certify that I understand that misrepresentation or 
falsification of any information contained in this application may be 
punishable by criminal, civil, and administrative action, fine and/or 
imprisonment under Federal law. Furthermore, I understand that if 
services identified in this application were provided or procured 
through payment directly or indirectly of a kickback or where otherwise 
illegal, criminal, civil, and administrative action, fines and/or 
imprisonment may result. I also certify that, to the best of my 
knowledge and belief, it is a true, correct, and complete application 
prepared from the books and records of the hospital in accordance with 
applicable instructions, except as noted. I further certify that I am 
familiar with the laws and regulations regarding Medicare payment to 
hospitals for the training of interns and residents.''
    The completed application must be submitted to CMS using an online 
application system under development. A link to the online application 
system as well as instructions for accessing the system and completing 
the online application process will be made available on the CMS DGME 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/DGME when the FY 2022 IPPS/LTCH PPS final 
rule goes on display.
    We note that the burden associated with this information collection 
requirement is the time and effort necessary to review instructions and 
register for the electronic submission system as well as the time and 
effort to gather, develop and submit various documents associated with 
a formal request of resident slot increases from teaching hospitals to 
CMS. The aforementioned burden is subject to the Paperwork Reduction 
Act (PRA); and as discussed in section XII.B.5., the burden associated 
with these requests will be discussed in a forthcoming information 
collection request, which is currently under development.
    We are soliciting comments on our proposals to implement section 
126 of the CAA to help address health inequities and prioritize 
applications from hospitals that will use the additional positions in 
residency programs serving underserved populations.

[[Page 25512]]

b. Proposal for Implementation of Section 127 of the CAA, ``Promoting 
Rural Hospital GME Funding Opportunity''
    To encourage the training of residents in rural areas, section 
407(c) of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement 
Act of 1999 (Pub. L. 106-113) (BBRA) amended section 1886(h)(4)(H) of 
the Act to add a provision (subsection (iv)) stating that, in the case 
of a hospital that is not located in a rural area (an urban hospital) 
that establishes separately accredited approved medical residency 
training programs (or rural tracks) in a rural area, or has an 
accredited training program with an integrated rural track, the 
Secretary shall adjust the urban hospital's cap on the number of FTE 
residents under subsection (F), in an appropriate manner in order to 
encourage training of physicians in rural areas. Section 407(c) of 
Public Law 106-113 was effective for direct GME payments to hospitals 
for cost reporting periods beginning on or after April 1, 2000, and for 
IME payments applicable to discharges occurring on or after April 1, 
2000. We refer readers to the August 1, 2000 interim final rule with 
comment period (65 FR 47026, 47033 through 47037) and the FY 2002 IPPS 
final rule (66 FR 39828, 39902 through 39909) where we implemented 
section 407(c) of Public Law 106-113. The regulations for establishing 
rural track FTE limitations are located at 42 CFR 413.79(k) for direct 
GME and at 42 CFR 412.105(f)(1)(x) for IME.
    In the August 1, 2003 IPPS final rule (68 FR 45456 through 45457), 
we clarified our existing policy that although the rural track 
provision allows an increase to the urban hospital's FTE cap, sections 
1886(h)(4)(H)(iv) and 1886(d)(5)(B) of the Act do not provide for an 
exclusion from the rolling average for the urban hospital for those FTE 
residents training in a rural track. These provisions are interpreted 
to mean that, except for new rural track programs begun by urban 
teaching hospitals that are establishing an FTE cap for the first time, 
when an urban hospital with an FTE resident cap establishes a new rural 
track program or expands an existing rural track program, FTE residents 
in the rural track that are counted by the urban hospital are included 
in the hospital's rolling average calculation immediately. This policy 
is reflected in the regulation at Sec.  412.105(f)(1)(v)(F) for IME and 
Sec.  413.79(d)(7) for direct GME, and applies for IME and direct GME 
to cost reporting periods beginning on or after April 1, 2000.
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57027), we finalized 
a revision to the regulations at Sec.  413.79(k) (and which, in turn, 
affect IME adjustments under Sec.  412.105(f)(1)(x)) to permit that, in 
the first 5 program years (rather than the first 3 program years) of 
the rural track's existence, the rural track FTE limitation for each 
urban hospital would be the actual number of FTE residents training in 
the rural training track at the urban hospital, and beginning with the 
urban hospital's cost reporting period that coincides with or follows 
the start of the sixth program year of the rural training track's 
existence, the rural track FTE limitation would take effect. However, 
as previously stated, due to the statutory language at sections 
1886(d)(5)(B) and 1886(h)(4)(H)(iv) of the Act as implemented in our 
regulations at Sec. Sec.  412.105(f)(1)(v)(F) and 413.79(d)(7), except 
for new rural track programs begun by urban teaching hospitals that are 
establishing an FTE cap for the first time, FTE residents in a rural 
training track (RTT) program at the urban hospital are subject 
immediately to the 3-year rolling average for direct GME and IME. In 
addition, under the regulations at Sec.  412.105(a)(1)(i), no exception 
to the IME intern- and resident-to-bed (IRB) ratio cap is provided for 
residents in a rural track training program (except for new rural track 
programs begun by urban teaching hospitals that are establishing an FTE 
cap for the first time).
    Since implementation of the rural training track provision from the 
BBRA of 1999, stakeholders and advocates of residency training in rural 
areas have raised concerns about inequities and unintended consequences 
of the BBRA provision. First, the BBRA provision allows an urban 
hospital to receive additional cap slots based on the time that 
residents in the RTT train at the urban hospital. However, the 
provision does not specify that the Secretary provide a cap adjustment 
for rural hospitals participating in RTTs. As a result, unless the RTT 
program was new, the rural hospital could not receive FTE resident cap 
increases, resulting in direct GME and IME payments going only to the 
urban hospital for the urban portion of the training, with no attending 
funding going to the rural hospital for the rural portion of the 
training. Second, the statutory provision does not specify that the 
Secretary may provide a cap adjustment to urban hospitals or rural 
hospitals when an urban hospital adds additional rural locations to 
already existing RTTs. Third, the provision stated that the Secretary 
would adjust the caps of an urban hospital that establishes separately 
accredited approved medical residency training programs (or rural 
tracks) in a rural area. Historically, the Accreditation Council for 
Graduate Medical Education (ACGME) has separately accredited family 
medicine programs in the ``1-2 format'' (meaning, residents in the 1-2 
format receive their first year experience at a core family medicine 
program in an urban area, and their second and third year experiences 
at another site, which may or may not be rural). Because the ACGME has 
only accredited family medicine programs in the 1-2 format, CMS 
interpreted the provision to mean that hospitals cannot seek funding 
opportunities for rural tracks developed in specialties other than 
family medicine. Fourth, residents added to a RTT were previously not 
exempt from the 3-year rolling average for IME and direct GME. We 
believe that section 127 of the CAA remedies each of these concerns, 
explained in more detail in this proposed rule.
(i) Cap Adjustment for Urban and Rural Hospitals Participating in Rural 
Training Track Programs
    As amended by the BBRA, section 1886(h)(4)(H)(iv) of the Act 
provided for IME and direct GME FTE resident cap adjustments for an 
urban hospital that establishes separately accredited rural tracks; 
however, the statute did not provide for a similar adjustment to rural 
hospitals participating in rural tracks. Specifically, section 
1886(h)(4)(H)(iv) refers to the case of a hospital that is not located 
in a rural area but establishes separately accredited approved medical 
residency training programs (or rural tracks) in a rural area. Because 
of this explicit incentive and permission for FTE resident cap 
adjustments for an urban hospital that establishes a rural track, the 
rural track does not need to be new for Medicare payment purposes, as 
it otherwise would in order for the urban hospital to qualify for the 
FTE resident cap adjustments. That is, under section 1886(h)(4)(H)(iv) 
of the Act, if an urban hospital already had an accredited family 
medicine residency program, it could establish from that existing 
family medicine program, for the first time, a rural track, and, 
assuming all applicable requirements are met, that urban hospital could 
receive IME and direct GME FTE resident cap adjustments. However, with 
regard to a rural hospital participating in the second and third years 
of training in the rural track, since the BBRA language did not mention 
cap adjustments to rural hospitals, only if the program is new for 
Medicare

[[Page 25513]]

payment purposes can the rural teaching hospital also receive a FTE 
resident cap adjustment for the program. (Under Sec.  413.79(e)(3), any 
time that a rural hospital participates in training residents in a new 
program, the rural hospital may receive an increase to its FTE resident 
caps. We refer readers to the FY 2010 IPPS/LTCH PPS final rule for the 
criteria identifying a new program for Medicare payment purposes (74 FR 
43908 through 43917)). In this case, a rural track established from an 
already existing urban family medicine program would not meet the 
newness requirement for the rural hospital. Consequently, Division CC, 
section 127 of the CAA 2021 revised section 1886(h)(4)(H)(iv) of the 
Act to state that in the case of a hospital not located in a rural area 
that established or establishes a medical residency training program 
(or rural tracks) in a rural area, the Secretary must adjust in an 
appropriate manner the limitation under subparagraph (F) for such 
hospital and each such hospital located in a rural area that 
participates in such a training. This revision provides for cap 
adjustments for both the urban teaching hospital and the rural teaching 
hospital(s). We are proposing that each time an urban hospital and 
rural hospital establish a RTT program for the first time, even if the 
RTT program does not meet the newness criteria for Medicare payment 
purposes, both the urban and rural hospitals may receive a rural track 
FTE limitation. For example, Urban Hospital A has an existing internal 
medicine program. In July 2023, it partners with Rural Hospital 1 to 
create a RTT from the existing internal medicine program. We are 
proposing that both Urban Hospital A and Rural Hospital 1 may receive 
adjustments to their resident caps (rural track FTE limitations) to 
reflect their portions of FTE residents training in the RTT. We propose 
to make various changes throughout the regulations text at 42 CFR 
413.79(k) ``Residents training in rural track programs'' to accommodate 
the rural track FTE limitations for both urban and rural hospitals. We 
also provide examples in this proposed rule, regarding how the rural 
track FTE limitations are calculated, according to the same methodology 
already in place at 42 CFR 413.79(k)(1) and as previously explained in 
the FY 2017 IPPS/LTCH PPS final rule (81 FR 57028).
(ii) Cap Adjustments When the Urban Hospital Adds Additional Rural 
Training Tracks
    As previously stated, under section 1886(h)(4)(H)(iv) prior to 
enactment of the CAA, if an urban hospital already had an accredited 
family medicine residency program, it could, for the first time, 
establish a rural track from that existing family medicine program and, 
assuming all applicable requirements were met, such hospital could 
receive the IME and direct GME FTE resident cap adjustments. Because 
section 1886(h)(4)(H)(iv) gave this explicit permission for FTE 
resident cap adjustments to an urban hospital that establishes a rural 
track, the rural track program does not need to be new for Medicare 
payment purposes in order for the urban hospital to qualify for the FTE 
resident cap adjustments. (We refer readers to the FY 2010 IPPS/LTCH 
PPS final rule for the criteria identifying a new program for Medicare 
payment purposes (74 FR 43908 through 43917)). However, after 
establishing its first RTT, the urban hospital can receive a rural 
track limitation adjustment for additional established RTTs only if 
those additional programs are ``new'' for Medicare payment purposes. We 
believe that section 127 of the CAA amends section 1886(h)(4)(H)(iv) 
such that it permits us to adjust the resident caps of an urban 
hospital wishing to create additional RTTs after establishing its first 
RTT, while also adjusting the residents caps of the rural hospital(s) 
added by creating the subsequent RTTs. Section 127 of the CAA amends 
section1886(h)(4)(H)(iv) of the Act to add a new subclause which states 
that for cost reporting periods beginning on or after October 1, 2022, 
in the case of a hospital not located in a rural area that established 
or establishes a medical residency training program (or rural tracks) 
in a rural area . . . adjust in an appropriate manner the limitation 
under subparagraph (F) for such hospital and each such hospital located 
in a rural area that participates in such a training. Because the law 
now states ``established or establishes,'' both past tense and future 
tense, we believe the statute grants the Secretary unique authority not 
previously held; that is, the authority to prospectively allow (under 
certain circumstances) cap adjustments to existing RTTs expanded in a 
cost reporting period beginning on or after October 1, 2022. That is, 
the provision gives explicit permission to adjust the RTT limitations 
of an urban hospital wishing to create additional RTTs after 
establishing its first RTT, while also adjusting the residents caps of 
the additional rural hospital(s) added by creating the second (or 
third, etc.) RTT. We believe this new statutory authority is separate 
and distinct from the statute's requirement that, for IME and direct 
GME payment purposes, caps can be adjusted only for new teaching urban 
hospitals and for rural hospitals with new programs under section 
1886(h)(4)(H)(i) of the Act. That is, in general, urban hospitals 
becoming teaching hospitals for the first time and rural hospitals may 
receive cap adjustments only if the program(s) in which they train 
residents is ``new'' in accordance with Medicare rules (as explained in 
detail at 74 FR 43908 through 43917). Therefore, under the explicit 
authority under section 127 of the CAA, we are proposing to 
prospectively allow increases to the IME and direct GME caps of both 
the participating urban and rural hospitals that expand a qualifying 
RTT. We are proposing that if, in a cost reporting period beginning on 
or after October 1, 2022, an urban hospital with an existing RTT 
(``hub'') adds an additional RTT (``spoke'') to the existing urban core 
program of the same specialty, the urban and rural hospitals may 
receive adjustments to their rural track FTE limitation. (For ease of 
reference, we are referring to the urban core hospital as the ``hub'' 
and the one or more RTTs as the ``spokes'' associated with that urban 
``hub.'') For example, Urban Hospital A has an existing family medicine 
program. In 2015, Urban Hospital A partnered with Rural Hospital 1 to 
create a RTT from the existing family medicine program and received 
rural track FTE limitation to reflect the time that residents training 
in the RTT spent at its facility. In July 2023, Urban Hospital A 
partners with Rural Hospital 2 in a different rural area of the State, 
to create an additional family medicine RTT (adding another ``spoke'' 
to the existing urban program ``hub.'') We are proposing that both 
Urban Hospital A and Rural Hospital 2 may receive adjustments to their 
resident caps (rural track FTE limitations) to reflect the portion of 
the time that FTE residents in the second family medicine RTT ``spoke'' 
spend at their respective facility. We believe that allowing 
prospective adjustments to RTT FTE limitations for additional RTT 
``spokes'' added in cost reporting periods beginning on or after 
October 1, 2022 is an efficient means of addressing rural healthcare 
workforce shortages, by allowing already experienced and successful 
urban ``hub'' RTTs to branch out and partner with additional rural 
communities, rather than relying solely on starting RTTs from scratch. 
That is, with the ability for CMS to provide funding for additional 
spokes, it should be easier for urban hospitals that already have one 
RTT to reach rural areas more quickly and efficiently with the addition

[[Page 25514]]

of more spokes, rather than starting brand new ``hubs''. However, we 
are proposing to limit the increases to the urban and rural hospitals' 
RTT FTE limitations only in the instance where additional residents are 
recruited to add a new rural ``spoke'' RTT, and not to allow increases 
to the RTT FTE limitations in the instance where the urban and rural 
hospital add additional FTE residents to an existing rural RTT 
``spoke.'' We believe it is appropriate to do so because section 127 of 
the CAA states that in the case of a hospital not located in a rural 
area that established or establishes a medical residency training 
program (or rural tracks) in a rural area or establishes an accredited 
program where greater than 50 percent of the program occurs in a rural 
area, the Secretary shall consistent with the principles of 
subparagraphs (F) and (G) and subject to paragraphs (7) and (8), 
prescribe rules for the application of such subparagraphs with respect 
to such a program and, in accordance with such rules, adjust in an 
appropriate manner the limitation under subparagraph (F) for such 
hospital and each such hospital located in a rural area that 
participates in such a training. That is, the statute directs the 
Secretary to adjust the cap (the limitation under subparagraph (F)) in 
an appropriate manner. We believe that ``appropriate'' means not 
rendering the RTT FTE limitations meaningless. If we would allow 
adjustments to the RTT FTE limitations at any time, for any type or any 
amount of expansion even to already existing rural site ``spokes,'' 
there would, in essence, not be any RTT FTE limitation at all. As a 
matter of public policy, as long as the FTE resident caps (that is, the 
``limitation under subparagraph (F)'') are in place, we believe that 
CMS should be judicious with providing for additional funded cap slots, 
as that, in turn, encourages thoughtful residency program expansion 
among hospital stakeholders. Therefore, we are proposing to limit the 
provision of an increase to the urban and rural hospitals' RTT FTE 
limitations only to the instance where additional residents are 
recruited to add a new rural RTT ``spoke'' to the existing urban 
``hub'', and not to allow increases under this section to the RTT FTE 
limitations in the instance where the urban and rural hospital add 
additional FTE residents to an existing rural RTT ``spoke.'' As with 
the general FTE resident caps, since the slots associated with the RTT 
FTE limitation are fungible, urban and rural hospitals with multiple 
RTT ``spokes'' may reduce the number of FTE residents training at one 
track and ``spoke'' in order to accommodate an increase in training and 
funding at another track and ``spoke.'' For example, Urban Hospital A 
has an existing family medicine program. In 2015, it partnered with 
Rural Hospital 1 to create a RTT from the existing family medicine 
program. Urban Hospital A received a cap/rural track FTE limitation to 
reflect residents in the RTT training at its facility. In July 2023, 
Urban Hospital A receives permission from the ACGME to permanently 
expand this family medicine RTT by 2 FTE residents, to train at both 
Urban Hospital A and Rural Hospital 1. We are proposing NOT to allow an 
adjustment to the rural track FTE limitation of Urban Hospital A and 
Rural Hospital 1 for the addition of 2 FTE residents, because this 
would be an expansion of an already existing RTT ``spoke.''
    We also note that if the urban hospital already has an existing RTT 
in one specialty and an associated rural track FTE limitation, the 
urban hospital may also receive an adjustment to its rural track FTE 
limitation if it starts another RTT in a different specialty, because 
starting a RTT in a different specialty would not be an expansion of 
the already existing RTT. For example, Urban Hospital A has an existing 
family medicine program. In 2015, it partnered with Rural Hospital 1 to 
create a RTT from the existing family medicine program and, as a 
result, received a cap/rural track FTE limitation adjustment to reflect 
residents in the RTT training in its facility. In July 2023, Urban 
Hospital A partners once again with Rural Hospital 1 to create a RTT in 
internal medicine. We are proposing that both Urban Hospital A and 
Rural Hospital 1 may receive adjustments to their cap/rural track FTE 
limitations to reflect the time that residents train in the internal 
medicine RTT ``spoke'' in their respective facilities. Thus, Urban 
Hospital A and Rural Hospital 1 would have cap/rural track FTE 
limitations reflecting FTE residents training in both a family medicine 
RTT and an internal medicine RTT.
(iii) Removal of Requirement That Rural Track Must Be ``Separately 
Accredited''
    Previously, section 1886(h)(4)(H)(iv) stated that the Secretary 
would adjust the caps of an urban hospital that establishes separately 
accredited approved medical residency training programs (or rural 
tracks) in a rural area. Historically, the ACGME has separately 
accredited family medicine programs in the ``1-2 format'' (meaning, 
residents in the 1-2 format receive their first year experience at a 
core family medicine program, and their second and third year 
experiences at another site, which may or may not be rural). Because 
the ACGME has only accredited family medicine programs in the 1-2 
format, hospitals have not been able to seek additional funding 
opportunities for rural tracks developed in specialties other than 
family medicine. Since implementation of the original BBRA provision, 
stakeholders have expressed concern that FTE cap adjustments have not 
been permitted for sending residents to rural areas if the program was 
not a separately accredited family medicine RTT. Section 127 of the CAA 
removes the requirement that the rural track be ``separately 
accredited.'' Specifically, section 1886(h)(4)(H)(iv)(II) now states 
that in the case of a hospital not located in a rural area that 
established or establishes a medical residency training program (or 
rural tracks) in a rural area, or establishes an accredited program 
where more than 50 percent of the training takes place in a rural area, 
the Secretary may adjust the resident cap in an appropriate manner. 
(Residency programs, whether they are ``rural tracks'' or any other 
program, must still be accredited under the law in order to receive IME 
and direct GME payments; see section 1886(h)(4)(H)(iv)(II) of the Act). 
Therefore, we are proposing that effective for cost reporting periods 
beginning on or after October 1, 2022, so long as the program in its 
entirety is accredited by the ACGME, regardless of the specialty, it 
may qualify as a RTT and urban and/or rural hospitals receive rural 
track FTE limitations, assuming all other requirements are met.
(iv) Requirement That Greater Than 50 Percent of the Program Occurs in 
a Rural Area
    Under existing regulations at 42 CFR 413.79(k)(1) and (2), the 
urban hospital establishing the RTT may only receive a cap/rural track 
FTE limitation to count residents in the RTT if the urban hospital 
rotates residents to either a rural hospital or rural non-provider 
site, for more than 50 percent of the duration of the program. As 
described in detail in rules implementing the original BBRA provision 
(see the August 1, 2000 interim final rule with comment period (65 FR 
47033 through 47037) and the FY 2002 IPPS final rule (66 FR 39902 
through 39909) where we implemented section 407(c) of Pub. L. 106-113), 
we adopted this greater than one-half duration rule based on the fact 
that residents training in separately accredited 1-2 family medicine 
RTTs spend greater than 50 percent of their training time in rural 
areas. We also wanted to ensure that cap adjustments would not be 
allowed for minimal

[[Page 25515]]

rotations to rural areas Section 1886(h)(4)(H)(iv)(II) is amended by 
section 127 of the CAA which states that in the case of a hospital not 
located in a rural area that established or establishes a medical 
residency training program (or rural tracks) in a rural area or 
establishes an accredited program where greater than 50 percent of the 
program occurs in a rural area, the Secretary shall consistent with the 
principles of subparagraphs (F) and (G) and subject to paragraphs (7) 
and (8), prescribe rules for the application of such subparagraphs with 
respect to such a program. We believe section 127 of the CAA now 
requires in statute what CMS has required in regulation; that is, we 
are proposing that in order for urban or rural hospitals to receive FTE 
cap adjustments for residents training in RTTs, the residents must be 
in ``an accredited program where greater than 50 percent of the program 
occurs in a rural area.'' We believe that a ``medical residency 
training program (or rural tracks)'' refers to what the ACGME currently 
separately accredits as a 1-2 program; family medicine residencies that 
typically would have a first year in an urban hospital and second and 
third years in a rural hospital/setting. These separately accredited 1-
2 family medicine RTTs may continue to maintain their RTT FTE 
limitations, assuming all applicable requirements are met. However, we 
are proposing that an ``accredited program where greater than 50 
percent of the program occurs in a rural area'' is the new statutory 
authorization for development of rural tracks in specialties other than 
family medicine, because eligibility for cap adjustments is no longer 
tied exclusively to ``separately accredited'', 1-2 programs. 
Specifically, as long as a program in its entirety is accredited by the 
ACGME, whether the program is in family medicine or in another 
specialty, and the residents spend more than 50 percent of the entire 
program in a rural area, then prospectively for cost reporting periods 
beginning on or after October 1, 2022, we are proposing to also provide 
additional slots to any program in any specialty. Therefore, for all 
accredited specialties, we are proposing to require that an urban 
hospital may include in its FTE count, not to exceed its rural track 
FTE limitation, residents training in the urban hospital that are 
designated to rotate to a rural area for greater than 50 percent of the 
duration of the particular program. In addition, we are proposing that 
a rural hospital that is partnered with the urban hospital in the RTT 
would similarly include in its FTE count, not to exceed its rural track 
FTE limitation, the time residents train in the rural hospital only if 
the residents rotate to a rural area for greater than 50 percent of the 
duration of the particular program. For example, greater than 50 
percent of the duration of a 3-year family medicine program would be 
more than 18 months rotating to a rural area; greater than 50 percent 
of the duration of a 4-year psychiatry program would be more than 24 
months training in a rural area.
(v) Exemption From the 3-Year Rolling Average During the 5-Year Rural 
Track FTE Limitation Window
    In the August 1, 2003 IPPS final rule (68 FR 45456 through 45457), 
we clarified our existing policy that although the rural track 
provision allows an increase to the urban hospital's FTE cap, sections 
1886(h)(4)(H)(iv) and 1886(d)(5)(B) of the Act do not provide for an 
exclusion from the rolling average for the urban hospital for those FTE 
residents training in a rural track. These provisions are interpreted 
to mean that, except for new rural track programs begun by urban 
teaching hospitals that are establishing an FTE cap for the first time, 
when an urban hospital with an FTE resident cap establishes a new rural 
track program or expands an existing rural track program, FTE residents 
in the rural track that are counted by the urban hospital are included 
in the hospital's rolling average calculation immediately. This policy 
is reflected in the regulation at Sec.  412.105(f)(1)(v)(F) for IME and 
Sec.  413.79(d)(7) for direct GME, and applies for IME and direct GME 
to cost reporting periods beginning on or after April 1, 2000.
    In addition, as stated in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 57028), under the regulations at Sec.  412.105(a)(1)(i), no 
exception to the IME intern- and resident-to-bed (IRB) ratio cap is 
provided for residents in a rural track training program (except for 
new rural track programs begun by urban teaching hospitals that are 
establishing an FTE cap for the first time, or for rural hospitals, if 
the rural track meets the definition of a new program).
    We believe that section 127 of the CAA amends section 
1886(h)(4)(H)(iv) of the Act to provide for an exemption from the 3-
year rolling average of the urban hospital and rural hospital during 
the 5-year growth window for FTE residents participating in rural 
tracks. Specifically, section 1886(h)(4)(H)(iv)(II) of the Act states 
that in the case of a hospital not located in a rural area that 
established or establishes a medical residency training program (or 
rural tracks) in a rural area or establishes an accredited program 
where greater than 50 percent of the program occurs in a rural area, 
the Secretary shall consistent with the principles of subparagraphs (F) 
and (G) and subject to paragraphs (7) and (8), prescribe rules for the 
application of such subparagraphs with respect to such a program. 
Subparagraph (F) is the FTE resident cap, and subparagraph (G) refers 
to the 3-year rolling average. This italicized language is the same as 
that used at section 1886(h)(4)(H)(i) regarding providing exemptions 
from the FTE resident cap and 3-year rolling average for new teaching 
hospitals starting new residency programs. That is, section 
1886(h)(4)(H)(i) states: ``(i) New facilities.--The Secretary shall, 
consistent with the principles of subparagraphs (F) and (G) and subject 
to paragraphs (7) and (8), prescribe rules for the application of such 
subparagraphs in the case of medical residency training programs 
established on or after January 1, 1995.'' The previous rural track 
language at section 1886(h)(4)(H)(iv) did not mention subparagraph (G); 
therefore, the law did not exempt from the rolling average any 
residents participating in a rural track, even during the cap building 
window as we explained in the August 1, 2003 IPPS final rule (68 FR 
45456 through 45457). Because section 127 of the CAA amends section 
1886(h)(4)(H)(iv) to add in new subclause (II) which contains language 
modeled on the language for providing for FTE resident cap and rolling 
average exemptions in the case of new programs started on or after 
January 1, 1995, we are proposing that similarly, during the 5-year cap 
growth window for RTTs, the FTE residents participating in the RTT 
either at the urban hospital or a rural hospital would not be included 
in a hospital's 3-year rolling average calculation during the cost 
reporting periods prior to the beginning of the applicable hospital's 
cost reporting period that coincides with or follows the start of the 
sixth program year of each rural track. That is, just as residents in 
new programs are exempt from the 3-year rolling average until the cost 
reporting period that coincides with or follows the start of the sixth 
program year, similarly, effective for RTTs started in cost reporting 
periods beginning on or after October 1, 2022, for each rural track 
started, full-time equivalent residents at an urban hospital or rural 
hospital in a rural track program are excluded from the rolling average 
calculation during the cost reporting periods prior to the beginning

[[Page 25516]]

of the applicable hospital's cost reporting period that coincides with 
or follows the start of the sixth program year of each rural track.
(vi) Proposed Changes to the Regulations Text
    Although section 127 of the CAA directly amends section 1886(h) for 
direct GME, and does not specifically refer to amendments for IME, the 
existing language at section 1886(d)(5)(B)(viii) of the Act states that 
rules similar to the rules of subsection (h)(4)(H) shall apply for 
purposes of clauses (v) and (vi). Accordingly, the statutory authority 
to make corresponding changes to IME for rural tracks already exists. 
Clause (v) refers to the IME resident caps, and clause (vi) refers to 
the 3-year rolling average. Therefore, we are proposing to apply to the 
IME payment the new authority under section 1886(h)(4)(H)(iv) of the 
Act to allow both urban and rural hospitals to receive IME rural track 
FTE limitations, as well as an exemption from the IME 3-year rolling 
average for FTE residents during the 5-year cap building window. We are 
proposing to make appropriate changes to the regulations text for IME 
at 42 CFR 412.105(f)(1)(v)(F) and 412.105(f)(1)(x) to mirror the 
following proposed regulations text changes for direct GME:
     We propose to modify the definition of Rural Track FTE 
limitation at 42 CFR 413.75(b) to add ``or rural hospital''.
     We propose to remove the requirement at 42 CFR 
413.79(d)(7) that FTE residents in the rural track are included in the 
3-year rolling average during the 5-year cap building window.
     We propose to make various changes throughout the 
regulations text at 42 CFR 413.79(k) ``Residents training in rural 
track programs.''
    (vii) Documentation Required for Medicare Administrative Contractor 
(MAC) to Pay for RTTs
    We intend to amend or clarify as necessary the Medicare cost 
report, CMS-2552-10, Worksheets E, Part A for IME and E-4 for direct 
GME, to accommodate additional rural track limitations. We expect that 
with this new authority to pay for more RTTs, MACs will face an influx 
of payment requests. While, as with payment for any GME program, 
hospitals must submit necessary documentation, to make review and 
processing of these new RTT payment requests more manageable, we are 
reiterating the documentation requirements here. That is, in order to 
facilitate the implementation of increases to RTT FTE limitations, 
either via interim payments or cost report adjustments, an urban 
hospital ``hub'' that adds one or more rural ``spokes'' in one or more 
specialties, we propose that the urban and rural hospitals must show 
its MAC the following:
     The accreditation for the ``spoke'', information whether 
the ``spoke'' is in the same specialty as a RTT that the urban hospital 
already has, or whether the ``spoke'' is a newly created RTT in a 
different specialty.
     Intern and resident rotation schedules (or similar 
documentation) showing that residents in each particular RTT program 
(both hub and spokes overall) spend greater than 50 percent of their 
training in the program in a geographically rural area in order to 
receive IME and direct GME rural track FTE limitations.
     The number of FTE residents and the amount of time 
training in all 5 program years at both the urban and rural settings 
since establishment of the particular ``spoke'', so that the MAC may be 
able to verify the RTT cap limitation.
    Following are examples of how the urban and rural hospital's rural 
track FTE limitations would be calculated:
    Example 1: Urban Hospital and Rural Hospital jointly sponsor an 
accredited rural track program. The program is in internal medicine (3 
years minimum accredited length), and is accredited for a total of 6 
residents, 2 in each program year (PGY). The residents spend PGY1 at 
Urban Hospital, and then the PGY2s and PGY3s rotate to a rural area, to 
train at both Rural Hospital and Rural Clinic (a nonprovider site). The 
PGY2 and PGY3 residents, while mostly assigned to the rural area, do 
come back to the Urban Hospital for some required training. However, 
the residents spend more than 50 percent of the duration of the 3 year 
program in the rural area. Therefore, the Urban Hospital qualifies to 
receive a cap/rural track FTE limitation adjustment. Rural Hospital 
incurs the cost of the salaries and fringe benefits of the residents 
for the time spent training at Rural Clinic and meets other applicable 
requirements at Sec.  413.78(g) to be able to count the time residents 
spend training at the Rural Clinic. The rotations and the cap 
calculation are as follows:

[[Page 25517]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.270

Urban Hospital's 5 YEAR FTE TOTAL = 11.1
Rural Hospital's 5 YEAR FTE TOTAL (includes time at Rural Clinic) = 
12.9
5 Year FTE Total = 24

    Step 1: Highest number of FTE residents training in any program 
year during fifth year across all participating hospitals is 2.0:

PGY 1s = 2.0
PGY 2s = 2.0
PGY 3s = 2.0

    Step 2: 2.0 x 3 (minimum accredited length) = 6.
    Step 3: Urban Hospital's cap adjustment is based on the ratio of 
training at Urban Hospital over all 5 years to the total training that 
is occurring at all sites over all 5 years: 6 x [11.1/(24)] = 2.76.
    Step 4: Rural Hospital's cap adjustment is based on the ratio of 
training at Rural Hospital and Rural Clinic over all 5 years to the 
total training that is occurring at all sites over all 5 years: 6 x 
[12.9/(24)] = 3.24.
    2.76 + 3.24 = 6.0, the total cap assignment does not exceed the 
total number of accredited slots. Urban Hospital's rural track FTE 
limitation is 2.76. Rural Hospital's rural track FTE limitation is 
3.24. (We note that this calculation is done separately for IME and 
direct GME caps respectively. Also note that during these 5 program 
years, the Urban Hospital and Rural Hospital exclude the FTE residents 
from the 3-year rolling average calculation on their Medicare cost 
reports.)
    Example 2: Urban Hospital and Rural Hospital jointly sponsor an 
accredited rural track program. The program is in psychiatry (4 years 
minimum accredited length), and is accredited for a total of 8 
residents, 2 in each program year (PGY). The residents spend PGY1 at 
Urban Hospital, and then the PGY2s and PGY3s and PGY4s rotate to a 
rural area, to train at both Rural Hospital and Rural Clinic (a 
nonprovider site). The PGY2 and PGY3 and PGY4 residents, while mostly 
assigned to the rural area, do come back to the Urban Hospital for some 
required training. However, the residents spend more than 50 percent 
(that is, more than 24 months) of the duration of the 4 year program in 
the rural area. Rural Hospital incurs the cost of the salaries and 
fringe benefits of the residents for the time spent training at Rural 
Clinic and meets other applicable requirements at Sec.  413.78(g) to be 
able to count the time residents spend training at the Rural Clinic. 
The rotations and the cap calculation are as follows:

[[Page 25518]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.271

Urban Hospital's 5 YEAR FTE TOTAL = 11.5
Rural Hospital's 5 YEAR FTE TOTAL (includes time at Rural Clinic) = 
16.5
5 Year FTE Total = 28

    Step 1: Highest number of FTE residents training in any program 
year during fifth year across all participating hospitals is 2.0:

PGY 1s = 2.0
PGY 2s = 2.0
PGY 3s = 2.0
PGY4s = 2.0.

    Step 2: 2.0 x 4 (minimum accredited length) = 8.
    Step 3: Urban Hospital's cap adjustment is based on the ratio of 
training at Urban Hospital over all 5 years to the total training that 
is occurring at all sites over all 5 years: 8 x [11.5/(28)] = 3.29.
    Step 4: Rural Hospital's cap adjustment is based on the ratio of 
training at Rural Hospital and Rural Clinic over all 5 years to the 
total training that is occurring at all sites over all 5 years: 8 x 
[16.5/(28)] = 4.71.
    3.29 + 4.71 = 8.0, the total cap assignment does not exceed the 
total number of accredited slots. Urban Hospital's rural track FTE 
limitation is 3.29. Rural Hospital's FTE cap adjustment is 4.71. (We 
note that this calculation is done separately for IME and direct GME 
caps respectively. Also note that during these 5 program years, the 
Urban Hospital and Rural Hospital exclude the FTE residents from the 3-
year rolling average calculation on their Medicare cost reports.)
    Example 3: Refer to Example 1 (as previously described), where 
Urban Hospital and Rural Hospital jointly sponsor an accredited 
internal medicine rural track program. The program is in internal 
medicine (3 years minimum accredited length), and is accredited for a 
total of 6 residents, 2 in each program year (PGY). Urban Hospital's 
rural track FTE limitation is 2.76. Rural Hospital's FTE cap adjustment 
is 3.24. In July 2023, Urban Hospital partners with Second Rural 
Hospital in a different rural part of the State to sponsor another 
internal medicine RTT (that is, Urban Hospital internal medicine 
``hub'' is adding another ``internal medicine RTT ``spoke''.) Urban 
Hospital adds 2 FTE residents to train in PGY1 at the Urban Hospital, 
and then the PGY2s and PGY3s rotate to a rural area, to train at both 
Second Rural Hospital and Second Rural Clinic (a nonprovider site). The 
PGY2 and PGY3 residents, while mostly assigned to the rural area, do 
come back to the Urban Hospital for some required training. However, 
the residents spend more than 50 percent of the duration of the 3 year 
program in the rural area. Therefore, Urban Hospital qualifies to 
receive another rural track FTE limitation. Second Rural Hospital 
incurs the cost of the salaries and fringe benefits of the residents 
for the time spent training at Second Rural Clinic and meets other 
applicable requirements at Sec.  413.78(g) to be able to count the time 
residents spend training at the Second Rural Clinic. The rotations and 
the cap calculation are as follows:

[[Page 25519]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.272

Urban Hospital's 5 YEAR FTE TOTAL = 11.1
Second Rural Hospital's 5 YEAR FTE TOTAL (includes time at Second Rural 
Clinic) = 12.9
5 Year FTE Total = 24

    Step 1: Highest number of FTE residents training in any program 
year during fifth year across all participating hospitals is 2.0:

PGY 1s = 2.0
PGY 2s = 2.0
PGY 3s = 2.0

    Step 2: 2.0 x 3 (minimum accredited length) = 6.
    Step 3: Urban Hospital's cap adjustment is based on the ratio of 
training at Urban Hospital over all 5 years to the total training that 
is occurring at all sites over all 5 years: 6 x [11.1/(24)] = 2.76.
    Step 4: Second Rural Hospital's cap adjustment is based on the 
ratio of training at Rural Hospital and Rural Clinic over all 5 years 
to the total training that is occurring at all sites over all 5 years: 
6 x [12.9/(24)] = 3.24
    2.76 + 3.24 = 6.0, the total cap assignment does not exceed the 
total number of accredited slots. Urban Hospital's rural track FTE 
limitation is 2.76. This second rural track FTE limitation is added to 
Urban Hospital's first rural track FTE limitation for a total rural 
track FTE limitation of 5.52 (2.76 + 2.76). Second Rural Hospital's FTE 
cap adjustment is 3.24. This second rural track FTE limitation is added 
to Second Rural Hospital's first rural track FTE limitation for a total 
rural track FTE limitation of 6.48 (3.24 + 3.24). (We note that this 
calculation is done separately for IME and direct GME caps 
respectively. Also note that during these 5 program years, the 
hospitals exclude the FTE residents from the 3-year rolling average 
calculation on their Medicare cost reports.)
    We are soliciting comments on our proposals.
c. Proposal for Implementation of Section 131 of the CAA, Addressing 
Adjustment of Low Per Resident Amounts (Direct GME) and Low FTE 
Resident Caps (Direct GME and IME) for Certain Hospitals
    Section 131 of the CAA provides us with the opportunity to reset 
the low or zero direct GME per resident amount of certain hospitals, 
and to reset the low IME and direct GME FTE resident caps of certain 
hospitals. Regarding direct GME PRAs, as stated previously, section 
1886(h)(2) of the Act sets forth a methodology for the determination of 
a hospital-specific base-period 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). For hospitals that became teaching hospitals after 1984, section 
1886(h)(2)(F) of the Act states that ``the Secretary shall, for the 
first such period for which it has such a residency training program 
and is participating under this title, provide for such approved FTE 
resident amount as the Secretary determines to be appropriate, based on 
approved FTE resident amounts for comparable programs. The regulations 
at 42 CFR 413.77(e)(1) implement this provision, stating that the per 
resident amount is based on the lower of the amount specified in 
paragraph (e)(1)(i) or paragraph (e)(1)(ii) of this section, subject to 
the provisions of paragraph (e)(1)(iii) of this section. In other 
words, the new teaching hospital's PRA generally will be based on the 
lower of its actual GME costs per FTE in its base period, or the 
weighted average PRA of existing teaching hospitals located in the same 
core-based statistical area (CBSA) as the new teaching hospital. Under 
section 1886(h)(2)(D) of the Act, once the PRA is established in a base 
period, no changes are made to it; it is only updated for inflation in 
each subsequent year.
    The calculations of both direct GME payments and the IME payment 
adjustment are affected by the number of FTE residents that a hospital 
is

[[Page 25520]]

allowed to count. 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.
(1) Background on Establishment of PRAs and FTE Resident Caps for 
Hospitals Hosting Residency Training
    Section 1886(h)(2)(F) of the Act does not require a hospital to 
incur costs, be the program sponsor, or train a certain minimum number 
of FTE residents, in order to become a teaching hospital. Accordingly, 
under the regulations at 42 CFR 415.152, ``Teaching hospital'' is 
defined as a hospital engaged in an approved GME residency program in 
medicine, osteopathy, dentistry, or podiatry. Our historical policy is 
that if a hospital has residents that are training in an approved GME 
residency program(s), and if the training is according to a planned and 
regular schedule (that is, not spontaneous or random), then we consider 
the hospital to be a teaching hospital, even if--
     Is not incurring the costs of the residents' salaries and 
fringe benefits,
     It is not the sponsor of the program,
     It is not a ``new'' program under Medicare rules,
    It is only training a very small number of FTE residents.
    In the past, a number of hospitals have found themselves in the 
situation of triggering establishment of a PRA, when they have served 
as a training site for only small numbers of residents from programs 
sponsored by a medical school or another hospital. In many cases, these 
hospitals did not incur any salaries for those residents and may have 
incurred only insignificant overhead costs associated with the 
residents' presence at their facilities and, therefore, their PRAs were 
either very low or $0. Such low PRAs preclude meaningful direct GME 
payment in the future if these hospitals expand their training of 
residents and incur significant costs associated with the training. 
Section 131(a) of the CAA amends section 1886(h)(2)(F) of the Act to 
direct the Secretary, for such hospitals with such extremely low or $0 
PRAs that meet certain criteria, to establish new PRAs using the 
methodology described in 42 CFR 413.77(e) if the hospital trains 
resident(s) in a cost reporting period beginning on or after its 
enactment (December 27, 2020) and before the date that is 5 years after 
enactment (December 26, 2025). In accordance with 42 CFR 413.77(e), a 
new teaching hospital's PRA is based on the lower of its actual GME 
costs per FTE, or the weighted average PRA of existing teaching 
hospitals located in the same core-based statistical area (CBSA) as the 
new teaching hospital.
    With regard to hospitals that have triggered establishment of a 
very small number of permanent IME and direct GME FTE caps (but greater 
than zero), this establishment occurs when a hospital participates in 
training residents in a new program started or accredited on or after 
January 1, 1995. The statute directs the Secretary to prescribe rules 
for the application of the FTE resident caps for approved medical 
residency training programs established on or after January 1, 1995 at 
section 1886(h)(4)(H)(i) of the Act. The regulations at 42 CFR 
413.79(l) defines a ``new medical residency training program'' as a 
medical residency that receives initial accreditation by the 
appropriate accrediting body or begins training residents on or after 
January 1, 1995.'' Similar to the circumstances under which a PRA is 
triggered, the law does not state that in order to establish permanent 
FTE caps, a hospital must incur the cost of the new program, be the 
sponsor of the new program, or train a specific number of FTE residents 
in the new program. Some previously non-teaching hospitals have hosted 
small numbers of residents who were in programs sponsored and funded by 
a medical school or another hospital. If those residents rotating to 
the previously non-teaching hospitals were in a new approved program, 
then that could have triggered establishment of IME and direct GME FTE 
resident caps at the previously non-teaching hospital. Should the 
previously non-teaching hospital wish to participate in training 
residents in a significant manner in the future, such minimal FTE 
resident caps preclude receipt of meaningful IME and direct GME 
payments. Section 131(b) of the CAA addresses this problem by amending 
section 1886(h)(4)(H)(i) to add new subclauses (III) and (IV) to direct 
the Secretary, for hospitals that meet certain criteria and that have 
very small FTE resident caps, to ``adjust''--that is, redetermine those 
caps if the Secretary determines the hospital begins training residents 
in a program year beginning on or after enactment (December 27, 2020) 
and before 5 years after enactment (December 26, 2025).
(2) Hospitals Qualifying To Reset Their PRAs
    Section 131(a) of the CAA also amends section 1886(h)(2)(F) of the 
Act to add a new clause (iii) to describe the categories of hospitals 
that qualify to receive a replacement PRA. For ease of reference, we 
will refer to these hospitals as Category A and Category B. A Category 
A Hospital is one that, as of the date of enactment (December 27, 
2020), has a PRA that was established based on less than 1.0 FTE in any 
cost reporting period beginning before October 1, 1997. Typically, a 
Category A hospital is one that trained less than 1.0 FTE in its most 
recent cost reporting period ending on or before December 31, 1996, and 
received a very low or $0 PRA. A Category B Hospital is one that, as of 
the date of enactment (December 27, 2020), has a PRA that was 
established based on training of no more than 3.0 FTEs in any cost 
reporting period beginning on or after October 1, 1997, and before the 
date of enactment (December 27, 2020). This new subclause provides that 
in lieu of these low PRAs, the Secretary shall, in accordance with 
Sec.  413.77(e), establish a new PRA for each such hospital if the 
hospital trains at least 1.0 FTE (in the case of a Category A hospital) 
or more than 3.0 FTE (in the case of a Category B hospital) (emphasis 
added). The recalculation period begins on December 27, 2020, and ends 
5 years later.
    We are proposing that to redetermine the PRA, the training 
occurring at a Category A Hospital or a Category B Hospital need not 
necessarily be training residents in a new program; the residents may 
be in either an approved program that is ``new'' for Medicare IME and 
direct GME purposes, or may be in an existing approved program. This is 
because the new subclause does not state that the training be in a 
``new'' program, and furthermore, CMS's current policy is that for a 
hospital which starts training residents for the first time, the PRA 
can be established based on the training of residents in either a 
``new'' approved program, or an existing approved program. However, for 
a Category A Hospital, we propose not to reset its PRA until we 
determine that the Category A Hospital trains at least 1.0 FTE, and 
that training must occur in a cost reporting period

[[Page 25521]]

beginning on or after December 27, 2020 (date of enactment) and before 
December 26, 2025 (5 years after enactment). Similarly, for a Category 
B Hospital, we propose not to reset its PRA until we determine that the 
Category B Hospital trains more than 3.0 FTEs, and that training must 
occur in a cost reporting period beginning on or after December 27, 
2020 (date of enactment) and before December 26, 2025 (5 years after 
enactment). Because new section 1886(h)(2)(F)(iii) uses the word 
``trains'', we interpret this to require ``continuous'' training, and 
therefore, we propose that for both Category A and B Hospitals, it is 
not relevant whether they may have trained at least 1.0 FTE or more 
than 3.0 FTEs in a cost reporting period or periods prior to December 
27, 2020. While we propose that such previous training of at least 1.0 
FTE or greater than 3.0 FTEs would not preclude resetting of a Category 
A Hospital's PRA or a Category B Hospital's PRA, we propose that the 
relevant factor in determining when to reset their PRAs is if and when 
the hospital trains the requisite amount of FTE residents in a cost 
reporting period beginning on or after December 27, 2020 (date of 
enactment) and 5 years after (December 26, 2025). For example, a 
Category A Hospital trains 6.05 FTEs in its cost reporting period 
beginning on January 1, 2020. The Category A Hospital trains 5.95 FTEs 
in its cost reporting period beginning on January 1, 2021. We are 
proposing that we would reset this Category A Hospital's PRA effective 
with its cost reporting period beginning on January 1, 2021. In a 
second example, a Category B Hospital trains 6.05 FTEs in its cost 
reporting period beginning on January 1, 2020. The Category B Hospital 
trains 2.0 FTEs in its cost reporting period beginning on January 1, 
2021. Then the Category B Hospital trains 3.25 FTE in its cost 
reporting period beginning on January 1, 2022. We are proposing that we 
would reset this Category B Hospital's PRA effective with its cost 
reporting period beginning on January 1, 2022. Once reset, in the 
absence of additional legislation, the PRAs for either a Category A 
Hospital or a Category B Hospital are permanent, subject to annual 
inflation updates under 42 CFR 413.77(c)(1).
(3) Proposal for How To Calculate the Replacement PRA and Cost 
Reporting Requirements
    Consistent with the new statute, we propose to calculate the 
replacement PRA using the existing regulations in place at 42 CFR 
413.77(e). First, we propose to use as the PRA base period the first 
cost reporting period in which either the Category A Hospital or 
Category B Hospital trains their requisite threshold FTEs; that is, the 
cost report beginning on or after December 27, 2020 in which at least 
1.0 FTE is trained at Category A Hospital, and the cost reporting 
period beginning on or after December 27, 2020 in which more than 3.0 
FTEs are trained at Category B Hospital. Then, as 42 CFR 413.77(e)(1) 
states, we propose to amend the regulations to add a new Sec.  
413.77(e)(1)(iv) to establish the replacement PRA as the LOWER OF:
     The hospital's actual cost per resident incurred in 
connection with the GME program(s) based on the cost and resident data 
from the hospital's replacement base year cost reporting period; and
     The updated weighted mean value of per resident amounts of 
all hospitals located in the same geographic wage area is calculated 
using all per resident amounts (including primary care and obstetrics 
and gynecology and nonprimary care) and FTE resident counts from the 
most recently settled cost reports of those teaching hospitals.
     If there are fewer than three existing teaching hospitals 
with per resident amounts that can be used to calculate the weighted 
mean value per resident amount, for base periods beginning on or after 
October 1, 1997, the per resident amount equals the updated weighted 
mean value of per resident amounts of all hospitals located in the same 
census region as that term is used in subpart D of part 412 of this 
subchapter.
    We plan on issuing instructions to the MACs and to hospitals to 
provide for an orderly process of request and review for the purpose of 
receiving replacement PRAs. The MACs of the Category A and Category B 
Hospitals would review the Medicare cost reports, GME costs, FTE 
counts, rotation schedules, etc. to determine at what point the 
requisite threshold of FTE residents are trained. As required under 42 
CFR 413.20 and 413.24, hospitals must provide sufficient documentation 
to ensure proper payment (for GME, this includes, but is not limited 
to, rotation schedules and training agreements). We note that newly 
amended section 1886(h)(2)(F) of Act makes two points regarding cost 
reporting. First, clause 1886(h)(2)(F)(ii) states that in the case of a 
hospital that trains residents and has not entered into a GME 
affiliation agreement (as defined by the Secretary for purposes of 
paragraph (4)(H)(ii)), on or after the date of enactment of this 
clause, the Secretary shall not establish an FTE resident amount until 
such time as the Secretary determines that the hospital has trained as 
least 1.0 FTE resident in an approved medical residency training 
program in a cost reporting period. Medicare GME affiliation 
agreements, as implemented in the regulations at 42 CFR 413.79(f), 
permit teaching hospitals that cross train residents in the same 
programs to aggregate and share their FTE resident caps to facilitate 
movement of residents and reimbursement for that training. Entering 
into a Medicare GME affiliation agreement is a voluntary and conscious 
action on the part of a hospital.
    Therefore, even if a hospital trains less than 1.0 FTE (and this 
would be any hospital, not just a Category A Hospital or a Category B 
Hospital), but has entered into a Medicare GME affiliation agreement 
for that training, we believe the law is directing the Secretary to 
establish a PRA for that hospital. Thus, effective for a cost reporting 
period beginning on or after enactment (December 27, 2020), we are 
proposing to establish a PRA in the instance where a hospital trains 
less than 1.0 FTE and that hospital has entered into a Medicare GME 
affiliation agreement for that training. However, in the instance where 
a hospital did not enter into a Medicare GME affiliation agreement for 
that training, we propose to establish a PRA only when a hospital 
trains at least 1.0 FTE. We propose to amend the regulations at 42 CFR 
413.79(f) to reflect this new provision.
    Second, section 1886(h)(2)(F)(iv) states that for purposes of 
carrying out this subparagraph for cost reporting periods beginning on 
or after the date of the enactment of this clause, a hospital shall 
report full-time equivalent residents on its cost report for a cost 
reporting period if the hospital trains at least 1.0 full-time 
equivalent residents in an approved medical resident training program 
or programs in such period. Accordingly, we are proposing that both a 
Category A Hospital and a Category B Hospital must accurately report 
FTEs on the IME Worksheet E, Part A and the direct GME Worksheet E-4 of 
CMS-Form-2552-10, when either category of hospital trains at least 1.0 
FTE on or after December 27, 2020. We are further proposing that all 
hospitals, even if they do not classify as Category A or Category B 
Hospitals, must enter the FTE counts on Worksheets E, Part A and E-4 of 
the CMS-Form-2552-10, for cost reporting periods during which the 
hospital trains at least 1.0. In addition, the hospital must provide 
the information required by the Interns and Residents Information 
System (IRIS) software for a cost report that contains at least 1.0 
FTEs on Worksheets E, Part A (IME) and E-4 (direct GME). We are

[[Page 25522]]

proposing this rule regardless of whether or not such hospital incurs 
the costs or is the program sponsor, because we believe that a PRA is 
established when a hospital trains at least 1.0 FTE (or, if there is a 
Medicare GME affiliation agreement, even less than 1.0 FTE). We are 
proposing to amend the regulations at 42 CFR 413.78(b), with a cross-
reference to 42 CFR 413.77(e) and 413.79(f), to require that effective 
for a cost reporting period beginning on or after December 27, 2020, a 
hospital must report FTE residents on its Medicare cost report for a 
cost reporting period if: (1) In the absence of a Medicare GME 
affiliation agreement, a hospital trains at least 1.0 FTE in an 
approved program or programs; or (2) if there is a Medicare GME 
affiliation agreement, a hospital trains less than 1.0 FTE in an 
approved program or programs. This proposed regulation would put 
hospitals on notice that they would establish a PRA when they report 
FTE residents on their Medicare cost report beginning on or after 
December 27, 2020.
    On a technical note, newly added clause1886(h)(2)(F)(v) states that 
as appropriate, the Secretary may consider information from any cost 
reporting period necessary to establish a new FTE resident amount. 
Keeping in mind the regulations regarding predicate facts at 42 CFR 
405.1885, our policy has been to refer, but not make changes, to a 
hospital's ``true'' base year under 42 CFR 413.77(e), even if that base 
year cost report is beyond the 3-year reopening rules. For example, if, 
in 2019, a MAC discovered that a hospital trained a small number of FTE 
residents in its 2005 cost reporting period, the MAC would use the 2005 
cost report and documentation to obtain direct GME costs (if any, or 
$0) and the FTE resident(s), determine a cost per FTE, and compare that 
to the 2005 weighted average PRA of the other teaching hospitals in the 
same CBSA, even though the 2005 cost report was beyond the 3-year 
reopening period. In accordance with 42 CFR 413.77(e), the MAC would 
establish the LOWER of the two amounts to be the hospital's base year 
PRA. Going forward, we propose to continue to be consistent with our 
existing predicate fact regulations, such that we would not reopen cost 
reports beyond their 3-year reopening period, but would refer to and 
use whatever contemporaneous documentation we would need to establish a 
PRA. However, because section 131 of the CAA directs the Secretary to 
replace a Category A Hospital's PRA or a Category B Hospital's PRA if 
the hospital trains at least 1.0 FTE or more than 3.0 FTE in a cost 
reporting period beginning on or after such date of enactment and 
before the date that is 5 years after, we are proposing to amend the 
regulations at 42 CFR 413.77(e) to use as the PRA base year for a 
Category A Hospital the cost reporting period beginning on or after 
December 27, 2020 and before December 26, 2025 in which that hospital 
trains at least 1.0 FTE, and for a Category B Hospital, the cost 
reporting period beginning on or after December 27, 2020 and before 
December 26, 2025 in which that hospital trains more than 3.0 FTEs. In 
determining whether a hospital trained the requisite thresholds of 1.0 
or more than 3.0 FTEs, we propose not to round up; that is, an FTE 
count of 0.99 would not be rounded up to be at least 1.00 FTE. Rather, 
the FTE count would have to equal at least 1.00 without rounding 
applied. Similarly, an FTE count would have to add to be greater than 
3.00 without rounding rules applied.
(4) Hospitals Qualifying To Reset Their FTE Resident Caps
    Section 131(b) of the CAA 2021 amends section 1886(h)(4)(H)(i) of 
the Act to add new subclauses (II) through (V) to describe the 
categories of hospitals that qualify to receive a replacement PRA. For 
ease of reference, we continue to refer to these hospitals as Category 
A and Category B. A Category A Hospital is one that, as of the date of 
enactment (December 27, 2020), has an IME and/or direct GME FTE 
resident cap that was established based on less than 1.0 FTE in any 
cost reporting period beginning before October 1, 1997. Typically, a 
Category A hospital is one that did train less than 1.0 FTE in its most 
recent cost reporting period ending on or before December 31, 1996, and 
therefore, received FTE caps of less than 1.0 FTE (along with a very 
low or $0 PRA). Category B Hospital is one that, as of the date of 
enactment (December 27, 2020), has an IME and/or direct GME FTE 
resident cap that was established based on training of no more than 3.0 
FTEs in any cost reporting period beginning on or after October 1, 
1997, and before the date of enactment (December 27, 2020). The new 
subparagraphs (III) and (IV) provide that the Secretary shall adjust 
the FTE resident cap in the manner applicable to a new approved medical 
residency training program, which under subparagraph (V), states that 
the adjustment to the FTE resident cap shall be made in a manner 
consistent with the methodology, as appropriate, in Sec.  413.79(e). 
The Secretary shall adjust the FTE resident caps if the hospital 
``begins training'' at least 1.0 FTE (in the case of Category A) or 
``begins training'' more than 3.0 FTE (in the case of Category B) in a 
program year beginning on or after such date of enactment and before 
the date that is 5 years after such date of enactment (emphases added).
    Unlike our preceding proposal regarding resetting the PRAs of 
Category A and B Hospitals, where a training program does not 
necessarily need to be new, in the case of resetting the FTE resident 
caps, we are proposing that the FTE resident caps would only be reset 
when a Category A Hospital or Category B Hospital ``begins training'' 
FTE residents in a new residency program(s) (see our discussion of the 
definition of ``new program'' at 42 CFR 413.79(l) and 74 FR 43908 
through 43917). Specifically, we emphasize that the new subparagraphs 
(III) and (IV) state that the Secretary shall adjust the FTE resident 
caps in the manner applicable to a new program if the Secretary 
determines the hospital ``begins training'' the requisite number of FTE 
residents (emphasis added). We propose that ``begins training'' means 
future training in a new program for the first time on or after 
enactment. We propose that for both Category A and B Hospitals, it is 
not relevant whether they may have trained at least 1.0 FTE or more 
than 3.0 FTEs in a new program in a cost reporting period or periods 
prior to December 27, 2020; rather, we propose that the relevant factor 
in determining the timing of resetting their FTE resident caps is if 
the hospital first begins training the requisite amount of FTE 
residents at some point in a cost reporting period beginning on or 
after December 27, 2020 (date of enactment) and 5 years after (December 
26, 2025). For example, a Category A Hospital trains 6.05 FTEs in a new 
program in its cost reporting period beginning on January 1, 2017. 
Category A Hospital trains 15.95 FTEs in its cost reporting period 
beginning on January 1, 2021. We are proposing that we would NOT reset 
this Category A Hospital's FTE resident caps effective with its cost 
reporting period beginning on January 1, 2021, because it first began 
training residents in a new program prior to its cost reporting period 
beginning on or after enactment, and continued to train FTE residents 
in the new program after enactment. Rather, in order to qualify for a 
replacement FTE resident cap, both a Category A Hospital and a Category 
B Hospital would have to wait to start training residents in a new 
program in a cost reporting period beginning on or after enactment; if 
they started training residents in a new program at some point prior to 
enactment, we are

[[Page 25523]]

proposing that they would not qualify to receive replacement FTE 
resident caps. For example, a Category A Hospital wanted to start 
training residents in a new program, but delayed doing so because it 
believed it could not support a new residency program with IME and 
direct GME FTE resident caps of less than 1.0. With the enactment of 
section 131 of the CAA, this Category A Hospital receives accreditation 
to start a new residency program, and begins to train at least 1.0 FTE 
residents in the new program on July 1, 2022. We propose to replace the 
small FTE resident caps of this Category A Hospital with new FTE 
resident caps in accordance with the regulations for calculating FTE 
resident caps for new programs at 42 CFR 413.79(e). We propose to apply 
the same policy for a Category B Hospital that waits to train more than 
3.0 FTE residents in a new program in a cost reporting period on or 
after December 27, 2020.
(5) Proposal for How To Calculate the Replacement FTE Resident Caps and 
Cost Reporting Requirements
    Consistent with the new statutory provisions, we would propose to 
calculate the replacement FTE resident caps using the existing 
regulations in place at 42 CFR 413.79(e)(1). First, we propose to use 
as the first program year of the 5-year cap building period in which 
either the Category A Hospital or Category B Hospital ``begins 
training'' their requisite threshold FTEs; that is, the program year 
beginning after December 27, 2020 in which at least 1.0 FTE begins to 
train at Category A Hospital, and the program year beginning after 
December 27, 2020 in which more than 3.0 FTEs are trained at Category B 
Hospital. Then, as 42 CFR 413.79(e)(1) states, we propose to calculate 
the FTE resident caps based on the sum of the products of the highest 
number of FTE residents in any program year during the fifth year of 
the first new program's existence and the number of years in which 
residents are expected to complete the program based on the minimum 
accredited length for each type of program. The adjustment to each 
qualifying hospital's cap for new residency training program (s) is 
equal to the sum of the products of--
     The highest total number of FTE residents trained in any 
program year during the fifth year of the first new program's existence 
at all of the hospitals to which the residents in the program rotate;
     The number of years in which residents are expected to 
complete the program, based on the minimum accredited length for each 
type of program.
     The ratio of the number of FTE residents in the new 
program that trained at the hospital over the entire 5-year period to 
the total number of FTE residents that trained at all hospitals over 
the entire 5-year period.
    We plan on issuing instructions to the MACs and to hospitals to 
provide for an orderly process of request and review for the purpose of 
receiving replacement FTE resident caps. The MACs of the Category A and 
Category B Hospitals would review the Medicare cost reports (including 
rotation schedules, information regarding any nonprovider-site 
training, and accreditation information, etc.) to determine at what 
point the requisite threshold of FTE residents would be trained. As 
required under 42 CFR 413.20 and 413.24, hospitals must provide 
sufficient documentation to ensure proper payment (for GME, this 
includes, but is not limited to, rotation schedules and training 
agreements, and ACGME accreditation information).
    Prospectively, consistent with new section 1886(h)(4)(H)(i)(II) of 
the Act, we propose not to establish permanent FTE resident caps for 
hospitals training residents in new programs begun on or after December 
27, 2020, until we determine that in a cost reporting period beginning 
on or after December 27, 2020, the hospital trains at least 1.0 FTE in 
a new medical residency program. We propose to amend the regulations at 
42 CFR 413.79(e) to reflect this new provision. We are proposing this 
for all hospitals that do not yet have caps triggered. Therefore, 
permanent FTE caps for new programs would no longer be triggered if the 
amount of FTEs being trained by a hospital in the new program equates 
to less than 1.0 FTE.
    As with the resetting of the PRAs, newly added section 
1886(h)(4)(H)(i)(V) states that as appropriate, the Secretary may 
consider information from any cost reporting period necessary to make 
such an adjustment to the limitation. Going forward, we propose to 
continue to be consistent with our existing predicate fact regulations 
at 42 CFR 405.1885, such that we would not reopen cost reports beyond 
their 3-year reopening period, but would refer to and use whatever 
contemporaneous documentation we would need to establish the FTE 
resident caps.
    We are soliciting comments on our proposals regarding resetting the 
applicable PRAs and FTE resident caps.
d. 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 2 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 counts 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. 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 this proposed rule, we are proposing to remove the reference in

[[Page 25524]]

the regulations to a diskette and instead reference ``Intern and 
Resident Information System data.'' Specifically, we are proposing 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 
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, we are proposing 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 are proposing to amend 42 CFR 413.24(f)(5)(i) 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.

K. 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) (Affordable Care Act), 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 proposed rule, we are 
summarizing the status of the demonstration program, and proposing 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. Proposed 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 Affordable Care Act (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 (Affordable Care Act) 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 Public Law 111-148 (Affordable Care 
Act)). 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 108-173 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

[[Page 25525]]

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 (Affordable Care Act) 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 were 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 propose 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 will 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 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.

[[Page 25526]]

c. Budget Neutrality Methodology for the Extension Period Authorized by 
CAA 2021
    For the newly enacted extension period, under CAA 2021, we propose 
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 Affordable Care Act). 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 
will use finalized cost reports when available that detail the actual 
costs of the demonstration for each of 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 27 hospitals that are eligible to continue participation in 
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 27 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 27 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 proposed market basket 
percentage increase for FY 2022, which can be found in section II.A. of 
the addendum to this proposed rule). The result for the 27 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 
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 proposed 
applicable percentage increase, per section II.A. of the Addendum of 
this proposed 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

[[Page 25527]]

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 27 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 proposed rule, the resulting amount is $63,829,479, 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. If updated data become available prior to the final rule, we 
will 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).
(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 
still, all of the cost reports have not been finalized for the 18 
hospitals that completed cost report periods under the demonstration 
payment methodology beginning in FY 2016. If the entire set of 
finalized cost reports is available in time for the FY 2022 final rule, 
we will be able to incorporate this amount in the overall budget 
neutrality offset amount.
(4) Total Proposed Budget Neutrality Offset Amount for FY 2022
    Therefore, for this FY 2022 IPPS/LTCH PPS proposed rule, the budget 
neutrality offset amount for FY 2022 is based on the amount determined 
under section V.K.c.(2). of the preamble of this proposed 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 27 hospitals 
eligible to participate 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 $63,829,479. We propose to 
subtract this amount from the national IPPS rates for FY 2022. We note, 
however, that the overall amount might change if there are any 
revisions prior to the final rule to the data used to formulate this 
estimate. In addition, if the entire set of finalized cost reports for 
FY 2016 is available ahead of the final rule, we will also include this 
amount within the total budget neutrality offset amount to be applied 
to the FY 2022 national IPPS rates.

L. Market-Based MS-DRG Relative Weight Policy--Proposed 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. Proposed 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 
are proposing 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 proposing 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. Comments 
received on the 60-day Paperwork Reduction Act (PRA) revision request 
of the information collection requirement (ICR) (approved under OMB 
control number 0938-0050, expiration date March 31, 2022, 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 are proposing to 
repeal the market-based data collection and MS-DRG relative weight 
methodology to allow for further consideration of these questions and 
possible alternative approaches.
    We also propose 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 propose 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.
    In light of this proposal to repeal the requirement for hospitals 
to report this median payer-specific negotiated charge data on the cost 
report, we will revise the forthcoming revision of the Information 
Collection Request currently approved under OMB control number 0938-
0050, expiration date March 31, 2022, accordingly.

[[Page 25528]]

    We are inviting public comment on our proposal to repeal the 
market-based data collection requirement and market-based MS-DRG 
relative weight methodology. We also invite public comment on 
alternative approaches or data sources that could be used in Medicare 
fee-for-service (FFS) ratesetting.

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 proposed rule for discussion of the procedure codes for 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies that 
we are proposing 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 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 are proposing 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 are proposing 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 are proposing 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 
are proposing 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 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 proposed 
rule, we are also soliciting 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 may consider finalizing for FY 2022 
based on consideration of comments received. We note 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.

VI. Proposed 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

[[Page 25529]]

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. Proposed Annual Update for FY 2022

    The proposed 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 proposed rule.
    In section II.C. of the preamble of this FY 2022 IPPS/LTCH PPS 
proposed 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 proposing 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. Because these provisions 
require us to make an adjustment only to the operating IPPS 
standardized amount, we are not proposing to make a similar adjustment 
to the national capital Federal rate (or to the hospital-specific 
rates).
    We also note that in section IV.G. of the preamble of this proposed 
rule, we discuss our proposed 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 IV.G. of this preamble for 
additional details on the proposed payment adjustment for these cases.

VII. Proposed Changes for Hospitals Excluded From the IPPS

A. Proposed 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 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

[[Page 25530]]

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 this FY 
2022 IPPS/LTCH PPS proposed rule, we are proposing to rebase and revise 
the IPPS operating basket to a 2018 base year. Therefore, we are 
proposing 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 this FY 2022 IPPS/LTCH PPS proposed rule, based on IGI's 2020 
fourth quarter forecast, we estimate 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 are proposing that if more recent data become 
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.
    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 is 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 is 2.5 percent, which is based on IGI's 2020 fourth quarter 
forecast. Furthermore, we are proposing that if more recent data become 
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.

B. 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 (Pub. L. 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

[[Page 25531]]

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 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

[[Page 25532]]

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 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

[[Page 25533]]

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 demonstration 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 
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

[[Page 25534]]

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 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

[[Page 25535]]

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 are not proposing 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''). 
Thus, the FCHIP Demonstration will resume on July 1, 2021 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 July 1.
    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. 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.

VIII. Proposed 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 
proposed 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

[[Page 25536]]

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 (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 proposed 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 state that our goal is to always use the best 
available data overall for ratesetting. Ordinarily, the best available 
claims data for the LTCH

[[Page 25537]]

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. 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 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, 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 this proposed rule, we discuss 
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 shows 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 have received at 
least one dose of vaccine; 63.7 percent are fully vaccinated. Nearly 
one-half (48.3 percent) of people 18 or older have received at least 
one dose of vaccine; 30.3 percent are fully vaccinated. Nationally, 
COVID-19-related emergency department visits as well as both hospital 
admissions and current hospitalizations have risen among patients ages 
18 to 64 years in recent weeks, but emergency department visits and 
hospitalizations among people ages 65 years and older have 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 recent 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, we believe 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 leads us to conclude based on the 
information available to us at this time 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 calls 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 proposed rule for the details on this analysis.
    In section I.F of the preamble of this proposed rule, we also 
discuss 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, 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.
    When comparing 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 
note 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, we believe that the utilization 
patterns reflected in the FY 2020 LTCH claims data were significantly 
altered by the COVID-19 PHE. We also believe 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 this proposed 
rule, including an increase in the number of individuals who are 
vaccinated against COVID-19. Therefore, 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 example, we are proposing 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. This proposal is consistent with the proposal 
made for FY 2022 IPPS ratesetting in section I.F of the preamble of 
this proposed 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 proposed rule for further information on 
this proposal.

B. Proposed 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

[[Page 25538]]

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 would be 767 
MS-DRG groupings based on the proposed changes, as discussed in section 
II.E. of the preamble of this proposed 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 proposed rule, we provide a general summary of our existing 
methodology for determining the FY 2022 MS-LTC-DRG relative weights 
under the LTCH PPS.
    We are proposing in this FY 2022 IPPS/LTCH PPS proposed rule, in 
general, for FY 2022, to continue 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 proposed rule). As 
we established when we implemented the dual rate LTCH PPS payment 
structure codified under Sec.  412.522, which began in FY 2016, we are 
proposing that 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 later in greater detail in section VII.B.3.c. of the 
preamble of this proposed rule). In addition, for FY 2022, we are 
proposing to continue 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 proposed rule.
    Furthermore, for FY 2022, in using data from applicable LTCH cases 
to establish MS-LTC-DRG relative weights, we are proposing to continue 
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 proposed 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

[[Page 25539]]

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 through 56790) and section II.E.1. of the preamble of this 
proposed 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. Proposed 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 proposed rule, we are proposing to update the MS-LTC-DRG 
classifications effective October 1, 2021 through September 30, 2022 
(FY 2022), consistent with the proposed changes to specific MS-DRG 
classifications presented in section II.F. of the preamble of this 
proposed rule. Accordingly, the proposed MS-LTC-DRGs for FY 2022 
presented in section II.F. of the preamble of this proposed rule are 
the same as the MS-DRGs being proposed for use under the IPPS for FY 
2022. In addition, because the proposed MS-LTC-DRGs for FY 2022 are the 
same as the proposed MS-DRGs for FY 2022, the other proposed changes 
that affect MS-DRG (and by extension MS-LTC-DRG) assignments under 
proposed GROUPER Version 39 as discussed in section II.E. of the 
preamble of this proposed rule, including the proposed changes to the 
MCE software and the ICD-10-CM/PCS coding system, also are applicable 
under the LTCH PPS for FY 2022.

[[Page 25540]]

3. Development of the Proposed 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.
b. Development of the Proposed MS-LTC-DRG Relative Weights for FY 2022
    In this proposed rule, we are proposing to continue 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 proposed application of our 
existing methodology for determining the proposed MS-LTC-DRG relative 
weights for FY 2022, and we discuss the effects of our proposals 
concerning the data used to determine the proposed 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 proposed rule, we would use FY 2020 
Medicare LTCH claims data for purposes of calculating the proposed MS-
LTC-DRG relative weights for FY 2022. As discussed in section VII.A.4 
of the preamble of this proposed rule, we believe the utilization 
patterns reflected in the FY 2020 LTCH claims data was significantly 
impacted by the COVID-19 PHE. Therefore, for the purposes of 
calculating the proposed MS-LTC-DRG relative weights for FY 2022, we 
are proposing to use 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 
VII.A.4 of the preamble of this proposed rule. Specifically, for this 
FY 2022 IPPS/LTCH PPS proposed rule, we obtained total charges from FY 
2019 Medicare LTCH claims data from the March 2020 update of the FY 
2019 MedPAR file and are proposing to use proposed Version 39 of the 
GROUPER to classify LTCH cases. Consistent with our historical 
practice, we are proposing to use the best available data, if 
applicable, in the final rule. Specifically, we would use those data 
and the finalized Version 39 of the GROUPER in establishing the FY 2022 
MS-LTC-DRG relative weights in the final rule.
    To calculate the proposed FY 2022 MS-LTC-DRG relative weights under 
the dual rate LTCH PPS payment structure, we are proposing to continue 
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

[[Page 25541]]

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 proposed 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 2021.
    In summary, in general, we identified the claims data used in the 
development of the proposed FY 2022 MS-LTC-DRG relative weights in this 
proposed rule by trimming claims data that were paid the site neutral 
payment rate or would have been paid the site neutral payment rate had 
the dual payment rate structure been in effect. Finally, we propose to 
trim 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. We are proposing to use 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 
proposed rule, we are proposing to continue 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 reduce 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, we are 
proposing to continue 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 proposed 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

[[Page 25542]]

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 Proposed 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 proposed 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 proposed 
rule). For FY 2022, we are proposing to continue to use applicable LTCH 
cases to establish the same volume-based categories to calculate the 
proposed FY 2022 MS-LTC-DRG relative weights.
    In determining the proposed FY 2022 MS-LTC-DRG relative weights, 
when necessary, as is our longstanding practice, we are proposing to 
make adjustments to account for nonmonotonicity, as discussed in 
greater detail later in Step 6 of section VII.B.3.g. of the preamble of 
this proposed 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. Proposed Low-Volume MS-LTC-DRGs
    In order to account for proposed MS-LTC-DRGs with low-volume (that 
is, with fewer than 25 applicable LTCH cases), consistent with our 
existing methodology, we are proposing to continue 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, we propose to make 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 proposed rule.
    In this proposed 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 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 proposed rule, the number of 
proposed MS-LTC-DRGs with less than 25 applicable LTCH cases was not 
evenly divisible by 5 and, therefore, we are proposing to employ our 
historical methodology for determining which of the low-volume 
quintiles would contain the additional low-volume MS-LTC-DRG. 
Specifically for this proposed 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 proposed 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 proposed rule, we are 
providing the list of the composition of the proposed low-volume 
quintiles for proposed 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 proposed 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 proposed FY 2022 relative weights for the 
proposed low-volume MS-LTC-DRGs, consistent with our historical 
practice, we are proposing to use the five low-volume quintiles 
described previously. We determined a proposed relative weight and 
(geometric) average length of stay for each of the five proposed low-
volume quintiles using the methodology described in section VII.B.3.g. 
of the preamble of this proposed rule. We are proposing to assign the 
same proposed relative weight and average length of stay to each of the 
proposed 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 Proposed FY 2022 MS-LTC-DRG Relative 
Weights
    In this proposed rule, we are proposing to continue to use our 
current methodology to determine the proposed FY 2022 MS-LTC-DRG 
relative weights.
    In summary, to determine the proposed FY 2022 MS-LTC-DRG relative 
weights, we are proposing to group applicable LTCH cases to the 
appropriate proposed MS-LTC-DRG, while taking into account the proposed 
low-volume quintiles (as described previously) and cross-walked 
proposed no-volume MS-LTC-DRGs (as described later in this section). 
After establishing the appropriate proposed MS-LTC-DRG (or proposed 
low-volume quintile), we are proposing to calculate the proposed FY 
2022 relative weights by first removing cases with a length of stay of

[[Page 25543]]

7 days or less and statistical outliers (Steps 1 and 2). Next, we are 
proposing to adjust the number of applicable LTCH cases in each 
proposed MS-LTC-DRG (or proposed 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), we are proposing to calculate proposed ``relative 
adjusted weights'' for each proposed MS-LTC-DRG (or proposed 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 proposed calculation of the proposed 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 proposed 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 proposed FY 2022 MS-LTC-DRG relative weights, we are 
proposing to remove 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 proposed calculation of the proposed 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, we are proposing to 
continue 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 proposed 
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 proposed 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 proposed 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 proposed 
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 proposed FY 2022 MS-LTC-
DRG relative weights, consistent with our historical approach, we are 
proposing to adjust 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, we are proposing to make this adjustment 
by counting an SSO case as a fraction of a discharge based on the ratio 
of the length of stay of the 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 proposed FY 2022 MS-LTC-DRG relative weights would 
lower the proposed 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, we are proposing to continue 
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 proposed FY 2022 MS-LTC-DRG relative weights 
on an iterative basis.
    Consistent with our historical relative weight methodology, we are 
proposing to calculate the proposed 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 proposed MS-LTC-DRG, we calculated the proposed FY 2022 
relative weight by dividing the SSO-adjusted average of the hospital-
specific relative charge values for applicable LTCH cases for the 
proposed 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 proposed 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 proposed 
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 proposed 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.

[[Page 25544]]

    Step 5--Determine a proposed 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 proposed 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 proposed 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, we are proposing to 
cross-walk each no-volume proposed MS-LTC-DRG to another proposed MS-
LTC-DRG for which we calculated a proposed relative weight (determined 
in accordance with the methodology as previously described). Then, the 
``no-volume'' proposed MS-LTC-DRG is assigned the same proposed 
relative weight (and average length of stay) of the proposed MS-LTC-DRG 
to which it was cross-walked (as described in greater detail in this 
section of this proposed rule).
    Of the 767 proposed 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 we would propose to assign a 
relative weight using our existing ``no-volume'' proposed MS-LTC-DRG 
methodology (that is, 375-11-2-15 = 347). We are proposing to assign 
proposed relative weights to each of the 347 no-volume proposed MS-LTC-
DRGs based on clinical similarity and relative costliness to 1 of the 
remaining 392 (767-375 = 392) proposed MS-LTC-DRGs for which we 
calculated proposed 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'' proposed MS-LTC-DRGs as one of the 392 proposed MS-
LTC-DRGs to which we cross-walked each of the 347 ``no-volume'' 
proposed MS-LTC-DRGs.) Then, we are generally proposing to assign the 
347 no-volume proposed MS-LTC-DRGs the proposed relative weight of the 
cross-walked proposed MS-LTC-DRG. (As explained in Step 6, when 
necessary, we made adjustments to account for nonmonotonicity.)
    We cross-walked the no-volume proposed MS-LTC-DRG to a proposed MS-
LTC-DRG for which we calculated proposed 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 proposed MS-LTC-DRGs in 
FY 2022, the proposed relative weights assigned based on the cross-
walked proposed 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 proposed relative weight of the cross-walked 
proposed MS-LTC-DRG as the proposed relative weight for the no-volume 
proposed MS-LTC-DRG such that both of these proposed MS-LTC-DRGs (that 
is, the no-volume proposed MS-LTC-DRG and the cross-walked proposed MS-
LTC-DRG) have the same proposed relative weight (and average length of 
stay) for FY 2022. We note that, if the cross-walked proposed MS-LTC-
DRG had 25 applicable LTCH cases or more, its proposed relative weight 
(calculated using the methodology as previously described in Steps 1 
through 4) is assigned to the no-volume proposed MS-LTC-DRG as well. 
Similarly, if the proposed MS-LTC-DRG to which the no-volume proposed 
MS-LTC-DRG was cross-walked had 24 or less cases and, therefore, was 
designated to 1 of the proposed low-volume quintiles for purposes of 
determining the proposed relative weights, we assigned the proposed 
relative weight of the applicable proposed low-volume quintile to the 
no-volume proposed MS-LTC-DRG such that both of these proposed MS-LTC-
DRGs (that is, the no-volume proposed MS-LTC-DRG and the cross-walked 
proposed MS-LTC-DRG) have the same proposed relative weight for FY 
2022. (As we noted previously, in the infrequent case where 
nonmonotonicity involving a no-volume proposed MS-LTC-DRG resulted, 
additional adjustments as described in Step 6 are required in order to 
maintain monotonically increasing proposed relative weights.)
    As discussed earlier, for this proposed rule, we are providing the 
list of the no-volume proposed MS-LTC-DRGs and the proposed MS-LTC-DRGs 
to which each was cross-walked (that is, the cross-walked proposed MS-
LTC-DRGs) for FY 2022 in a supplemental data file for public use posted 
via the internet on the CMS website for this proposed 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 proposed methodology for determining the 
proposed relative weights for the proposed FY 2022 MS-LTC-DRGs with no 
applicable LTCH cases, we are providing the following example, which 
refers to the no-volume proposed 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 proposed rule).
    Example: There were no trimmed applicable LTCH cases in the FY 2019 
MedPAR file that we are using for this proposed 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 are 
proposing to assign the same relative weight (and average length of 
stay) of MS-LTC-DRG 70 of 0.8730 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 proposed 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,

[[Page 25545]]

we are proposing to use the best available claims data, if applicable, 
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 are proposing 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, we are proposing to establish 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, we are proposing to establish 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). We propose to establish 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 proposed 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-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 proposed FY 2022 MS-LTC-DRG 
relative weights, consistent with our historical methodology, we are 
proposing to continue 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 proposed FY 2022 MS-
LTC-DRG relative weights in this proposed rule by applying this 
methodology are denoted in Table 11, which is listed in section VI. of 
the Addendum to this proposed rule and is available via the internet on 
the CMS website.
    Step 7--Calculate the proposed 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

[[Page 25546]]

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, we are proposing to update the MS-LTC-DRG classifications 
and relative weights for FY 2022 based on the best available LTCH data 
for applicable LTCH cases, and continue to apply a budget neutrality 
adjustment in determining the FY 2022 MS-LTC-DRG relative weights.
    In this proposed rule, to ensure budget neutrality in the update to 
the MS-LTC-DRG classifications and relative weights under Sec.  
412.517(b), we are proposing to continue to use our established two-
step budget neutrality methodology.
    To calculate the proposed normalization factor for FY 2022, we are 
proposing to group applicable LTCH cases using the proposed FY 2022 
Version 39 GROUPER, and the recalibrated proposed 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 proposed FY 2022. That ratio is the proposed 
normalization factor. Because the calculation of the proposed 
normalization factor involves the proposed relative weights for the 
proposed MS-LTC-DRGs that contained applicable LTCH cases to calculate 
the average CMIs, any low-volume proposed MS-LTC-DRGs are included in 
the calculation (and the proposed MS-LTC-DRGs with no applicable LTCH 
cases are not included in the calculation).
    To calculate the proposed budget neutrality adjustment factor, we 
simulated estimated total FY 2022 LTCH PPS standard Federal payment 
rate payments for applicable LTCH cases using the proposed FY 2022 
normalized relative weights and proposed 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 
proposed FY 2022 MS-LTC-DRG relative weights and the proposed GROUPER 
Version 39. The resulting ratio is the proposed budget neutrality 
adjustment factor. The calculation of the proposed budget neutrality 
factor involves the proposed relative weights for the LTCH cases used 
in the payment simulation, which includes any cases grouped to low-
volume proposed MS-LTC-DRGs, and generally does not include payments 
for cases grouped to a proposed 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 proposed 
relative weight calculation in step 2 that are grouped to a proposed 
MS-LTC-DRG with no applicable LTCH cases are included in the payment 
simulations used to calculate the proposed budget neutrality factor. 
However, the number and payment amount of such cases have a negligible 
impact on the proposed budget neutrality factor calculation).
    In this proposed rule, to ensure budget neutrality in the update to 
the MS-LTC-DRG classifications and relative weights under Sec.  
412.517(b), we are proposing to continue to use our established two-
step budget neutrality methodology. Therefore, in this proposed rule, 
in the first step of our MS-LTC-DRG budget neutrality methodology, for 
FY 2022, we are proposing to calculate and apply a proposed 
normalization factor to the recalibrated proposed 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 proposed changes to the classification system. That 
is, the proposed normalization adjustment is intended to ensure that 
the recalibration of the proposed MS-LTC-DRG relative weights (that is, 
the process itself) neither increases nor decreases the average case-
mix index.
    To calculate the proposed 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 proposed FY 2022 GROUPER (that is, proposed 
Version 39 for FY 2022) and the recalibrated proposed 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 proposed MS-
LTC-DRG relative weights for FY 2022, each recalibrated proposed MS-
LTC-DRG relative weight is multiplied by the proposed normalization 
factor of 1.25811 (determined in Step 1.c.) in the first step of the 
proposed 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 proposed rule, for FY 2022, under the second step 
of the budget neutrality methodology, we are proposing to determine the 
proposed 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 
proposed normalized relative weights for FY 2022 and proposed 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.)

[[Page 25547]]

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 proposed FY 2022 MS-LTC-DRG relative weights, each 
proposed normalized relative weight is then multiplied by a budget 
neutrality factor of 1.000275 (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 proposed FY 2022 MS-LTC-DRG 
relative weights in this proposed rule, consistent with our existing 
methodology, we are proposing to apply a normalization factor of 
1.25811 and a budget neutrality factor of 1.000275. Table 11, which is 
listed in section VI. of the Addendum to this proposed rule and is 
available via the internet on the CMS website, lists the proposed MS-
LTC-DRGs and their respective proposed 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. Proposed Changes to the LTCH PPS Payment Rates and Other Proposed 
Changes to the LTCH PPS for FY 2022

1. Overview of Development of the Proposed 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 412.535. In this section, we discuss the factors that we are 
proposing to use 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 proposed rule, we present our 
proposed policies related to the annual update to the LTCH PPS standard 
Federal payment rate for FY 2022.
    The proposed update to the LTCH PPS standard Federal payment rate 
for FY 2022 is presented in section V.A. of the Addendum to this 
proposed rule. The components of the proposed 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 VII.C.2.c. of the 
preamble of this proposed rule). We are also proposing to make 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 
proposed rule). (We note that we are not making any proposals which 
would change the proposed 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. Proposed 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 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. Proposed 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

[[Page 25548]]

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 multifactor productivity adjustment (MFP). In 
this proposed rule, we are proposing to use the iBoxx AAA Corporate 
Bond Yield index instead of the Moody's AAA Corporate Bond Yield index. 
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 history of the two series are very similar. Over the historical 
time period of FY 2001 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 series. However, given the 
relatively small weight for this cost category, replacing the Moody's 
series with the iBoxx series does not impact the historical top-line 
market basket increases when rounded to the nearest tenth of a 
percentage point over the past ten fiscal years (FY 2011 to FY 2020). 
Therefore, 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.
    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 proposed rule, we are proposing to use 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 multifactor 
productivity (MFP) adjustment''). 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. Proposed 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 proposed 
rule.)
d. Proposed Annual Market Basket Update Under the LTCH PPS for FY 2022
    Consistent with our historical practice, we estimate the market 
basket increase and the MFP adjustment based on IGI's forecast using 
the most recent available data. Based on IGI's fourth quarter 2020 
forecast, the FY 2022 full market basket estimate for the LTCH PPS 
using the 2017-based LTCH market basket is 2.4 percent. The current 
estimate of the MFP adjustment for FY 2022 based on IGI's fourth 
quarter 2020 forecast is 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, that is, the MFP adjustment as 
previously noted, described in section 1886(b)(3)(B)(xi)(II) of the 
Act. Consistent with the statute, we are proposing to reduce the full 
estimated FY 2022 market basket increase by the FY 2022 MFP adjustment. 
To determine the proposed market basket increase for LTCHs for FY 2022, 
as reduced by the proposed MFP adjustment, consistent with our 
established methodology, we are subtracting the proposed FY 2022 MFP 
adjustment from the estimated FY 2022 market basket increase. (For 
additional details on our established methodology for adjusting the 
market basket increase by the MFP 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 
MFP 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 this FY 2022 IPPS/LTCH PPS proposed rule, in accordance with the 
statute, we are proposing 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 
MFP 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 are proposing to establish an annual market 
basket update to the LTCH PPS standard Federal payment rate for FY 2022 
of 2.2

[[Page 25549]]

percent (that is, the most recent estimate of the LTCH PPS market 
basket increase of 2.4 percent less the MFP 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 are proposing 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 are proposing 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 are proposing to use a more recent estimate 
of the market basket and the MFP 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 are also proposing 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 this proposed rule).

IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers

    In this section of the preamble of this proposed rule, we are 
seeking public comment on two focus areas, and are also proposing 
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 this proposed 
rule, we are proposing 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 are issuing 
this request for information (RFI). The purpose of this RFI is to 
gather broad public input solely for planning purposes for our 
transition to digital quality measurement. Any updates to specific 
program requirements related to providing data for quality measurement 
and reporting provisions would be addressed through future rulemaking, 
as necessary. This RFI contains 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.\966\ 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.
---------------------------------------------------------------------------

    \966\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    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).\967\ 
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.
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    \967\ What are patient generated health data: https://www.healthit.gov/topic/otherhot-topics/what-are-patient-generated-health-data.
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    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

[[Page 25550]]

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.
    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).\968\ 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.\969\ 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).\970\
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    \968\ 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.
    \969\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
    \970\ 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 [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.\971\ 
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.
---------------------------------------------------------------------------

    \971\ 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.
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    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 this section we seek 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 seek 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 note 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 proposed rule. In this 
section, we are seeking comment on the potential definition of dQMs in 
this RFI.
    We also seek feedback on how leveraging advances in technology (for

[[Page 25551]]

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.\972\ 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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    \972\ 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 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 strongly 
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 are requesting 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

[[Page 25552]]

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 drawn from 
associations, as data are received, to ensure high quality data are 
used for measurement.
    We are seeking feedback on the goal of aligning data needed for 
quality measurement with interoperability requirements and the 
strengths and limitations of this approach. We are also seeking 
feedback on the importance of and approaches to supporting inclusion of 
PGHD and other currently non-standardized data. We also welcome 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 seek 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 are 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

[[Page 25553]]

(MIPS) program are potential examples \973\ 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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    \973\ 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.
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    We seek feedback on aggregation of data from multiple sources to 
inform measurement and potential policy considerations. We also seek 
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.\974\ It would focus on the 
quality domains of safety, 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.
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    \974\ 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 seek 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 seek 
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
    As noted previously, we seek input on the future development of the 
following:
     Definition of Digital Quality Measures. We are seeking 
feedback on the following as described in section IX.A.2. of the 
preamble of this proposed 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 welcome more specific 
comments on the attributes or functions to support such an approach of 
deploying dQMs.
     Use of FHIR for Current eCQMs. We are seeking feedback on 
the following as described in section IX.A.3. of the preamble of this 
proposed 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 are seeking feedback on the following as described in section 
IX.A.4.a. of the preamble of this proposed 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 are seeking feedback on the following as described in section 
IX.A.4.b. of the preamble of this proposed 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

[[Page 25554]]

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 seek feedback on the following as described in section 
IX.A.4.c. of the preamble of this proposed 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 seek feedback on the following as described in section 
IX.A.4.d. of the preamble of this proposed rule:
    -- What are initial priority areas for the dQM portfolio given 
evolving interoperability requirements (for example, measurement areas, 
measure requirements, tools)?
    -- We also seek 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.
    Commenters should 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 Request for Information in the 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.

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 look forward 
to receiving feedback on these topics and note for readers that 
responses to the RFI will not directly impact payment decisions. 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.975 976 977 978 979 980 981 982 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 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.983 984 985 986 987 988 Readmission rates for 
common conditions in the Hospital Readmissions Reduction Program are 
higher for Black

[[Page 25555]]

Medicare beneficiaries and higher for Hispanic Medicare beneficiaries 
with Congestive Heart Failure and Acute Myocardial 
Infarction.989 990 991 992 993 Studies have also shown that 
African Americans are significantly more likely than White Americans to 
die prematurely from heart disease and stroke.\994\ 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.995 996 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.'' \997\ 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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    \975\ 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.
    \976\ 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.
    \977\ 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.
    \978\ 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.
    \979\ 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.
    \980\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \981\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \982\ 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.
    \983\ 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.
    \984\ 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.
    \985\ 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.
    \986\ 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.
    \987\ 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.
    \988\ 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.
    \989\ 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.
    \990\ 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.
    \991\ 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.
    \992\ 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.
    \993\ 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.
    \994\ Health and Human Services. Heart disease and African 
Americans. (March 29, 2021). https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \995\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \996\ 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/.
    \997\ 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.\998\ 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.'' \999\ 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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    \998\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \999\ 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, local, and tribal 
organizations; providers; researchers; policymakers; beneficiaries and 
their families; and other stakeholders in activities to achieve health 
equity.\1000\ 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.\1001\ The CMS Quality Strategy \1002\ and Meaningful 
Measures Framework \1003\ 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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    \1000\ 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.
    \1001\ 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.
    \1002\ 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.
    \1003\ 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.\1004\
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    \1004\ 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 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.\1005\
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    \1005\ 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.\1006\
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    \1006\ 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

[[Page 25556]]

reduce readmissions in diverse populations.\1007\
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    \1007\ 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.\1008\
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    \1008\ 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) \1009\ and the Office of the 
Assistant Secretary for Planning and Evaluation (ASPE) \1010\ 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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    \1009\ 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.
    \1010\ 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).\1011\ 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 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 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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    \1011\ 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 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

[[Page 25557]]

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. One 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 account 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,\1012\ 
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.
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    \1012\ 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.\1013\ These results underscore the importance of 
continuing to make health care equity information more available to 
providers to promote quality improvement.
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    \1013\ 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.\1014\ 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 are seeking 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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    \1014\ 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.\1015\ 
The 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.\1016\ Another example, the ``Race & Ethnicity--CDC'' code 
system in PHIN Vocabulary Access and Distribution System (VADS) \1017\ 
permits a much 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

[[Page 25558]]

aggregation and reporting using the OMB standard. ONC includes both the 
CDC and OMB standards in its criterion for certified health IT 
products.\1018\ 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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    \1015\ Revisions to the standards for the classification of 
Federal data on race and ethnicity. 62 FR 58782-58790.
    \1016\ https://www.census.gov/topics/population/hispanic-origin/about.html.
    \1017\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
    \1018\ 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.
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    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.\1019\ 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.1020 1021 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.\1022\ Incorrectly classified race or ethnicity may 
result in overestimation or underestimation in the quality of care 
received by certain groups of beneficiaries.
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    \1019\ 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.
    \1020\ 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.
    \1021\ Eicheldinger, C., & Bonito, A. (2008). More accurate 
racial and ethnic codes for Medicare administrative data. Health 
Care Financing Review, 29(3), 27-42.
    \1022\ 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 
\1023\ 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.\1024\ 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.\1025\
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    \1023\ 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.
    \1024\ 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.
    \1025\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
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    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.\1026\ Indirectly estimated data 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.\1027\
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    \1026\ 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.
    \1027\ 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.
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    As described earlier, we previously supported the development of 
two such methods of indirect estimation of race and ethnicity among 
Medicare

[[Page 25559]]

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).\1028\ 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.\1029\
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    \1028\ 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.
    \1029\ 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.
---------------------------------------------------------------------------

    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.\1030\ 
Validation testing reveals concordance of 0.88-0.95 between indirectly 
estimated and self-report among individuals who identify as White, 
Black, Hispanic and API for the MIBSG version 2.0 and concordance with 
self-reported race and ethnicity of 0.96-0.99 for these same groups for 
MBISG version 2.1.1031 1032 The algorithms under 
consideration are considerably less accurate for individuals who self-
identify as American Indian/Alaskan Native or multiracial.\1033\ 
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.
---------------------------------------------------------------------------

    \1030\ 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.
    \1031\ 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.
    \1032\ 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.
    \1033\ 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 feel 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 
are interested in learning more about, and soliciting 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.\1034\ 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.\1035\ This could 
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.
---------------------------------------------------------------------------

    \1034\ 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.
    \1035\ 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

[[Page 25560]]

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 are interested in learning about, and are soliciting 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 are interested in 
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 \1036\) 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 \1037\). 
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.
---------------------------------------------------------------------------

    \1036\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
    \1037\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
---------------------------------------------------------------------------

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.\1038\
---------------------------------------------------------------------------

    \1038\ 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.
---------------------------------------------------------------------------

    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.\1039\
---------------------------------------------------------------------------

    \1039\ 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 are currently seeking comment on the possibility of expanding 
our current disparities methods to include reporting by race and 
ethnicity using indirect estimation. We are also seeking 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 are seeking comment on the design of a 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 look forward to receiving feedback on these topics and note for 
readers that responses to the RFI will not directly impact payment 
decisions. We also note our intention for additional RFI or rulemaking 
on this topic in the future.
    Specifically, we are inviting 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

[[Page 25561]]

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 
and disparity measures.
    ++ Interventions hospitals could institute to improve a low 
hospital equity score and how improved demographic data could assist 
with these efforts.

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);
     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 are not 
proposing any changes to these policies in this 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 are not proposing any changes to our policies 
regarding measure removal in this 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

[[Page 25562]]

and providers. We are not proposing any changes to these policies in 
this 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. Proposals To Adopt New Measures for the Hospital IQR Program Measure 
Set
    In this proposed rule, we are proposing 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 would 
run from July 1, 2022 through June 30, 2023, and 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. The following sections discuss these proposals in more 
detail.
a. Proposed 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.\1040\ 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.\1041\ Similar to maternal mortality, maternal 
morbidity is highly preventable.\1042\ Without proper treatment, 
maternal morbidities can lead to mortality.\1043\ 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.\1044\ Timely and appropriate 
treatment of maternal morbidities is imperative to prevent 
complications that can lead to maternal mortality.\1045\
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    \1040\ 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/.
    \1041\ 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/.
    \1042\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17.
    \1043\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17-B22.
    \1044\ 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.
    \1045\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3): B17.
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    One of the main factors contributing to the increase in maternal 
morbidity and mortality is inconsistent obstetric practice.\1046\ 
Hospitals in the U.S. lack standardized protocols to address obstetric 
emergencies and complications that arise during pregnancy and 
childbirth.\1047\ A standardized approach to address these concerns is 
necessary to effectively manage obstetric emergencies and 
complications.\1048\ 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.
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    \1046\ 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/.
    \1047\ 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/.
    \1048\ 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 this proposed rule, we are proposing to adopt the 
Maternal Morbidity Structural Measure (Maternal Morbidity measure), 
beginning with a shortened reporting period running from October 1, 
2021 through December 31, 2021, affecting the FY 2023 payment 
determination, to help address this maternal health crisis. After 
which, the reporting period would 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.\1049\ This measure would: (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.
---------------------------------------------------------------------------

    \1049\ 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.
---------------------------------------------------------------------------

    State level QI programs have been shown to be effective in 
decreasing maternal morbidity.\1050\ One controlled trial conducted at 
147 California hospitals utilizing a QI toolkit, which

[[Page 25563]]

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.\1051\ We believe the Maternal Morbidity 
measure will help us better understand the current efforts of hospitals 
to improve nationwide inpatient maternal morbidity.
---------------------------------------------------------------------------

    \1050\ 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.
    \1051\ 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.\1052\ The implementation of triggers, bundles, protocols, and 
checklists have been shown to improve the quality and safety of 
obstetric care delivery.\1053\ Triggers are used to identify an event 
that mandates further action by a healthcare professional, which then 
facilitates timely intervention and patient safety.\1054\ Examples of 
triggers include hypertension greater than 180/110 and fever 
(temperature over 38.5[deg]C).\1055\ Bundles are a collection of 
interventions such as checklists, protocols, and educational materials 
that target a specific morbidity such as hypertension or 
hemorrhage.\1056\ 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.\1057\ These 
evidence-based tools also facilitate improvements in timely diagnosis 
and treatment that serve to prevent morbidity.\1058\ This measure would 
allow us to assess hospital participation in QI collaborative programs 
in the inpatient setting and the implementation of safety practices or 
bundles.
---------------------------------------------------------------------------

    \1052\ 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.
    \1053\ 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.
    \1054\ 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.
    \1055\ 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.
    \1056\ 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.
    \1057\ 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.
    \1058\ 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.
---------------------------------------------------------------------------

    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.'' \1059\ Because many of the 
factors contributing to maternal morbidity are preventable, this 
measure would 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.
---------------------------------------------------------------------------

    \1059\ 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.
---------------------------------------------------------------------------

(2) Overview of Measure
    To report on this measure, hospitals would 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 implemented patient safety 
practices or bundles related to maternal morbidity to address 
complications, including, but not limited to, hemorrhage, severe 
hypertension/preeclampsia or sepsis?'' Hospitals would 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 
would 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'' \1060\ (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.\1061\ 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?'' 
\1062\ The MAP Hospital Workgroup's preliminary recommendation was to 
not support MUC2019-114 Maternal Morbidity for rulemaking, with 
potential for mitigation.\1063\
---------------------------------------------------------------------------

    \1060\ 2019 Measures Under Consideration. Information available 
at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91406.
    \1061\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
    \1062\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
    \1063\ 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

[[Page 25564]]

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.\1064\ To address 
the MAP's feedback regarding the measure's usability, we made the 
aforementioned change to the measure, thereby clarifying that the 
measure would 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).
---------------------------------------------------------------------------

    \1064\ 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.\1065\ 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?'' \1066\ Upon the review of the 
measure, the MAP Coordinating Committee conditionally supported 
MUC2019-114 Maternal Morbidity for rulemaking.\1067\
---------------------------------------------------------------------------

    \1065\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \1066\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \1067\ 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.\1068\ 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.
---------------------------------------------------------------------------

    \1068\ 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.\1069\ 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.
---------------------------------------------------------------------------

    \1069\ 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.\1070\ 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 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.''
---------------------------------------------------------------------------

    \1070\ 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 and receive endorsement.\1071\ The MAP Coordinating Committee 
underscored that maternal morbidity is increasing at an alarming rate 
in the U.S., nearly doubling in the last decade.\1072\ With no quality 
measures that address maternal morbidity, the MAP Coordinating 
Committee strongly supported our attempts to address this healthcare 
crisis through measurement.\1073\
---------------------------------------------------------------------------

    \1071\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \1072\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \1073\ 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 are proposing 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 are proposing 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 are 
proposing that the reporting period would be: January 1 through 
December 31.

[[Page 25565]]

    We propose 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.8.i. of the preamble of this 
proposed rule for more details on our data submission and deadline 
requirements for structural measures.
    We invite public comment on our proposal to adopt the Maternal 
Morbidity measure beginning with a shortened reporting period running 
from October 1, 2021 through December 31, 2021, affecting the FY 2023 
payment determination, followed by the annual reporting period of 
January 1 through December 31 for the FY 2024 payment determination and 
subsequent years.
b. Proposed 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.\1074\ 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.\1075\ \1076\ 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.\1077\ \1078\ \1079\ 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 as much as $73.5 to $735 
billion.1080 1081 1082
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    \1074\ James JT. A new, evidence-based estimate of patient harms 
associated with hospital care. Journal of patient safety. 2013; 
9(3):122-128.
    \1075\ 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.
    \1076\ 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.
    \1077\ 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.
    \1078\ 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.
    \1079\ 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.
    \1080\ 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.
    \1081\ 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.
    \1082\ 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.
---------------------------------------------------------------------------

    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.\1083\ Now, we are interested in also measuring hospital 
performance across a broader set of patients and across more areas of 
the hospital.
---------------------------------------------------------------------------

    \1083\ 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.\1084\
---------------------------------------------------------------------------

    \1084\ 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 
proposed 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.\1085\

[[Page 25566]]

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. of the preamble of this proposed rule for more 
detail on the core clinical data elements used in this measure.
---------------------------------------------------------------------------

    \1085\ 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.\1086\ The MAP expressed concern regarding 
the potential unintended consequences of unnecessary interventions for 
patients at the end of life.\1087\ 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.
---------------------------------------------------------------------------

    \1086\ 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.
    \1087\ 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 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.\1088\ 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.\1089\
---------------------------------------------------------------------------

    \1088\ 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.
    \1089\ 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.\1090\
---------------------------------------------------------------------------

    \1090\ 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.\1091\ We note that by proposing to adopt 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.\1092\ Thereafter, the NQF endorsed 
the Hybrid HWM measure on October 23, 2019.\1093\ The MAP also 
recommended the Hybrid HWM measure have a voluntary reporting period 
before mandatory implementation.\1094\ Our 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 
proposed rule.
---------------------------------------------------------------------------

    \1091\ 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.
    \1092\ 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.
    \1093\ National Quality Forum. Available at: https://www.qualityforum.org/QPS/3502.
    \1094\ 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

[[Page 25567]]

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 would 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 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.
(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) 
\1095\ 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.\1096\ 
The Hybrid HWM measure uses those CCS categories as part of cohort 
specification and risk-adjustment, including the 15 service-line risk 
models.
---------------------------------------------------------------------------

    \1095\ Clinical Classifications Software Refined (CCSR) https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp.
    \1096\ 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

[[Page 25568]]

Factors Measure Methodology Report Version 2.0.\1097\
---------------------------------------------------------------------------

    \1097\ 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.\1098\
---------------------------------------------------------------------------

    \1098\ 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 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 221099 1100 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).
---------------------------------------------------------------------------

    \1099\ 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.
    \1100\ 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.

[[Page 25569]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.273

    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 \1101\--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.\1102\
---------------------------------------------------------------------------

    \1101\ 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.
    \1102\ 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 would 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 would 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 would 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

[[Page 25570]]

``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.\1103\
---------------------------------------------------------------------------

    \1103\ 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.\1104\
---------------------------------------------------------------------------

    \1104\ 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 would start with voluntary reporting in 
response to the MAP recommendation before requiring data submission. We 
believe that taking an incremental approach to implementing this 
proposed measure would 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 are proposing 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 would 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 
would include four quarters of data. Specifically, the voluntary 
reporting period would 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 would be required no later than the first 
business day 3 months following the end of the reporting period).
    We are proposing that mandatory reporting would 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 would be required to submit the core clinical data elements 
and linking variables within 3 months following the end of the 
applicable reporting period (submissions would be required no later 
than the first business day 3 months following the end of the reporting 
period). This proposed 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), 
here, we are only proposing to have one voluntary reporting period for 
the Hybrid HWM measure, which would 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 would 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 are proposing that 
hospitals would 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 
would 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 would need to 
submit the core clinical data elements included in the Hybrid HWM 
measure, as 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 would 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

[[Page 25571]]

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 would 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 would 
be included in the risk adjustment model.
(d) Linking Variables and Other Data Elements
    Hospitals would 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 would 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) Proposed Voluntary Reporting Period
    Under this proposal, we would not publicly report data collected 
during the voluntary reporting period. Hospitals that submit data for 
this measure during the voluntary reporting period would 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 
would 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 are proposing 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 would be included in the July 2025 refresh of the Care Compare 
website or its successor website.
    The EHR data would be merged with the associated claims data, and 
then Hybrid HWM measure results would 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 would 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.8.f. of the preamble of this 
proposed rule for more details and proposals related to data submission 
requirements for hybrid measures, including the Hybrid HWM measure.
    We invite public comment on our proposal to adopt the Hybrid 
Hospital-Wide Mortality Measure with Claims and Electronic Health 
Record Data (NQF #3502) (Hybrid HWM measure) into the Hospital IQR 
Program, beginning with voluntary reporting period which would 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, and 
subsequent years.
c. Proposal To Adopt 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).\1105\ COVID-19 is a contagious respiratory infection 
\1106\ 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.\1107\
---------------------------------------------------------------------------

    \1105\ 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.
    \1106\ 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.
    \1107\ 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.
---------------------------------------------------------------------------

    As of April 2, 2021 the U.S. reported over 30 million cases of 
COVID-19 and over 550,000 COVID-19 deaths.\1108\ Hospitals and health 
systems saw significant surges of COVID-19 patients as community 
infection levels increased.\1109\ From December 2, 2020 through January 
30, 2021, more than 100,000 Americans were in the hospital with COVID-
19 at the same time.\1110\
---------------------------------------------------------------------------

    \1108\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \1109\ 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.
    \1110\ US Currently Hospitalized [bond] 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.\1111\

[[Page 25572]]

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.\1112\ 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.\1113\ Experts believe that 
COVID-19 spreads less commonly through contact with a contaminated 
surface (although that is not thought to be a common way that COVID-19 
spreads),\1114\ and that in certain circumstances, infection can occur 
through airborne transmission.\1115\ 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.\1116\ Although 
personal protective equipment (PPE) and other infection-control 
precautions can reduce the likelihood of transmission in health care 
settings, COVID-19 can 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.\1117\ The CDC has emphasized that 
health care settings, including long-term care settings, can be high-
risk places for COVID-19 exposure and transmission.\1118\
---------------------------------------------------------------------------

    \1111\ 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.
    \1112\ 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.
    \1113\ 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.
    \1114\ 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.
    \1115\ 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.
    \1116\ 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.
    \1117\ 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.
    \1118\ 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.\1119\ On December 11, 2020, the FDA issued the 
first Emergency Use Authorization (EUA) for a COVID-19 vaccine in the 
U.S.\1120\ Subsequently, the FDA issued EUAs for additional COVID-19 
vaccines.\1121\
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    \1119\ 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.
    \1120\ 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.
    \1121\ 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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    The 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.\1122\
---------------------------------------------------------------------------

    \1122\ 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.\1123\ 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.\1124\ 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.\1125\ Research suggests most states followed this 
recommendation,\1126\ and HCP began receiving the vaccine in mid-
December of 2020.\1127\
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    \1123\ 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/.
    \1124\ 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.
    \1125\ 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.
    \1126\ 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/.
    \1127\ Associated Press. `Healing is Coming:' U.S. 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.\1128\ As of April 3, 2021, the CDC reported that over 162 
million doses of the COVID-19 vaccine had been administered, and 
approximately 60 million people had received a complete vaccination 
course.\1129\ President Biden indicated on April 6, 2021 that the 
United States has

[[Page 25573]]

sufficient vaccine supply to make every adult eligible to receive a 
vaccine beginning April 19, 2021.\1130\
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    \1128\ 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.
    \1129\ CDC. COVID Data Tracker. COVID-19 Vaccinations in the 
United States. Accessed on 2/18/21 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \1130\ The White House. Remarks by President Biden Marking the 
150 Millionth COVID-19 Vaccine Shot. Accessed April 8, 2021 at: 
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/06/remarks-by-president-biden-marking-the-150-millionth-covid-19-vaccine-shot/.
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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, we are proposing 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 are proposing 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.\1131\ Data from influenza 
vaccination demonstrates that provider uptake of the vaccine is 
associated with that provider recommending vaccination to 
patients,\1132\ and we believe HCP COVID-19 vaccination in hospitals 
could similarly increase uptake among that patient population.
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    \1131\ 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.
    \1132\ 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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    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 submission period, 
excluding persons with contraindications to COVID-19 vaccination that 
are described by the CDC.\1133\
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    \1133\ 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 submission 
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.\1134\ Vaccination coverage 
for the purposes of this measure is defined as the estimated percentage 
of HCP eligible to work at the IPF for at least one day who received a 
completed vaccination course. 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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    \1134\ Measure Application Partnership 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) 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.\1135\ When the MAP Hospital 
Workgroup convened on January 11, 2021, it reviewed the measures on the 
MUC List, including the COVID-19 HCP vaccination measure.\1136\ 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.\1137\ 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.\1138\
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    \1135\ 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.
    \1136\ The MUC List and the MAP referred to the measure as the 
``SARS-CoV-2 Vaccination Coverage Among Healthcare Personnel.''
    \1137\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1138\ 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.\1139\ 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.\1140\ 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.'' \1141\ In its final report, the MAP 
noted that the measure would

[[Page 25574]]

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.\1142\ The 
spreadsheet of final recommendations no longer cited concerns regarding 
evidence, testing, or NQF endorsement.\1143\
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    \1139\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1140\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1141\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1142\ 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.
    \1143\ 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 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 
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.\1144\ 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 IQR Program.
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    \1144\ 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. CMS will consider the potential for 
future NQF endorsement as part of its ongoing work with the MAP.
    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 are proposing that for the FY 2023 program year, the reporting 
period would be from October 1, 2021 through December 31, 2021. The 
reporting period we are proposing 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 propose 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 are proposing that hospitals 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 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 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 are proposing that the CDC would calculate a single quarterly COVID-
19 HCP vaccination coverage rate for each hospital, which would be 
calculated by taking the average of the data from the three weekly 
rates submitted by the hospital for that quarter. If finalized, CMS 
would publicly report each quarterly COVID-19 HCP vaccination coverage 
rate as calculated by the CDC.
    As described in section IX.C.10.c.2.a., hospitals would 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 invite public comment on our proposal to add a new measure, 
COVID-

[[Page 25575]]

19 Vaccination Coverage Among HCP, to the Hospital IQR Program, 
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 for subsequent years.
d. Proposal To Adopt Two Medication-Related Adverse Event Electronic 
Clinical Quality Measures Beginning With the CY 2023 Reporting Period/
FY 2025 Payment Determination
    In this proposed rule, we are proposing 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); and (2) Hospital Harm--Severe 
Hyperglycemia eCQM (NQF#3533e). 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.
(1) Proposed 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.\1145\ Hypoglycemic events are among the most common 
adverse drug events in hospitals.1146 1147 1148 1149 
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.1150 1151 Most individuals with hypoglycemia 
recover fully, but in rare instances, hypoglycemia can progress to coma 
and death.\1152\
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    \1145\ 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).
    \1146\ 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.
    \1147\ 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.
    \1148\ 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.
    \1149\ 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.
    \1150\ 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.
    \1151\ 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.
    \1152\ 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.
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    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.\1153\ 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).\1154\ Hypoglycemia is associated 
with higher in-hospital mortality, increased length of stay, and 
consequently, increased resource utilization.\1155\
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    \1153\ 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.
    \1154\ 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.
    \1155\ 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.1156 1157 1158 1159 Severe hypoglycemia 
rates have been reported to range from 2.3-5 percent of hospitalized 
patients with diabetes, and from 0.4 percent of non-ICU patient days to 
1.9 percent of ICU patient days.1160 1161 1162 Severe 
hypoglycemic events are largely avoidable by careful use of anti-
diabetic medication and close monitoring of blood glucose 
values.1163 1164 1165
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    \1156\ Hospital Harm--Severe Hypoglycemia (NQF #3503e) Available 
at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3503.
    \1157\ 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.
    \1158\ 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.
    \1159\ Krinsley JS, Grover A. Severe hypoglycemia in critically 
ill patients: risk factors and outcomes. Crit Care Med. 2007 Oct; 
35(10):2262-7.
    \1160\ 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.
    \1161\ 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.
    \1162\ 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.
    \1163\ 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).
    \1164\ 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.
    \1165\ 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.
---------------------------------------------------------------------------

    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.1166 1167 Unlike the

[[Page 25576]]

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.\1168\
---------------------------------------------------------------------------

    \1166\ 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.
    \1167\ 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.
    \1168\ 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 are proposing 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.\1169\ 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.'' \1170\
---------------------------------------------------------------------------

    \1169\ Hospital Harm--Severe Hypoglycemia (NQF #3503e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3503.
    \1170\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
---------------------------------------------------------------------------

    This measure is a re-specification of another hypoglycemia measure 
originally endorsed by the NQF, Glycemic Control--Hypoglycemia (NQF 
#2363).\1171\ 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.\1172\ 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.
---------------------------------------------------------------------------

    \1171\ Glycemic Control--Hyperglycemia NQF#2363. Available at: 
http://www.qualityforum.org/QPS/2363e.
    \1172\ 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.'' \1173\ 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.1174 1175 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.\1176\ 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 2019.1177 1178
---------------------------------------------------------------------------

    \1173\ Measures Under Consideration List December 1, 2018. 
Available at http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=88812.
    \1174\ 2018-2019 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \1175\ 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.
    \1176\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Preliminary Recommendations. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \1177\ NQF October 2019 CSAC Endorsement. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91440.
    \1178\ 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 proposed 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

[[Page 25577]]

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.1179 1180 1181 1182 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.1183 1184 1185 
These causes are largely controllable in hospital environments, and 
risk can be reduced by following best practices. We would continue to 
evaluate the appropriateness of risk adjustment in measure 
reevaluation.
---------------------------------------------------------------------------

    \1179\ 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.
    \1180\ 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.
    \1181\ 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.
    \1182\ 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.
    \1183\ 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).
    \1184\ 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.
    \1185\ 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 invite public comment on our proposal to adopt the Hospital 
Harm--Severe Hypoglycemia eCQM for the CY 2023 reporting period/FY 2025 
payment determination and for subsequent years. We refer readers to 
section IX.C.5.d.1. of the preamble of this proposed rule for a similar 
proposal to adopt this eCQM under the Medicare Promoting 
Interoperability Program. We also refer readers to section IX.C.8.e.2. 
of the preamble of this proposed rule for additional proposals related 
to eCQM certification requirements under the Hospital IQR Program.
(2) Proposed 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.1186 1187 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.\1188\ 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.1189 1190 1191 1192 1193 1194 1195 1196 1197 The rate 
of severe hyperglycemia varies across hospitals, which suggests there 
are opportunities for improvement in inpatient glycemic 
management.1198 1199 Rates of inpatient

[[Page 25578]]

severe hyperglycemic events can be considered an indicator for quality 
of hospital care, since inpatient hyperglycemia is largely avoidable 
with proper glycemic management.1200 1201 1202 The use of 
evidence-based standardized protocols and insulin management protocols 
have been shown to improve glycemic control and 
safety.1203 1204 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.
---------------------------------------------------------------------------

    \1186\ 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.
    \1187\ 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.
    \1188\ 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).
    \1189\ 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).
    \1190\ 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.
    \1191\ 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.
    \1192\ 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.
    \1193\ 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.
    \1194\ 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.
    \1195\ 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.
    \1196\ 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.
    \1197\ 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.
    \1198\ 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.
    \1199\ 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.
    \1200\ 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.
    \1201\ 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.
    \1202\ 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.
    \1203\ 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.
    \1204\ 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.
---------------------------------------------------------------------------

(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.\1205\ 
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.''\1206\
---------------------------------------------------------------------------

    \1205\ Hospital Harm--Severe Hyperglycemia (NQF #3533e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3533.
    \1206\ 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 Measures Under Consideration for 
December 1, 2019.'' \1207\ 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.\1208\ The MAP recommended 
monitoring the implementation of the measure using the severe high 
blood glucose threshold of >300mg/dL for defining harm events to assess 
for unintended measurement consequences, such as hypoglycemia.\1209\ 
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.1210 1211 1212 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.\1213\
---------------------------------------------------------------------------

    \1207\ Measures Under Consideration List December 1, 2019. 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91406.
    \1208\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1209\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1210\ NQF Scientific Methods Panel October 2019 Meeting Summary 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91486.
    \1211\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1212\ 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.
    \1213\ 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 proposed 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.1214 1215 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 proposed measure, which focuses 
specifically on severe hyperglycemic events in the hospital setting, 
has the potential to reduce preventable harm. Therefore, we are 
proposing to adopt the Hospital Harm--Severe Hyperglycemia eCQM (NQF # 
3533e) beginning with the CY 2023 reporting period/FY 2025 payment 
determination.
---------------------------------------------------------------------------

    \1214\ Glycemic Control--Hyperglycemia (NQF # 2362e). Available 
at: http://www.qualityforum.org/QPS/2362e.
    \1215\ Hospital Harm--Severe Hyperglycemia (NQF #3533e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3533.
---------------------------------------------------------------------------

(c) Data Sources
    The proposed 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

[[Page 25579]]

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.1216 1217 1218 The rate of 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.1219 1220 1221 We would continue 
to evaluate the appropriateness of risk adjustment in measure 
reevaluation.
---------------------------------------------------------------------------

    \1216\ 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.
    \1217\ 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.
    \1218\ 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.
    \1219\ 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.
    \1220\ 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.
    \1221\ 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 invite public comment on our proposal to adopt the Hospital 
Harm--Severe Hyperglycemia eCQM for the CY 2023 reporting period/FY 
2025 payment determination and for subsequent years. We refer readers 
to section IX.F.5.d.2 of the preamble of this proposed rule for a 
similar proposal to adopt the Hospital Harm--Severe Hyperglycemia eCQM 
under the Medicare Promoting Interoperability Program. We also refer 
readers to section IX.C.8.e.2. of the preamble of this proposed rule 
for additional proposals related to eCQM certification requirements 
under the Hospital IQR Program.
6. Proposed 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 this proposed rule, we are proposing to remove five 
measures from the Hospital IQR Program across the FY 2023 and FY 2026 
payment determinations as further discussed in this rule.
a. Proposal To Remove 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 this proposed rule, we are proposing 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 this proposed rule, we propose the Hybrid HWM measure (NQF #3502). 
We refer readers to section IX.C.5.b. 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

[[Page 25580]]

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 much 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 invite public comment on our proposal to remove the Death Among 
Surgical Inpatients with Serious Treatable Complications (CMS PSI-04) 
measure beginning with the FY 2023 payment determination.
b. Proposal To Remove 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). We 
are proposing to remove PC-05 beginning with the CY 2024 reporting 
period/FY 2026 payment determination under 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 are 
proposing 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 proposed rule for more 
detail on that proposed measure. We believe that the proposed Maternal 
Morbidity structural measure is more strongly aligned with our current 
focus on maternal health than the PC-05 eCQM. The proposed Maternal 
Morbidity Structural Measure focuses on determining 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, 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 proposed 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 would be overlap 
with the proposed Maternal Morbidity Structural Measure in the program 
until PC-05 would be removed. The proposed Maternal Morbidity 
Structural Measure would have a reporting period beginning on October 
1, 2021 through December 31, 2021, affecting the FY 2023 payment 
determination, which would 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 adoption of 
the Maternal Morbidity Structural Measure.
    We invite public comment on our proposal to remove the Exclusive 
Breast Milk Feeding (PC-05) measure beginning with the CY 2024 
reporting period/FY 2026 payment determination.
c. Proposal To Remove Three Measures Under--Removal Factor 8, Costs 
Associated With a Measure Outweigh the Benefit of its Continued Use in 
the Program
    We are proposing 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.\1222\ 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.\1223\
---------------------------------------------------------------------------

    \1222\ 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.
    \1223\ 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.\1224\

[[Page 25581]]

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,\1225\ 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.
---------------------------------------------------------------------------

    \1224\ 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.''
    \1225\ 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.\1226\
---------------------------------------------------------------------------

    \1226\ 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 have 
reassessed the value of retaining the ED-2 eCQM in the Hospital IQR 
Program and are proposing 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 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 would 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 propose to remove this measure beginning with the CY 2024 
reporting period/FY 2026 payment determination.
    We invite public comments on our proposal to remove Admit Decision 
Time to ED Departure Time for Admitted Patients (ED-2) measure 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination.
(2) Stroke Related Electronic Clinical Quality Measures (eCQMs)
    We are proposing 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 are proposing 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.\1227\ 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.
---------------------------------------------------------------------------

    \1227\ 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

[[Page 25582]]

acute period.1228 1229 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.1230 1231 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.
---------------------------------------------------------------------------

    \1228\ 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.
    \1229\ 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.
    \1230\ 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.
    \1231\ 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 would 
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 would 
reduce provider and program costs alike.
    In summary, removing STK-03 and STK-06 would 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 propose to remove 
both measures beginning with the CY 2024 reporting period/FY 2026 
payment determination.
    We invite public comment on our proposal to remove both the 
Anticoagulation Therapy for Atrial Fibrillation/Flutter (STK-03) and 
the Discharged on Statin Medication (STK-06) measures beginning with 
the CY 2024 reporting period/FY 2026 payment determination.
8. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures
a. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2023 Payment Determination
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2023 Payment Determination:
[GRAPHIC] [TIFF OMITTED] TP10MY21.274


[[Page 25583]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.275

b. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2024 Payment Determination
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2024 Payment Determination 
and Subsequent Years:
[GRAPHIC] [TIFF OMITTED] TP10MY21.276


[[Page 25584]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.277

c. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2025 Payment Determination
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2025 payment determination:

[[Page 25585]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.278


[[Page 25586]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.279

d. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2026 Payment Determination
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2026 payment determination:

[[Page 25587]]

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[GRAPHIC] [TIFF OMITTED] TP10MY21.281


[[Page 25588]]


9. 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 measure 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 are seeking 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 are currently seeking public comment on the 
potential future inclusion of a COVID-19 mortality measure in the 
Hospital IQR Program. Specifically, we are seeking 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.
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 US.\1232\ Osteoarthritis accounts for more than 
half of all arthritis-related hospitalizations,\1233\ and in 2013 there 
were approximately 1,023,000 hospitalizations for osteoarthritis.\1234\ 
Hip and knee osteoarthritis is one of the leading causes of disability 
among non-institutionalized adults,\1235\ and roughly 80 percent of 
patients with osteoarthritis have some limitation in mobility.\1236\ 
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.\1237\ 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.1238 1239 1240 1241 However, not all patients 
experience benefit from these procedures.\1242\ Many patients note that 
their preoperative expectations for functional improvement have not 
been met.1243 1244 1245 1246 In addition, clinical

[[Page 25589]]

practice variation has been well documented in the 
U.S.,1247 1248 1249 readmission and complication rates vary 
across hospitals,1250 1251 and international experience 
documents wide hospital-level variation in patient-reported outcome 
measure results following THA and TKA.\1252\ 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.1253 1254
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    \1232\ 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.
    \1233\ 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.
    \1234\ 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.
    \1235\ 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.
    \1236\ 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.
    \1237\ Centers for Disease Control and Prevention (CDC). 
Osteoarthritis (OA). https://www.cdc.gov/arthritis/basics/osteoarthritis.htm. Accessed March 8, 2019.
    \1238\ 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.
    \1239\ 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.
    \1240\ 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.
    \1241\ 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.
    \1242\ National Joint Registry. National Joint Registry for 
England and Wales 9th Annual Report 2012. available at 
www.njrcentre.org.uk: National Joint Registry;2012.
    \1243\ 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.
    \1244\ 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.
    \1245\ 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.
    \1246\ Jourdan C, Poiraudeau S, Descamps S, et al. Comparison of 
patient and surgeon expectations of total hip arthroplasty. PLoS 
one. 2012;7(1):e30195.
    \1247\ Roos EM. Effectiveness and practice variation of 
rehabilitation after joint replacement. Current opinion in 
rheumatology. 2003;15(2):160-162.
    \1248\ 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.
    \1249\ 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.
    \1250\ 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.
    \1251\ 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/.
    \1252\ 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.
    \1253\ 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.
    \1254\ 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.1255 1256 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.1257 1258 1259 1260 1261 1262
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    \1255\ Feng J, Novikov D, Anoushiravani A, Schwarzkopf R. Total 
knee arthroplasty: improving outcomes with a multidisciplinary 
approach. J Multidiscip Healthc. 2018;11:63-73.
    \1256\ 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.
    \1257\ 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.
    \1258\ 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.
    \1259\ 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.
    \1260\ 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.
    \1261\ 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.
    \1262\ 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). 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.\1263\ 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.\1264\ The THA/TKA PRO-PM is fully developed aligns with these 
Meaningful Measures 2.0 goals.
---------------------------------------------------------------------------

    \1263\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1264\ 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,1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277
 are influenced by

[[Page 25590]]

a range of improvements in 
care,1278 1279 1280 1281 1282 1283 1284 1285 and demonstrate 
hospital-level variation even after patient case mix 
adjustment.1286 1287 Further, THA/TKA procedures are 
specifically intended to improve function and reduce pain, making PROs 
a meaningful outcome metric to assess.\1288\
---------------------------------------------------------------------------

    \1265\ 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.
    \1266\ 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.
    \1267\ 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.
    \1268\ 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.
    \1269\ 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.
    \1270\ Lau RL, Gandhi R, Mahomed S, Mahomed N. Patient 
satisfaction after total knee and hip arthroplasty. Clin Geriatr 
Med. 2012;28(3):349-365.
    \1271\ 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.
    \1272\ 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.
    \1273\ 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.
    \1274\ 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.
    \1275\ 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.
    \1276\ 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.
    \1277\ White D, Master H. Patient Reported Measures of Physical 
Function in Knee Osteoarthritis. Rheum Dis Clin North Am. 
2016;42(2):239-252.
    \1278\ 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.
    \1279\ 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.
    \1280\ 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.
    \1281\ 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.
    \1282\ 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.
    \1283\ 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.
    \1284\ 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.
    \1285\ 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.
    \1286\ 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.
    \1287\ 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.
    \1288\ 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.
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(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,\1289\ 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, 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).
---------------------------------------------------------------------------

    \1289\ 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.'' \1290\ The MAP 
supported the measure, as referenced in the 2020-2021 Final 
Recommendations report to HHS and CMS.\1291\ This measure was submitted 
for NQF review in March 2020.\1292\ In November 2020, the NQF endorsed 
the THA/TKA PRO-PM (NQF#3559).
---------------------------------------------------------------------------

    \1290\ 2020 Measures Under Consideration List. Available at 
https://www.cms.gov/media/492911.
    \1291\ 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.
    \1292\ 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 (described in 
section IX.C.9.b. of the preamble of this proposed rule) 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 \1293\ allows for derivation of the 
Agency for Healthcare Research and Quality (AHRQ) socioeconomic status 
(SES) index score.
---------------------------------------------------------------------------

    \1293\ 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

[[Page 25591]]

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).
(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.9.b.(7). of the preamble of this 
proposed 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

[[Page 25592]]

EHRs so the PRO data are available at the point of care.
    We invite public comment on the possible future inclusion of the 
THA/TKA PRO-PM in the Hospital IQR Program.
    We also invite public comment on other aspects of the measure 
related to future implementation. Specifically, we are seeking 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).
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.\1294\ 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.\1295\ Please see Closing the Health Equity Gap in CMS Quality 
Programs--A Request for Information, in section IX.B. of the preamble 
of this proposed rule, for additional information about our current 
disparity methods and its potential expansion.
---------------------------------------------------------------------------

    \1294\ 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.
    \1295\ 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/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 proposed 
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
    We are seeking 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 
are seeking 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 
proposed rule. We also seek 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.\1296\ 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.
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    \1296\ 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 invite 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

[[Page 25593]]

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)\1297\ and The Joint Commission (TJC)\1298\ have 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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    \1297\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Safety. 2019. https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
    \1298\ 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 are seeking 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'' \1299\ which identifies and 
prioritizes actionable steps towards addressing health disparities;
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    \1299\ 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\1300\, as 
defined by the CMS Office of Minority Health, to competently care for 
individuals with limited English proficiency;
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    \1300\ 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\1301\, as described by the CMS Office of Minority Health, to 
competently care for individuals who have visual or sensory 
disabilities;
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    \1301\ 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\1302\ and interoperable exchange standards; 
1303 1304 and
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    \1302\ 2015 Edition Cures Update certification criteria 
Demographic Data. 45 CFR 170.315(a)(5)
    \1303\ 2015 Edition Cures Update Certification Criteria 
Standardized API for Patient and Population Services. 45 CFR 
170.315(g)(10)
    \1304\ 2015 Edition Cures Update Certification Criteria United 
States Core Data for Interoperability (USCDI). 45 CFR 213
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     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.'' \1305\ 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 are 
interested in obtaining 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 seek feedback on an 
appropriate measure regarding organizational commitment to health 
equity and accessibility for individuals with intellectual and 
developmental disabilities.
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    \1305\ 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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8. 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

[[Page 25594]]

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 are not proposing any changes to these policies in this 
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 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 proposed rule 
where we request 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 this proposed rule, we 
are proposing to: (1) Update references to the QualityNet website, and 
(2) use the term ``QualityNet security official'' instead of 
``QualityNet Administrator''.
(1) Proposal To Update 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.\1306\ As a 
result, we are proposing to update the references to this CMS resource 
in the Hospital IQR Program regulation text. Specifically, we are 
proposing to remove reference to the QualityNet.org URL in two places:
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    \1306\ 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 invite 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).
(2) Proposal to Update Reference 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 this proposed rule, we propose to use the term ``QualityNet 
security official'' instead of ``QualityNet Administrator'' or 
``QualityNet System Administrator''. This proposed 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.\1307\ 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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    \1307\ Medicare Program; CY 2021 Medicare hospital outpatient 
prospective payment system. 85 FR 86182.
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    Therefore, we propose to revise existing language at 42 CFR 
412.140(a)(2) by replacing ``QualityNet Administrator'' with 
``QualityNet security official.'' If finalized, the revised paragraph 
(a)(2) would read: ``Identify and register a QualityNet security 
official as part of the registration process under paragraph (a)(1) of 
this section.''
    In addition, we propose to revise existing language at 42 CFR 
412.140(e)(2)(iii) by replacing ``QualityNet system administrator'' 
with ``QualityNet security official.'' If finalized, the revised 
paragraph (e)(2)(iii) would 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 invite 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).
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 are not proposing any changes to 
these policies in this 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

[[Page 25595]]

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 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.
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a progressive 
increase in the numbers 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 are not proposing any changes to these policies in 
this proposed rule, 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) Proposed Updates to Certification Requirements for eCQM Reporting
    In this proposed rule, we are proposing 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) Proposal To Require 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) Proposal
    In this proposed rule, beginning with the CY 2023 reporting period/
FY 2025 payment determination and subsequent years, we are proposing 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 invite public comment on our proposal to require hospitals to 
use only certified technology updated consistent with the 2015 Edition 
Cures Update beginning with the CY 2023 reporting period/FY 2025 
payment determination and subsequent years.

[[Page 25596]]

(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 
are not proposing any changes to this policy in this proposed rule. We 
note that if our proposal to require hospitals to use the 2015 Edition 
Cures Update beginning with the CY 2023 reporting period/FY 2025 
payment determination is finalized, 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 are not proposing any changes to these policies in this 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 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 are not proposing any changes to these policies 
in this proposed rule.
f. Data Submission and Reporting Requirements for Hybrid Measures
    In this proposed rule, we are proposing that hybrid measures comply 
with the same certification requirements and timeline as eCQMs. This 
proposal 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.8.f. of the preamble of this proposed rule 
for more information on our proposal to adopt 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) Proposed Changes to the Certification Requirements for Hybrid 
Measure Reporting Beginning With the CY 2023 Reporting Period/FY 2025 
Payment Determination
    In this proposed rule, to align with the health IT certification 
requirements for eCQM reporting, we are proposing 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 proposed changes to the certification requirements for 
eCQMs.

[[Page 25597]]

    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 if our proposals are finalized. We refer 
readers to section VIII.F.11.a.4. of the preamble of this proposed rule 
where the same proposed requirements are discussed for the Medicare 
Promoting Interoperability Program.
    We invite public comment on our proposal, as previously discussed.
(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 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.\1308\ We are not proposing any changes to 
these policies in this proposed rule.
---------------------------------------------------------------------------

    \1308\ 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 
are not proposing any changes to these policies in this 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 are not proposing any 
changes to these policies in this 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 are not proposing 
any changes to these policies in this 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.8.i. of the preamble of this 
proposed rule, where we are proposing to adopt the Maternal Morbidity 
Structural Measure. For the Maternal Morbidity Structural Measure and 
the CY 2021 reporting period/FY 2023 payment determination only, we are 
proposing 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, if our proposal is 
finalized as proposed, hospitals would 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, under the proposal in the VIII.C.8.i. of the preamble 
of this proposed rule, the reporting period for the Maternal Morbidity 
Structural Measure would run from: January 1 through December 31 on an 
annual basis, and that the data submission period would be 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.8.j. of the 
preamble of this proposed rule for more detail on our 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

[[Page 25598]]

Healthcare Safety Component, available at https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. For this measure, we would 
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.\1309\ 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 weekly submission 
period (denominator) and the number of those HCP who have received 
COVID-19 vaccination (numerator).
---------------------------------------------------------------------------

    \1309\ 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 are proposing that 
hospitals 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 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. Each quarter, 
we are proposing that the CDC would calculate a single quarterly COVID-
19 HCP vaccination coverage rate for each hospital, which would be 
calculated by taking the average of the data from the three weekly 
rates submitted by the hospital for that quarter. If finalized, CMS 
would publicly report each quarterly COVID-19 HCP vaccination coverage 
rate as calculated by the CDC.
9. Validation of Hospital IQR Program Data
    In this proposed rule, we are proposing changes to our Educational 
Review Process to extend the effects of the educational review 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 proposal 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] TP10MY21.282


[[Page 25599]]


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:
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[GRAPHIC] [TIFF OMITTED] TP10MY21.284


[[Page 25600]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.285

(b) Proposal To Extend 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 are proposing 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 
propose 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 this 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, this proposal does not apply to the educational review 
process for eCQMs, which is discussed in the next section.
    We invite public comment on our proposal, as previously discussed.
(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 are not proposing any changes to these policies in this 
proposed rule.
10. 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 are not 
proposing any changes to this policy in this proposed rule.
11. 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

[[Page 25601]]

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 are not 
proposing any changes to these policies in this proposed rule.
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 are not proposing any changes to these policies in this 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 are not proposing any changes to these policies in this proposed 
rule.
12. 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 are not proposing any changes to these policies in this proposed 
rule.
13. 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 are not proposing any changes to these policies in this proposed 
rule.

D. Proposed 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 1866(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 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); and
     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 this proposed rule, we are proposing 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. In section IX.D.5. of this proposed rule, we are 
proposing to adopt the COVID-19 Vaccination Coverage Among Healthcare 
Personnel measure, beginning with the FY 2023 program year and for 
subsequent years. In section I.X.D.9. of this proposed rule, we are 
proposing to update our terminology for this program by replacing the 
term ``QualityNet Administrator'' with ``QualityNet security 
official.'' In section IX.D.11. of this proposed rule, we are proposing 
to codify existing PCHQR Program policies at 42 CFR 412.23(f)(3) and 42 
CFR 412.24.
    We also refer readers to section IX.B of this proposed rule, 
Closing the Health Equity Gap in CMS Quality Programs--A Request for 
Information, where we request 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 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 
PCHQR Program.
    We also refer readers to section IX.A. of this proposed rule where 
we request 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 
are not proposing any changes to these policies in this proposed rule.

[[Page 25602]]

4. Proposed 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 are proposing 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. 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. 
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).
    Through our Meaningful Measures Initiative, 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.\1310\ 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 believe 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.
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    \1310\ 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.
---------------------------------------------------------------------------

    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 are proposing to remove the Oncology: Plan of Care 
for Pain measure from the PCHQR measure set.
    We invite 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.
5. Proposal To Adopt 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).\1311\ COVID-19 is a 
contagious respiratory illness \1312\ 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-19.1313 1314
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    \1311\ 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.
    \1312\ 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.
    \1313\ 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.
    \1314\ 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.
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    As of April 2, 2021, the U.S. has reported over 30 million cases of 
COVID-19 and over 550,000 COVID-19 deaths.\1315\ Hospitals and health 
systems saw significant surges of COVID-19 patients as community 
infection levels increased.\1316\ From December 2, 2020 to January 30, 
2021, more than 100,000 Americans were in the hospital with COVID-19 at 
the same time.\1317\
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    \1315\ Centers for Disease Control and Prevention. (2021). CDC 
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \1316\ 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.
    \1317\ US Currently Hospitalized  The COVID Tracking 
Project. Accessed January 31, 2021 at: https://covidtracking.com/data/charts/us-currently-hospitalized.
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    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\1318\ 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.\1319\ 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.\1320\,\1321\ Although less 
common, COVID-19 can also spread when individuals are not in close 
contact if small droplets or particles containing the virus linger in 
the air after the person who is infected as left the space.\1322\ 
Another means of less common transmission is contact with a 
contaminated surface.\1323\ According to the CDC, those at greatest 
risk of

[[Page 25603]]

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.\1324\ Although personal protective equipment (PPE) and 
other infection-control precautions can reduce the likelihood of 
transmission in health care settings, COVID-19 can spread between 
health care personnel (HCP) and patients given the close contact that 
may occur during the provision of care.\1325\ The CDC has emphasized 
that health care settings, including long-term care settings, can be 
high-risk places for COVID-19 exposure and transmission.\1326\
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    \1318\ 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.
    \1319\ 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.
    \1320\ 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.
    \1321\ 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.
    \1322\ 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.
    \1323\ 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.
    \1324\ 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.
    \1325\ 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.
    \1326\ 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 help restore 
societal functioning.\1327\ On December 11, 2020, the FDA issued the 
first Emergency Use Authorization (EUA) for a COVID-19 vaccine in the 
U.S.\1328\ Subsequently, the FDA issued EUAs for additional COVID-19 
vaccines.\1329\ \1330\
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    \1327\ 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.
    \1328\ 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.
    \1329\ U.S. Food and Drug Administration. (2021). Moderna COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download.
    \1330\ 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 on March 25, 2021 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.\1331\ 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.\1332\ 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.\1333\ Research suggests most states 
followed this recommendation,\1334\ and HCP began receiving the vaccine 
in mid-December of 2020.\1335\
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    \1331\ The White House. Remarks by President Biden in Press 
Conference. Accessed April 8, 2021 at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/25/remarks-by-president-biden-in-press-conference/.
    \1332\ 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.
    \1333\ 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.
    \1334\ 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/.
    \1335\ 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.\1336\ 
As of April 3, 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.\1337\ President Biden indicated on 
April 6, 2021 that the United States has sufficient vaccine supply to 
make every adult eligible to receive a vaccine beginning April 19, 
2021.\1338\
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    \1336\ Centers for Disease Control and Prevention. Healthcare 
Workers. (2017) Accessed February 18, 2021 at: https://www.cdc.gov/niosh/topics/healthcare/default.html.
    \1337\ Centers for Disease Control and Prevention. COVID Data 
Tracker. COVID-19 Vaccinations in the United States. (2021) Accessed 
February 18, 2021 at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \1338\ The White House. Remarks by President Biden Marking the 
150 Millionth COVID-19 Vaccine Shot. Accessed April 8, 2021 at: 
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/06/remarks-by-president-biden-marking-the-150-millionth-covid-19-vaccine-shot/.
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    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 are proposing 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, see 
section IX.D.5.c. of this proposed rule. The measure will assess the 
proportion of a PCH's HCP that has been vaccinated against COVID-19.
    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 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.\1339\ Data from influenza vaccination demonstrates 
that provider uptake of the vaccine is also associated with that 
provider recommending vaccination to patients,\1340\ and we believe HCP 
COVID-19 vaccination in PCHs could similarly increase uptake among that 
patient population. 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 PCHs from which to seek treatment. Under CMS' Meaningful 
Measures Framework, the COVID-19 HCP vaccination measure

[[Page 25604]]

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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    \1339\ 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.
    \1340\ 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.\1341\
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    \1341\ 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.) 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.\1342\ 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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    \1342\ Measure Application Partnership 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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(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,'' \1343\ 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.\1344\ 
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.\1345\
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    \1343\ The National Quality Forum. (2021) Accessed March 14, 
2021 at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94212.
    \1344\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1345\ 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.\1346\ 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.\1347\ 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.'' \1348\ 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.\1349\
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    \1346\ Ibid.
    \1347\ Ibid.
    \1348\ 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.
    \1349\ 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.\1350\ Because 
of the high correlation across a large number of facilities and high 
number of HCP within those facilities receiving at least

[[Page 25605]]

one dose of the COVID-19 vaccine, we believe these data indicates the 
measure is feasible and reliable for use in PCHs.
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    \1350\ 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 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 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. CMS 
continues to engage with the MAP to mitigate its concerns and 
appreciates 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.
    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 are proposing 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 propose quarterly reporting deadlines for the PCHQR 
Program. If our proposal to adopt this measure is finalized, PCHs would 
report the measure through the NHSN web-based surveillance 
system.\1351\ 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).
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    \1351\ 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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    To report this measure, we are proposing 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 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 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 are 
proposing 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. If finalized, 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)., 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.
    We invite 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 a October 1, 2021 through December 
31, 2021 reporting period for that program year, and continuing with 
quarterly reporting deadlines for subsequent PCHQR Program years.
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 if our proposal to adopt the COVID-19 
Vaccination Coverage Among HCP measure is finalized.

[[Page 25606]]

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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 are not proposing 
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.

[[Page 25607]]

    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 are not proposing any changes to these 
public display requirements.
[GRAPHIC] [TIFF OMITTED] TP10MY21.287

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. Proposal To Update Reference to QualityNet Administrator
    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 this proposed rule, we propose to use the term ``QualityNet 
security official'' instead of ``QualityNet Administrator'' to align 
with the terminology we use or are proposing to use in other quality 
reporting programs. This proposed update in terminology would not 
change the individual's responsibilities or add burden.
    Additionally, we are clarifying 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 invite public comment on our proposal to replace the term 
``QualityNet administrator'' with ``QualityNet security official.''
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 are 
not proposing any changes to this policy.
11. Proposal To Codify 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 are proposing 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. We believe that 
the codification of these requirements will make it easier for 
stakeholders to find these requirements.
    Specifically, we propose 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.

[[Page 25608]]

We also propose 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 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 welcome public comment on the proposed codification of these 
existing PCHQR Program policies.

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 IX.E.-01. 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).

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4. LTCH QRP Quality Measure Proposals 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 propose to adopt one new measure, the COVID-19 Vaccination 
Coverage among Healthcare Personnel (HCP) \1352\ 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 below.
---------------------------------------------------------------------------

    \1352\ 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 propose 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. Proposed 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) coronavirus that causes a disease named ``coronavirus 
disease 2019'' (COVID-19).\1353\ COVID-19 is a contagious respiratory 
infection \1354\ that can cause serious illness and death. Older 
individuals, racial and ethnic

[[Page 25611]]

minorities,\1355\ and those with underlying medical conditions are 
considered to be at higher risk for more serious complications from 
COVID-19.\1356\ As of April 10, 2021, the U.S. reported over 30 million 
cases of COVID-19 and over 558,000 COVID-19 deaths.\1357\ Hospitals and 
health systems saw significant surges of COVID-19 patients as community 
infection levels increased.\1358\ In December 2020 and January 2021, 
media outlets reported that more than 100,000 Americans were in the 
hospital with COVID-19.\1359\
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    \1353\ 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.
    \1354\ 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.
    \1355\ 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.
    \1356\ 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.
    \1357\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \1358\ 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.
    \1359\ 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.
---------------------------------------------------------------------------

    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\1360\ 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.\1361\ Experts believe that COVID-19 spreads less 
commonly through contact with a contaminated surface \1362\ and is not 
thought to be a common way that COVID-19 spreads, and that in certain 
circumstances, infection can occur through airborne transmission.\1363\ 
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.\1364\ Although 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.\1365\ The CDC has emphasized that 
healthcare settings, including LTCHs, can be high-risk places for 
COVID-19 exposure and transmission.\1366\ Vaccination is a critical 
part of the nation's strategy to effectively counter the spread of 
COVID-19 and ultimately help restore societal functioning.\1367\
---------------------------------------------------------------------------

    \1360\ 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.
    \1361\ 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.
    \1362\ 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.
    \1363\ 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.
    \1364\ 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.
    \1365\ 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.
    \1366\ 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.
    \1367\ 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.
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    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.\1368\ 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.1369 1370 1371
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    \1368\ 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.
    \1369\ Ibid.
    \1370\ 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.
    \1371\ 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.
---------------------------------------------------------------------------

    As part of its national strategy to address COVID-19, the current 
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.\1372\ 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 individuals 
at highest risk for developing severe illness from COVID-19.\1373\ 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.\1374\ Research suggests most 
states followed this recommendation,\1375\ and HCP began receiving the 
vaccine in mid-December of 2020.\1376\
---------------------------------------------------------------------------

    \1372\ 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/.
    \1373\ 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.
    \1374\ 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.
    \1375\ 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/.
    \1376\ 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.
---------------------------------------------------------------------------

    HCP are at risk of carrying COVID-19 infection to patients, 
experiencing

[[Page 25612]]

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 are proposing 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.\1377\ To meet this 
requirement, the following opportunity was provided for stakeholder 
input.
---------------------------------------------------------------------------

    \1377\ Centers for Medicare & Medicaid Services. Pre-rulemaking. 
Accessed at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rulemaking.
---------------------------------------------------------------------------

    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).\1378\ 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.
---------------------------------------------------------------------------

    \1378\ 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.\1379\ 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.\1380\
---------------------------------------------------------------------------

    \1379\ 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.
    \1380\ Ibid.
---------------------------------------------------------------------------

    In its preliminary recommendations, the MAP PAC-LTC Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\1381\ To mitigate its concerns, the MAP believed that the 
measure needed well-documented evidence, finalized specifications, 
testing, and NQF endorsement prior to implementation.\1382\ 
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.
---------------------------------------------------------------------------

    \1381\ Ibid.
    \1382\ 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 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.\1383\ 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%.\1384\
---------------------------------------------------------------------------

    \1383\ 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).
    \1384\ 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

[[Page 25613]]

weeks of reporting. Of note, assessment of data element reliability may 
not be required by NQF if data element validity is demonstrated.\1385\ 
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),\1386\ 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.
---------------------------------------------------------------------------

    \1385\ 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).
    \1386\ Ibid.
---------------------------------------------------------------------------

    This measure is not NQF endorsed, but the CDC, in collaboration 
with CMS, plans to submit the measure for NQF endorsement in the 
future.
(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 
propose 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 proposed 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 
proposed 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.\1387\
---------------------------------------------------------------------------

    \1387\ 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 one 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 propose that LTCHs would submit data for the measure through the 
CDC/NHSN data collection and submission framework.\1388\ This 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 one 
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 three 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.
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    \1388\ 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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    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 E.9.d. of this proposed rule.
    We invite public comment 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.

[[Page 25614]]

b. Proposed Update to the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) Measure Beginning With the FY 2023 LTCH 
QRP
    We are proposing 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-based 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, this rule proposes 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 are proposing to remove this location from the definition of 
the denominator for the TOH-Patient measure. Therefore, we are 
proposing to update 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 (SPADEs)'' available 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/Downloads/Final-Specifications-for-LTCH-QRP-Quality-Measures-and-SPADEs.pdf.
    We invite public comment 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.
5. LTCH QRP Quality Measures Under Consideration for Future Years: 
Request for Information
    We are seeking 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] TP10MY21.290

    While we will not be responding to specific comments submitted in 
response to this Request for Information in the FY 2022 IPPS/LTCH PPS 
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. Background
    The LTCH QRP is authorized by section 1886(m)(5) of the Act and 
furthers our mission to improve the quality of health care for 
beneficiaries through measurement, transparency, and public reporting 
of data. The LTCH QRP and CMS's other quality programs are foundational 
for contributing to improvements in health care, enhancing patient 
outcomes, and informing consumer choice. In October 2017, we launched 
the Meaningful Measures Framework. This framework captures our vision 
to address health care quality priorities and gaps, including

[[Page 25615]]

emphasizing digital quality measurement (dQM), reducing measurement 
burden, and promoting patient perspectives, while also focusing on 
modernization and innovation. The scope of the Meaningful Measures 
Framework has evolved to accommodate the changes in the health care 
environment, initially focusing on measure and burden reduction to 
include the promotion of innovation and modernization of all aspects of 
quality.\1389\ 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.
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    \1389\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    In alignment with Meaningful Measures 2.0, we are seeking feedback 
on our future plans to define digital quality measures (dQMs) for the 
LTCH QRP. We also are seeking feedback on the potential use of Fast 
Healthcare Interoperable Resources (FHIR) for dQMs within the LTCH QRP 
aligning where possible with other quality programs. FHIR is a free and 
open source standards framework (in both commercial and government 
settings) created by Health Level Seven International (HL7[supreg]) 
establishes a common language and process for all health information 
technology.
b. Definition of Digital Quality Measures
    We are considering proposing to adopt a standardized definition of 
Digital Quality Measures (dQMs) in alignment across quality programs, 
including the LTCH QRP. We are considering in the future to propose the 
adoption within the LTCH QRP the following definition: Digital Quality 
Measures (dQMs) are quality measures that use one or more sources of 
health information that are captured and can be transmitted 
electronically via interoperable systems.\1390\ A dQM includes a 
calculation 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. As an example, the 
quality measures calculated from patient assessment data submitted 
electronically to CMS would be considered digital quality measures.
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    \1390\ Definition taken from the CMS Quality Conference 2021.
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c. Use of FHIR for Future dQMs in the LTCH QRP
    One of the first areas CMS has identified relative to improving our 
digital strategy is through the use of Fast Healthcare Interoperability 
Resources (FHIR)-based standards to exchange clinical information 
through application programming interfaces (APIs), aligning with other 
programs where possible, to allow clinicians to digitally submit 
quality information one time that can then be used in many ways. We 
believe that in the future proposing such a standard within the LTCH 
QRP could potentially enable collaboration and information sharing, 
which is essential for delivering high-quality care and better outcomes 
at a lower cost.
    We are currently evaluating the use of FHIR based APIs to access 
assessment data collected and maintained through the Quality 
Improvement and Evaluation System (QIES) and internet QIES (iQIES) 
health information systems and are working with healthcare standards 
organizations to assure that their evolving standards fully support our 
assessment instrument content. Further, as more LTCHs are adopting 
EHRs, we are evaluating using the FHIR interfaces for accessing patient 
data (including standard assessments) directly from LTCH EHRs. 
Accessing data in this manner could also enable the exchange of data 
for purposes beyond data reporting to CMS, such as care coordination 
further increasing the value of EHR investments across the healthcare 
continuum. Once providers map their EHR data to a FHIR API in standard 
FHIR formats it could be possible to send and receive the data needed 
for measures and other uses from their EHRs through FHIR APIs.
d. 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 achieve interoperable data exchange and to transition 
to full digital quality measurement in our quality programs. We are 
considering the future potential development and staged implementation 
of a cohesive portfolio of dQMs across our quality programs (including 
the LTCH QRP), agencies, and private payers. This cohesive portfolio 
would require, where possible, 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 measures. Further, the required data 
elements would be limited to standardized, interoperable 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 this coordination to be ongoing and allow for continuous 
refinement to ensure quality measures remain aligned with evolving 
healthcare practices and priorities (for example, patient reported 
outcomes (PROs), disparities, care coordination), and track with the 
transformation of data collection. This includes conformance with 
standards and health IT module updates, future adoption of technologies 
incorporated within the ONC Health IT Certification Program and may 
also include standards adopted by ONC (for example, to enable 
standards-based APIs). The coordination would build on the principles 
outlined in HHS' National Health Quality Roadmap.\1391\ It would focus 
on the quality domains of safety, 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 (DoD/VA); the Core Quality Measure Collaborative, 
which convenes stakeholders from America's Health Insurance Plans 
(AHIP), CMS, 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

[[Page 25616]]

recognition of current healthcare practice and priorities.
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    \1391\ Department of Health and Human Services. National Health 
Quality Roadmap. May 15, 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 as well as the requirements of other agencies and payers.
e. Solicitation of Comments
    We seek 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?
    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 plan to continue working with other agencies and stakeholders to 
coordinate and to inform our transformation to dQMs leveraging health 
IT standards. While we will not be responding to specific comments 
submitted in response to this RFI in the 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.
7. Closing the Health Equity Gap in Post-Acute Care Quality Reporting 
Programs--Request for Information (RFI)
a. Background
    Significant and persistent inequities in health outcomes exist in 
the United States. In recognition of persistent health disparities and 
the importance of closing the health equity gap, we request information 
on revising several CMS programs to make reporting of health 
disparities based on social risk factors and race and ethnicity more 
comprehensive and actionable for providers and patients. 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; or being near or below the poverty level, is often 
associated with worse health 
outcomes.1392 1393 1394 1395 1396 1397 1398 1399 Such 
disparities in health outcomes are the result of a number of factors, 
but importantly for CMS programs, although not the sole determinant, 
poor access and provision of lower quality health care contribute 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 operative 
complications.1400 1401 1402 1403 1404 1405 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.1406 1407 1408 1409 1410 Studies have 
also shown that African Americans are significantly more likely than 
white Americans to die prematurely from heart disease and stroke.\1411\ 
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.1412 1413 
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

[[Page 25617]]

from COVID-19''.\1414\ One important strategy for addressing these 
important inequities is by improving data collection to allow for 
better measurement and reporting on equity across post-acute care 
programs and policies.
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    \1392\ 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.
    \1393\ 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.
    \1394\ 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.
    \1395\ 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.
    \1396\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018.
    \1397\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \1398\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \1399\ 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.
    \1400\ 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.
    \1401\ 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.
    \1402\ 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.
    \1403\ 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.
    \1404\ 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.
    \1405\ 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.
    \1406\ 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.
    \1407\ Centers for Medicare and Medicaid Services. Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures; 
2014.
    \1408\ 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.
    \1409\ 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.
    \1410\ 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.
    \1411\ HHS. Heart disease and African Americans. (March 29, 
2021). https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \1412\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \1413\ 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/.
    \1414\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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    We are also 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.1415 1416 For the purposes of this rule, we 
are using a definition of ``equity'' established in Executive Order 
13985 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.'' \1417\ We note that this definition was recently 
established by the current administration, and provides a useful, 
common definition for equity across different areas of government, 
although numerous other definitions of equity exist.
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    \1415\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \1416\ Report to Congress: Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing 
Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.
    \1417\ 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, including the PAC QRPs, 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 Networks and Quality Improvement Organizations (QIN-QIOs); 
Federal, State, local, and tribal organizations; providers; 
researchers; policymakers; beneficiaries and their families; and other 
stakeholders in activities to achieve health equity. The CMS Equity 
plan includes three core elements: (1) Increasing understanding and 
awareness of disparities; (2) developing and disseminating solutions to 
achieve health equity; and (3) implementing sustainable actions to 
achieve health equity.\1418\ The CMS Quality Strategy and Meaningful 
Measures Framework \1419\ include elimination of racial and ethnic 
disparities as a central principle. Our ongoing commitment to closing 
the health equity gap in the LTCH QRP is demonstrated by the adoption 
of standardized patient assessment data elements (SPADEs) which include 
several social determinants of health (SDOH) that were finalized in the 
FY 2020 IPPS/LTCH PPS final rule for the LTCH QRP (84 FR 42577 through 
42588).
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    \1418\ Centers for Medicare & Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \1419\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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    We continue to work with public and private partners to better 
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 \1420\ 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. We continue to work to improve our understanding of this 
important issue and to identify policy solutions that achieve the goals 
of attaining health equity for all patients.
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    \1420\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
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b. Solicitation of Public Comment
    Under the authority of the IMPACT Act and section 1886(m)(5) of the 
Act, we are seeking comment on the possibility of revising measure 
development, and the collection of other SPADEs 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 inviting 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 SPADEs on SDOH, 
including race, ethnicity, preferred language, interpreter services, 
health literacy, transportation and social isolation.\1421\ CMS is 
seeking guidance on any additional SPADEs that could be used to assess 
health equity in the care of LTCH patients, for use in the LTCH QRP.
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    \1421\ 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 \1422\ 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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    \1422\ 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.

[[Page 25618]]

    While we will not be responding to specific comments submitted in 
response to this RFI in the FY 2022 IPPS/LTCH PPS final rule, we intend 
to use this input to inform future policy development. We look forward 
to receiving feedback on these topics, and note for readers that 
responses to the RFI should focus on how they could be applied to the 
quality reporting program requirements. Please note that any responses 
provided will not impact payment decisions.
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. Proposed 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 E.4.a. of this proposed rule, we are 
proposing 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 propose 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.\1423\ 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 one week each month and the CDC would report to CMS 
quarterly.
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    \1423\ 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 invite public comment on this proposal.
9. Proposed 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. Proposal To 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 propose 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 propose 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 after July 1, 2018. To ensure 
the statistical reliability of the data, we propose not to publicly 
report an LTCH's performance on the measure if the LTCH had fewer than 
20 eligible cases \1424\ 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.''
---------------------------------------------------------------------------

    \1424\ 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 invite public comment 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.
c. Proposal To Publicly Report the Ventilator Liberation Rate for the 
PAC LTCH QRP Measure Beginning With the FY 2023 LTCH QRP
    We propose 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 
propose publicly reporting the Ventilator Liberation rate for the PAC 
LTCH QRP measure for data collected from July 1, 2018 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

[[Page 25619]]

measure began with patients admitted and discharged on or after July 1, 
2018. To ensure the statistical reliability of the data, we propose 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), 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 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 invite public comment on the proposal to publicly display the 
measure, Ventilator Liberation Rate for the PAC LTCH QRP on Care 
Compare and PDC.
d. Proposal To Publicly Report the COVID-19 Vaccination Coverage Among 
Healthcare Personnel (HCP) Measure Beginning With the FY 2023 LTCH QRP
    We propose 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 invite public comment on this proposal for the public display of 
the measure, COVID-19 Vaccination Coverage among HCP on Care Compare.
e. Proposals for 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 of Health and Human Services 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.\1425\ 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,\1426\ 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 exceptions from Q1 
and Q2 of 2020. This exception impacted the schedule for public 
reporting that would have included those two quarters of data.
---------------------------------------------------------------------------

    \1425\ https://www.phe.gov/emergency/news/healthactions/section1135/Pages/covid19-13March20.aspx
    \1426\ 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 IX.E.-03 
displays the original schedule for public reporting of LTCH QRP 
measures.\1427\
---------------------------------------------------------------------------

    \1427\ 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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[[Page 25621]]


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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 below). 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 
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 and Proposal 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:

[[Page 25622]]

    1. 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.
    2. 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 are proposing 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 proposal of the 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 changes in reportability 
and reliability. Table IX.E.-04 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 IX.E.-05 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.
    We invite public comments on the proposal to use the CAR scenario 
to publicly report LTCH measures for the December 2021-June 2023 
refreshes.

[[Page 25623]]

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[[Page 25624]]


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[[Page 25625]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.295

(4) Update on Data Freeze and Proposal 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 IX.E.-06 and 07 display 
the original schedules for public reporting of LTCH CDI, CAUTI and 
CLABSI measures and the HCP Influenza measure, respectively. Tables 
IX.E.-08 and 09 summarize the revised schedule and the proposed 
schedule for LTCH CDI, CAUTI, and CLABSI measures and the HCP Influenza 
measure, respectively.

[[Page 25626]]

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[[Page 25627]]


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[[Page 25628]]


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F. Proposed 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 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 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 
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 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 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. Proposed EHR Reporting Period in CY 2023 and CY 2024 for Eligible 
Hospitals and CAHs
    For CY 2023, we are proposing 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.
    For CY 2024, we are proposing an EHR reporting period of a minimum 
of

[[Page 25629]]

any continuous 180-day period for new and returning participants 
(eligible hospitals and CAHs) in the Medicare Promoting 
Interoperability Program.
    We are proposing 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.
    This 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 are seeking comment on the proposed EHR reporting periods in CYs 
2023 and 2024, and proposed changes to the regulation text at 42 CFR 
495.4.
3. Proposed 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 noted 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 CDC and 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.\1428\ 
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.\1429\ We believe these standards and 
technical approaches are likely to rapidly reach maturity to support 
exchange across health care system stakeholders.
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    \1428\ https://www.pdmpassist.org/RxCheck.
    \1429\ 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. Proposed 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.
    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,

[[Page 25630]]

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, we are proposing 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 proposing corresponding changes to the 
regulation at 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 are proposing to revise 
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.
    We seek 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.
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 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).\1430\ 
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.
---------------------------------------------------------------------------

    \1430\ HL7[supreg] and FHIR[supreg] are registered trademarks of 
Health Level Seven International.
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    A number of recent efforts have sought to improve interoperability 
between EHRs and PDMPs. In 2020, ONC completed work to map the NCPDP 
SCRIPT standard version 2017071, the Prescription Monitoring 
Information eXchange (PMIX) standard version 2, and the 2015 American 
Society for Automation in Pharmacy (ASAP) Prescription Monitoring 
Program Web Service standard version 2.1A to the Health Level Seven 
International (HL7[supreg]) Fast Healthcare Interoperability Resources 
(FHIR[supreg]) standard version Release 4.
    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.
    While we believe the Query of PDMP measure is very important to 
avoid and address the over-prescribing of opioids, we also recognize 
that some states and systems may not be ready at this time to 
effectively exchange this data. In light of further work in this area 
and our stated goals for increasing the impact of this measure, we are 
seeking stakeholder comment on plans for requiring the Query of PDMP 
measure in the Medicare Promoting Interoperability Program in the near 
future. To advance in this direction with both transparent proposals 
and informed guidance, we request public comment on the future 
direction for the measure, specifically:
     To what degree would all eligible hospitals and CAHs be 
prepared to report on the current attestation-based Query of PDMP 
measure in the near future? What additional considerations would need 
to be addressed before transitioning to a performance-based version of 
the measure?
     Would changes to the Query of PDMP measure be necessary to 
accommodate other technical approaches that may be implemented in the 
future, such as exchange of information with a PDMP or with multiple 
PDMPs using HL7[supreg] FHIR[supreg]?
     What, if any, exclusions should be made available as part 
of the measure's specifications with regard to eligible hospitals and 
CAHs?
     When will State PDMPs be ready to effectively exchange 
data with provider systems using HL7[supreg] FHIR[supreg] to support 
this measure? What are the most common standards and approaches used to 
access PDMP data through provider systems currently?
     What technical considerations exist for intrastate vs. 
interstate PDMP queries? How could health information exchange networks 
play a role in expanding access to PDMP data? In what ways could 
FHIR[supreg] applications be supported to safely share PDMP data within 
a clinician's workflow?

[[Page 25631]]

4. Proposed 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. Proposed Data Availability Requirement for Eligible Hospitals and 
CAHs
    We are proposing to modify the Provide Patients Electronic Access 
to Their Health Information measure to require 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). Eligible hospitals 
and CAHs would be required to ensure this information remains available 
indefinitely (that is, not merely for a defined period of time). The 
proposed 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 are proposing to add 
corresponding regulatory text at 495.24(e)(7)(ii)(C), as well as 
proposing to restructure 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 it will 
exercise enforcement discretion and not enforce these new requirements 
until July 1, 2021.\1431\ 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)).
---------------------------------------------------------------------------

    \1431\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Interoperability/index.
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    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 want to align the date under our proposal for 
making information about encounters available, with the date of service 
start date (January 1, 2016) 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 are seeking public comment on our proposal to modify the Provide 
Patients Electronic Access to Their Health Information measure, as well 
as the alternatives we considered.
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. 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 
health information exchanges with improved medication reconciliation, 
improved immunization and health record completeness, and improved 
population level immunization rates,\1432\ while other research has 
shown a decrease in emergency department utilization and improved care 
process when using an HIE.\1433\
---------------------------------------------------------------------------

    \1432\ https://academic.oup.com/jamia/article/25/9/1259/4990601: 
ibid.
    \1433\ 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''.
---------------------------------------------------------------------------

    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.\1434\ 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

[[Page 25632]]

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.
---------------------------------------------------------------------------

    \1434\ https://protect2.fireeye.com/url?k=d8978709-84c28e1a-d897b636-0cc47adb5650-e634c1ba410d0153&u=https://www.healthit.gov/sites/default/files/reports/finalsummativereportmarch_2016.pdf.
---------------------------------------------------------------------------

    Recent data indicate that there is wide availability of HIEs across 
the nation, yet gaps remain. Forthcoming analysis of a recent survey of 
HIEs found that 45 states, including DC, were covered by one or more 
operational HIOs that reported a statewide catchment area. Moreover, 81 
percent (or 2,770) of health service areas (HSAs) in the United States 
were in the catchment area of at least one operational HIE effort and 
32 percent of HSAs had more than one operational HIE effort.\1435\ 
Despite the widespread availability of HIE services, however, HIE 
participation data suggest there are still significant opportunities to 
increase health care provider engagement with HIEs. For instance, in a 
2019 survey, 74 percent of hospitals reported participating in either a 
State, regional, or local HIE and 69 percent reported participation in 
a national HIE network, 11 percent of hospitals reported not 
participating in any type of HIE.\1436\
---------------------------------------------------------------------------

    \1435\ Health Affairs, in press. Forthcoming analysis of survey 
conducted under Contract No. HHSP233201700049C, OMB Control No: 
0955-0019.
    \1436\ ``Use of Certified Health IT and Methods to Enable 
Interoperability by U.S. Non-Federal Acute Care Hospitals, 2019'' 
ONC Data Brief No. 54, February 2021. Seehttps://www.healthit.gov/sites/default/files/page/2021-03/Hospital%20Use%20of%20Certified%20HIT_Interop%20v10_1.pdf.
---------------------------------------------------------------------------

b. Proposed 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)). For example, consider a patient who has 
a hospital emergency room visit in January 2020 and receives a 
prescription, then goes to her primary care physician appointment in 
March 2020 without notifying the primary care physician of the hospital 
visit or the new medication. The primary care physician refers the 
patient to a specialist and the specialist receives and reconciles the 
patient's data from her primary care physician records. In this 
scenario, the hospital may not have had access to the patient's health 
record from the primary care physician, and the primary care physician 
and the specialist may not have access to the data from the hospital 
including essential information like an update to current medications.
    Moreover, if the patient were to have another emergent issue and 
require emergency room care, the situation becomes further compounded. 
For this scenario, if the hospital, primary care physician, and 
specialist participated in a bi-directional exchange with a health 
information network, each health care provider from the hospital to the 
specialist would have access to all of the patient's records that may 
be critical for patient care and safety. 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 are proposing, 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 current 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 FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20537), we 
requested comment on whether eligible hospital or CAH participation in 
the Trusted Exchange Framework and Common Agreement (TEFCA) should be 
considered a health IT activity that could count for credit within the 
Health Information Exchange objective in lieu of reporting on measures 
for this objective. TEFCA, which is currently under development, 
addresses the 21st Century Cures Act requirement to ``develop or 
support a trusted exchange framework, including a common agreement 
among health information networks nationally.'' We received comments in 
support of this concept (83 FR 41669) although some disagreed 
indicating that they were concerned about adding additional burden.
    Subsequently, 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. We are now proposing 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.
    We are proposing 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 propose 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 are proposing that 
eligible hospitals and CAHs may either report the two existing measures 
and associated exclusions OR

[[Page 25633]]

may choose to report the new measure and are proposing to revise 42 CFR 
495.24(e)(6)(ii) to reflect this change. We propose 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 are 
proposing 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 propose 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 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.
    While we believe there are a significant number of HIEs across the 
country that would meet the standards described in the attestation 
statements, some HIE arrangements may not have the capacity to enable 
bi-directional exchange for all unique patients, and thus would not 
meet the standard described in the attestation statements required to 
fulfill the measure. For instance, we would exclude exchange networks 
that only support information exchange between affiliated entities, 
such as health care providers that are part of a single health system, 
or networks that only facilitate sharing between health care providers 
that use the same EHR vendor.
    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 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

[[Page 25634]]

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, we wish to clarify that 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 invite comments on this 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.
    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.
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 will 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. Proposed Modifications to the Reporting Requirements for the Public 
Health and Clinical Data Exchange Objective
    In this section, we are proposing 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 proposing 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.
(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

[[Page 25635]]

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 February 1, 2021, nearly 6,000 healthcare 
facilities covering 49 states and the District of Columbia contribute 
data to NSSP, representing approximately 70% of all U.S. nonfederal 
EDs.\1437\ Although some additional facilities report to local 
syndromic systems, and approximately 3 in 10 nonfederal hospitals are 
not participating in NSSP, there remain major gaps in syndromic 
surveillance coverage, leaving blind spots in the ability of State, 
local, and Federal PHAs to adequately prepare for emerging local and 
regional public health events.
---------------------------------------------------------------------------

    \1437\ Overview of the National Syndromic Surveillance Program 
(NSSP), https://www.cdc.gov/nssp/overview.html.
---------------------------------------------------------------------------

    We are proposing 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 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 COVID-19 outbreaks. 
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 the first 
indication 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 homeless, 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 49 states are already participating 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.\1438\ 
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.
---------------------------------------------------------------------------

    \1438\ 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.
    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 are 
proposing 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 proposing to codify this change at 42 CFR 495.24(e)(8)(ii)(A). We 
are also proposing that the first exclusion for this measure be 
modified to remove the reference to urgent care. The other two 
exclusions are unchanged. We propose to modify the first exclusion 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.\1439\ 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.
---------------------------------------------------------------------------

    \1439\ 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 jurisdiction. At the point 
of clinical care, an immunization registry can provide consolidated 
immunization histories to assist vaccine providers in determining 
appropriate patient

[[Page 25636]]

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.\1440\ 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.
---------------------------------------------------------------------------

    \1440\ https://www.cdc.gov/vaccines/programs/iis/annual-report-iisar/2019-data.html.
---------------------------------------------------------------------------

    We are proposing 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 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 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 
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. Fear of COVID-19 has 
caused deferrals of routine vaccinations as patients limit their 
interactions, including with their family doctors. 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 are not proposing 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).
(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.\1441\ 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.
---------------------------------------------------------------------------

    \1441\ 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] API to establish electronic case reporting capability in 
EHR systems. 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, and not directly to a PHA, which means that any 
health care provider that has established an electronic case reporting 
connection also has a connection with every State PHA, many large local 
health departments and some territories. 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

[[Page 25637]]

both states that would have jurisdiction over this report. This 
increases inter-jurisdictional reporting, allowing for more seamless 
case investigation at the national level. The interoperable 
infrastructure and the use of a standard data format also reduces the 
variability of case report forms across conditions and jurisdictions, 
streamlining reporting forms for EHR vendors and health care providers.
    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 11 large local 
jurisdictions have connected to the eCR Now shared services platform 
and are currently receiving electronic case reports, with more than 
7,200 healthcare facilities on board and 7.1 million reports for COVID-
19 received by PHAs as of March 8, 2021.\1442\ 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 99 reportable and 
notifiable conditions. While these are significant advancements, the 
piecemeal approach of encouraging adoption of these tools by individual 
health care providers has not been an effective or efficient means to 
quickly scale this effort nationally as has been needed for the COVID-
19 PHE response.
---------------------------------------------------------------------------

    \1442\ Healthcare Facilities in Production for COVID-19 
Electronic Case Reporting [bond] CDC.
---------------------------------------------------------------------------

    We believe the uneven adoption of electronic case reporting creates 
a public health vulnerability. We are proposing 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. 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 CAHs. 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) which relates to how the health IT 
uses structured data within an EHR to trigger or indicate the 
generation of an electronic initial case report.\1443\ 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.
---------------------------------------------------------------------------

    \1443\ 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 
would provide certainty to EHR vendors and facilitate an organized and 
industry-wide rollout of electronic case reporting capabilities.
    We are not proposing 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.
(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 are proposing 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 are not proposing to change the description of the Electronic 
Reportable Laboratory Result Reporting measure

[[Page 25638]]

and the exclusions that we established at 42 CFR 495.24(e)(8)(iii)(F) 
will remain available.
7. Proposed Scoring of the Public Health and Clinical Data Exchange 
Objective
    We are proposing 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. In the event an eligible hospital or CAH is able to claim an 
exclusion for three or fewer of these four required measures, we are 
proposing 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 proposing 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 propose to redistribute the points 
associated with the objective to the Provider to Patient Exchange 
objective. We are proposing corresponding changes to 42 CFR 
495.24(e)(8)(ii) and (iii) to reflect these proposals.
    We are proposing 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 are proposing 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 are proposing 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 proposal to make these measures optional, we 
are proposing 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 are 
proposing to revise 42 CFR 495.24(e)(8)(iii)(D), and for the Clinical 
Data Registry Reporting measure we are proposing to revise 42 CFR 
495.24(e)(8)(iii)(E).
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.\1444\ 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.
---------------------------------------------------------------------------

    \1444\ https://www.healthit.gov/topic/safety/safer-guides.
---------------------------------------------------------------------------

    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.

[[Page 25639]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.300

b. Proposed New SAFER Guides Measure
    We are proposing 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 are proposing 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 propose 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 are also proposing 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. However, 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 are proposing that a 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 are inviting public comment on these proposals.
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

[[Page 25640]]

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). 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. Proposed 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 are proposing 
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 proposed 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 noted, 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

[[Page 25641]]

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 are proposing 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 invite public comment on our proposals.
    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 proposals 
made in this proposed rule. Table IX.F.-03 lists the 2015 Edition 
certification criteria required to meet the objectives and measures.

[[Page 25642]]

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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 are proposing to increase the 
minimum scoring threshold from 50 points to 60 points, and proposing 
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 seek comments on our proposal to increase the minimum scoring 
threshold from 50 to 60 points.
b. Performance-Based Scoring Methodology Table Updates
    The following table reflects the objectives and measures for CY 
2022 if the proposed changes discussed in this section are finalized, 
including 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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[[Page 25650]]


11. Clinical Quality Measurement for Eligible Hospitals and CAHs 
Participating in the Medicare Promoting Interoperability Program
a. Proposed 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) Proposed eCQM Removals
    As we discuss in the Hospital IQR Program section of this proposed 
rule, we are proposing to remove four eCQMs from the Hospital IQR 
Program's measure set effective for the CY 2024 reporting period/FY 
2026 payment determination. Specifically, we are proposing 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 proposed 
rule for additional discussion of the rationales for these proposed 
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 proposed rule, we 
propose to remove STK-03, 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 welcome public comments on these proposed eCQM removals.
(3) Proposed 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 proposed rule, we are proposing to adopt 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 proposed 
rule for additional discussion of the technical details associated with 
these measures,

[[Page 25651]]

their data sources, calculations, cohorts, and risk adjustment.
    As previously discussed, with respect to proposed 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 proposed, we propose to adopt 
the Severe Hypoglycemia and Severe Hyperglycemia CQMs for the Medicare 
Promoting Interoperability Program beginning with the reporting period 
in CY 2023.
    We welcome public comments on these proposed eCQM adoptions.
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(4) Proposed 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). 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 the revised criteria (85 FR 
70066 through 70068). The 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. 
These updates were finalized to reduce burden on health IT developers 
under the ONC Health IT certification program and have no impact on 
providers' existing reporting practices for CMS programs.
    In this proposed rule, we are proposing 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 proposal for the Hospital IQR Program discussed in 
section IX.C. of the preamble of this proposed 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 proposed rule for 
additional information related to this proposal.
    We invite public comment on our proposal to require 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.
(5) References to Additional Requests for Information
    We also refer readers to section IX.A of the preamble of this 
proposed rule where we request information on potential actions and 
priority areas that would enable the continued transformation of our 
quality measurement enterprise toward use of the Health Level Seven 
International (HL7[supreg]) Fast Healthcare Interoperability Resources 
(FHIR[supreg]) standard. Additionally, we refer readers to section IX.B 
of the preamble of this proposed rule where we request information on 
the possibility of expanding our current social disparities methods in 
order to include race and ethnicity as well as seeking comment on the 
potential design of a hospital equity score for calculating results 
across multiple social risk factors and measures.
12. Requests for Information
a. Request for Information on Additional Objectives or Measures 
Adopting FHIR[supreg]-Based API Standards
    Fast Healthcare Interoperability Resources (FHIR[supreg]) (http://hl7.org/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 IT. FHIR[supreg] allows systems to communicate 
and information to be shared seamlessly with a lower burden on 
stakeholders. Through the HL7[supreg] FHIR[supreg] standard, cost and 
burden for health care providers and patients are reduced since it 
simplifies implementation without sacrificing information integrity, 
and establishes fast, efficient, and flexible health data exchange as a 
stand-alone standard or combined with existing standards. Essentially, 
HL7[supreg]'s FHIR[supreg] standard framework provides an interoperable 
platform for a variety of healthcare data by defining a standard way to 
structure this information as `resources' and allows the developer-
friendly automated data-exchange to occur via APIs. The use of APIs 
utilizing the FHIR[supreg] standard has the potential to improve data 
exchange by providing consistent security, performance, scalability, 
and structure to all users.
    Given the progress of such emerging health IT innovation standards 
to promote interoperability at large, we see increased adoption of 
approaches utilizing the latest HL7[supreg] FHIR[supreg] standard as an 
opportunity to consider how these approaches can support other program 
goals.

[[Page 25653]]

    In the CY 2021 PFS final rule, we finalized alignment of the CEHRT 
definition for the Promoting Interoperability programs with updates to 
2015 Edition certification criteria as finalized in the ONC 21st 
Century Cures Act final rule. As part of the ONC 21st Century Cures Act 
final rule, ONC finalized a new certification criterion ``Standardized 
API for patient and population services'' at 45 CFR 170.315(g)(10) 
which supports the availability in certified health IT of an API using 
the FHIR[supreg] R4 standard and other implementation specifications. 
We noted that technology certified to this criterion will be used to 
support the API requirements in the Provide Patients Access to their 
Health Information objective. Regarding the bi-directional HIE measure 
finalized for eligible clinicians in the 2021 PFS final rule (85 FR 
84888 through 84893) (this rule is proposing a similar measure for 
adoption in the Medicare Promoting Interoperability Program for 
eligible hospitals and CAHs), we also noted that the standards-based 
API criterion at 45 CFR 170.315(g)(10) could be used to support 
connections to an HIE in order to complete the measure's actions.
    We are seeking comments on our intention to further align Medicare 
Promoting Interoperability Program measures with approaches utilizing 
HL7[supreg] FHIR[supreg] standard Release 4-based API functionality (or 
the appropriately evolved standard), with the Health Information 
Exchange as well as the Public Health and Clinical Data Exchange 
objectives. Throughout this ongoing developmental process, we are 
partnering with ONC and continuing to strengthen collaboration on the 
implementation of the ONC 21st Century Cures Act final rule.
    We are interested in public comments on how these two program 
objectives could be furthered through the use of FHIR[supreg]-based API 
solutions. Specifically, we are interested in the following questions:
     To what degree are stakeholders currently using or 
interested in using APIs to exchange information in support of the 
numerator/denominator measures under the HIE objective? What revisions 
to the measures under the HIE objective should CMS explore to 
facilitate use of standards-based APIs in health IT modules certified 
under the 2015 Edition Cures Update?
     How could technical approaches utilizing the FHIR[supreg] 
standard enhance existing data flows required under the public health 
measures? What are promising FHIR-based approaches to public health 
reporting use cases that ONC and CMS should explore for potential 
future consideration as part of the Promoting Interoperability program 
and the ONC Health IT Certification Program?
     To what degree are PHAs and individual states currently 
exploring API-based approaches to conducting public health registry 
reporting? What other factors do stakeholders see as critical factors 
to adopting FHIR[supreg]-based approaches?
     What potential policy and program changes in CMS and other 
HHS programs could reduce health care provider and health IT developer 
burden related to measures under the Health Information Exchange and 
the Public Health and Clinical Data Exchange objectives?
b. Request for Information on a Patient Access Outcomes Measures
    The evolution of EHRs has created a greater and more seamless flow 
of information within a digital healthcare infrastructure, which allows 
for comprehensive records to be made available wherever and whenever 
they are needed in the clinical setting. These advances have led to: 
(1) Improved patient care; (2) increased patient participation; (3) 
improved care coordination; (4) greater practice efficiencies and cost 
savings; and (5) improved diagnostics and patient outcomes.\1445\ Much 
research has been dedicated to looking at the implementation of health 
IT in practice settings with its wide array of potential benefits, but 
equally important is better understanding the patient's role as an 
active end-user as well.
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    \1445\ https://www.healthit.gov/topic/health-it-basics/benefits-ehrs.
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    Several large, nationally representative surveys have been 
completed annually in order to collect and evaluate the public's access 
and use of health information. One of these endeavors operated by the 
National Cancer Institute (with support from ONC) is called The Health 
Information National Trends Survey (HINTS) that produces a plethora of 
key utilization data specifically pertaining to consumers' access and 
use of their online medical records via patient portals. The HINTS 
results point to an overall year-over-year rise in the number of 
Americans who are not only accessing their medical records online (from 
51% in 2018 to 58% in 2019 \1446\) but are increasingly doing so to 
perform meaningful actions such as to view lab test results, transmit 
their data to a third-party, and to securely message their health care 
provider. While sources like the HINTS survey are revealing 
preferential trends, habits, and other key utilization points, the data 
also show some strong barriers associated with patients accessing EHR 
technology and continue to stress the need for further work in 
understanding these users' access outcomes.
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    \1446\ Patel, V. Johnson, C. (2020). The Current State of 
Patients' Access and Use of their Electronic Health Information 
[PowerPoint presentation]. The Office of the National Coordinator 
for Health Information Technology Annual Meeting.
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    We believe a strong partnership between EHR vendors, health care 
providers, and beneficiary users' outcomes is critical to improving the 
future of health care and furthering interoperability. Therefore, we 
are seeking comments surrounding changes to the Medicare Promoting 
Interoperability Program and related efforts which could better target 
patient access outcomes related to use of patient portals or third-
party application(s). This request for information is an opportunity to 
garner general interest, solicit stakeholder feedback on how to best 
evaluate issues of patient behavior, and to explore additional key 
outcome variables to capture for measurement.
    Specifically, we are looking for feedback on the following 
questions:
     What do stakeholders believe would be useful ways to 
measure patients' access to their electronic health information using 
health IT methods such as patient portals and/or third-party 
applications? What actionable figures related to users' medical record 
behavior, including but not limited to, the frequency of logins, number 
of messages sent, or lab results viewed could be captured?
     How effectively is the Medicare Promoting Interoperability 
Program currently measuring the use of health IT-enabled processes to 
improve patient outcomes? What measures in the current program are most 
relevant to patient outcomes?
     Should we consider requiring providers to maintain a 
record of third-party applications which patients have used to access 
their patient health information through APIs incorporated within 
certified technology so that this information could be used to assess 
patient usage of these applications?
     What are specific technologies, capabilities, or system 
features (beyond those currently addressed in the Medicare Promoting 
Interoperability Program) that can increase patient utilization of 
tools to access their health information? How do these technologies and 
features support improved access or usability within EHR systems and 
other applications (for instance, alternate authentication technologies 
that can simplify consumer logon)? How could

[[Page 25654]]

CMS reward health care providers for higher adoption rates and use of 
these available technologies?
     What are key administrative processes that could benefit 
from more efficient electronic workflows? How could CMS measure and 
reward participating eligible hospitals or CAHs for either greater 
uptake of patient portal access or subsequent health outcomes?
c. Request for Information on Clinical Notes
    OpenNotes is an international movement aimed to spread and study 
the effects of transparent communication among patients, families, and 
clinicians.\1447\ With more than 50 million patients in the U.S. and 
Canada having gained access to their clinical notes, the push for 
patient engagement and transparent communication continues to 
grow.\1448\ ``Clinical notes'' are regarded as highly desirable data 
necessary for the interoperable exchange of health information and 
patient access. Comprised of structured and unstructured data, clinical 
notes may include the assessment, diagnosis, plan of care and 
evaluation of plan, patient teaching, and other relevant data.
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    \1447\ https://www.opennotes.org/about/.
    \1448\ https://www.opennotes.org/history/.
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    While the ability to share clinical notes has been previously 
supported for certified health IT in different ways, ONC took 
additional steps to ensure this important patient information is 
available as part of the recent ONC 21st Century Cures Act final rule 
(85 FR 25674 through 25677). In the rule, ONC finalized eight types of 
``clinical notes'' required under the USCDI version 1: (1) Discharge 
Summary Note; (2) History & Physical; (3) Progress Note; (4) 
Consultation Note; (5) Imaging Narrative; (6) Laboratory Report 
Narrative; (7) Pathology Report Narrative; and (8) Procedure 
Note.\1449\
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    \1449\ https://www.healthit.gov/isa/uscdi-data/clinical-notes#uscdi-v1.
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    As previously discussed in the CY 2021 PFS final rule (85 FR 
84825), we finalized to align the CEHRT definition under the Medicare 
Promoting Interoperability Program with the updates to certification 
criteria finalized under the ONC 21st Century Cures Act final rule. 
This alignment includes updates to several certification criteria to 
refer to the USCDI and the expanded support for clinical notes 
specified in the USCDI version 1 standard. New and updated 
certification criteria incorporating the USCDI, include the ``view, 
download, and transmit'' criterion at 45 CFR 170.315(e)(1), and the 
``Standardized API for patient and population services'' criterion at 
45 CFR 170.315(g)(10). Once health IT developers and providers have 
completed implementation of these updates, certified health IT utilized 
for participation in the Promoting Interoperability Programs will 
support availability of the clinical note types in the USCDI as part of 
the data set made available to patients under the Provide Patients 
Access to their Health Information measure. According to the policy 
finalized in the CY 2021 PFS final rule, eligible hospitals and CAHs 
may begin using updated technology as soon as it is available from 
their developers (effective upon the effective date of the CY 2021 PFS 
final rule), with updated technology being required for reporting 
periods beginning in CY 2023.
    Under this RFI, we are seeking feedback on changes we can make that 
will better support the goals of the OpenNotes movement to ensure that 
clinical notes are widely available to patients. Given the 
implementation of updates to certified technology, as previously 
described, that support the Provide Patients Access to their Health 
Information measure, are there additional changes to this measure, or 
other program guidance, which could further facilitate ensuring 
clinical notes are available to patients consistent with the goals of 
the OpenNotes movement? We are also seeking stakeholder feedback on the 
development of a required and independently scored measure for the 
Medicare Promoting Interoperability Program to allocate points for the 
use of ``clinical note'' types supported by certified health IT. 
Finally, we are seeking comment on the types of clinical notes that are 
commonly sought, but not easily accessible to patients.
d. Request for Information on Designating High Performing Hospitals
    Several industry-sponsored models have been developed to recognize 
and distinguish hospitals and CAHs for their adoption and utilization 
of EHR functionality. Scored and ranked, these designations have been 
developed by industry experts to highlight key areas such as level of 
EHR adoption, comparative capabilities to rank hospitals, and serving 
as a marketing tool for public recognition. Two examples include the 
HIMSS Analytics Electronic Medical Record Adoption Model (EMRAM)\1450\, 
and the CHIME Most Wired Model\1451\. EMRAM is an eight-stage model 
scoring hospitals relative to their Electronic Medical Records (EMR) 
capabilities, measuring the adoption and utilization of EMR 
functionality. The Most Wired is a ten-stage model, which encourages 
maximizing the use of information technology to improve patient safety 
and outcomes, while forging change in health IT.
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    \1450\ https://www.himssanalytics.org/emram.
    \1451\ https://chimecentral.org/chime-most-wired-2/#tab_ert_pane1-0.
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    We are seeking stakeholder feedback on the development of, or 
support and adoption of, designating high performing hospitals in the 
context of EHR excellence. Specifically, we seek stakeholder input on 
the following questions:
     Are there specific industry-based models that are wholly 
representative of EHR excellence in the hospital or CAH setting? Which 
model is most representative and why?
     What are the limitations in applying for, or receiving one 
of the industry-based designations? What would help facilitate 
hospitals and CAHs to obtain and maintain such a designation?
     Does earning a designation accurately reflect EHR 
excellence within the patient community or amongst hospitals and CAHs?
     Is there interest in a CMS-driven designation program? If 
so, which components are most meaningful and valuable to hospitals and 
CAHs?
     We would like feedback on the potential of developing a 
Star Rating for Promoting Interoperability, or, adding Promoting 
Interoperability as a category for existing Star Ratings. Would this 
effort accurately represent EHR excellence?

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,\1452\ which is a Medicaid benefit that assists low-
income Medicare beneficiaries with Medicare Part A and Part B premiums

[[Page 25655]]

and cost sharing. QMB ``Medicare cost-sharing'' amounts, as defined in 
section 1905(p)(3) of the Act,\1453\ 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.
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    \1452\ 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.
    \1453\ 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.\1454\ 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.
---------------------------------------------------------------------------

    \1454\ 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 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) \1455\ that sets forth the State's cost-sharing liability for the 
items and services the beneficiary received (the ``RA'' policy).
---------------------------------------------------------------------------

    \1455\ 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, to allow 
providers with pending appeals a way to submit alternative 
documentation to the Medicaid RA that sets forth the state's 
liability for the cost-sharing. 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.\1456\ 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.
---------------------------------------------------------------------------

    \1456\ https://www.medicaid.gov/Federal-policy-guidance/downloads/cib-06-07-2013.pdf.
---------------------------------------------------------------------------

    To clarify states' obligations regarding claims for Medicare cost-
sharing by adding a new paragraph (d) to 42 CFR 455.410 to clearly 
specify in regulation how states must meet this obligation. 
Specifically, we propose 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 its 
responsibility, already required pursuant to 42 CFR 433.112(b)(3), to 
process claims for dual eligible beneficiaries. We note that neither 
this existing guidance nor the provisions of this proposed rule would 
require states to recognize or enroll additional provider types for 
purposes other than submission, adjudication of cost-sharing claims, 
and issuance of a Medicaid RA. Accordingly, 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 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.\1457\ However, states should 
consult with CMS to help ensure their compliance with 42 CFR 455.410(d) 
and other Federal provider enrollment requirements related to this 
proposal.
---------------------------------------------------------------------------

    \1457\ Medicaid Provider Enrollment Compendium (MPEC).
---------------------------------------------------------------------------

    We propose 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. 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. If necessary, we will propose specific 
enforcement penalties for non-compliance in future rule making. We

[[Page 25656]]

discuss Medicaid burden associated with these system changes in section 
I.H.10 of Appendix A of this proposed rule.
    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, the proposal 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.10 of Appendix A of this proposed rule.
    Failure of State MMIS to provide an 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 believe this proposal may 
have a positive impact on beneficiary access to care through reduced 
provider burden.
    In addition to certain Medicare-recognized provider and supplier 
types having difficulty enrolling in some Medicaid programs for 
purposes of submitting cost-sharing claims, as previously discussed, we 
have also heard that some providers have had difficulty getting states 
to process certain cost-sharing claims for services that are not 
payable by the State under the terms of the Medicaid State Plan. We 
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.\1458\ 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 request additional feedback from stakeholders on the scope 
of this practice, including State and service specific examples, and we 
will consider whether to include such a policy or otherwise address the 
issue in future rulemaking.
---------------------------------------------------------------------------

    \1458\ 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.
---------------------------------------------------------------------------

B. Organ Acquisition Payment Policies

1. Background
a. History of Medicare Organ Acquisition Policies
    The Medicare Program supports organ transplantation by providing an 
equitable means of payment for the variety of organ acquisition 
services. Medicare excludes organ acquisition costs from the inpatient 
hospital prospective diagnosis-related group (DRG) payment for an organ 
transplant, and separately reimburses transplant hospitals \1459\ (THs) 
for the organ acquisition costs on a reasonable cost basis (42 CFR. 
412.2(e)(4) and 412.113(d)).\1460\
---------------------------------------------------------------------------

    \1459\ Under 42 CFR 482.70 a transplant hospital is a hospital 
that furnishes organ transplants and other medical and surgical 
specialty services required for the care of transplant patients.
    \1460\ Pursuant to 42 CFR 412.113(d), organ acquisition costs 
incurred by hospitals with approved transplant programs are paid for 
on a reasonable cost basis.
---------------------------------------------------------------------------

    Medicare's current organ acquisition policy is modeled after the 
kidney acquisition policy that was implemented for kidney transplants 
following the Social Security Amendments of 1972 (Pub. L. 92-603) that 
extended Medicare coverage to individuals with end stage renal disease 
(ESRD) who required dialysis or transplantation. In July 1973, CMS 
(then the Bureau of Health Insurance \1461\ (BHI)) issued Intermediary 
Letters (ILs) which set forth procedures and policies for Medicare 
reimbursement for kidney transplants. The IL 73-25 (July 1, 1973) set 
forth policies for the reimbursement for kidney transplants and 
dialysis, including policies for hospital reimbursement for the 
acquisition of a kidney from cadaveric and living donors for transplant 
into a Medicare beneficiary. In IL 73-25, the BHI commented that as it 
received and analyzed data and studied reimbursement methodology, it 
would develop and issue more detailed reimbursement instructions to 
support the delivery of quality services in an efficient manner. In 
July 1974, the BHI issued IL 74-23, which set forth additional policies 
for Medicare reimbursement of kidney acquisition costs, many of which 
remain in place currently. In 1978, to clarify that the Secretary of 
the Department of Health and Human Services (the Secretary) has 
authority and to provide reimbursement for the costs incurred in 
connection with kidney donations, Congress enacted legislation that 
added special provisions relating to coverage under the Medicare 
Program for ESRD (Pub.L. 95-292). This legislation added section 1881 
to the Act that set forth Medicare payment for kidney transplantation 
and the coverage of organ procurement costs and living donor expenses, 
including Part A and Part B benefits for the living donor.\1462\ As CMS 
stated in the 1978 Federal Register (43 FR 44803), the purpose of 
section 1881 of the Act was to encourage kidney transplantation and the 
scope of Medicare benefits to cover all reasonable preparatory, 
operation and post-operation expenses associated with a kidney donor, 
through the actual period of recovery.
---------------------------------------------------------------------------

    \1461\ To implement the Medicare statute, the Social Security 
Administration was reorganized and the Bureau of Health Insurance 
(BHI) was established on July 30, 1965. The BHI then became 
responsible for the development of health insurance policy before 
the creation of the Health Care Financing Administration (HCFA), 
later renamed the Centers for Medicare & Medicaid (CMS). CMS 
Milestones 1937-2015 (July 2015).
    \1462\ H. Rep. 95-549 (July 29, 1977), section III.B.; S. Report 
95-714 (Mar. 22, 1978), section III.B.
---------------------------------------------------------------------------

    Over the years through various rulings and national coverage 
determinations, Medicare has added coverage for transplantation of non-
renal organs such as heart, liver or lungs; we modeled our 
reimbursement for the acquisition costs for non-renal organs based on 
our earlier

[[Page 25657]]

kidney acquisition policies. Medicare's organ acquisition payment 
policy is mostly set forth in CMS Pub. 15-1, chapter 31,\1463\ the 
Provider Reimbursement Manual (herein referred to as PRM) and in 
Medicare regulations at 42 CFR 412.2(e)(4), 412.100, 412.113(d), 
413.200, 413.202, and 413.203. The entities involved in organ 
acquisition, which we will further define and discuss herein, are THs, 
donor community hospitals (Medicare-certified non-transplant 
hospitals), organ procurement organizations (OPOs), some of which are 
hospital-based OPOs (HOPOs), and histocompatibility laboratories.
---------------------------------------------------------------------------

    \1463\ CMS Pub. 15-1, chapter 31 can be found at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Paper-Based-Manuals-Items/CMS021929) (Prior to the creation of chapter 31, the 
kidney acquisition policy was set forth in CMS Pub. 15-1, chapter 
27, Outpatient Maintenance Dialysis Reimbursement).
---------------------------------------------------------------------------

    Section 1102 of the Act authorizes the Secretary to publish rules 
and regulations necessary for the efficient administration of the 
functions with which the Secretary is charged under the Act. Section 
1871(a) of the Act authorizes the Secretary to prescribe such 
regulations as may be necessary to carry out the administration of the 
insurance programs under this title. In this proposed rule, we are 
proposing to codify into the Medicare regulations some longstanding 
Medicare organ acquisition payment policies, with clarifications where 
necessary, and proposing to codify some new organ acquisition payment 
policies. We are also proposing to move existing organ acquisition 
payment regulations or portions of existing kidney acquisition 
regulations within title 42 of the CFR part 412, subpart G and Part 
413, subpart H to a new proposed Part 413, subpart L, so that all organ 
acquisition payment policies are housed together. We are also proposing 
to codify into new subpart L certain policies pertaining to organ 
acquisition, as set forth in section 733 of the Medicare Prescription 
Drug, Improvement and Modernization Act of 2003 (Pub. L. 108-173) and 
section 17006 of the 21st Century Cures Act (Pub. L. 114-255), pursuant 
to their statutory effective dates. We are also proposing to make 
conforming changes and technical corrections to the regulations, where 
necessary.
    We are aware of OIG audits reporting that some OPOs have billed the 
Medicare Program for unallowable expenditures.\1464\ There have also 
been recent Congressional oversight interest and inquiries into OPO 
financial management.\1465\ We believe the proposals that follow would 
provide clarity and allow providers and stakeholders to more easily 
locate and understand organ acquisition payment policy, resulting in 
more accurate payment based on reasonable cost principles. We look 
forward to considering public comments on this proposed rule.
---------------------------------------------------------------------------

    \1464\ https://oig.hhs.gov/oas/reports/region9/90800033.pdf; 
https://oig.hhs.gov/oas/reports/region9/90900087.pdf; https://oig.hhs.gov/oas/reports/region9/90500034A.pdf; https://oig.hhs.gov/oas/reports/region9/91102039.pdf.
    \1465\ https://oversight.house.gov/news/press-releases/oversight-subcommittee-launches-investigation-into-poor-performance-waste-and ; https://www.young.senate.gov/newsroom/press-releases/young-joins-finance-committee-members-to-probe-us-organ-transplant-system.
---------------------------------------------------------------------------

b. Overview of Medicare Reimbursement in Transplantation
    Medicare reimburses THs for organ acquisition costs, the transplant 
surgery, inpatient, and post-transplant costs for the Medicare 
recipients, but through different payment systems. Medicare Part A pays 
for hospital costs of a transplant surgery and certain follow-up care 
through a DRG payment and the organ acquisition costs associated with a 
transplant on a reasonable cost basis. In general, Medicare Part B pays 
for the physician services and other services furnished to eligible 
Medicare beneficiaries. CMS established Conditions of Participation 
(CoP) for hospitals under 42 CFR part 482, subpart E. Transplant 
programs, located within a TH that has a Medicare provider agreement, 
must meet the hospital CoPs at Sec. Sec.  482.1 through 482.70 and the 
transplant program CoPs, located at Sec. Sec.  482.72 through 482.104, 
and additional requirements in order to be eligible to participate in 
the Medicare Program.
    OPOs coordinate the procurement, preservation and transportation of 
organs from deceased donors, and maintain a system for locating 
prospective recipients for organ transplantation. Section 1138 of the 
Act sets forth hospital protocols for the identification of potential 
organ donors and the standards for OPOs. To be an OPO, an entity must 
meet the applicable requirements of both the Act and the Public Health 
Service Act (the PHS Act). The statutory functions of an OPO are also 
set forth in 42 U.S.C. 273; section 371 of the PHS Act. Section 1138(b) 
of the Act provides the statutory qualifications and requirements that 
an OPO must meet in order to be reimbursed under the Medicare or 
Medicaid Program for certain organ procurement costs. CMS established 
Conditions for Coverage (CfCs) OPOs must meet in order to receive 
payment under Medicare or Medicaid for organ procurement costs in the 
regulations at 42 CFR part 486, subpart G. Section 1138(b)(1)(A) of the 
Act specifies that payment may be made for organ procurement costs only 
if the agency is a qualified OPO operating under a grant made under 
section 371(a) of the PHS Act or has been certified or re-certified by 
the Secretary as meeting the standards to be a qualified OPO. Among 
those requirements, each OPO must be a member of, participate in, and 
abide by the rules and requirements of the Organ Procurement 
Transplantation Network (OPTN) that are approved by the Secretary. (See 
42 CFR 486.320.)
    Medicare reimburses THs for organ acquisition costs under 
reasonable cost principles \1466\ pursuant to section 1861(v) of the 
Act, based on the TH's ratio of Medicare usable organs to total usable 
organs. Medicare authorizes payment to designated OPOs for kidney 
acquisition costs, under reasonable cost principles \1467\ pursuant to 
section 1861(v) of the Act, based on the OPO's ratio of Medicare usable 
kidneys to total usable kidneys (see section 1881(b)(2)(A) of the Act).
---------------------------------------------------------------------------

    \1466\ See 42 CFR 412.113(d); HCFA Ruling 87-1 (April 1987); CMS 
Ruling 1543-R (December 2006).
    \1467\ Id. Section 1138(b)(1)(F) of the SSA; 42 CFR 
413.1(a)(1)(ii)(A); 413.200(a).
---------------------------------------------------------------------------

    Histocompatibility laboratories provide laboratory services to 
ensure compatibility between donor organs and potential recipients in 
preparation for transplants. Section 1881(b)(2)(A) of the Act 
authorizes Medicare reimbursement for the cost incurred by a 
histocompatibility laboratory pursuant to sections 1861(v) or 1886 (if 
applicable). Histocompatibility laboratories are either independent or 
hospital-based. A histocompatibility laboratory is ``independent'' 
unless it is considered a department of the hospital and subject to 
control of the hospital.\1468\ 42 CFR 413.200(a) requires the 
reasonable costs of services furnished by histocompatibility 
laboratories be reimbursed in accordance with the principles contained 
in 42 CFR 413.60 and 413.64.
---------------------------------------------------------------------------

    \1468\ 43 FR 58371 (December 14, 1978).
---------------------------------------------------------------------------

2. Organ Acquisition Payment Policy Proposals
a. Terminology Notes and Proposed Definitions
(1) Use of Consistent Terminology
    Throughout this proposed rule, we will use consistent terminology 
such as ``transplant hospital'' and ``transplant program.'' These terms 
have been

[[Page 25658]]

defined in other CMS regulations at 42 CFR 482.70 as:
    Transplant hospital means a hospital that furnishes organ 
transplants and other medical and surgical specialty services required 
for the care of transplant patients.
    Transplant program means an organ-specific transplant program 
within a transplant hospital (as defined in this section).
    The regulations in 42 CFR parts 412 and 413 had previously used 
``transplantation center'' to mean a ``transplant program.'' Our PRM 
also uses ``certified transplant center'' to mean a TH, but we are 
proposing to use consistent language in this rule to avoid confusion. 
Thus, throughout this proposed rule, we will refer to a hospital that 
has an approved organ-specific transplant program as a TH, and we will 
use ``transplant program'' to refer to the organ-specific program 
itself. In section X.B.2.m.(1) of this proposed rule, we are proposing 
conforming changes to some existing regulations to ensure that 
``transplant hospital'' and ``transplant program'' are used 
consistently and as described here.
(2) Proposed Definitions
    In addition to using consistent terminology throughout this rule, 
we are proposing to add specific definitions into the regulations by 
adding Sec.  413.400, entitled ``Definitions,'' to new subpart L of 42 
CFR, part 413. We are also proposing to move all definitions in 
existing Sec.  413.200(b) ``Definitions,'' to new Sec.  413.400 to 
maintain this regulation with all other organ acquisition regulations 
in proposed new subpart L of part 413. Further, we are proposing to 
revise some of the definitions proposed to be moved from Sec.  
413.200(b) to new Sec.  413.400, as noted in the following discussion.
    For organ acquisition payment purposes, an ``organ,'' means a human 
kidney, liver, heart, lung, pancreas, or intestine (or multivisceral 
organs when transplanted at the same time as an intestine) as defined 
in 42 CFR 486.302. Effective October 1, 2004, organs also include 
pancreata procured for the purpose of acquiring pancreatic islet cells 
for transplantation into individuals who are participating in a 
National Institute of Diabetes and Digestive and Kidney Diseases 
clinical trial. We are proposing to codify our proposed definition for 
``organ'' in Sec.  413.400, new subpart L.
    Medicare makes payment for such pancreata in accordance with 
section 733 of the Medicare Prescription Drug, Improvement and 
Modernization Act of 2003 (Pub. L. 108-173) which requires Medicare to 
pay for items and services that are reasonable and necessary routine 
patient care costs related to acquisition and delivery of pancreatic 
islet cells for transplantation into Medicare beneficiaries included in 
a National Institute of Diabetes and Digestive and Kidney Diseases 
clinical trial of islet cell transplants.
    Our proposed definition of organ is for Medicare organ acquisition 
payment purposes and differs from the definition set forth in 42 CFR 
486.302 CfC for OPOs. The CMS OPO CfCs final rule (85 FR 77947 
published December 2, 2020), defines ``organ'' under 42 CFR 486.302, to 
mean a human kidney, liver, heart, lung, pancreas, or intestine (or 
multivisceral organs when transplanted at the same time as an 
intestine). The pancreas counts as an organ even if it is used for 
research or islet cell transplantation. The final rule describes the 
inclusion in the performance measures for OPO certification of 
pancreata used for research in the definition of organ as necessary in 
order to meet the statutory requirements of section 371(c) of the 
Public Health Service Act that provides pancreata procured by an OPO 
and used for islet cell transplantation or research shall be counted 
for purposes of certification or recertification (85 FR 77902). 
However, for Medicare payment purposes, an organ procured for research 
is not counted as a Medicare organ in Medicare's share of organ 
acquisition costs, except where explicitly required by law. Therefore, 
in order to mitigate potential stakeholder confusion, we are proposing 
a definition of ``organ'' for organ acquisition payment purposes that 
differs from the definition set forth in the OPO CfCs.
    We are proposing to include the definition of Organ Procurement 
Organization (OPO) as it currently exists in Sec.  413.200(b). As 
defined in 42 CFR 486.302, an OPO means an organization that performs 
or coordinates the procurement, preservation, and transport of organs 
and maintains a system for locating prospective recipients for 
available organs. An OPO can be a HOPO or an independent OPO. An OPO is 
``independent'' unless it is considered a department of the hospital 
and subject to control of the hospital.
    Additionally, we are proposing to codify the definition of a HOPO 
as an OPO that is considered a department of the TH and reports organ 
acquisition costs it incurs on the TH's Medicare cost report 
(MCR).\1469\ The proposed definition is consistent with the description 
of HOPO in the PRM, and is commonly known in the organ acquisition and 
transplant community. We are proposing to codify our proposed 
definition in Sec.  413.400, new subpart L. As of March 12, 2021, there 
are 7 HOPOs in operation.\1470\
---------------------------------------------------------------------------

    \1469\ Hospital and Health Care Complex Cost Report, currently 
Form CMS-2552, OMB No. 0938-0050.
    \1470\ Information available at https://optn.transplant.hrsa.gov/members/; accessed March 12, 2021.
---------------------------------------------------------------------------

    We are also proposing that a transplant hospital/HOPO (TH/HOPO) 
refers to a transplant hospital, or a transplant hospital that operates 
a HOPO (as defined previously in this section) and performs organ 
procurement activities as one entity reported on the transplant 
hospital's MCR. We are proposing to codify our proposed definition in 
Sec.  413.400 new subpart L.
    We are also proposing to revise the terminology ``freestanding'' as 
it currently exists in 42 CFR 413.200(b) in relation to OPOs, to be 
``independent OPO (IOPO)'' because this terminology is more widely used 
in the industry. We are also proposing to revise the IOPO definition by 
adding a third distinguishing factor. The proposed definition for an 
IOPO would mean an OPO that files a MCR separate from a hospital and 
meets all of the following: (1) Is not subject to the control of a 
hospital with respect to the hiring, firing, training, and paying of 
employees; (2) is not considered as a department of a hospital for 
insurance purposes (including malpractice insurance, general liability 
insurance, worker's compensation insurance, and employee retirement 
insurance); and (3) reports organ acquisition costs it incurs on the 
IOPO MCR.\1471\ We are clarifying that an IOPO that wishes to have the 
cost of its pre-transplant services reimbursed under Medicare must 
agree to certain requirements specified in 42 CFR 413.200(c). If an 
IOPO operates a histocompatibility laboratory, the costs of its 
histocompatibility laboratory are included on the IOPO's MCR. We are 
proposing to codify our proposed definition in Sec.  413.400, new 
subpart L.
---------------------------------------------------------------------------

    \1471\ Organ Procurement Organizations and Histocompatibility 
Laboratory, currently Form CMS-216, OMB. No. 0938-0102.
---------------------------------------------------------------------------

    A histocompatibility laboratory performs laboratory services to 
determine the degree of histocompatibility between donor organs and 
potential recipients. We are also proposing to include a definition of 
``histocompatibility laboratory'' as it currently exists in Sec.  
413.200(b) with a technical correction. We are proposing to make a 
technical correction to the cross-reference to Sec.  413.2171(d) 
because

[[Page 25659]]

this regulation citation is no longer correct. We are proposing that 
``histocompatibility laboratory'' means a laboratory meeting the 
requirements set forth in 42 CFR 493.1227 and providing the services 
for the acquisition of kidneys or other organs for transplantation. We 
are proposing to codify our proposed definition in Sec.  413.400, new 
subpart L.
    We are proposing that standard acquisition charge (SAC) means a 
charge as defined in proposed new Sec.  413.404 in section X.B.2.c. of 
this proposed rule. We are proposing to codify our proposed definition 
in Sec.  413.400, new subpart L.
    We are also proposing to add the definitions for ``transplant 
hospital'' and ``transplant program'' that currently exist in 42 CFR 
482.70 in Sec.  413.400, to new subpart L.
b. Proposals Related to Organ Acquisition Costs
(1) Proposed Items and Services Considered Organ Acquisition Costs
    In this proposed rule, we are proposing to add Sec.  413.402(a) to 
new subpart L to specify that costs incurred in the acquisition of 
organs from a living donor or a cadaveric donor by the hospital or by 
an OPO, as appropriate, are organ acquisition costs. To make necessary 
policy revisions and clarifications of acquisition costs for kidneys as 
well as for non-renal organs, we are proposing to revise Sec.  
412.100(b), by removing the list of organ acquisition costs found in 
that paragraph and re-codifying them with some revisions by adding 
Sec.  413.402(b) to new subpart L.
    We are proposing to codify that the costs of acquiring organs 
(kidneys and non-renal organs) covered by Medicare Part A are: (1) 
Tissue typing, including tissue typing furnished by independent 
laboratories; (2) donor and beneficiary evaluation; (3) other costs 
associated with excising organs, such as general routine and special 
care services provided to the donor; (4) operating room and other 
inpatient ancillary services applicable to the donor; (5) preservation 
and perfusion costs; (6) OPTN registration fees; (7) surgeons' fees for 
excising cadaveric organs (currently limited to $1,250 for kidneys); 
(8) transportation of the excised organ to the TH; (9) costs of organs 
acquired from other hospitals or OPOs; (10) hospital costs normally 
classified as outpatient costs applicable to organ excisions (services 
include donor and recipient tissue typing, work-up, and related 
services furnished prior to admission); (11) costs of services 
applicable to organ excisions which are rendered by residents and 
interns not in approved teaching programs; and (12) all pre-admission 
services applicable to organ excisions, such as laboratory, 
electroencephalography, and surgeons' fees for cadaveric excisions, 
applicable to organ excisions including the costs of physicians' 
services.
    We are proposing to apply the existing elements of kidney 
acquisition costs found in Sec.  412.100(b) to all organs, with 
clarifying revisions as described here. These items and services are 
currently specified in Sec.  412.100(b) (for kidneys only) and also 
discussed in sections 3101, 3102, and 3103 of the PRM. We are proposing 
to revise Sec.  412.100(b) to reference that kidney acquisition costs 
are specified in new Sec.  413.402(b) of this chapter.
    We are proposing to add Sec.  413.402(b) to new subpart L to 
include the costs for registration of a beneficiary for a kidney 
transplant as specified in Sec.  412.100(b)(6) and also include the 
costs for registration of a beneficiary for a non-renal transplant. The 
OPTN registration fee is assessed for all transplant candidates placed 
on the OPTN waiting list.\1472\ We are proposing to limit these 
registration fees to the OPTN registration fee. Reasonable cost 
principles, as set forth in section 1861(v) of the Act and specified in 
42 CFR 413.1(b) and Sec.  413.9, do not permit Medicare to pay for 
duplicate services. Any registration fee outside of the OPTN 
registration fee would be considered unnecessary and duplicative under 
reasonable cost principles for Medicare organ acquisition costs.
---------------------------------------------------------------------------

    \1472\ The hospital CoPs at 42 CFR 482.45(b)(1) require each TH 
to be a member of the OPTN and abide by its rules, which for THs 
include registering potential transplant recipients on the OPTN 
registry as described in section 1.2.D of the OPTN Bylaws, available 
at https://optn.transplant.hrsa.gov/media/1201/optn_bylaws.pdf.
---------------------------------------------------------------------------

    Some kidney acquisition costs differ depending on whether the donor 
is living or is cadaveric. Our proposal would codify that surgeon fees 
are included as kidney acquisition costs only when the kidney excision 
occurs with a cadaveric donor. When a living donor enters the hospital 
for the actual kidney excision, surgeon fees for excising the kidney 
are not included as kidney acquisition costs. The surgeon bills these 
surgeon fees to Medicare Part B using the transplant recipient's 
Medicare Beneficiary Identifier (MBI). Congress enacted section 1881(d) 
in 1978, which (in part) entitled living donors to benefits under 
Medicare Part B with respect to the kidney donation, as if the donor 
were eligible for Medicare, and allowed the Secretary to prescribe in 
regulation how that would occur. CMS (then HCFA) implemented 
regulations at 42 CFR 405.231 and 405.244-1,\1473\ (which were 
subsequently relocated to 42 CFR 410.55 and 410.163),\1474\ which 
required Medicare Part B to pay for medical and other health services 
furnished in connection with a kidney donation if the kidney is 
intended for a Medicare beneficiary with ESRD, regardless of whether 
the donor is entitled to Medicare, and without deductibles or co-
insurance. As such, our proposed codification of Part A kidney 
acquisition costs related to donor surgeon fees only focuses on 
surgeons' fees for cadaveric excisions.
---------------------------------------------------------------------------

    \1473\ 43 FR 49720 to 49723.
    \1474\ 51 FR 41332.
---------------------------------------------------------------------------

    Section 371(b)(3)(F) of the PHS Act, 42 U.S.C. 273(b)(3)(F), 
requires that OPOs provide or arrange for the transportation of donated 
organs to transplant centers. Our proposal clarifies our longstanding 
policy in PRM section 3101 that Medicare covers the transportation of 
donated organs as an organ acquisition cost as authorized by section 
371(b)(3)(F) of Public Health Service Act.
    We are proposing to add Sec.  413.402(b) to new subpart L to 
specify the acquisition costs given at Sec.  412.100(b) of this 
chapter, with minor clarifying revisions, and to revise Sec.  
412.100(b) to cross-reference Sec.  413.402(b). We are also proposing 
to make additional revisions, technical corrections and conforming 
changes to Sec.  412.100 in sections X.B.2.b.(1) and X.B.2.m.(2) of the 
preamble of this proposed rule.
    Finally, we have received inquiries from various stakeholders about 
whether costs resulting from services to living kidney donors with 
complications are organ acquisition costs. We are proposing to codify 
that policy in Sec.  413.402(c) in new subpart L, to provide greater 
clarity to stakeholders. We discuss details of our policy and proposed 
codification related to living kidney donor complications in section 
X.B.2.e.(4) of this proposed rule.
(2) Cost Reporting, Billing, and Payment of Organ Acquisition Costs
    Both THs and OPOs can acquire organs for transplantation; 
therefore, both THs and OPOs can have organ acquisition costs. A TH can 
acquire organs from either a cadaveric donor or a living donor, while 
OPOs acquire organs from cadaveric donors. In accordance with 
requirements at Sec.  413.24(f), at the end of its fiscal year a TH/
HOPO files an annual hospital cost report (currently Form CMS-2552) and 
an IOPO files an annual OPO/

[[Page 25660]]

histocompatibility cost report (currently Form CMS-216). Organ 
acquisition costs incurred by a TH/HOPO are included on the appropriate 
organ acquisition cost center on its hospital MCR. Organ acquisition 
costs incurred by an IOPO (or by a histocompatibility laboratory, as 
authorized in section 1881(b)(2)(A) of the Act and discussed in section 
X.B.2.d.(3) of this proposed rule) are included in the appropriate 
organ acquisition cost center on its MCR.
    Currently, Medicare pays THs prospective payment amounts based on a 
DRG for the actual organ transplant; Medicare also reimburses THs for 
reasonable and necessary costs associated with acquiring organs for 
transplantation into Medicare beneficiaries (Sec.  412.113(d)). CMS 
excludes from the prospective payment amounts inpatient hospital organ 
acquisition costs for hearts, kidneys, livers, lungs, pancreas, and 
intestines (or multivisceral organs) incurred by approved THs, as 
specified in Sec.  412.2(e)(4). Medicare makes payment for organ 
acquisition costs incurred by hospitals with approved transplantation 
programs on a reasonable cost basis, as specified in Sec.  412.113(d), 
and in accordance with the principles of reasonable cost as set forth 
in section 1861(v) of the Act and in 42 CFR 413.1 and 413.9.
    When the TH cost report is settled, the Medicare contractor 
calculates the Medicare organ acquisition costs by multiplying the 
total of all allowable organ acquisition costs by the ratio of Medicare 
usable organs to total usable organs, for each organ type. The 
contractor reconciles the TH's Medicare organ acquisition costs by 
comparing the total interim payment amounts paid for organ acquisition 
costs under Sec.  413.64(f) to the total actual Medicare organ 
acquisition costs, and either pays amounts owed or collects from the TH 
any overpayment.
    The statute at section 1881(b)(2)(A) of Act authorizes Medicare to 
pay THs for services provided by OPOs for kidney acquisition. Medicare 
does not directly reimburse OPOs as these services are not covered 
until the transplant occurs at the TH. At the time of procurement, the 
OPO does not always know if the organ recipient is a Medicare 
beneficiary, as the registry database payor information may not be up-
to-date. Therefore, OPOs receive an interim payment based on their 
kidney SAC which is paid directly to them by the TH (or other OPO) that 
receives the kidney procured. Medicare pays IOPOs for kidney 
acquisition indirectly, through the reconciliation of actual costs 
incurred for kidney acquisition to actual kidney SAC payments received, 
as part of cost report settlement in accordance with Sec.  
413.200(e)(2), to ensure that the Medicare Program is paying its 
appropriate share. There is no explicit statutory requirement for 
Medicare to pay IOPOs for non-renal organs in the same way, so 
reconciliation and settlement of IOPO non-renal organ acquisition costs 
does not occur. Similar to kidney acquisition costs, IOPOs are paid an 
interim rate (SAC) directly by the TH (or other IOPO) which receives 
the non-renal organs the IOPO procures. Kidney and non-renal SACs are 
discussed in more detail in section X.B.2.c of this proposed rule.
(3) Services Not Considered Organ Acquisition Costs
    Medicare does not pay for certain costs incurred by OPOs, in 
accordance with section 1861(v)(1)(A) of the Act, and we are proposing 
to establish rules identifying those specific items. These activities 
or services include incurred costs found to be unnecessary in the 
efficient delivery of health care services, and are not limited to: 
\1475\
---------------------------------------------------------------------------

    \1475\ PRM 15-1, ch 31, Sec.  3108.C.
---------------------------------------------------------------------------

     Burial and funeral expenses for the cadaveric donor, 
including transportation of the cadaveric donor before and after 
excision (burials and funerals are not costs of acquiring organs and 
are not mentioned in section 371(b)(3) of the PHS Act (42 U.S.C. 
273(b)(3)), which lists a number of activities or services that OPOs 
perform; transportation costs are limited to the cost of transporting 
donated organs to the transplant hospital);
     Costs associated with the transportation of a living or 
cadaveric donor \1476\ (there may be programs outside of Medicare that 
pay for transportation costs for living donors \1477\);
---------------------------------------------------------------------------

    \1476\ 42 U.S.C. 273(b)(3)(F).
    \1477\ 85 FR 59438, September 22, 2020; see also the National 
Living Donor Assistance Center website at https://www.livingdonorassistance.org/About-Us/Mission-Background.
---------------------------------------------------------------------------

     Costs incurred prior to a potential donor being declared 
brain dead (healthcare costs incurred prior to declaration of death are 
the responsibility of the potential donor's health insurance);
     Fees or in-center payments for donor referrals (all 
hospitals are required to timely notify OPOs of imminent deaths; \1478\ 
PRM 15-2, chapter 40, section 4013 stipulates that, ``No amounts or 
fees paid to a donor, their estate, heirs, or assigns in exchange for 
an organ or for the right to remove or transplant an organ are included 
in organ acquisition costs.'');
---------------------------------------------------------------------------

    \1478\ 42 CFR 482.45.
---------------------------------------------------------------------------

     Costs associated with OPO sponsored seminars where 
continuing education credits are given \1479\ (these costs are not 
directly associated with acquiring organs); and
---------------------------------------------------------------------------

    \1479\ See CMS Pub. 15-1, chapter 4 for more information 
regarding allowable costs of educational activities.
---------------------------------------------------------------------------

     Certain costs incurred for administrator's duties 
associated with professional organizations (these costs are not 
directly associated with acquiring organs).
c. Proposals Related to Standard Acquisition Charges
(1) General
    In this proposed rule, we are proposing to clarify and codify 
Medicare's policy regarding TH/HOPO SACs, as set forth in PRM section 
3101, and as discussed herein. The IL 74-23, issued in July 1974, set 
forth the policies and procedures for a hospital to develop standard 
kidney acquisition charges for the acquisition of kidneys from living 
or cadaveric donors. Over the years, as Medicare added coverage for 
non-renal transplants, Medicare used these same policies and procedures 
for THs to develop living and cadaveric SACs for non-renal organs and 
OPOs to develop cadaveric SACs for non-renal organs.
    A SAC for an organ is an amount that represents the estimated costs 
a TH or an OPO expects to incur to acquire an organ. The SAC does not 
represent the actual acquisition cost for an individual organ. Instead, 
the SAC generally represents the average of the total actual costs 
associated with procuring either cadaveric donor organs or living donor 
organs.
    A TH or OPO cannot bill Medicare directly for the cost of procuring 
an organ because procuring an organ is not a covered service when 
performed independent of a Medicare covered transplant, and it is not 
always known at the time of organ procurement whether the potential 
recipient is a Medicare beneficiary. However, the reasonable costs of 
procuring an organ are reimbursable when billed in connection with a 
Medicare covered transplant. When a TH bills Medicare for the 
transplant, it bills the DRG charge for the organ transplant and uses 
its SAC to bill Medicare for the procured organ (currently using 
revenue code 081X \1480\). THs develop categories

[[Page 25661]]

of living or cadaveric SACs, by organ type (for example, heart, liver 
or lung). When a TH/HOPO or IOPO provides an organ to another TH or 
OPO, we are proposing that it must bill the receiving TH, TH/HOPO or 
IOPO its SAC. We are proposing to codify these provisions pertaining to 
SACs at proposed new Sec.  413.404(a) in new subpart L.
---------------------------------------------------------------------------

    \1480\ Medicare Internet Only Manual 100-04, Medicare Claims 
Processing Manual, Chapter 3, Section 90, available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.
---------------------------------------------------------------------------

(2) Transplant Hospitals and HOPOs
    In this proposed rule, we are proposing to codify provisions 
pertaining to SACs for TH/HOPOs for living and cadaveric donors at 
proposed new Sec.  413.404(b) in new subpart L, as described in this 
section.
(a) Living Donor Standard Acquisition Charge
    In this proposed rule, we are proposing to codify Medicare's 
longstanding policy regarding a TH's standard acquisition charges for 
living donors, as set forth in PRM section 3101.A., and as discussed 
herein, because these policies remain relevant. THs must develop a SAC 
for living organs, by organ type (for example heart, liver, or lung). 
THs/HOPOs must develop a SAC for cadaveric organs, by organ type. The 
living donor SAC is an average cost the transplant hospital incurs to 
procure an organ from a living donor. As medicine and transplantation 
have advanced, there now can be transplants from living donors for 
kidneys, lungs, and portions of livers, pancreata or intestines, and a 
living SAC can be established for them.
    A TH must establish a living donor SAC (living donor SAC) before 
the TH bills its first living donor transplant to Medicare. The TH 
develops the initial living donor SAC for each living donor organ type, 
by estimating the reasonable and necessary costs it expects to incur 
for services furnished to living donors, and pre-admission services 
furnished to recipients of living donor organs during the hospital's 
cost reporting period. The TH divides the estimated amount by the 
projected number of living donor organs to be procured by the TH, 
within the hospital's cost reporting period. A TH calculates its 
subsequent living donor SAC for each living organ type by using the 
transplant hospital's actual organ acquisition costs for the living 
donor organ type from the prior year's MCR, adjusted for any changes in 
the current year. The TH divides these costs by the actual number of 
usable living organs procured by the TH during that prior cost 
reporting period. Currently, when a TH/HOPO provides an organ to 
another transplant hospital or OPO, it must bill the receiving TH or 
OPO its SAC, by organ type, or the hospital's standard departmental 
charges that are reduced to cost. The TH/HOPO includes the actual 
incurred cost for organ procurement services in the organ acquisition 
cost center on the hospital's MCR.
    Costs that may be used to develop the living donor SAC include, but 
are not limited to: Costs of tissue typing services, including those 
furnished by independent laboratories; costs of physician pre-admission 
transplant evaluation services; OPTN registration fees; costs for donor 
and recipient evaluation and workup furnished prior to admission for 
transplantation; other costs associated with procurement, for example, 
general routine and special care services related to the donor; costs 
of operating room and other inpatient ancillary services related to the 
donor; preservation and perfusion costs; and transportation costs of 
the excised organ. We are proposing to codify these provisions at 
proposed new Sec.  413.404(b)(3)(i) in new subpart L.
(b) Cadaveric Donor Standard Acquisition Charge
    In this proposed rule, we are proposing to codify Medicare's 
longstanding policy regarding TH/HOPO standard acquisition charges for 
cadaveric donors and the costs that may be included in the cadaveric 
donor SAC, as set forth in PRM section 3101.B, and as discussed herein, 
because these policies remain relevant. The cadaveric donor standard 
acquisition charge (cadaveric donor SAC) is an average cost that a TH/
HOPO incurs to procure an organ from a cadaveric donor. The TH/HOPO 
calculates its initial cadaveric donor SAC for each cadaveric organ 
type, by estimating the reasonable and necessary costs it expects to 
incur in procuring cadaveric organs, combined with the expected costs 
of acquiring cadaveric organs from OPOs or other THs. The TH/HOPO 
divides this estimated amount by the projected number of usable 
cadaveric organs to be procured by the TH/HOPO within the TH's cost 
reporting period.
    The TH/HOPO calculates the subsequent cadaveric donor SAC for each 
cadaveric organ type, by using the transplant hospital's actual organ 
acquisition costs for the cadaveric donor organ type from the prior 
year's Medicare cost report, adjusted for any changes in the current 
year. The TH/HOPO divides this estimated amount by the actual number of 
usable cadaveric organs procured by the TH/HOPO during that prior cost 
reporting period.
    Where the TH/HOPO provides the organ to an OPO or another TH, the 
TH/HOPO uses its cadaveric donor SAC to bill the OPO or the TH 
receiving the organ. Costs that may be used to develop the cadaveric 
donor SAC include, but are not be limited to: Costs of organs acquired 
from other THs or OPOs; costs of transportation of the excised organs; 
surgeons' fees for excising cadaveric organs (currently limited to 
$1,250 for kidneys); costs of tissue typing services, including those 
furnished by independent laboratories; preservation and perfusion 
costs; general routine and special care service costs; and operating 
room other inpatient ancillary service costs. We are proposing to 
codify these provisions at proposed new Sec.  413.404(b)(3)(ii) in new 
subpart L.
(3) Independent OPO Standard Acquisition Charge
    In this proposed rule, we are proposing to codify, at proposed new 
Sec.  413.404(c) in new subpart L, Medicare's longstanding policy 
regarding IOPO standard acquisition charges for cadaveric donors, as 
set forth in PRM section 3108, and as discussed herein, because these 
policies remain relevant. An OPO is required under section 371(b)(1)(B) 
of the PHS Act (42 U.S.C. 273(b)(1)(C)) to have an agreement with the 
Secretary to be reimbursed under Medicare for the procurement of 
kidneys. The IOPO's Medicare contractor establishes the kidney SAC, 
which is considered an interim rate as currently specified in Sec.  
413.200(d) (proposed to be added to new subpart L as Sec.  413.420(d)), 
and which consists of an estimate of the reasonable and necessary costs 
the IOPO expects to incur procuring cadaveric kidneys during the IOPO's 
cost reporting period. The contractor divides the estimated amount by 
the projected number of usable cadaveric kidneys procured. The IOPO's 
Medicare contractor may adjust the kidney SAC during the year, if 
necessary, for cost changes. Because the contractor must establish and 
may adjust, if necessary, the kidney SAC, the IOPO cannot charge or 
change its kidney SAC without the contractor's approval.
    The Medicare contractor develops an IOPO's initial kidney SAC based 
on the IOPO's budget information. The kidney SAC for subsequent years 
is based on the IOPO's cost report, that is, costs of operating during 
its prior cost reporting year. These standard charges are the basis for 
the interim rate (that is, the kidney SAC) paid by the TH to the IOPO. 
When the IOPO bills the TH for its kidney acquisition services, the TH

[[Page 25662]]

is responsible for paying the IOPO's interim rate (that is, its kidney 
SAC). The IOPO's submitted cost report is used to reconcile kidney 
acquisition costs pursuant to Sec.  413.200(d) (proposed to be added as 
Sec.  413.420(d)).
    An OPO is required under (42 U.S.C. 273(b)(1)(B)) to have 
accounting and other fiscal procedures (as specified by the Secretary) 
necessary to assure the fiscal stability of the organization. As such, 
an IOPO establishes non-renal SACs based on its costs of procuring 
organs, similar to procedures set forth in section 3101, Certified 
Transplant Centers and Organ Acquisition Costs. An IOPO develops its 
SACs for each type of non-renal organs, by estimating the reasonable 
and necessary costs it expects to incur for services furnished to 
procure cadaveric donor non-renal organs during the IOPO's cost 
reporting period. The IOPO divides this estimated amount by the 
projected number of cadaveric donor non-renal organs the IOPO expects 
to procure within its cost reporting period.
    When an IOPO receives an organ from another IOPO, the receiving 
IOPO is responsible for paying the procuring IOPO's SAC. The IOPO uses 
its own SAC and not the SAC paid to another IOPO, when billing a TH 
receiving the organ. For example, IOPO A has a SAC of $35,000 and IOPO 
B has a SAC of $50,000. IOPO A receives an organ from IOPO B and pays 
IOPO B their SAC of $50,000. IOPO A provides the organ to the TH and 
bills the TH its SAC of $35,000.
d. Accounting for Outpatient Costs and Laboratory Services
    Outpatient costs including pre-transplant evaluation service costs 
were described for kidneys in ILs, as well as in the Medicare Claims 
Processing Manual and in a CMS Change Request.\1481\ After non-renal 
organs were covered for transplantation through a CMS Ruling (for heart 
transplants) and through NCDs (other non-renal organs),\1482\ payment 
policies were subsequently implemented through notice-and-comment 
rulemaking.\1483\
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    \1481\ Part A Intermediary Letter, July 01, 1973 No. 73-25 and 
Part B Intermediary Letter, No. 73-22; July 1973; Medicare Claims 
Processing Manual (IOM 100-04, chapter 3, section 90.1.1.A. 
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf); and change request 6978, available 
at (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Downloads/R2008CP.pdf).
    \1482\ See CMS Ruling 87-1, April 1987; National Coverage 
Determinations Manual, IOM 100-03, chapter 1, Part 4, section 260 
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/ncd103c1_Part4.pdf).
    \1483\ 52 FR 33034, September 1, 1987 (heart); 55 FR 8545, March 
8, 1990 and 56 FR 15013, April 12, 1991 (liver); 60 FR 6537, 
February 2, 1995 (lung); 64 FR 41497, July 30, 1999 (pancreas); 66 
FR 39828, August 1, 2001 (intestine, with reasonable cost coverage 
of acquisition costs beginning October 1, 2001).
---------------------------------------------------------------------------

(1) Outpatient Costs
    Section 3102.A. of the PRM describes how to account for certain 
hospital outpatient costs applicable to a potential organ transplant. 
The TH's organ acquisition costs include donor and recipient work-ups 
furnished prior to admission and costs of services rendered by interns 
and residents not in an approved teaching program. These costs would 
typically be billed to Medicare Part B. However, these costs are 
predominantly cadaveric donor related, incurred without an identifiable 
beneficiary, and are included in the TH's organ acquisition cost 
center.
(2) Pre-transplant Evaluation and Laboratory Services
    Section 3102.C. of the PRM specifies that pre-transplant evaluation 
services for recipients and donors provided by the TH, including 
laboratory services, are paid through the organ acquisition costs of 
the TH. When pre-transplant laboratory tests are performed by the TH, 
the TH accumulates these costs in its organ acquisition cost center. 
The TH also includes the reasonable charges paid for physician tissue 
typing services provided to living donors and recipients.
(3) Histocompatibility Laboratory Services
    Histocompatibility laboratories are required by the statute at 
section 1881(b)(2)(A) of the Act to be paid on a reasonable cost basis, 
in accordance with section 1861(v) of the Act. 42 CFR 413.200 sets 
forth the payment policy for services furnished by histocompatibility 
laboratories in connection with kidney acquisition and transplantation. 
When the laboratory services are performed by a histocompatibility 
laboratory, the Medicare contractor establishes interim rates which are 
used by the laboratory in billing a TH. The contractor disseminates 
information on the interim rates to all THs, OPOs, and other 
contractors, or posts the information on its website. The TH pays the 
laboratory the approved interim rate. When the laboratory bills an OPO 
for services, the OPO is responsible for paying the interim rate. The 
contractor determines the final payment to the histocompatibility 
laboratory for kidney-related transplant tests by reconciling interim 
payments and reasonable costs during final settlement of the MCR.
e. Accounting for the Cost of Services Provided to Living Kidney Donors
    Section 1881(d) of the Act sets forth Medicare coverage for living 
kidney donors. Under section 1881(d) of the Act, any individual who 
donates a kidney for transplant surgery shall be entitled to benefits 
under parts A and B of Medicare with respect to such donation. The Act 
requires that reimbursement for the reasonable expenses incurred by 
such an individual with respect to a kidney donation shall be made 
(without regard to the deductible, premium, and coinsurance 
provisions), in such manner as may be prescribed by the Secretary in 
regulations,\1484\ for all reasonable preparatory, operation, and 
postoperation recovery expenses associated with such donation. It 
further provides that payments for postoperation recovery expenses 
shall be limited to the actual period of recovery. Medicare's coverage 
is limited to those donor expenses that are incurred directly in 
connection with the kidney donation.
---------------------------------------------------------------------------

    \1484\ 42 CFR 409.18, 42 CFR 409.89 (Part A); 42 CFR 410.55, 42 
CFR 410.163 (Part B).
---------------------------------------------------------------------------

(1) Hospital Services to a Living Kidney Donor
    When a living donor is admitted to a hospital (before admission for 
excising the donor kidney) for a medical evaluation in anticipation of 
a kidney donation, costs of all hospital services applicable to medical 
evaluation are considered kidney acquisition costs. When the living 
donor subsequently enters the hospital for the actual excision, the 
hospital costs of services rendered to the donor will continue to be 
treated as kidney acquisition costs under Part A.\1485\
---------------------------------------------------------------------------

    \1485\ 42 CFR 409.18.
---------------------------------------------------------------------------

    The donor of a kidney for a Medicare transplant is covered for an 
unlimited number of days of inpatient care in connection with the organ 
removal operation. Days of inpatient hospital care used by the donor in 
connection with the organ removal operation are not charged against 
either party's utilization record.
(2) Physician Services to a Living Kidney Donor
    When a living donor is admitted to a hospital (before admission for 
excising the donor kidney) for a medical

[[Page 25663]]

evaluation in anticipation of a kidney donation, costs of all 
physicians' services applicable to medical evaluation are considered 
kidney acquisition costs. When a living donor is admitted to a hospital 
for the kidney excision, physician services are no longer considered 
kidney acquisition costs and are not reimbursable under Part A. Under 
the Medicare Physician Fee Schedule, surgical excision of living donor 
kidneys is included in the global surgery policy, with a reasonable 
post-surgical follow-up defined as 90 days.\1486\ This standard 90-day 
post-operative period includes all services by the primary surgeon 
during this period unless the service is for a condition or issue 
unrelated to the diagnosis for which the surgery is performed or is for 
an added course of treatment other than normal recovery from the 
surgery. During the donor's inpatient stay for the excision surgery and 
during any subsequent donor inpatient stays resulting from a direct 
complication of the organ donation, physician services are billed under 
Part B. They are billed in the normal manner but under recipient's MBI 
at 100 percent of the fee schedule,\1487\ with no deductible or 
coinsurance.\1488\
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    \1486\ See Addendum B in 59 FR 63515, for CPT code 50320, which 
is for living donor kidney excision.
    \1487\ 42 CFR 410.55 and 410.163.
    \1488\ 42 CFR 410.55 and 410.163. See also the kidney policy for 
living donors, which is described in the Medicare Benefit Policy 
Manual 100-02, chapter 11, section 140.5, available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/bp102c11.pdf and billing instructions in the Medicare Claims 
Processing Manual 100-04, chapter 3, section 90.1.1.F. and G., 
available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.
---------------------------------------------------------------------------

(3) Living Kidney Donor Follow-Up
    Costs incurred by the TH for routine kidney donor follow-up care 
are included in the TH's organ acquisition cost center.
    For routine follow-up care, the period of postoperative recovery 
ceases when the donor no longer exhibits symptoms related to the kidney 
donation. Beyond the reasonable and necessary 90-day global payment 
period, routine follow-up services are billed to Part B using the 
recipient's MBI. Routine follow-up services billed to Medicare by a 
physician other than the operating physician for up to 3 months 
following donation surgery must be billed using the recipient's MBI. 
The Medicare Administrative Contractor will review claims for services 
rendered more than 3 months after kidney donation surgery. Medicare may 
cover routine follow-up examinations up to 6 months after the kidney 
donation to monitor for possible complications. In all of these 
situations, the kidney donor is not responsible for co-insurance or 
deductible amounts.\1489\
---------------------------------------------------------------------------

    \1489\ 42 CFR 410.163.
---------------------------------------------------------------------------

    The OPTN policy provides for follow-up visits, which occur at 6 
months, 12 months, and 24 months post-donation. These follow-up visits 
are not allowable nor reportable as organ acquisition costs on the MCR 
and cannot be billed to Medicare. These follow-up visits are for 
collecting longer term data on the effects of living donation on the 
donor rather than for meeting medical needs of the donor.\1490\
---------------------------------------------------------------------------

    \1490\ Information from https://optn.transplant.hrsa.gov/resources/guidance/procedures-to-collect-post-donation-follow-up-data-from-living-donors/, accessed on March 16, 2021.
---------------------------------------------------------------------------

(4) Proposals Related to Living Kidney Donor Complications
    Living kidney donor complications related to the surgery to remove 
a kidney, which occur after the date of discharge, are not considered 
kidney acquisition costs. Living kidney donor complications are 
statutorily authorized to be paid under Part A or Part B in section 
1881(d) of the Act, with no liability for deductibles or 
coinsurance.\1491\ In accordance with IL 73-25,\1492\ Medicare covers 
costs incurred for living kidney donor complications only if they are 
directly attributable to the kidney donation. Costs incurred for 
complications arising after the kidney donor's discharge date are 
billed under the Medicare transplant recipient's MBI, including 
facility costs and physician services. The contractor reviews costs for 
kidney donor complications billed under the transplant recipient's MBI. 
We are proposing to codify this longstanding policy by adding 42 CFR 
413.402(c) to new subpart L.
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    \1491\ Section 1881(d) of the Act; 42 CFR 409.18, 409.89 for 
Part A costs; 42 CFR 410.55 and 410.163 for Part B costs.
    \1492\ Part A Intermediary Letter, July 1, 1973, No. 73-25.
---------------------------------------------------------------------------

f. Accounting for the Cost of Services Provided to Transplant 
Recipients
    Certain costs related to organ transplant recipients are not organ 
acquisition costs, but instead are billed under Part B to the 
transplant recipient's MBI. These costs include standard backbench 
preparation services; physician services for the surgeon who performs 
the transplant (and sometimes performs other surgical procedures at the 
time of the transplant) and provides 90 days of post-operative surgical 
care; \1493\ and/or immunosuppressant therapy management; and recipient 
laboratory services which occur after discharge from the hospital. See 
the Medicare Claims Processing Manual, IOM 100-04, chapter 12, sections 
30.6.3, 40.1, and 40.4 for more details on these services.\1494\
---------------------------------------------------------------------------

    \1493\ See Addendum B in 59 FR 63516, for CPT codes 50360 and 
50365 for kidney transplantation.
    \1494\ Available online at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c12.pdf.
---------------------------------------------------------------------------

g. Proposed Codification of Statutory Provisions Related to Pancreata 
Used for Pancreatic Islet Cell Transplants
    Our longstanding policies related to pancreata used for pancreatic 
islet cell transplants are discussed in section 3110 of the PRM. 
Section 733 of the Medicare Prescription Drug, Improvement and 
Modernization Act of 2003 \1495\ (MMA) requires Medicare to pay for 
items and services that are reasonable and necessary routine patient 
care costs related to acquisition and delivery of pancreatic islet 
cells for transplantation into Medicare beneficiaries included in a 
National Institute of Diabetes and Digestive and Kidney Diseases 
clinical trial of islet cell transplants. The pancreata procured for 
islet cell transplants require the same quality and care to procure as 
pancreata procured for solid organ transplants. Therefore, as described 
in section X.B.2.a.(2) of this proposed rule, we are proposing to 
define for organ acquisition payment purposes, pancreata, procured for 
the purpose of acquiring pancreatic islet cells for transplantation 
into individuals who are participating in an National Institute of 
Diabetes and Digestive and Kidney Diseases clinical trial, to be an 
organ. Accordingly, pancreata procured for islet cell transplants are 
treated as solid organs for procurement purposes, and pancreata 
procured for covered islet cell transplants must be assigned a full 
standard acquisition charge. We are proposing to codify this policy by 
adding Sec.  413.406 in part 413, new subpart L, in accordance with the 
statute. There are other clinical trials of islet cell transplants that 
are not funded by the National Institute of Diabetes and Digestive and 
Kidney Diseases, which section 733 of the MMA explicitly prohibits 
Medicare from covering under title XVIII of the Act.
---------------------------------------------------------------------------

    \1495\ Section 733 of the Medicare Prescription Drug, 
Improvement and Modernization Act of 2003 (Pub. L. 108-173); 42 
U.S.C. 1395l.

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[[Page 25664]]

h. Proposed Calculation of Medicare's Share of Organ Acquisition Costs, 
Counting of Organs
(1) General
    Medicare currently calculates its share of organ acquisition costs 
for THs/HOPOs by multiplying the total allowable organ acquisition 
costs by the ratio of Medicare usable organs (the numerator) to total 
usable organs (the denominator) reported on the Medicare hospital cost 
report.\1496\ To ensure that a TH/HOPO's organ acquisition costs are 
accurately allocated to the Medicare Program, THs/HOPOs must accurately 
count and report Medicare usable organs and total usable organs on 
their MCRs.
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    \1496\ CMS Pub. 15-2, chapter 40, section 4028.
---------------------------------------------------------------------------

    For IOPOs, Medicare currently calculates its share of kidney 
acquisition costs by multiplying the total allowable kidney acquisition 
costs by the ratio of Medicare usable kidneys (the numerator) to total 
usable kidneys (the denominator) reported on the Medicare IOPO cost 
report.\1497\ Similarly, IOPOs must accurately count and report on 
their MCRs the number of kidneys they procure and furnish to THs or 
other OPOs, to ensure that kidney acquisition costs are accurately 
allocated to the Medicare Program.
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    \1497\ CMS Pub. 15-2, chapter 33, section 3312.
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(2) Medicare Usable Organs, Total Usable Organs, Medicare Usable 
Kidneys, and Total Usable Kidneys
    Currently, Medicare reimburses THs/HOPOs for their reasonable costs 
incurred to acquire ``Medicare usable organs.'' For Medicare to 
calculate its share of organ acquisition costs, currently the THs/HOPOs 
must include the following as Medicare usable organs: \1498\ (1) Organs 
transplanted into Medicare beneficiaries; (2) organs transplanted into 
Medicare beneficiaries that were partially paid by a primary insurance 
payor in addition to Medicare; (3) organs sent to other THs or IOPOs; 
(4) kidneys transplanted into Medicare Advantage beneficiaries for 
dates of service on or after January 1, 2021; \1499\ (5) kidneys sent 
to United States military renal transplant centers (MRTCs) with a 
reciprocal sharing agreement with the HOPO in effect prior to March 3, 
1988, and approved by the contractor; and (6) pancreata procured for 
the purpose of acquiring pancreatic islet cells for transplantation 
into Medicare beneficiaries participating in a National Institute of 
Diabetes and Digestive and Kidney Diseases clinical trial pursuant to 
section 733 of the MMA, as discussed in section X.B.2.g of this 
proposed rule.\1500\ (For counting purposes, the TH/HOPO does not count 
pancreata procured for islet cell transplant as a solid organ, but 
counts the number of Medicare beneficiaries who received these islet 
cell injections as the proxy for Medicare usable organs. For example, 
if a TH/HOPO procured pancreata for islet cell transplant and injected 
these islet cells into three Medicare beneficiaries and four non-
Medicare patients during its cost reporting period, the TH/HOPO enters 
three in the Medicare usable organ count, and seven in the total usable 
organ count, on its Medicare hospital cost report.)
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    \1498\ Pursuant to PRM Sec.  3115.A. and CMS Pub. 15-2, chapter 
40, section 4028.3.
    \1499\ Section 17006 of the 21st Century Cures Act, (Pub. L. 
114-255). Section 17006(c) of the Cures Act amended section 
1852(a)(1)(B)(i) of the Act to exclude coverage for organ 
acquisitions for kidney transplants from the Medicare benefits an MA 
plan is required to cover for an MA enrollee, including as covered 
under section 1881(d) of the Act. Effective January 1, 2021, these 
costs will be covered under the original Medicare FFS program. The 
MA kidney transplants will be included in the numerator and 
denominator on the MCR to determine Medicare's share of kidney 
acquisition costs. (85 FR 33796, 33824, June 2, 2020).
    \1500\ Section 733 of the Medicare Prescription Drug, 
Improvement and Modernization Act of 2003 (Pub. L. 108-173)); 42 
U.S.C 1395l.
---------------------------------------------------------------------------

    Medicare does not share in the cost of acquiring organs not 
transplanted into Medicare beneficiaries (except those organs 
designated for transplant but determined to be unusable). Organs not 
transplanted into Medicare beneficiaries must be counted as total 
usable organs in the denominator of the fraction of Medicare usable 
organs to total usable organs. THs/HOPOs must include the following as 
total usable organs: (1) Medicare usable organs; (2) organs excised 
with the intention to be used for research; (3) organs excised and 
either transplanted or furnished to other THs or OPOs; (4) organs 
obtained from another OPO or transplant hospital and either 
transplanted or furnished to other THs or OPOs; (5) organs sent to 
veterans' hospitals or organs sent outside the United States pursuant 
to 42 CFR 413.203; (6) organs transplanted into non-Medicare 
beneficiaries, pursuant to Sec.  413.203; (7) organs for which the 
transplant was totally or partially paid by primary insurance other 
than Medicare; (8) organs for which the transplant was covered by a 
Medicare Advantage plan for dates of service prior to January 1, 2021; 
(9) kidneys sent to United States MRTCs with or without a contractor-
approved reciprocal sharing agreement with the HOPO in effect prior to 
March 3, 1988; and (10) pancreata procured for the purpose of acquiring 
pancreatic islet cells for transplantation into participants in a 
National Institute of Diabetes and Digestive and Kidney Diseases 
clinical trial pursuant to the MMA,\1501\ as discussed in section 
X.B.2.g of this proposed rule.
---------------------------------------------------------------------------

    \1501\ Id.
---------------------------------------------------------------------------

    Medicare also currently reimburses IOPOs for their reasonable costs 
incurred to procure ``Medicare kidneys.'' Organ acquisition costs are 
not paid directly by Medicare to an IOPO. The IOPO is reimbursed for 
its services by the TH, subject to later reconciliation by Medicare for 
kidneys. Medicare currently calculates its share of kidney acquisition 
costs by multiplying the total allowable kidney acquisition costs by 
the ratio of Medicare usable kidneys (the numerator) to total usable 
kidneys (the denominator) reported on the Medicare IOPO cost report. 
For Medicare to calculate its share of Medicare kidney acquisition 
costs, the IOPO must include the following as Medicare kidneys: (1) 
Kidneys sent to THs; (2) kidneys sent to certified OPOs; and (3) 
kidneys sent to United States MRTCs with a reciprocal sharing agreement 
with the IOPO in effect prior to March 3, 1988, and approved by the 
contractor. Medicare kidneys do not include kidneys sent to VA 
hospitals, military hospitals, or kidneys sent to foreign countries or 
transplanted into non-Medicare beneficiaries, pursuant to 42 CFR 
413.202.
    IOPOs must also count total usable kidneys in the denominator of 
the fraction of Medicare usable kidneys to total usable kidneys. IOPOs 
must include the following in total usable kidneys: (1) Medicare usable 
kidneys; (2) kidneys procured with the intention to be used for 
research; (3) kidneys procured and furnished to other THs or OPOs; (4) 
kidneys procured from another OPO or transplant hospital and either 
transplanted or furnished to other THs or OPOs; (5) kidneys sent to 
veterans' hospitals or organs sent outside the United States pursuant 
to 42 CFR 413.203; (6) kidneys for which the transplant was covered by 
a Medicare Advantage plan for dates of service prior to January 1, 
2021; and (7) kidneys sent to United States MRTCs with or without a 
contractor-approved reciprocal sharing agreement with the IOPO in 
effect prior to March 3, 1988. Currently THs/HOPOs that excise organs 
and send them to other THs or IOPOs, or kidneys sent to MRTCs pursuant 
to an approved reciprocal sharing agreement in effect prior to March 3, 
1988, are presumed to be transplanted into Medicare beneficiaries, even 
if they are not.

[[Page 25665]]

Similarly, some kidneys that an IOPO procures and sends to other IOPOs, 
THs, or MRTCs pursuant to an approved reciprocal sharing agreement in 
effect prior to March 3, 1988, are presumed to be transplanted into 
Medicare beneficiaries, even if they are not. These categories do not 
have a distinction to determine whether the organs are actually 
transplanted into Medicare beneficiaries. In this regard, Medicare 
organ acquisition payment policy includes the presumption that some 
organs are transplanted into Medicare beneficiaries, despite the 
category name ``Medicare usable organs'' or ``Medicare kidneys.'' As a 
result, through unintended consequences, Medicare currently shares in 
the organ acquisition costs for some organs that are not actually 
transplanted into Medicare beneficiaries.
    When Medicare added the ESRD benefit to Medicare coverage in 1972, 
Medicare presumed that most kidney transplant recipients would be 
Medicare beneficiaries receiving the ESRD benefit, and thus Medicare 
would pay a larger share of kidney acquisition costs.\1502\ As Medicare 
added benefits for transplantation of non-renal organs and included the 
costs to procure non-renal organs, Medicare cost reporting instructions 
incorporated the presumption that the ultimate transplant recipient was 
unknown, but likely a Medicare beneficiary. Thus, when a TH sends an 
organ to another TH or to an OPO, or when an OPO sends an organ to 
another OPO or TH, Medicare assumed that some of the unknown transplant 
recipients are Medicare beneficiaries, and permits those organs to be 
counted as Medicare usable organs in the numerator of the fraction for 
Medicare usable organs to total usable organs, to be assured that 
Medicare is paying its share of organ acquisition costs.
---------------------------------------------------------------------------

    \1502\ Intermediary Letter 73-25 (July 1973) and 54 FR 5619, 
February 6, 1989.
---------------------------------------------------------------------------

    However, Medicare declared its intention and a methodology to 
calculate its share of acquisition costs, for kidneys transplanted into 
Medicare beneficiaries only, in a 1978 Federal Register final rule with 
comment.\1503\ Specifically, for each kidney transplant performed on a 
Medicare beneficiary, the transplanting hospital shall receive a 
prescribed amount of reimbursement from Medicare for the pre-
transplantation services of an OPA [organ procurement organization] or 
laboratory having such an agreement. The 1978 final rule set forth that 
an OPO's cost report must provide a complete accounting of the cost 
incurred by the agency or laboratory in providing covered services, the 
total number of Medicare beneficiaries for whom services were furnished 
by the agency or laboratory, and any other necessary data to enable the 
intermediary to determine the reasonable cost of covered services to 
Medicare beneficiaries. [Emphasis added.] Additionally, if the 
intermediary determines that the interim rate payments exceeded the 
reasonable cost of the services furnished, then the OPA or 
histocompatibility laboratory must pay the excess amount per Medicare 
patient to the intermediary. [Emphasis added.] These multiple 
declarations in the 1978 final rule establish Medicare's intention to 
pay for kidney acquisition costs incurred for kidneys transplanted into 
Medicare beneficiaries and were originally codified at 42 CFR 405.436 
and later moved to 42 CFR 413.178 (currently reserved).
---------------------------------------------------------------------------

    \1503\ 43 FR 58370, December 14, 1978.
---------------------------------------------------------------------------

    The longstanding policy that Medicare must only share in organ and 
kidney acquisition costs for Medicare beneficiaries is also set forth 
in 42 CFR 413.202 and 413.203. Section 413.202 requires OPOs to 
separate from Medicare allowable costs, acquisition costs for procuring 
kidneys sent to foreign transplant centers and kidneys transplanted in 
non-Medicare patients. Similarly, Sec.  413.203 requires THs to 
separate from Medicare allowable costs, acquisition costs for procuring 
organs sent to foreign transplant centers and organs transplanted in 
non-Medicare patients. In a 1988 proposed rule, CMS expressed belief 
that allowing all kidneys to be counted as Medicare kidneys was not 
aligned with anti-cross subsidization principles set forth in section 
1861(v)(1)(A) of the Act. CMS stated that the Medicare program has 
always paid the total costs of OPAs [OPOs] because we assumed that all 
kidneys procured were for Medicare beneficiaries. However, we now 
realize that this assumption is incorrect and that technology has 
allowed a significant number of kidneys to be shipped overseas. Since 
the Medicare program has been paying the cost of procuring kidneys 
shipped overseas or transplanted into non-Medicare beneficiaries, we 
believe that some action needs to be taken. We believe it is necessary 
to amend the regulations in order to effectuate the statutory 
principles embodied in section 1861(v)(1)(A) of the Act. Section 
1861(v)(1)(A) of the Act requires that the cost of services be borne by 
the appropriate payor. Accordingly, the cost associated with the 
kidneys not used by Medicare beneficiaries must be borne by the 
responsible individual or third party payor. Medicare is precluded from 
paying any costs associated with kidneys not used by Medicare 
beneficiaries. 53 FR 6672 at 6673 (March 2, 1988).
    Medicare's decades-old presumption that most kidney transplant 
recipients are Medicare beneficiaries was also applied to non-renal 
organs because of the lack of organ tracking capabilities over the 
years and has led Medicare to reimburse THs and OPOs for organ 
acquisition costs for organs that were not actually transplanted into 
Medicare beneficiaries. Similar to the beliefs expressed in the 1988 
proposed rule, we believe that organ tracking capabilities allow 
transplant hospitals and OPOs to discern organ recipients' health 
insurance payor information so that organ acquisition costs can be more 
appropriately assigned to the Medicare program for organs transplanted 
into Medicare beneficiaries. The Scientific Registry of Transplant 
Recipients (SRTR) \1504\ collects and maintains data that identifies, 
among other things, transplant recipients and their health insurance 
payors. Data obtained from SRTR show the percentage of transplants 
where Medicare was the recipients' payor to all transplant recipients' 
payors, by organ type. We compared the SRTR data for years 2017 and 
2018, to the Medicare share ratio for Medicare usable organs (including 
kidneys) to total usable organs, for 2017 and 2018. Table X.B.-01 
reflects these data. In the majority of organ types, the SRTR 
percentages of transplant recipients who were actual Medicare 
beneficiaries were lower than the Medicare share percentages for those 
same years. Although there is a difference in the calendar year data 
from SRTR and the cost reporting fiscal year data from the MCR, these 
data show that the majority of SRTR's percentage of Medicare transplant 
recipients was less than the percentages of Medicare's share compared 
to 2017 and 2018 submitted MCR data from the Worksheet D-4.
---------------------------------------------------------------------------

    \1504\ Section 373 of the Public Health Service (PHS) Act 
requires the operation of Scientific Registry of Transplant 
Recipients (SRTR) to support ongoing evaluation of the scientific 
and clinical status of solid organ transplantation. The U.S. 
Congress passed the National Organ Transplant Act (NOTA; Pub. L. 98-
507) in 1984.
    \1505\ Scientific Registry of Transplant Recipients. Request for 
Information. Requested on 01/29/2021.

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[[Page 25666]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.315

    We are aware that the capability exists to track the location and 
disposition of organs, from the time organs are excised from donors 
until they are transplanted into recipients. Organ tracking capability 
allows THs and OPOs the ability to know the identity of all organ 
transplant recipients and the donor from whom the recipient's 
transplanted organ was excised. Knowing the identity of all organ 
transplant recipients, and the donor from whom the recipient's 
transplanted organ was excised, allows THs and OPOs the ability to also 
know whether a transplant recipient is a Medicare beneficiary. OPTN 
policy provides that OPOs use organ tracking capability,\1506\ and some 
THs also optionally use organ tracking capability. Per OPTN policies, 
THs and OPOs report information to the OPTN on the identity of 
transplant recipients and donors.\1507\ Additionally, the OPTN data 
collection forms show what data elements the OPTN currently 
collects.\1508\ The OMB form NO. 0915-0157 collects the recipient's and 
payor's information for the transplant. The identity of the recipient 
is required to be reported. THs, histocompatibility laboratories, and 
organ procurement organizations enter data into the OPTN database in 
UNet, a centralized computer network that links all 57 OPOs, 254 THs 
and 150 histocompatibility labs to list patients for transplant, match 
patients with available donor organs and submit required OPTN 
data.\1509\ By way of knowing the identity of the recipient, the 
providers can further discern whether a recipient is a Medicare 
beneficiary. Therefore, it is possible for THs and OPOs to report, on 
their respective MCRs, the number of organs and kidneys transplanted 
into Medicare beneficiaries, eliminating the reason for Medicare organ 
acquisition payment policy to presume that some organs and kidneys are 
transplanted into Medicare beneficiaries, when they are not.
---------------------------------------------------------------------------

    \1506\ OPTN Policy 16, https://optn.transplant.hrsa.gov/media/1200/optn_policies.pdf.
    \1507\ OPTN Policy 18, https://optn.transplant.hrsa.gov/media/1200/optn_policies.pdf.
    \1508\ https://unos.org/data/data-collection/.
    \1509\ https://unos.org/technology/unet/.
---------------------------------------------------------------------------

    We believe it is necessary to update Medicare organ acquisition 
payment policy to recognize organ tracking capabilities and the ability 
for OPOs and THs/HOPOs to discern the identity of the recipient into 
whom the excised organ is transplanted, and whether that recipient is a 
Medicare beneficiary. Doing so will result in Medicare more accurately 
paying its share of organ acquisition costs. We believe it is necessary 
to require that OPOs and THs report on their cost reports only organs 
and kidneys transplanted into Medicare beneficiaries as Medicare usable 
organs and Medicare kidneys, respectively. Doing so would help 
safeguard the Medicare Trust Fund and ensure that Medicare 
appropriately pays only its share of organ acquisition costs, and that 
acquisition costs for organs not transplanted into Medicare 
beneficiaries are not borne by Medicare. The Medicare reasonable cost 
principles, upon which Medicare organ acquisition payment policy is 
based, and the prohibition of cross-subsidization articulated in 
section 1861(v) of the Act require the cost of services be borne by the 
appropriate payor.
    While all OPOs, and some THs, use an organ tracking capability, we 
believe that THs that do not use an organ tracking capability can also 
ascertain the exact recipient, and thus recipient's payor, when an 
organ is excised in their hospital and sent to another TH or OPO. We 
understand that some THs that do not use an organ tracking capability 
still track organs they send to other THs or OPOs by using manual, 
written methodologies. In this regard, THs can determine the organ 
recipient from their records and by verifying the insurance payor of 
the recipient with the transplant recipient's hospital. Additionally, 
THs can contact the OPO to which they gave the organ, and because the 
OPTN directs OPOs to use an organ tracking system, the OPO can relay 
the recipient's information and recipient's payor to the TH. Likewise, 
Medicare contractors, who review MCRs submitted by THs and OPOs, can 
confirm Medicare usable organs and Medicare usable kidneys reported by 
THs and OPOs with supporting documentation from provider's records.
    Pursuant to Sec.  413.202, Medicare kidneys include, for cost 
reporting statistical purposes and counting, kidneys procured by an OPO 
and sent to a MRTC for transplant, pursuant to certain long-standing 
arrangements that existed before March 3, 1988, approved by the 
contractor. However, due to organ tracking capability, and to achieve 
equitable treatment among all OPOs (for OPOs that do not have a long 
standing arrangements with military THs), and to also achieve 
appropriate Medicare expenditures for kidney acquisition

[[Page 25667]]

costs, we no longer believe it is appropriate to allow such kidneys to 
be designated as Medicare kidneys under such arrangements. Because 
organ tracking capability permits OPOs the ability to know a donor's 
transplant recipient, and thus their payor's identity, it is no longer 
necessary for Medicare to continue to apply its longstanding policy to 
deem and count all kidneys an OPO excises at, or provides to, a MRTC as 
Medicare kidneys for purposes of apportioning Medicare's share of the 
kidney acquisition costs. Thus, we are proposing to change our 
regulation with respect to MRTCs.
    For the reasons discussed in this section, in this proposed rule we 
are proposing to add Sec.  413.408(a) to new subpart L to specify that 
THs/HOPOs must accurately count and report Medicare usable organs and 
total usable organs on their Medicare hospital cost reports to ensure 
that costs to acquire Medicare usable organs are accurately allocated 
to Medicare. We are also proposing to add Sec.  413.408(b) to new 
subpart L to specify that for cost reporting periods beginning on or 
after October 1, 2021, for THs/HOPOs, Medicare usable organs include 
only organs transplanted into Medicare beneficiaries (including kidneys 
for Medicare Advantage beneficiaries with dates of service after 
January 1, 2021), organs for which Medicare has a secondary payer 
liability \1510\ for the organ transplant, and pancreata procured for 
the purpose of acquiring pancreatic islet cells acquired for 
transplantation for Medicare beneficiaries participating in a National 
Institute of Diabetes and Digestive and Kidney Diseases clinical trial.
---------------------------------------------------------------------------

    \1510\ Medicare secondary payer is governed by section 
1862(b)(2) of the Act and 42 CFR 411.20 through 411.39.
---------------------------------------------------------------------------

    We are also proposing to add Sec.  413.408(c) to new Subpart L to 
specify that for cost reporting periods beginning on or after October 
1, 2021, for THs/HOPOs, total usable organs include: (1) Medicare 
usable organs; (2) organs excised with the intention to be used for 
research; (3) organs excised and either transplanted or furnished to 
other transplant hospitals or OPOs; (4) organs obtained from another 
OPO or transplant hospital and either transplanted or furnished to 
other transplant hospitals or OPOs; (5) organs sent to veterans' 
hospitals or organs sent outside the United States; (6) organs 
transplanted into non-Medicare beneficiaries; (7) organs for which the 
transplant was totally or partially paid by primary insurance other 
than Medicare; (8) organs for which the transplant was covered by a 
Medicare Advantage plan for dates of service prior to January 1, 2021; 
(9) kidneys sent to United States MRTCs with or without a contractor-
approved reciprocal sharing agreement with the HOPO in effect prior to 
March 3, 1988; and (10) pancreata procured for the purpose of acquiring 
pancreatic islet cells for transplantation into participants in a 
National Institute of Diabetes and Digestive and Kidney Diseases 
clinical trial.
    We are also proposing to remove Sec.  413.203, and add Sec.  
413.408(d) to new subpart L, so that all organ acquisition policies are 
housed together, to specify that a TH's total costs for all organs are 
reduced by the costs associated with procuring organs that are sent to 
foreign transplant centers or transplanted in patients other than 
Medicare beneficiaries; and to specify that THs must separate costs for 
procuring organs that are sent to foreign transplant centers and organs 
transplanted in patients other than Medicare beneficiaries from 
Medicare allowable costs prior to final cost settlement by the Medicare 
contractors. The separation of cost is achieved using the Medicare 
ratio set forth in proposed Sec.  413.408(e).
    We are also proposing to add Sec.  413.408(e) to new subpart L to 
specify that for cost reporting periods beginning on or after October 
1, 2021, Medicare's share of organ acquisition costs for a TH/HOPO is 
calculated by multiplying the total allowable organ acquisition costs 
by the ratio of Medicare usable organs transplanted into Medicare 
beneficiaries, as specified in proposed Sec.  413.408(b), to total 
usable organs, as specified in proposed Sec.  413.408(c).
    For rules pertaining to counting kidneys and calculating Medicare's 
share of kidney acquisition costs for IOPOs, in this proposed rule, we 
are proposing to add Sec.  413.410(a) to new subpart L to specify that 
IOPOs must accurately count and report Medicare usable kidneys and 
total usable kidneys on their Medicare IOPO cost reports to ensure that 
costs to acquire Medicare usable kidneys are accurately allocated to 
Medicare. We are also proposing to add Sec.  413.410(b) to new subpart 
L to specify that, for cost reporting periods beginning on or after 
October 1, 2021, for IOPOs, Medicare kidneys include only kidneys 
transplanted into Medicare beneficiaries.
    We are also proposing to add Sec.  413.410(c) to new subpart L to 
specify that for cost reporting periods beginning on or after October 
1, 2021, for IOPOs, total usable kidneys include: (1) Medicare usable 
kidneys; (2) kidneys procured with the intention to be used for 
research; (3) kidneys procured and furnished to other transplant 
hospitals or OPOs; (4) kidneys procured from another OPO or transplant 
hospital and either transplanted or furnished to other transplant 
hospitals or OPOs; (5) kidneys sent to veterans' hospitals or organs 
sent outside the United States; (6) kidneys for which the transplant 
was covered by a Medicare Advantage plan for dates of service prior to 
January 1, 2021; and (7) kidneys sent to United States MRTCs with or 
without a contractor-approved reciprocal sharing agreement with the 
IOPO in effect prior to March 3, 1988.
    We are proposing to remove Sec.  413.202 and add Sec.  413.410(d) 
to new subpart L, to specify that an IOPO's total costs for all kidneys 
is reduced by the costs associated with procuring kidneys sent to 
foreign transplant centers or transplanted in patients other than 
Medicare beneficiaries; and to specify that IOPOs must separate costs 
for procuring kidneys sent to foreign transplant centers and kidneys 
transplanted in patients other than Medicare beneficiaries from 
Medicare allowable costs prior to final settlement by the Medicare 
contractors. The separation of cost is achieved using the Medicare 
ratio set forth in proposed Sec.  413.410(e).
    We are also proposing to add Sec.  413.410(e) to new subpart L to 
specify that for cost reporting periods beginning on or after October 
1, 2021, Medicare's share of kidney acquisition costs is calculated by 
multiplying the total allowable kidney acquisition costs by the ratio 
of Medicare usable kidneys, as specified in proposed Sec.  413.410(b), 
to total kidneys, as specified in proposed Sec.  413.410(c).
i. Proposals Related to Intent To Transplant, and Counting En Bloc, 
Research, and Discarded Organs
    In this section, we are proposing to add Sec.  413.412, to new 
subpart L, to specify our longstanding policies set forth in CMS Ruling 
1543-R, issued December 21, 2006, and PRM-1, sections 3111 and 3115, 
pertaining to intent to transplant, counting en bloc organs, research 
organs, and discarded organs for THs and OPOs. These policies provide 
for the proper calculation of Medicare's share of organ acquisition 
costs that are used for the appropriate allocation of organ acquisition 
costs on the MCR. The calculation of Medicare's share of organ 
acquisition costs is discussed in section X.B.2.h.(1). of this proposed 
rule. The methodology of counting organs to calculate Medicare's share 
of organ acquisition costs is used for the

[[Page 25668]]

allocation of organ acquisition costs on the MCR and differs from 
Medicare's organ counting policy to assess OPOs' performance, which is 
set forth under the OPO CfCs, 42 CFR part 486, subpart G. To calculate 
Medicare's share of organ acquisition costs, when organ procurement is 
attempted, but no organ is actually retrieved (or the organ is instead 
discarded or donated for research), proper counting of the organ must 
occur to ensure that overhead costs are appropriately allocated to 
Medicare and non-Medicare payors. However, cost allocation is not a 
factor when counting organs for evaluating an OPO's performance under 
Medicare's CfC.
(1) Principle of Intent To Transplant
    Medicare presumes that THs and OPOs intend to procure all donor 
organs that are medically suitable for transplant.\1511\ We are 
proposing to add Sec.  413.412(a)(1) to new subpart L, to specify, for 
organ acquisition payment purposes, an organ is intended for transplant 
when the OPO or TH designates it for transplant prior to the time the 
donor enters the hospital's operating room for surgical excision/
recovery of the organ(s). Regardless of whether the OPO or TH procures 
organs for transplant, it incurred cost in attempting to procure 
organs.\1512\ We are proposing to add Sec.  413.412(a)(2) to new 
subpart L, to specify, OPOs and THs must identify the costs associated 
with the recovered and unrecovered organs and apportion those costs to 
the appropriate cost centers by organ type.
---------------------------------------------------------------------------

    \1511\ CMS Ruling 1543-R (December 2006), and the PRM 15-1, 
chapter 31, sections 3111 & 3115.
    \1512\ The PRM 15-1, chapter 31, and PRM 15-2, chapter 33, 
section 3306 and chapter 40, section 4028 set forth our current, 
longstanding policies regarding the counting of organs for Medicare 
organ acquisition payment purposes.
---------------------------------------------------------------------------

(2) Counting and Cost Allocation of En Bloc Organs
    Our policy for counting en bloc organs for cost allocation purposes 
is set forth in PRM-1 section 3115. We are proposing to add Sec.  
413.412(b) to new subpart L, to specify our policy for counting en bloc 
organs for Medicare cost allocation purposes and to specify that en 
bloc organs can be en bloc lungs or en bloc kidneys.
    We are proposing to add Sec.  413.412(b)(1) to new subpart L to 
specify that OPOs and THs count en bloc lungs or en bloc kidneys 
procured and transplanted en bloc (two organs transplanted as one unit) 
as one total usable organ. En bloc organs transplanted into a Medicare 
beneficiary count as one Medicare usable organ or one Medicare usable 
kidney, in accordance with the proposed Medicare organ counting policy 
in section X.B.2.h.(2). of this proposed rule.
    We are also proposing to add Sec.  413.412(b)(2) to new subpart L 
to specify that OPOs and THs count en bloc lungs and en bloc kidneys 
procured en bloc but separated and transplanted into two different 
recipients as two total usable organs. For each organ transplanted into 
a Medicare beneficiary, count each as one Medicare usable organ or one 
Medicare usable kidney, in accordance with the proposed Medicare organ 
counting policy in section X.B.2.h.(2). of this proposed rule.
(3) Counting and Cost Allocation of Research Organs
    Our longstanding policy regarding counting of organs excised and 
used for research for Medicare cost allocation purposes is set forth in 
PRM-1 sections 3111 and 3115. We are clarifying that for organ 
acquisition cost allocation purposes, a ``research organ'' is an organ 
procured and used for research regardless of whether it is transplanted 
as part of clinical care (with the exception of pancreata previously 
discussed in section X.B.2.h.(2)) of the preamble of this proposed 
rule. We are proposing to add Sec.  413.412(c) to new subpart L to 
specify that organs used for research are not counted as Medicare 
usable organs in Medicare's share of organ acquisition costs (except 
pancreata previously discussed in section X.B.2.h.(2)). of the preamble 
of this proposed rule. However, we are also clarifying that Medicare 
shares in the costs of organs that are designated for transplant prior 
to the time the donor entered the hospital's operating room, but 
determined to be unusable and donated to research. The costs incurred 
are allocated amongst all remaining usable organs.
    We are proposing to add Sec.  413.412(c)(1)(i) to new subpart L to 
specify that OPOs and THs do not count organs designated for research 
activities prior to the time the donor entered the hospital's operating 
room for surgical removal of the organs as Medicare usable organs. We 
are also proposing to add Sec.  413.412(c)(1)(ii) to specify that OPOs 
and THs count organs designated for research activities prior to the 
time the donor entered the hospital's operating room for surgical 
removal of the organs, as total usable organs.
    We are proposing to add Sec.  413.412(c)(2) to new subpart L to 
specify that OPOs and THs do not count organs designated for transplant 
prior to the time the donor entered the hospital's operating room for 
surgical removal of the organs but subsequently determined to be 
unusable and donated to research, as Medicare usable organs or total 
usable organs.
(4) Counting and Cost Allocation of Discarded/Unusable Organs
    Our longstanding policy regarding counting of discarded/unusable 
organs for cost allocation purposes is set forth in CMS Ruling 1543-R 
issued December 21, 2006 and PRM-1 sections 3111 and 3116. We are 
proposing to add Sec.  413.412(d) to new subpart L, to specify that an 
organ is not counted as a Medicare usable organ or a total usable organ 
if the excising surgeon determines, upon initial inspection or after 
removal of the organ, that the organ is not viable and not medically 
suitable for transplant and the organ is determined to be unusable and 
discarded. This includes organs that are determined to be unusable and 
subsequently donated to research as previously described in section 
X.B.2.i.(3). of this proposed rule.
j. Proposals Related to Medicare as Secondary Payer--Organ Acquisition 
Costs and Medicare Organ Count
    If a Medicare beneficiary has a primary health insurer other than 
Medicare and that primary health insurer has primary liability for the 
transplant and organ acquisition costs, the Medicare Program may share 
a liability for organ acquisition costs as a secondary payer in certain 
instances. Medicare prohibits secondary payment if the provider is 
either obligated to accept, or voluntarily accepts, as payment in full, 
a primary payment that is less than its charges. See 42 CFR 411.32(b). 
When a provider or supplier is obligated to accept as full payment an 
amount less than its charges, Medicare considers that lower amount to 
be the provider's charges. (For more information see the October 11, 
1989 final rule (54 FR 41728)). Medicare organ acquisition cost 
reimbursement policy when beneficiaries have a primary insurer other 
than Medicare, is set forth in PRM-1 section 3104, Accounting for the 
Cost of Medicare Secondary Payer. In this proposed rule, we are 
proposing to codify into the regulations the organ acquisition cost 
reimbursement policy with regard to Medicare secondary payer policy, as 
set forth in PRM-1 section 3104.
    To determine whether the provider is contractually obligated to 
accept the primary insurer's payment as payment in full, and thus 
whether Medicare has zero liability as a secondary payer, it is 
necessary to review the provider or

[[Page 25669]]

supplier's agreement with the primary insurer. If the primary insurer's 
agreement requires the TH to accept the primary insurer's payment as 
payment in full for the transplant and the associated organ acquisition 
costs, Medicare has zero liability as a secondary payer with no payment 
obligation for the transplantation costs or the organ acquisition 
costs, and the organ at issue is not counted as a Medicare usable 
organ.
    When the primary insurer's agreement does not require the provider 
to accept the payment from the primary insurer as payment in full and 
the payment the provider receives from the primary insurer for the 
transplant and the organ acquisition costs is insufficient to cover the 
entire cost, Medicare may have a secondary payer liability for the 
organ acquisition costs. To determine whether Medicare has a secondary 
payer liability, it is necessary for the provider to submit a bill to 
its Medicare contractor and to compare the total cost of the 
transplant, including the transplant DRG amount and the organ 
acquisition costs, to the payment received from the primary payer. The 
provider's Medicare remittance advice may or may not show that Medicare 
has a liability because the remittance advice only reflects the 
transplant portion of the payment. Thus, the provider will need to 
compare the total Medicare cost (the transplant DRG and the organ 
acquisition costs) to the payment from the primary payer to determine 
whether Medicare has a liability for the organ acquisition costs. If 
the payment from the primary payer is greater than the cost of the 
transplant DRG and the organ acquisition costs, there is no Medicare 
liability and the organ must not be counted as a Medicare usable organ. 
If the payment from the primary payer is less than the transplant DRG 
and the organ acquisition costs, there is a Medicare secondary payer 
liability and the organ is counted as a Medicare usable organ. In this 
circumstance, the payment from the primary payer is pro-rated between 
the transplant DRG payment and the organ acquisition payment. If the 
organ is counted as Medicare usable, the organ acquisition portion of 
the primary payment must be included on the appropriate line as a 
revenue offset on the TH's MCR (currently Form CMS-2552). This is 
consistent with the cost reporting instructions in CMS Pub. 15-2, (PRM-
2) chapter 40, section 4028.
    Consider the following example as an illustration of Medicare's 
payment of organ acquisition costs as a secondary payer. A TH 
transplants a patient that has private health insurance and Medicare. 
The private health insurance is primary and Medicare is secondary. The 
private health insurance pays the TH $70,000 for the transplant and the 
organ acquisition costs; there is no requirement in the primary 
insurer's agreement with the provider for the TH to accept this payment 
as payment in full. If Medicare was the primary payer, the combined 
payment to the TH would have been $100,000 ($60,000 for the transplant 
and $40,000 for the organ acquisition costs). The TH compares the 
primary payer payment to the total amount Medicare would have paid if 
it had been primary (the transplant DRG and organ acquisition costs). 
The TH prorates the primary payer's payment of $70,000 between a 
portion of the transplant DRG and a portion of the organ acquisition 
costs. The TH determines the primary payer amount for the transplant 
DRG payment is $42,000 ($70,000 payment from the primary payer x 
[$60,000 for the transplant portion from Medicare/$100,000 combined 
Medicare payment]) and for organ acquisition costs is $28,000 ($70,000 
payment from the primary payer x [$40,000 for the organ acquisition 
portion from Medicare/$100,000 combined Medicare payment]). The TH 
counts the organ as a Medicare usable organ on its MCR and offsets the 
primary payment amount ($28,000) as revenue received, thereby reducing 
Medicare's liability. In this proposed rule, we are proposing to add 
Sec.  413.414(a) to new subpart L to set forth the general principle 
that if a Medicare beneficiary has a primary health insurer other than 
Medicare and that primary health insurer has primary liability for the 
transplant and organ acquisition costs, the Medicare Program may share 
a liability for organ acquisition costs as a secondary payer in certain 
instances. To determine whether Medicare has liability as a secondary 
payer for organ acquisition costs, it is necessary to review the TH's 
agreement with the primary insurer.
    We are also proposing to add Sec.  413.414(b) to new subpart L to 
set forth the circumstances when Medicare has no secondary payer 
liability for organ acquisition costs. If the primary insurer's 
agreement requires the TH to accept the primary insurer's payment as 
payment in full for the transplant and the associated organ acquisition 
costs, Medicare has zero liability as a secondary payer with no payment 
obligation for the transplantation costs or the organ acquisition 
costs, and the organ at issue is not a Medicare usable organ. We are 
also proposing to add Sec.  413.414(c) to new subpart L to set forth 
the policy for when Medicare may have a secondary payer liability for 
organ acquisition costs, which is based upon the provider's agreement 
with the primary insurer that does not require the provider to accept 
the payment from the primary insurer as payment in full, and the 
payment from the primary payer for the transplant and the organ 
acquisition costs is less than the provider's costs for the transplant 
and the organ acquisition costs. When the primary insurer's agreement 
does not require the TH to accept the payment from the primary insurer 
as payment in full and the payment the TH receives from the primary 
insurer for the transplant and organ acquisition costs is insufficient 
to cover the entire cost, Medicare may have a secondary payer liability 
for the organ acquisition costs. To determine whether Medicare has a 
secondary payer liability for the organ acquisition costs, it is 
necessary for the TH to submit a bill to its Medicare contractor and to 
compare the total cost of the transplant, including the transplant DRG 
amount and the organ acquisition costs, to the payment received from 
the primary payer. If the payment from the primary payer is greater 
than the cost of the transplant DRG and the organ acquisition costs, 
there is no Medicare liability and the organ cannot be counted as a 
Medicare usable organ. If the payment from the primary payer is less 
than the transplant DRG and the organ acquisition costs, there is a 
Medicare secondary payer liability and the organ is counted as a 
Medicare usable organ. In this circumstance, the payment from the 
primary payer is pro-rated between the transplant DRG payment and the 
organ acquisition payment and the portion of the payment applicable to 
organ acquisition will be used on the cost report to reduce the 
Medicare organ acquisition costs.
k. Proposed Organ Acquisition Charges for Kidney Paired Exchanges
    In a directed living kidney donation, the donor names a specific 
recipient who will receive the donor's kidney.\1513\ Because the donor 
and recipient are known prior to the organ excision and 
transplantation, the organ acquisition costs can be appropriately and 
accurately matched to the recipient's account. In a non-directed 
donation, the donor does not name a specific recipient for the kidney 
and instead, the donor is matched with a recipient in need.\1514\

[[Page 25670]]

Kidney paired exchanges are similar to directed living donations; 
however when the living donor and recipient do not match, they can 
consent to participate in a kidney paired exchange program. Kidney 
paired exchanges can occur when two or more living donor/recipient 
pairs match each other and the donated kidneys from two or more donors 
are exchanged so each recipient receives a compatible kidney for 
transplantation.
---------------------------------------------------------------------------

    \1513\ https://www.kidney.org/transplantation/livingdonors/general-information-living-donation.
    \1514\ Id.
---------------------------------------------------------------------------

    In a kidney paired exchange, the living donor and matched recipient 
may have their procedures performed at different THs. When a recipient 
and donor elect to participate in a kidney paired exchange, the costs 
of the initial living donor evaluations are incurred by the originally 
intended recipient's TH, regardless of whether the living donor 
actually donates to their originally intended recipient, a kidney 
paired exchange recipient, or does not donate at all. The Medicare 
organ acquisition payment policy for kidney paired donations is 
currently set forth at PRM section 3106. In this proposed rule, we are 
proposing to codify Medicare's organ acquisition payment policy with 
respect to KPD transactions to ensure that the kidney acquisition costs 
in a kidney paired exchange are documented so that the kidney 
acquisition costs are appropriately and accurately assigned to the 
transplant recipient's account, and appropriate organ acquisition 
payment outcomes are achieved, consistent with a directed donation.
    The costs of all hospital and physician services for pre-transplant 
living donor and recipient evaluations become acquisition costs and are 
included in the MCR of the recipient's TH, regardless of whether the 
recipient is a Medicare beneficiary. Additionally, all total usable 
kidneys and all Medicare usable kidneys are recorded by the transplant 
hospital on its MCR so that Medicare's share of kidney acquisition 
costs can be computed; this is true regardless of whether the 
transplant results from a KPD or from a directed donation. In a kidney 
paired exchange, once the donor and recipient are matched, any 
additional tests requested by the recipient's TH, and performed by the 
donor's TH, are billed to the recipient's TH as charges reduced to cost 
(using the donor's TH's cost to charge ratio) and included as 
acquisition costs on the recipient TH's MCR, regardless of whether an 
actual donation occurs, and regardless of whether the recipient is a 
Medicare beneficiary. When a donor's TH procures and sends a kidney to 
a recipient's TH, the donor's TH bills the recipient's TH the donor 
TH's kidney SAC, or alternatively, its standard departmental charges 
reduced to cost, for the reasonable costs associated with procuring, 
packaging and transporting the kidney. The donor's TH records these 
costs on its MCR as kidney acquisition costs and offsets any payments 
received from the recipient's TH against its kidney acquisition costs. 
The recipient's TH records as part of its kidney acquisition costs, the 
amounts billed by the donor's TH for the reasonable costs associated 
with procuring, packaging, and transporting the organ, as well as any 
additional testing performed and billed by the donor's TH.
    In the scenario where a donor's TH does not procure a kidney, and 
instead the donor travels to the recipient's TH and the recipient's TH 
procures the organ from the donor, the reasonable costs associated with 
the organ procurement are included on the MCR of the recipient's TH. As 
discussed in section X.B.2.b.(3). of this proposed rule, transportation 
and travel expenses of the living donor are not allowable Medicare 
costs. Under 42 U.S.C. 273(b)(3), the cost of transportation of donated 
organs to the TH are organ acquisition costs. Programs outside of 
Medicare, such as that of the National Living Donor Assistance Center, 
may pay for transportation costs for living donors.
    Example. The following is an example of the accounting of organ 
acquisition costs in a kidney paired exchange for Medicare cost 
reporting purposes.
    (Step 1), the Participants. There are 4 THs: TH A, TH B, TH C, and 
TH D. Each TH has a potential transplant recipient in need of a kidney 
and each recipient has a willing, but poorly matched, donor; thus, all 
donors and recipients enter into a kidney paired exchange. Each 
recipient and donor pair has been evaluated at their respective TH.
     TH A. Recipient A is a patient of TH A. TH A evaluates 
three potential living donors for Recipient A before a donor, Donor A, 
is identified. The costs of these evaluations are reported as kidney 
acquisition costs on TH A's cost report. Recipient A and Donor A do not 
match each other but both agree to participate in a KPD exchange.
     TH B. Recipient B is a patient of TH B. TH B evaluates two 
potential living donors for Recipient B before a donor, Donor B, is 
identified. The costs of these evaluations are reported as kidney 
acquisition costs on TH B's cost report. Recipient B and Donor B do not 
match each other but both agree to participate in a KPD exchange.
     TH C. Recipient C is a patient of TH C. TH C evaluates 
three potential living donors for Recipient C before a donor, Donor C, 
is identified. The costs of these evaluations are reported as kidney 
acquisition costs on TH C's cost report. Recipient C and Donor C do not 
match each other but both agree to participate in a KPD exchange.
     TH D. Recipient D is a patient of TH D. TH D evaluates 
three potential living donors for Recipient D before a donor, Donor D, 
is identified. The costs of these evaluations are reported as kidney 
acquisition costs on TH D's cost report. Recipient D and Donor D do not 
match each other but both agree to participate in a KPD exchange.
    (Step 2), the KPD Match. Through the KPD exchange it is determined 
that Recipient A matches Donor C; Recipient B matches Donor D; 
Recipient C matches Donor A; and Recipient D matches Donor B.
    (Step 3), After the KPD Match.
     Recipient C's TH requests Donor A's TH perform an 
additional test that was not included in Donor A's initial evaluation. 
Donor A's TH performs the additional test and bills Recipient's C's TH, 
charges reduced to cost, for the additional tests of Donor A. The 
amounts billed by TH A to TH C are included in TH C's MCR as organ 
acquisition costs for Recipient C.
     Donor B elects to travel to TH D for the procurement and 
any additional testing. (Note: The cost of travel for a living donor is 
not an allowable organ acquisition cost.)
     Donor A, Donor C, and Donor D remain at their original 
intended recipients' THs (TH A, TH C and TH D, respectively) where they 
were evaluated and where their organ procurement will occur.
    (Step 4), Procuring, Packaging and Transporting the Kidneys.
     TH A procures Donor A's kidney and packages and transports 
it to TH C for Recipient C. TH A bills TH C, charges reduced to cost, 
for the reasonable costs associated with procuring, packaging and 
transporting the kidney as well as any additional testing requested by 
TH C that was not included in the initial evaluation of Donor A. Donor 
A's TH records these costs on its MCR as kidney acquisition costs and 
offsets any payments received from TH C against its kidney acquisitions 
costs.
     TH B does not procure a kidney. Donor B elects to travel 
to TH D for the procurement. TH D procures Donor B's kidney and records 
these costs on its cost report as kidney acquisition costs. TH B 
receives a kidney from TH D for transplant into recipient B. TH B 
records the amounts it pays to TH D on TH B's MCR as kidney acquisition 
costs.

[[Page 25671]]

     TH C procures Donor C's kidney and packages and transports 
it to TH A for Recipient A. TH C bills TH A, charges reduced to cost, 
for the reasonable costs associated with procuring, packaging and 
transporting the kidney as well as any additional testing requested by 
TH A that was not included in the initial evaluation of Donor C. Donor 
C's TH records these costs on its MCR as kidney acquisition costs and 
records any payments received from TH A on TH C's MCR to offset its 
kidney acquisitions costs.
     TH D procures Donor D's kidney and packages and transports 
it to TH B for recipient B. TH D bills TH B, charges reduced to cost, 
for the reasonable costs associated with procuring, packaging and 
transporting the kidney, as well as any additional testing requested by 
TH B that was not included in the initial evaluation of Donor D. Donor 
D's TH records these costs on its MCR as kidney acquisition costs and 
records any payments received from TH B on TH D's MCR to offset its 
kidney acquisitions costs. TH B records the amounts it pays to TH D for 
Donor D's kidney on TH B's MCR as kidney acquisition costs.
    (Step 5), Counting Medicare Usable Organs. Because of the proposed 
policy in section X.B.2.h. of the preamble of this proposed rule and 
proposed new Sec.  413.408 for Medicare usable organ counting, all 
organs that are transplanted into Medicare beneficiaries are counted as 
Medicare usable kidneys.
    The following tables summarize the KPD exchange described 
previously.
[GRAPHIC] [TIFF OMITTED] TP10MY21.316


[[Page 25672]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.317

[GRAPHIC] [TIFF OMITTED] TP10MY21.318

    In this proposed rule, we are proposing to codify into the 
regulations the Medicare organ acquisition payment policy for kidney 
paired exchanges, as set forth in PRM section 3106. Consistent with 
this proposal, we are proposing to add Sec.  413.416(a) to new subpart 
L to specify that when a recipient and donor elect to participate

[[Page 25673]]

in a kidney paired exchange, the costs of the initial living donor 
evaluations are incurred by the originally intended recipient's TH, 
regardless of whether the living donor actually donates to their 
originally intended recipient, a kidney paired exchange recipient, or 
does not donate at all. We are also proposing to add Sec.  413.416(b) 
to new subpart L to specify that in a kidney paired exchange, 
regardless of whether an actual donation occurs, once the donor and 
recipient are matched, any additional tests requested by the 
recipient's TH and performed by the donor's TH, are billed to the 
recipient's TH as charges reduced to cost (using the donor's TH's cost 
to charge ratio) and included as acquisition costs on the recipient 
TH's MCR. We are also proposing to add Sec.  413.416(c) to new subpart 
L to specify that in a kidney paired exchange, when a donor's TH 
procures and sends a kidney to a recipient's TH, all costs must be 
reasonable and necessary and (1) the donor's TH bills the recipient's 
TH the donor TH's charges reduced to cost or the TH's applicable SAC 
for the reasonable costs associated with procuring, packaging and 
transporting the kidney; (2) the donor's TH records these costs 
associated with procuring, packaging and transporting the kidney on its 
MCR as kidney acquisition costs and offsets any payments received from 
the recipient's TH against these kidney acquisition costs; and (3) the 
recipient's TH records as part of its kidney acquisition costs, the 
amounts billed by the donor's TH for the reasonable costs associated 
with procuring, packaging, and transporting the organ as well as any 
additional testing performed and billed by the donor's TH. We are also 
proposing to add Sec.  413.416(d) to new subpart L to specify that, in 
a kidney paired exchange (1) when a donor's TH does not procure a 
kidney, but the donor travels to the recipient's TH for the organ 
procurement, the reasonable costs associated with the organ procurement 
are included on the MCR of the recipient's TH, and (2) travel expenses 
of the living donor are not allowable Medicare costs. In section 
X.B.2.c.(2). of this proposed rule, we are proposing to add Sec.  
413.404(b)(2) to specify that when a transplant hospital/HOPO provides 
an organ to another transplant hospital or OPO, it must bill the 
receiving transplant hospital or OPO its SAC or the hospital's standard 
departmental charges that are reduced to cost.
l. Proposals Requiring Donor Community Hospitals To Charge OPOs 
Reasonable Costs, Charges Reduced to Cost
    Medicare-certified hospitals that are not THs but collaborate with 
OPOs to procure organs from cadaveric donors for transplantation are 
hereinafter referred to as ``donor community hospitals''. To 
participate in the Medicare Program, donor community hospitals and THs 
have organ procurement responsibilities and must have an agreement with 
a designated OPO to timely notify the OPO of individuals whose death is 
imminent or who have died in the hospital (42 CFR 482.45(a)(1)). The 
OPO then implements its donation protocol and, when appropriate (after 
declaration of death and consent to donate), will arrange for the 
procurement of all medically suitable cadaveric donor organs for 
transplant, at the donor community hospital or TH. In this regard, 
donor community hospitals and THs may incur costs for services provided 
to cadaveric organ donors following the consent to donate through the 
procurement of the organs (for example, use of the hospitals operating 
room, staff, and ventilators to maintain the viability of the cadaveric 
donor organs).
    Currently, when a donor community hospital incurs costs for 
services provided to the cadaveric donor, as authorized by the OPO 
following the declaration of death and consent to donate, it bills the 
OPO its customary charges (not reduced to cost) or a negotiated rate. 
(PRM-1 section 3107). Donor community hospital billing procedures are 
described in IL 74-23, published July 1, 1974, which provides, ``where 
the excising hospital is not a TH, it will bill its customary charges 
for those services used in excising the cadaver kidney.'' Thereafter, 
the OPO includes the charges from the donor community hospital on its 
cost report as part of the OPO's organ acquisition costs. At the end of 
its accounting period, the TH/HOPO uses these amounts to calculate its 
renal and non-renal SAC amounts for the following year, and the IOPO 
uses these amounts to calculate its non-renal SAC amounts for the 
following year. Medicare contractor's also use these amounts to 
calculate the IOPO's kidney SAC for the following year.
    When the IOPO furnishes an organ to a TH (or other OPO), the IOPO 
bills the TH (or other OPO) the IOPO's SAC for the specific organ type. 
Currently, when a TH/HOPO provides an organ to another TH or OPO, it 
must bill its SAC or its standard departmental charges reduced to cost. 
The OPO's SAC is a charge which reflects an average of the total actual 
costs the OPO incurs to furnish an organ and reflects amounts the OPO 
is charged by the donor community hospital for services the donor 
community hospital provides to cadaveric donors. THs then include these 
SACs they have paid to OPOs to procure organs as allowable acquisition 
costs in their bills to Medicare, which Medicare pays. Therefore, 
because the OPO's incurred costs are passed on to and paid by the TH, 
and because the TH then includes these amounts as organ acquisition 
costs on its cost report, this chain of incurred costs results in 
Medicare paying these donor hospital charges (that are not reduced to 
cost) when it reconciles the organ acquisition costs on the TH cost 
report.
    Stakeholders have made CMS aware that some donor community 
hospitals are charging OPOs amounts that are in excess of reasonable 
costs for services provided to cadaveric organ donors, resulting in 
Medicare paying more than reasonable costs for the acquisition of 
cadaveric donor organs for transplant. In one instance, an OPO 
identified a donor community hospital in its designated service area 
that billed amounts in excess of reasonable costs. CMS reviewed the 
donor community hospital's bills to the OPO and the donor community 
hospital's MCR information to evaluate the costs associated with those 
charges. CMS computed, using the hospitals cost-to-charge ratios, that 
the charges billed by the donor community hospital in the amount of 
$194,000, equated to a cost of $11,000. Thus, the donor community 
hospital's actual costs were approximately 6 percent of their billed 
charges.
    Organ acquisition costs are reimbursed under Medicare's principles 
of reasonable cost established under section 1861(v) of the Act. Donor 
community hospitals (and THs) are Medicare-certified hospitals and must 
follow Medicare's reasonable cost principles under section 1861(v) of 
the Act. Because the services donor community hospitals provide to 
cadaveric donors, and thus charge to OPOs, are included as organ 
acquisition costs on OPOs' cost reports, these charges should also be 
subject to Medicare's principles of reasonable cost established under 
section 1861(v) of the Act, and 42 CFR 413.5 and 413.9.
    In a 1978 final rule with comment, CMS similarly noted that THs 
have no basis for determining the reasonableness

[[Page 25674]]

of the charges made by the OPO.\1515\ CMS observed that services 
furnished by OPOs, if they are not part of the transplant hospital, are 
billed to transplant hospitals, which pay the charges shown on the 
bill. The charges then become allowable costs of the hospitals.\1516\ 
When donor community hospitals charge OPOs amounts not reduced to 
costs, and the OPOs pay the charges shown on the bill, those charges 
become incorporated as organ acquisition costs to the TH and are 
subsequently shared by Medicare; thus, Medicare's reasonable cost 
principles applicable to organ acquisition costs are not observed. We 
note that organs recovered from donor community hospitals comprised 62 
percent of all transplanted organs in 2017 and 2018.\1517\ We recognize 
that because THs bill the OPOs' charges to Medicare, Medicare is paying 
more than reasonable costs for these services that become organ 
acquisition costs.
---------------------------------------------------------------------------

    \1515\ 43 FR 58370 (December 14, 1978).
    \1516\ Id.
    \1517\ Scientific Registry of Transplant Recipients. Request for 
Information. Requested on 02/08/2021.
---------------------------------------------------------------------------

    Because these charges become allowable organ acquisition costs of 
the TH, we believe that donor community hospitals should be required to 
reduce their charges to cost for services provided to cadaveric donors 
and billed to OPOs, in accordance with reasonable cost principles given 
in section 1861(v) of the Act and in our regulations at 42 CFR 413.5 
and 413.9. Doing so will result in conformance to Medicare reasonable 
cost principles, and result in reduced costs to the OPOs, subsequently 
reducing cadaveric donor SACs billed to THs or OPOs, which may benefit 
other payors, as well as Medicare. Donor community hospitals are 
reimbursed either a DRG payment by Medicare (if the patient is a 
Medicare beneficiary), or a payment from other payers, for services 
provided to a potential organ donor prior to declaration of death and 
consent to donate. For services provided after declaration of death and 
consent to donate payment, if our proposal is implemented, donor 
hospitals would be reimbursed by OPOs for their reasonable costs in 
accordance with Medicare's principles of reimbursement. Therefore, a 
donor community hospital would see a reduction in reimbursement from 
OPOs, because the donor hospital was previously permitted to bill the 
OPO its customary charges or negotiated rates. However, donor community 
hospitals would still have their reasonable costs reimbursed.
    We believe that an equitable and accurate methodology to reduce a 
donor community hospital's charges to cost would be to use the most 
recently available hospital specific CCR. Using the hospital's specific 
CCR would be unique to each donor community hospital and would more 
accurately compensate them for services provided to cadaveric organ 
donors, as opposed to using an alternative like the statewide CCR. 
Because contractors recalculate each hospital's specific CCR on an 
ongoing basis, whenever more recent cost report data is available, the 
hospital's specific CCR is arguably more accurate and more closely 
aligned with creating a uniform charge to cost structure.
    One methodology we considered to reduce a donor community 
hospital's charges to cost was to require them to use their statewide 
average operating CCR and apply this statewide average CCR to its 
charges. The statewide average operating CCR is updated annually in the 
FY IPPS/LTCH rule and is a transparent source of data. We note that the 
statewide average operating CCR published in the FY 2021 IPPS/LTCH 
final rule was 0.272 for urban hospitals and 0.336 for rural hospitals. 
Using a statewide average CCR would even out any instances in which a 
hospital's operating costs fall above or below established parameters. 
However, because it is an average, it would not accurately represent 
the variability in actual hospital specific CCRs. Therefore, using a 
statewide CCR may not adequately serve the purpose of reducing charges 
to cost.
    Stakeholders have suggested that some donor community hospitals are 
improperly billing OPOs for services provided to cadaveric donors prior 
to the declaration of death and consent to donate. This would be 
inappropriate because hospital services provided prior to declaration 
of death and consent to donate are billable to the donor's insurance in 
the same manner hospital services are billable to an individual 
receiving services, regardless of whether the payor is Medicare. We 
reiterate that when a donor community hospital or TH incurs costs for 
providing services to a cadaveric donor, as authorized by the OPO, only 
those costs incurred after the declaration of the donor's death and 
consent to donate are permitted to be billed to the OPO. The OPO must 
accept bills from donor community hospitals and THs for costs only 
incurred after the declaration of death and consent to donate. 
Contractors will review OPO cost reports to ensure that donor community 
hospitals and THs charge OPOs for cadaveric donor costs incurred after 
declaration of death and consent to donate.
    In this proposed rule we are proposing to add Sec.  413.418(a) in 
new subpart L, to specify that a donor community hospital (a Medicare-
certified non-transplant hospital) incurs organ acquisition costs for 
donor organ procurement services, authorized by the OPO following 
declaration of death and consent to donate.
    We are proposing to add Sec.  413.418(b) in new subpart L, to 
specify that for cost reporting periods beginning on or after October 
1, 2021, when a donor community hospital incurs costs for services 
furnished to a cadaveric donor, as authorized by the OPO, the donor 
community hospital must bill the OPO its customary charges that are 
reduced to cost by applying its most recently available hospital 
specific cost-to-charge ratio for the period in which the service was 
rendered.
m. Proposed Revisions, Technical Corrections, and Conforming Changes to 
42 CFR Part 412, Subparts A, E, G, and H and to Part 413, Subparts A, 
C, and H
(1) Conforming Changes to Terminology in 42 CFR Parts 412 and 413
    In section X.B.2.a.(1). of the preamble of this proposed rule, we 
noted terminology differences in the use of ``transplantation center'', 
where the regulations in 42 CFR part 412, subparts A, E, G, and H and 
in Part 413, subparts A, C, and H use the term to mean an organ-
specific transplantation program that is within a TH. We are proposing 
to conform the language in the regulation text to the terminology used 
in the CoPs at Sec.  482.70 by replacing the term ``transplantation 
center'' and its various permutations with the term ``transplant 
program'' and its various permutations. We are proposing to make this 
conforming change in the text of the following regulations: Sec. Sec.  
412.1(a)(1)(ii), 412.2(e)(4), 412.71(b)(3), 412.90(d), 412.100 (in the 
title and in the text at Sec. Sec.  412.100(a)(1)), 412.113(d), 
412.116(c), and 413.40(a)(3). We are also proposing to update the 
terminology to replace ``organ procurement agency'' and its various 
permutations with ``organ procurement organization'' and its various 
permutations. Further, we are proposing to replace the acronym ``OPAs'' 
with ``OPOs''. We are proposing to make these terminology changes to 
the regulation text at Sec. Sec.  412.100(b) and 413.1(a)(2)(v) to 
conform to the terminology used in the CoPs found in 42 CFR part 482. 
Finally, we are proposing to change ``renal'' to ``kidney'' in 
Sec. Sec.  412.71(b)(3), 412.90(d), in the title and paragraph (a) of 
Sec.  412.100, and in Sec.  412.116(c), to

[[Page 25675]]

conform to the terminology used in the CoPs at Sec.  482.104.
(2) Revisions, Technical Corrections, and Conforming Changes to Sec.  
412.100
    We are proposing to revise the text currently found in Sec.  
412.100(a) and (b) to change ``expenses'' to ``costs'' and to remove 
the word ``estimated'' from Sec.  412.100(a)(1). We are also proposing 
to make a technical correction to remove from Sec.  412.100(a)(1) 
cross-references to CoPs which no longer exist, and replace them with 
Sec.  482.104 and are proposing to add language to clarify that CMS 
adjusts inpatient prospective payment system (IPPS) rates for inpatient 
operating costs. We are proposing to revise Sec.  412.100(a)(1) to read 
CMS adjusts the inpatient prospective payment system (IPPS) rates for 
inpatient operating costs determined under subparts D and E of this 
part for hospitals with approved kidney transplant programs (discussed 
at Sec.  482.104) to remove the net costs associated with kidney 
acquisition.
    Additionally, we are proposing to revise Sec.  412.100(a)(2) to 
clarify the language, and to specify that Medicare payment for kidney 
acquisition costs includes only those costs for kidneys transplanted 
into Medicare beneficiaries. We are proposing to revise Sec.  
412.100(a)(2) to specify the following:
     Payment for Medicare kidney acquisition costs, as set 
forth in subpart L of part 413 of this chapter, is made on a reasonable 
cost basis apart from the prospective payment rate for inpatient 
operating costs.
     IPPS payment to the hospital is adjusted in each cost 
reporting period to reflect an amount necessary to compensate the 
hospital for reasonable costs of Medicare kidney acquisition.
    In section X.B.2.b.(1). of the preamble of this proposed rule, we 
are proposing to revise Sec.  412.100(b) by revising and relocating the 
list of organ acquisition costs given in that paragraph and adding the 
list as paragraph (b) in proposed Sec.  413.402 of new subpart L. 
Further, we are proposing to revise Sec.  412.100(b) to make it clearer 
that kidney acquisition costs must be incurred. Finally, we are 
proposing to revise Sec.  412.100(b) to add language that the items and 
services covered as kidney acquisition costs are specified in Sec.  
413.402(b).
(3) Proposed Revisions and Conforming Changes to 42 CFR 412.113(d)
    In addition to the conforming change discussed in section 
X.B.2.m.(1). of the preamble of this proposed rule, we are proposing to 
revise the regulation text at Sec.  412.113(d) to reference the organ 
acquisition policies given in new subpart L of part 413, rather than to 
maintain the existing cross-reference to the definition of organ given 
in Sec.  486.302.
(4) Technical Corrections and Conforming Changes to Sec.  413.1
    In addition to the conforming change discussed in section 
X.B.2.m.(1). of the preamble of this proposed rule, we are proposing to 
revise the text in Sec.  413.1(d)(2)(i) to put it into list form. We 
are also proposing to revise the text related to kidney acquisition 
costs to read organ acquisition costs as specified in part 413 subpart 
L.
(5) Proposed Revision to 42 CFR 413.40(a)(3)
    In addition to the proposed conforming changes discussed in 
X.B.2.m.(1). of the preamble of this proposed rule, we are proposing a 
technical correction and a revision to paragraph (a)(3) of Sec.  
413.40. We are proposing to revise the regulation text that references 
heart, kidney, and liver acquisition costs to read organ acquisition 
costs as specified in part 413 subpart L so that the language reflects 
all solid organs for which Medicare covers organ acquisition costs and 
directs readers to the organ acquisition cost in part 413.
(6) Proposed Regulatory Changes to Section 413.200
    We are proposing to remove the regulation found at 42 CFR 413.200 
entitled Payment of Independent organ procurement organizations and 
histocompatibility laboratories. We are proposing to add Sec.  413.400 
to contain revised text from Sec.  413.200(b), and to add Sec.  413.420 
to contain the remaining regulation text from Sec.  413.200 (a) and (c) 
through (g), along with a revised title, so that the content of Sec.  
413.200, with revisions, is located with other regulations specific to 
organ acquisition in part 413, new subpart L. We are proposing to make 
a technical correction or revisions to two of the three definitions 
found in Sec.  413.200(b), as described in section X.B.2.a.(2). of the 
preamble of this proposed rule. We are proposing to add these 
definitions to proposed Sec.  413.400, as described in section 
X.B.2.a.(2). of the preamble of this proposed rule.
    We are proposing to relocate and revise the regulation title and 
regulation text currently existing in Sec.  413.200 in paragraphs (a), 
and (c) through (g), by adding Sec.  413.420, entitled ``Payment to 
independent organ procurement organizations and histocompatibility 
laboratories for kidney acquisition costs'' and by adding paragraphs 
(a), and (c) through (g) with the text from those same paragraphs in 
Sec.  413.200. We are proposing to make conforming changes to the 
regulation text in Sec.  413.420(a) and (c) through (g) to distinguish 
independent OPOs (IOPOs) from all OPOs where appropriate, in accordance 
with the proposed definition of IOPO in Sec.  413.400. We also are 
proposing to add paragraph (b) to Sec.  413.420 with a subtitle of 
``Definitions'', to provide a cross-reference to the definitions in 
Sec.  413.400 of new subpart L. Therefore, the proposed new Sec.  
413.420 would maintain the same paragraph structure as the existing 
Sec.  413.200. Finally, we are proposing minor revisions to clarify the 
regulation text, including changing language from passive to active 
tense, changing verbs from future tense to present tense, and editing 
to improve readability.
3. Solicitation of Comments Regarding Surgeon Fees for Cadaveric Donor 
Excisions
    Since 1987, we have limited the amount an OPO may reimburse a 
physician for cadaveric kidney donor retrieval services. Chapters 27 
and 31 of the PRM limit the physician payment for cadaveric kidney 
retrieval to $1,250 per donor (one or two kidneys). The history behind 
the limitation on physician payment may be based on a July 1974 $400 
physician services limitation on excising kidneys in community 
hospitals that do not participate in Medicare, which was noted in a 
Part A Intermediary Letter (IL No. 74-23, July 1974); it may also be 
based in part on the 1983 median cost paid by OPOs for surgical 
excision of cadaveric kidneys, which was approximately $800.\1518\ 
Although the payments made to physicians for organ retrieval services 
associated with other types of organ transplants have increased, 
cadaveric kidney retrieval rates have remained capped at $1,250. We 
have received several requests to change the amount we pay for 
cadaveric kidney retrievals. In the CY 2009 Revisions to Payment 
Policies Under the Physician Fee Schedule and Other Revisions to Part B 
for CY 2009 (hereafter, Physician's Fee) proposed rule (73 FR 38580 and 
38581), we solicited public comments and data that are reflective of 
organ retrieval service costs for all types of organs. At that time, we 
did not have data upon which

[[Page 25676]]

to base a change in payment. We stated that we may use this information 
to determine the extent to which a recalculation of the payment for 
cadaveric organ retrieval services performed by a physician is 
warranted and to inform any future rulemaking on this subject. We 
received four timely public comments in response to our request for 
information and data for use in updating the organ retrieval physician 
payment amount included in organ acquisition costs, which were 
discussed in detail in the CY 2009 Physicians Fee Schedule final rule 
(73 FR 69864). However, we did not receive any data that would be 
useful in evaluating the appropriateness of the $1,250 per donor 
surgeon fee limit for cadaveric kidney retrievals.
---------------------------------------------------------------------------

    \1518\ Organ Transplants: Hearings before the Subcommittee on 
Investigations and Oversight, of the House Committee on Science and 
Technology. 98th Cong. 43 (1983) (testimony of Carolyne K. Davis, 
Ph.D., Administrator, Health Care Financing Administration).
---------------------------------------------------------------------------

    For this proposed rule, we used 2017 cost report data from 48 OPOs 
to calculate a surgeon fee cost per local kidney for each provider, by 
dividing the kidney surgeon fee costs reported on Worksheet A-2, line 
13, column 3 of the MCR by the number of local kidneys reported on 
Worksheet S-1, Part 1, Line 1, column 1 of the MCR. Excluding three 
providers with extremely low surgeon fees per local kidney (ranging 
from $0 to $231), the average surgeon fee cost per local kidney was 
$745. These provider-reported data suggest that the $1,250 limit on 
surgeon fees for cadaveric donor kidney retrievals is sufficient and 
allows for some higher cost excisions. However, we have received 
comments suggesting that this limit needs to be reconsidered.
    While we are not proposing to change the physician payment limit 
for cadaveric kidney retrieval in this proposed rule, we are soliciting 
information on the physician effort and resources required to procure a 
cadaveric kidney for transplantation. Specifically, we are soliciting 
data or other information on surgical time, dry runs (number and 
percentage of retrievals in which an organ is not recovered), travel 
and wait times, as well as the incremental time required for extended 
criteria donors and donors after cardiac death. Additionally, we are 
soliciting resource information to determine the difference in 
procuring one kidney or a pair of kidneys from a single donor. The 
comments we receive may inform development of future proposals related 
to surgeon fee payment for organ retrieval from cadaveric donors. Any 
possible future rulemaking would provide for notice and public comment.

C. Medicare Shared Savings Program--Proposed 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 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

[[Page 25677]]

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. Proposal Regarding Basic Track Risk ``Freeze'' Option
    Due to the continued PHE for COVID-19, ACOs and other stakeholders 
have 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.
    Stakeholders have continued to express 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 have 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. We believe 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 are also concerned 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, the duration of the PHE for COVID-19 remains 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 propose 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 propose 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 
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

[[Page 25678]]

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 2023, 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 have 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 as specified at Sec.  
425.600(a)(4)(i)(B)(2)(ii).
[GRAPHIC] [TIFF OMITTED] TP10MY21.319

[GRAPHIC] [TIFF OMITTED] TP10MY21.320

    We propose 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 
recognize that the annual application and change request cycle will 
begin before the FY 2022 IPPS/LTCH PPS rulemaking is finalized. 
Accordingly, we will give ACOs the

[[Page 25679]]

opportunity during the change request cycle to indicate whether they 
are interested in maintaining their participation at Level A or Level B 
under this proposed policy, should it be finalized. ACOs expressing 
such an interest would not be required to submit a repayment mechanism 
at that time. In the event this proposed policy is not finalized in the 
FY 2022 IPPS/LTCH PPS final rule, ACOs that are required under Sec.  
425.600(a)(4)(i)(B)(2)(iii) to advance from Level A or Level B to a 
two-sided risk model for PY 2022 would have a limited opportunity to 
submit a repayment mechanism, resolve any deficiencies, and have it 
approved in time for the start of the performance year. ACOs that fail 
to establish a repayment mechanism that complies with the requirements 
of Sec.  425.204(f) by the deadline specified by CMS would be 
terminated as required under Sec.  425.600(a)(4)(i)(B)(3).
    We propose to redesignate Sec.  425.600(a)(4)(i)(B)(2)(iv) as Sec.  
425.600(a)(4)(i)(B)(2)(v). Additionally, we propose 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 intend to continue to monitor the 
PHE for COVID-19 and assess its impact on the Shared Savings Program. 
We will address any additional flexibilities that may be warranted as a 
result of the ongoing PHE through future notice and comment rulemaking.
    Lastly, 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). In making this amendment, we 
inadvertently omitted the revision to the cross-reference in paragraph 
(a)(4)(i)(B)(3). In this proposed rule, we are proposing 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 
propose 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).

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 
proposed policies set forth in this proposed rule. MedPAC 
recommendations for the IPPS for FY 2022 are addressed in Appendix B to 
this proposed 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. Following is 
a listing of the IPPS-related data files that are available.
    As discussed in section II.A. of the preamble of this proposed 
rule, we are proposing to use 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. As discussed in section 
I.O. of Appendix A of this proposed rule, as an alternative to our 
proposed approach, we considered using the FY 2020 data we would 
ordinarily use in the FY 2022 IPPS and LTCH PPS ratesetting. In order 
to facilitate comments on this alternative approach, which we may 
consider finalizing for FY 2022 based on consideration of comments 
received, we are making available the FY 2020 MedPAR file and the FY 
2019 HCRIS file that we would ordinarily have provided in conjunction 
with this proposed rule, as well as other proposed rule supporting data 
files based on the use of the FY 2020 data, including the IPPS and LTCH 
PPS Impact Files, the AOR/BOR File, the Case Mix Index File, and the 
Standardizing File. We refer the reader to section I.O. of Appendix A 
of this proposed rule for a discussion of the files that we are making 
available with regard to our alternative approach of using the FY 2020 
data that we would ordinarily use in the FY 2022 IPPS and LTCH PPS 
ratesetting.
    Commenters interested in discussing any data files used in 
construction of this proposed rule should contact Michael Treitel at 
(410) 786-4552.
1. CMS Wage Data Public Use File
    This file contains the hospital hours and salaries from Worksheet 
S-3, parts II and III from FY 2018 Medicare cost reports used to create 
the proposed FY 2022 IPPS wage index. Multiple versions of this file 
are created each year. For a discussion of the release of different 
versions of this file, we refer readers to section III.L. of the 
preamble of this proposed rule.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html. Periods 
Available: FY 2007 through FY 2022 IPPS Update.
2. CMS Occupational Mix Data Public Use File
    This file contains the CY 2019 occupational mix survey data to be 
used to compute the occupational mix adjusted wage indexes. Multiple 
versions of this file are created each year. For a discussion of the 
release of different versions of this file, we refer readers to section 
III.L. of the preamble of this proposed rule.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html. Period 
Available: FY 2022 IPPS Update.
3. Provider Occupational Mix Adjustment Factors for Each Occupational 
Category Public Use File
    This file contains each hospital's occupational mix adjustment 
factors by occupational category. Two versions of these files are 
created each year to support the rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html.
    Period Available: FY 2022 IPPS Update.
4. Other Wage Index Files
    CMS releases other wage index analysis files after each proposed 
and final rule. Media: internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Files.html. Periods Available: FY 2005 through FY 2022.
5. FY 2022 IPPS FIPS CBSA State and County Crosswalk
    This file contains a crosswalk of State and county codes used by 
the Federal Information Processing Standards (FIPS), county name, and a 
list of Core Based Statistical Areas (CBSAs).

[[Page 25680]]

    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel 
on the left side of the page, click on the FY 2022 proposed rule home 
page or the FY 2022 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/AcuteInpatient-Files-for-Download.html.
    Period Available: FY 2022 IPPS Update.
6. HCRIS Cost Report Data
    The data included in this file contain cost reports with fiscal 
years ending on or after September 30, 1996. These data files contain 
the highest level of cost report status.
    Media: internet at: https://www.cms.gov/Research-Statistics-Dataand-Systems/Downloadable-Public-UseFiles/Cost-Reports/Cost-Reports-byFiscal-Year.html.
    (We note that data are no longer offered on a CD. All of the data 
collected are now available free for download from the cited website.)
7. Provider-Specific File
    This file is a component of the PRICER program used in the MAC's 
system to compute DRG/MS-DRG payments for individual bills. The file 
contains records for all prospective payment system eligible hospitals, 
including hospitals in waiver States, and data elements used in the 
prospective payment system recalibration processes and related 
activities. Beginning with December 1988, the individual records were 
enlarged to include pass-through per diems and other elements.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/ProspMedicareFeeSvcPmtGen/psf_text.html.
    Period Available: Quarterly Update.
8. CMS Medicare Case-Mix Index File
    This file contains the Medicare case-mix index by provider number 
based on the MS-DRGs assigned to the hospital's discharges using the 
GROUPER version in effect on the date of the discharge. The case-mix 
index is a measure of the costliness of cases treated by a hospital 
relative to the cost of the national average of all Medicare hospital 
cases, using DRG/MS-DRG weights as a measure of relative costliness of 
cases. Two versions of this file are created each year to support the 
rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/Acute-InpatientFiles-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/index.html 
(on the navigation panel on the left side of page, click on the 
specific fiscal year proposed rule home page or fiscal year final rule 
home page desired).
    Periods Available: FY 1985 through FY 2022.
9. MS-DRG Relative Weights (Also Table 5--MS-DRGs)
    This file contains a listing of MS- DRGs, MS-DRG narrative 
descriptions, relative weights, and geometric and arithmetic mean 
lengths of stay for each fiscal year. Two versions of this file are 
created each year to support the rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/Acute-InpatientFiles-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/index.html 
(on the navigation panel on the left side of page, click on the 
specific fiscal year proposed rule home page or the fiscal year final 
rule home page desired).
    Periods Available: FY 2005 through FY 2022 IPPS Update.
10. IPPS Payment Impact File
    This file contains data used to estimate payments under Medicare's 
hospital inpatient prospective payment systems for operating and 
capital-related costs. The data are taken from various sources, 
including the Provider-Specific File, HCRIS Cost Report Data, MedPAR 
Limited Data Sets, and prior impact files. The data set is abstracted 
from an internal file used for the impact analysis of the changes to 
the prospective payment systems published in the Federal Register. Two 
versions of this file are created each year to support the rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/Historical-ImpactFiles-for-FY-1994-through-Present.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel on the left side of page, click on 
the specific fiscal year proposed rule home page or fiscal year final 
rule home page desired).
    Periods Available: FY 1994 through FY 2022 IPPS Update.
11. AOR/BOR File
    This file contains data used to develop the MS-DRG relative 
weights. It contains mean, maximum, minimum, standard deviation, and 
coefficient of variation statistics by MS-DRG for length of stay and 
standardized charges. The BOR file are ``Before Outliers Removed'' and 
the AOR file is ``After Outliers Removed.'' (Outliers refer to 
statistical outliers, not payment outliers.) Two versions of this file 
are created each year to support the rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/Acute-InpatientFiles-for-Download.html, or for the more recent data files, https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/index.html 
(on the navigation panel on the left side of page, click on the 
specific fiscal year proposed rule home page or fiscal year final rule 
home page desired).
    Periods Available: FY 2005 through FY 2022 IPPS Update.
12. Prospective Payment System (PPS) Standardizing File
    This file contains information that standardizes the charges used 
to calculate relative weights to determine payments under the hospital 
inpatient operating and capital prospective payment systems. Variables 
include wage index, cost-of-living adjustment (COLA), case-mix index, 
indirect medical education (IME) adjustment, disproportionate share, 
and the CoreBased Statistical Area (CBSA). The file supports the 
rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel 
on the left side of the page, click on the FY 2022 proposed rule home 
page or the FY 2022 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/AcuteInpatient-Files-for-Download.html.
    Period Available: FY 2022 IPPS Update.
13. MS-DRG Relative Weights Cost Centers File
    This file provides the lines on the cost report and the 
corresponding revenue codes that we used to create the 19 national cost 
center cost-to-charge ratios (CCRs) that we used in the relative weight 
calculation.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-

[[Page 25681]]

Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation 
panel on the left side of the page, click on the FY 2022 proposed rule 
home page or the FY 2022 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/AcuteInpatient-Files-for-Download.html.
    Period Available: FY 2022 IPPS Update
14. Hospital Readmissions Reduction Program Supplemental File
    Updated data are not available at this time. Therefore, we refer 
readers to the FY 2021 IPPS/LTCH PPS final rule supplemental file, 
which has the most recent finalized payment adjustment factor 
components and is the same data as would have been used to create the 
FY 2022 IPPS/LTCH PPS proposed rule supplemental file.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel 
on the left side of the page, click on the FY 2022 proposed rule home 
page or the FY 2022 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/AcuteInpatient-Files-for-Download.html.
    Period Available: FY 2022 IPPS Update.
15. Medicare Disproportionate Share Hospital (DSH) Supplemental File
    This file contains information on the calculation of the 
uncompensated care payments for FY 2022. Variables include the data 
used to determine a hospital's share of uncompensated care payments, 
total uncompensated care payments and estimated per claim uncompensated 
care payment amounts. The file supports the rulemaking.
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel 
on the left side of the page, click on the FY 2022 proposed rule home 
page or the FY 2022 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/AcuteInpatientPPS/AcuteInpatient-Files-for-Download.html.
    Period Available: FY 2022 IPPS Update.
16. New Technology Thresholds File
    This file contains the cost thresholds by MS-DRG that are generally 
used to evaluate applications for new technology add-on payments for 
the fiscal year that follows the fiscal year that is otherwise the 
subject of the rulemaking. (As discussed in section II.G. of this 
proposed rule, we use the proposed threshold values associated with the 
proposed rule for that fiscal year to evaluate the cost criterion for 
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.) Two versions of this file are created 
each year to support rulemaking. (We note that the information in this 
file was previously provided in Table 10 of the annual IPPS proposed 
and final rules (83 FR 41739).)
    Media: internet at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/index.html (on the navigation panel 
on the left side of the page, click on the applicable fiscal year's 
proposed rule or final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-InpatientFiles-for-Download.html.
    Periods Available: For FY 2022 and FY 2023 applications.

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 this proposed rule, we are soliciting 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 proposed rule, we discuss 
proposed requirements for the Hospital Readmissions Reduction Program. 
In this proposed rule, we are not proposing to remove or adopt 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 proposed rule, we discuss 
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 Public Health Emergency on this measure, for FY 2023. 
However, we believe that the proposed 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.
3. ICRs for the Hospital Value-Based Purchasing (VBP) Program
    In section V.H. of the preamble of this proposed rule, we discuss 
proposed requirements for the Hospital VBP Program. Specifically, in 
this proposed rule, with respect to quality measures, we are proposing 
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 proposing to remove the CMS PSI 90 measure 
beginning with the FY 2023 program year and 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 fee-for-service claims data that hospitals are already 
submitting to CMS for payment purposes, we do not anticipate any change 
in burden associated with this proposed rule.

[[Page 25682]]

4. ICRs for the Hospital Acquired Condition (HAC) Reduction Program
    In this proposed rule, we are not proposing to remove any measures, 
adopt any new measures into the HAC Reduction Program, or update our 
validation procedures. The HAC Reduction Program has adopted six 
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 hospitals are already 
submitting to the Medicare program for payment purposes. We note the 
burden associated with collecting and submitting data for the HAI 
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 will not impact our burden estimates.
5. ICRs Regarding the Implementation of Section 126 of the Consolidated 
Appropriations Act--Distribution of Additional Residency Positions
    As discussed in section V.J.2.a. of the preamble of this proposed 
rule, teaching hospitals would be able to submit electronic 
applications to CMS for resident slot increase requests. The burden 
associated with these requests will be discussed in a forthcoming 
information collection request, which is currently under development. 
However, upon completion of the ICR, we will publish the required 60-
day and 30-day notices to solicit public comments in accordance with 
the requirements of the PRA.
6. ICR for Proposed 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 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. Further instructions for the reporting of this 
market-based data on the Medicare cost report were discussed in the 
revision of the ICR currently approved under OMB control number 0938-
0050, expiration date March 31, 2022 and 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).
    In the FY 2021 IPPS/LTCH PPS final rule we estimated an average 
annual burden per hospital of 20 hours (5 hours for recordkeeping and 
15 hours for reporting) for completing the Worksheet S-12 and complying 
with 42 CFR 413.20(d)(3). The 20 hours per hospital to complete the 
Worksheet S-12 includes 5 hours for recordkeeping, including 
bookkeeping, accounting and auditing clerk tasks. The remaining 15 
hours for reporting include accounting and audit professionals' 
activities. We estimated that 3,189 hospitals would be required to 
comply with this market-based data collection requirement. This equated 
to an estimated total annual burden hours as follows: 3,189 hospitals 
times 20 hours per hospital equals 63,780 annual burden hours.\1519\ We 
calculated a total annual cost of $1,353.40 per hospital, or $4,315,993 
across all hospitals. We refer readers to 85 FR 59015 for further 
information.
---------------------------------------------------------------------------

    \1519\ This estimate was finalized in the FY 2021 IPPS/LTCH PPS 
final rule. These estimates were based on the most recent data, 
available at the time of the final rule, from the System for 
Tracking Audit and Reimbursement, an internal CMS data system 
maintained by the Office of Financial Management (OFM).
---------------------------------------------------------------------------

    Section V.L. of the preamble of this proposed rule discusses the 
proposed repeal of the market-based MS-DRG relative weight data 
collection and market-based methodology for calculating MS-DRG relative 
weights. If we were to finalize our proposal to repeal the market-based 
data collection and relative weight methodology, we estimate a 
reduction of 63,780 annual burden hours for hospitals, which equals a 
reduction of $4,315,993 across all hospitals.
7. 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 this proposed rule, we describe the 
burden changes regarding collection of information under OMB control 
number 0938-1022 (expiration date December 31, 2022) for IPPS hospitals 
due to the proposals in this proposed rule.
    We refer readers to section IX.C. for more detail on our proposals. 
In this year's proposed rule, we are making several proposals which, if 
finalized, would affect the information collection burden associated 
with the Hospital IQR Program. We are proposing to adopt the: (1) 
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) 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. We expect these 
proposals will affect our collection of information burden estimates. 
Details on these policies as well as the expected burden changes are 
discussed further in this section of this proposed rule.
    We are also proposing several updates which would not affect the 
information collection burden associated with the Hospital IQR Program. 
In section IX.C. of the preamble to this proposed rule, we are 
proposing to: (1) Adopt the Hospital Harm--Severe Hyperglycemia 
electronic clinical quality measure (eCQM) beginning with the CY 2023 
reporting period/FY 2025 payment determination; (2) adopt the Hospital 
Harm--Severe Hypoglycemia eCQM beginning with the CY 2023 reporting 
period/FY 2025 payment determination; (3) 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; (4) remove the 
Death Rate among

[[Page 25683]]

Surgical Inpatients with Serious Treatable Complications (CMS PSI-04) 
claims-based measure beginning with the 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 Anticoagulation 
Therapy for Atrial Fibrillation/Flutter (STK-03) eCQM measure beginning 
with the CY 2024 reporting period/FY 2026 payment determination; (8) 
remove the Discharged on Statin Medication (STK-06) eCQM measure 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (9) 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''; (10) 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''; (11) 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 (12) 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 further in this proposed rule, 
we do not expect these proposals to affect our information collection 
burden estimates.
    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 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.\1520\ 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.
---------------------------------------------------------------------------

    \1520\ 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 Proposed Maternal 
Morbidity Structural Measure
    In section IX.C.5.a. of the preamble of this proposed rule, we are 
proposing to adopt the Maternal Morbidity Structural Measure beginning 
with the CY 2021 reporting period/FY 2023 payment determination. 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 would 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).''
    If our proposal is finalized, hospitals would be required to submit 
the response on an annual basis during the submission period. We 
estimate the information collection burden associated with this 
proposed structural measure to be no more than five 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 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 Proposed 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 proposed rule, we are 
proposing 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 
proposing 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 
our proposal will result in a burden increase of 40 minutes (0.67 
hours) per hospital per year.
    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). If our proposal to adopt

[[Page 25684]]

the Hybrid HWM measure is finalized, we will 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 
would 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 of 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 Proposed Adoption of 
Two Hospital Harm eCQMs Beginning With the CY 2022 Reporting Period/FY 
2024 Payment Determination and Removal of Four eCQMs Beginning With the 
CY 2024 Reporting Period/FY 2026 Payment Determination
    In section IX.C.5.d. of the preamble of this proposed rule, we are 
proposing 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 proposed rule, we are proposing to 
remove four 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); 
(3) Anticoagulation Therapy for Atrial Fibrillation/Flutter (STK-03); 
and (4) Discharged on Statin Medication (STK-05) eCQMs. We do not 
believe that our proposals to add two eCQMs and remove four eCQMS from 
the eCQM measure set 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 proposals would 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 new eCQMs proposed in 
this proposed rule would 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 our proposals to adopt 
or remove these measures would impact our information collection burden 
estimates. However, we refer readers to section I.K. of Appendix A of 
this proposed 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 the Proposed Removal of 
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 proposed rule, we are 
proposing 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 PSI-04 is calculated using data that are already 
reported to the Medicare program for payment purposes, we do not 
anticipate that removing this measure will decrease our previously 
finalized burden estimates.
f. Information Collection Burden Estimate for the Proposed Adoption of 
the COVID-19 HCP Vaccination Measure Beginning With an Interim 
Reporting Period in CY 2021
    In section IX.C.5.c. of the preamble of this proposed rule, we are 
proposing to adopt a COVID-19 HCP Vaccination 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. 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 (OMB control number 0920-1317) because the agency has been granted 
a waiver under Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA).\1521\ As such, the proposed measure would 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 Among HCP measure is not accounted for under the CDC PRA 
0920-1317 or 0920-0666 due to the NCVIA waiver, the cost and burden 
information is included in the Regulatory Impact Analysis section 
(Appendix A, section I.K.) of this rule. Upon receiving comment, we 
will work with CDC to ensure that this burden is accounted for in an 
updated PRA under OMB control number 0920-1317.
---------------------------------------------------------------------------

    \1521\ 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 Proposals To Adopt 
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.8.e.2.(a). and IX.C.8.f.2.(b). of the preamble of 
this proposed rule, we are proposing to require hospitals use the 2015 
Edition Cures Update beginning with the CY 2023 reporting period/FY 
2025 payment determination and subsequent years. Under this proposal, 
hospitals would no longer be able to use the 2015 Edition

[[Page 25685]]

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 these proposals, if finalized, would 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 proposed rule.
h. Information Collection Burden Estimate for the Proposals To Update 
References and Code of Federal Regulations Text Relating to QualityNet 
Security Administrator
    In section IX.C.8.c.2. of the preamble of this proposed rule, we 
are proposing to use the term ``QualityNet security official'' instead 
of ``QualityNet Administrator.'' Specifically, we are proposing 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 proposals 
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.
i. Information Collection Burden Estimate for the Proposal To Update 
References to the QualityNet Website in the Hospital IQR Program 
Regulation Text
    In section IX.C.8.c.(1). of the preamble of this proposed rule, we 
are proposing 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 proposing 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 proposals 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 Proposal To Extend 
the Effects of the Educational Review Process for Chart-Abstracted 
Measures for the FY 2024 Payment Determination and Subsequent Years
    In section IX.C.9.b.(1).(b). of the preamble, we are proposing 
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 proposal 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 proposed rule will result in an 
increase of 2,475 hours annually for 3,300 IPPS hospitals 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. 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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8. ICRs for the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program
    As discussed in section IX.D. of the preamble of this final rule, 
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 reimbursement if a PCH does not participate.
    In section IX.D.5. of the preamble of this proposed rule, we are 
proposing to adopt the COVID-19 Vaccination Coverage Among Healthcare 
Personnel measure beginning with a shortened reporting period from 
October 1, 2021 through December 31, 2021, affecting the FY 2023 
program year, followed by annual reporting periods (affecting the FY 
2024 program year and for subsequent years). We are proposing that PCHs 
would submit data on the measure through the Centers for Disease 
Control and Prevention (CDC)/National Healthcare Safety Network (NHSN). 
The NHSN is a secure, internet-based surveillance system maintained by 
the CDC and provided free of charge to healthcare facilities, including 
PCHs. Currently the CDC does not estimate burden for COVID-19 
vaccination reporting under the CDC PRA package currently 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).\1522\ Although the burden as associated with the COVID-19 HCP 
Vaccination measure is not accounted for under the CDC package 
currently approved under OMB control number 920-1317 or 0920-0666, the 
cost and burden information is included in the Regulatory Impact 
Analysis section (Appendix A, section I.K.) of this rule. Upon 
receiving comments, 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.
---------------------------------------------------------------------------

    \1522\ 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 proposed rule, we are 
proposing 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. 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 estimate 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.
    If these policies are finalized as proposed, as previously stated, 
we estimate a reporting burden reduction of 0.25 hours per PCH or 2.75 
total hours across 11 PCHs, beginning in the FY 2024 program year. 
Because the estimated reporting burden reduction per PCH is so small 
(0.25 hours), there is essentially no net change in the burden hours 
per PCH (6,889 hours [previous burden per PCH]-0.25 hours [proposed 
change in burden per PCH] = 6,888.975, which rounded is 6,889 hours). 
We estimate our total program burden across all 11 PCHs to be 75,776 
hours (75,779 [previous total burden]-2.75 hours [proposed total change 
in burden]). The most recent data from the Bureau of Labor Statistics 
reflects a median hourly wage of $20.50 (previously $19.40),\1523\ 
which when accounting for overhead and fringe benefits, results in an 
hourly wage of $41.00. Using the estimate of 75,776 burden hours across 
the 11 PCHs for data collection and submission of all 14 measures, we 
estimate a total annual labor cost of $3,106,816 (75,776 hours x $41.00 
per hour) for all 11 PCHs for the FY 2024 program year. The updated 
burden estimates will be submitted to OMB under control number 0938-
1175.
---------------------------------------------------------------------------

    \1523\ Bureau of Labor Statistics, Occupational Employment and 
Wages. Accessed on February 12, 2021: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------

8. ICRs for the Long-Term Care Hospital Quality Reporting Program (LTCH 
QRP)
    This proposed rule does not impose any new information collection 
requirements. However, this proposed rule does reference associated 
information collections that are not discussed in the regulation text 
contained in this document. The following is a discussion of these 
information collections, some of which have already received OMB 
approval.
    As stated in section IX.E. of the preamble of this proposed rule 
for purposes of calculating the FY 2023 Annual Payment Update (APU), we 
propose 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 would 
submit the COVID-19 Vaccination Coverage among Healthcare Personnel 
(HCP) measure data to CMS through the NHSN, a web-based tool hosted by 
the CDC. This reporting service is provided free of charge to 
healthcare facilities. 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 14, 1986 (NCVIA).\1524\ 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.
---------------------------------------------------------------------------

    \1524\ 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 would 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.

[[Page 25689]]

    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.
10. ICRs for the Promoting Interoperability Programs
a. Historical Background
    In section IX.D. of the preamble of this proposed rule, we discuss 
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 proposed 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.D.3.b. of the preamble of this rule, we are proposing 
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 CY 2022 EHR reporting period; (2) to modify technical 
specifications of the Provide Patient's Electronic Access to Their 
Health Information Measure to include establishing a data availability 
requirement beginning with encounters with a date of service on or 
after January 1, 2016, effective January 1, 2022; (3) to add a new 
Health Information Exchange (HIE) Bi-Directional Exchange measure as a 
yes/no attestation, beginning in CY 2022 to the HIE objective as an 
optional alternative to the two existing measures; (4) 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); (5) that eligible 
hospitals and CAHs must attest to having completed an annual assessment 
via a SAFER Guides measure, under the Protect Patient Health 
Information Objective, beginning January 1, 2022; (6) to remove 
attestation statements 2 and 3 from the Promoting Interoperability 
Program's prevention of information blocking requirement; and (7) 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 proposed changes.
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.D.3.b. of the preamble of this rule, we are proposing 
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 proposals 
under the Hospital IQR Program. We are amending our regulation text as 
necessary to incorporate these proposed changes.
d. Summary of Policies for Eligible Hospitals and CAHs That Attest to 
CMS Under the Medicare Promoting Interoperability Program for CY 2024
    In section IX.D.3.b. of the preamble of this rule, we are proposing 
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 four 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 
under the Hospital IQR Program. We are amending our regulation text as 
necessary to incorporate these proposed changes.
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 one minute to complete. We estimated 
that the Security Risk Analysis measure will take approximately six 
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 proposed rule, there are two proposed measure changes 
which would 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 CY 2021, 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 proposed time 
for CY 2022 would be 2 minutes (or an increase in 0.03 hours per 
reporting hospital). Although the Objective's Syndromic Surveillance 
Reporting measure is proposed to

[[Page 25690]]

change its setting for which data is required to be submitted, we don't 
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. Second is the 
proposed requirement for a new measure based on SAFER Guides Reporting, 
which we have anticipated will take one minute to report (as it is 
proposed to be completed via a single yes/no attestation response). The 
proposed inclusion of reporting on this SAFER Guides measure would 
increase the total burden by 0.02 hours. Lastly, we would like to note 
that the proposed inclusion of a new HIE Bi-Directional Exchange 
measure would not have any effect on the estimated reporting burden 
given that it would be offered as an optional, alternative reporting 
method to the two current Support Electronic Referral Loops measures, 
therefore resulting in no net change. 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.
    In proposing to continue the EHR reporting period as any self-
selected 90-days in CY 2023 and any self-selected 180-days in CY 2024, 
we do not anticipate additional burden due to how the QualityNet 
attestation system is setup and operated to account for the estimated 
time spent with reporting (submitting automated reports via CEHRT or 
attesting to the Program's objectives and measures wouldn't be impacted 
by a longer EHR reporting period). A similar approach applies to the 
proposal 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 attesting to the Program, especially 
noting that all objectives and measures are currently required to be 
reported on (the threshold only indicates the minimum score necessary 
to be considered a meaningful EHR user). Finally, we do not believe 
that our proposals aligned with the Hospital IQR Program to add two 
eCQMs and remove four 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 
proposals would 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 proposed rule.
    Given the proposals, we estimate a total burden estimate of 6 hours 
33 minutes per respondent (roughly 6.5 hours) which is an increase of 2 
minutes from the FY 2021 IPPS/LTCH PPS final rule (85 FR 58432).
[GRAPHIC] [TIFF OMITTED] TP10MY21.323


[[Page 25691]]


(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).\1525\
---------------------------------------------------------------------------

    \1525\ https://www.bls.gov/oes/current/oes231011.htm.
---------------------------------------------------------------------------

    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 propose to replace 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).\1526\ If finalized, it would more accurately reflect the 
real-world scenario of those staff members performing the required 
labor.
---------------------------------------------------------------------------

    \1526\ https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm#tab-1. Accessed on [02/10/21].
---------------------------------------------------------------------------

    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 will calculate cost burden to hospitals using a wage 
plus benefits estimate of $41 per hour throughout the discussion in 
this section of this rule for the Medicare Promoting Interoperability 
Program.
    In summary, if our proposals are finalized as proposed, we estimate 
a minimal increase in total burden hours for the Medicare Promoting 
Interoperability Program for CY 2022 (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 proposed 
updates would result in a net cost decrease of $607,893 for the 
Medicare Promoting Interoperability Program.
    If our proposals are finalized as proposed for CY 2023 and CY 2024, 
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 proposals only include an extension of the current 
90-day EHR reporting period and the adoption of two new eCQMs to the 
Program's eCQM measure set (in alignment with the proposals under the 
Hospital IQR Program), whereas CY 2024 proposals include a 180-day EHR 
reporting period and the removal of four eCQMs from the Program's eCQM 
measure set (in alignment with proposals under the Hospital IQR 
Program). Both proposals 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.
[GRAPHIC] [TIFF OMITTED] TP10MY21.324


[[Page 25692]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.325

11. Summary of All Burden in This Proposed Rule
    The following chart reflects the total burden and associated costs 
for the provisions included in this proposed rule.
[GRAPHIC] [TIFF OMITTED] TP10MY21.326

C. Response to Comments

    Because of the large number of public comments we normally receive 
on Federal Register documents, we are not able to acknowledge or 
respond to them individually. We will consider all comments we receive 
by the date and time specified in the DATES section of this preamble, 
and, when we proceed with a subsequent document, we will respond to the 
comments in the preamble to that document.

    I, Elizabeth Richter, Acting Administrator of the Centers for 
Medicare & Medicaid Services, approved this document on April 16, 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 
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.

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 revising paragraph (a)(1)(ii), adding 
paragraph (a)(7), and revising paragraph (b)(2) to read as follows:


Sec.  412.1   Scope of part.

    (a) * * *
    (1) * * *
    (ii) Payment for other costs related to inpatient hospital services 
is made on a reasonable cost basis as follows:
    (A) Organ acquisition costs incurred by hospitals with approved 
organ transplant programs.
    (B) The costs of qualified nonphysician anesthetist's services, as 
described in Sec.  412.113(c).
    (C) Direct costs of approved nursing and allied health educational 
programs.
    (D) Costs related to hematopoietic stem cell acquisition for the 
purpose of an allogeneic hematopoietic stem cell transplant as 
described in Sec.  412.113(e).
* * * * *
    (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:

[[Page 25693]]

    (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 412.2 is amended by revising paragraph (e)(4) to read as 
follows:


Sec.  412.2   Basis of payment.

* * * * *
    (e) * * *
    (4) The acquisition costs of hearts, kidneys, livers, lungs, 
pancreas, and intestines (or multivisceral organs) incurred by approved 
transplant programs.
* * * * *
0
4. 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
5. 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 all 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 QualityNet website (http://qualitynet.cms.gov) to attest 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. Except as provided in paragraph (d)(2)(ii) 
of this section, 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 (ECE). (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's 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 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

[[Page 25694]]

website (http://qualitynet.cms.gov) and applicable listservs.
0
6. 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
7. Section 412.71 is amended by revising paragraph (b)(3) to read as 
follows:


Sec.  412.71   Determination of base-year inpatient operating costs.

* * * * *
    (b) * * *
    (3) Kidney acquisition costs incurred by hospitals with approved 
kidney transplant programs as described in Sec.  412.100. Kidney 
acquisition costs in the base year are determined by multiplying the 
hospital's average kidney acquisition cost per kidney times the number 
of kidney transplants covered by Medicare Part A during the base 
period.
* * * * *
0
8. Section 412.90 is amended by revising paragraph (d) to read as 
follows:


Sec.  412.90   General rules.

* * * * *
    (d) Kidney acquisition costs incurred by hospitals with approved 
kidney transplant programs. CMS pays for kidney acquisition costs 
incurred by kidney transplant programs on a reasonable cost basis. The 
criteria for this special payment provision are set forth in Sec.  
412.100.
* * * * *
0
9. 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
10. Section 412.100 is revised to read as follows:


Sec.  412.100   Special treatment: Kidney transplant programs.

    (a) Adjustments for kidney transplant programs. (1) CMS adjusts the 
inpatient prospective payment system (IPPS) rates for inpatient 
operating costs determined under subparts D and E of this part for 
hospitals with approved kidney transplant programs (discussed at Sec.  
482.104) to remove the net costs associated with kidney acquisition.
    (2)(i) Payment for Medicare kidney acquisition costs, as set forth 
in subpart L of part 413 of this chapter, is made on a reasonable cost 
basis apart from the prospective payment rate for inpatient operating 
costs.
    (ii) IPPS payment to the hospital is adjusted in each cost 
reporting period to reflect an amount necessary to compensate the 
hospital for reasonable costs of Medicare kidney acquisition.
    (b) Costs of kidney acquisition. Kidney acquisition costs include 
costs incurred in the acquisition of a kidney from a living or a 
cadaveric donor, by the hospital or an organ procurement organization, 
as appropriate. These costs are listed in Sec.  413.402(b) of this 
chapter.
0
11. 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

[[Page 25695]]

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. The hospital's 
cancellation of the classification is effective beginning the Federal 
fiscal year that begins in the calendar year following the calendar 
year in which the cancelation request is submitted.
* * * * *
0
12. Section 412.105 is amended by adding paragraph (f)(1)(iv)(C)(3) and 
revising paragraphs (f)(1)(v)(F), (f)(1)(vii), and (f)(1)(x) to read as 
follows:


Sec.  412.105   Special treatment: Hospitals that incur indirect costs 
for graduate medical education programs.

* * * * *
    (f) * * *
    (1) * * *
    (iv) * * *
    (C) * * *
    (3) Effective for portions of cost reporting periods beginning on 
or after July 1, 2023, a hospital may qualify to receive an increase in 
its otherwise applicable FTE resident cap if the criteria specified in 
Sec.  413.79(p) of this subchapter are met.
* * * * *
    (v) * * *
    (F)(1) Subject to the provisions of paragraph (f)(1)(x) of this 
section, effective for cost reporting periods beginning on or after 
April 1, 2000, and before October 1, 2022, full-time equivalent 
residents at an urban hospital in a rural track program are included in 
the urban hospital's rolling average calculation described in paragraph 
(f)(1)(v)(B) of this section.
    (2) Subject to the provisions of paragraph (f)(1)(x) of this 
section, for cost reporting periods beginning on or after October 1, 
2022, for each rural track started, full-time equivalent residents at 
an urban hospital or rural hospital in a rural track program are 
excluded from the rolling average calculation described in paragraph 
(f)(1)(v)(B) of this section during the cost reporting periods prior to 
the beginning of the applicable hospital's cost reporting period that 
coincides with or follows the start of the sixth program year of each 
rural track.
* * * * *
    (vii)(A) If a hospital establishes a new medical residency training 
program, as defined in Sec.  413.79(l) of this subchapter, the 
hospital's full-time equivalent cap may be adjusted in accordance with 
the provisions of Sec.  413.79(e) of this subchapter.
    (B)(1) A hospital that, as of December 27, 2020, has a full-time 
equivalent cap of less than 1.0 FTE based on a cost reporting period 
beginning before October 1, 1997, that begins training residents in a 
new medical residency training program, as defined at Sec.  413.79(l) 
of this subchapter, in a cost reporting period beginning on or after 
December 27, 2020, and before December 26, 2025, may receive an 
adjustment to its full-time equivalent cap when it trains at least 1.0 
FTE in such new medical residency training program(s), to be calculated 
in accordance with Sec.  413.79(e) of this subchapter.
    (2) A hospital that has a full-time equivalent cap of no more than 
3.0 FTEs based on a cost reporting period beginning on or after October 
1, 1997, and before December 27, 2020, that begins training residents 
in a new medical residency training program, as defined at Sec.  
413.79(l) of this subchapter, in a cost reporting period beginning on 
or after December 27, 2020 and before December 26, 2025, may receive an 
adjustment to its full-time equivalent cap when it trains more than 3.0 
FTE in such new medical residency training program(s), to be calculated 
in accordance with the provisions of Sec.  413.79(e) of this 
subchapter.
* * * * *
    (x)(A) For rural track programs started in a cost reporting period 
beginning before October 1, 2022, an urban hospital that establishes a 
new residency program (as defined in Sec.  413.79(l) of this 
subchapter), or has an existing residency program, with a rural track 
(or an integrated rural track) may include in its FTE count residents 
in those rural tracks in accordance with the applicable provisions of 
Sec.  413.79(k) of this subchapter.
    (B) For cost reporting periods beginning on or after October 1, 
2022, an urban hospital or rural hospital that establishes a new 
residency program (as defined in Sec.  413.79(l) of this subchapter) 
with a rural track, or adds an additional rural track, may include in 
its FTE count residents in those rural tracks in accordance with the 
applicable provisions of Sec.  413.79(k) of this subchapter.
* * * * *
0
13. Section 412.106 is amended by--
0
a. Revising paragraph (b)(4)(i)
0
b. Removing paragraph (b(4)(ii) and redesginating paragraphs (b(4)(iii) 
and (iv) as (b(4)(ii) and (iii), respectively;
0
c. Revising paragraph (g)(1)(iii)(C)(8); and
0
d. Adding paragraph (g)(1)(iii)(C)(9).
    The revisions and addition read as follows:


Sec.  412.106   Special treatment: Hospitals that serve a 
disproportionate share of low-income patients.

* * * * *
    (b) * * *
    (4) * * *
    (i) For purposes of this computation, a patient is deemed eligible 
for Medicaid on a given day only if the patient is eligible for 
inpatient hospital services under an approved State Medicaid plan that 
includes coverage for inpatient hospital care on that day or directly 
receives inpatient hospital insurance coverage on that day under a 
waiver authorized under section 1115(a)(2) of the Act, regardless of 
whether particular items or services were covered or paid under the 
State plan or the authorized waiver.
* * * * *
    (g) * * *
    (1) * * *
    (iii) * * *
    (C) * * *
    (8) For each subsequent fiscal year, for all eligible hospitals, 
except 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 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,

[[Page 25696]]

a proxy for Medicare SSI utilization data).
* * * * *
0
14. Section 412.113 is amended by revising paragraph (d) to read as 
follows:


Sec.  412.113  Other payments.

* * * * *
    (d) Organ acquisition. Payment for organ acquisition costs as 
specified in part 413, subpart L, incurred by hospitals with approved 
transplant programs is made on a reasonable cost basis.
* * * * *
0
15. Section 412.116 is amended by revising paragraph (c) to read as 
follows:


Sec.  412.116  Method of payment.

* * * * *
    (c) Special interim payments for certain costs. For capital-related 
costs for cost-reporting periods beginning before October 1, 1991, and 
the direct costs of medical education, which are not included in 
prospective payments but are reimbursed as specified in Sec. Sec.  
413.130 and 413.85 of this chapter, respectively, interim payments are 
made subject to final cost settlement. Interim payments for capital-
related items for cost-reporting periods beginning before October 1, 
1991, and the estimated cost of approved medical education programs 
(applicable to inpatient costs payable under Medicare Part A and for 
kidney acquisition costs in hospitals with approved kidney transplant 
programs) are determined by estimating the reimbursable amount for the 
year based on the previous year's experience and on substantiated 
information for the current year and divided into 26 equal biweekly 
payments. Each payment is made 2 weeks after the end of a biweekly 
period of services, as described in Sec.  413.64(h)(5) of this 
subchapter. The interim payments are reviewed by the intermediary at 
least twice during the reporting period and adjusted if necessary.
* * * * *


Sec.  412.140   [Amended]

0
16. 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
17. 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
18. 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
19. 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
20. 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
21. 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://www.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://www.qualitynet.cms.gov)''.


Sec.  412.167   [Amended]

0
22. Section 412.167 is amended in paragraph (b)(5) by removing 
``QualityNet System Administrator'' and adding in its place 
``QualityNet security official''.
0
23. 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 will calculate a measure rate for all measures selected 
under Sec.  412.164(a) for fiscal year 2022 but will only apply 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 will calculate 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 will 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 will award 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
24. 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.
* * * * *

[[Page 25697]]

0
25. 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.
* * * * *

PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR 
END-STAGE RENAL DISEASE SERVICES; OPTIONAL PROSPECTIVELY DETERMINED 
PAYMENT RATES FOR SKILLED NURSING FACILITIES

0
26. 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
27. Section 413.1 is amended by revising the paragraphs (a)(2)(v) and 
(d)(2)(i) to read as follows:


Sec.  413.1   Introduction.

    (a) * * *
    (2) * * *
    (v) Organ procurement organizations (OPOs) and histocompatibility 
laboratories.
* * * * *
    (d) * * *
    (2) * * *
    (i) Payment for the following is described in Sec.  412.113 of this 
chapter:
    (A) Capital related costs for cost reporting periods beginning 
before October 1991.
    (B) Medical education costs.
    (C) Organ acquisition costs as specified in part 413, subpart L.
    (D) The costs of certain anesthesia services.
* * * * *
0
28. 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
29. 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.
* * * * *
0
30. Section 413.40 is amended by revising paragraph (a)(3) to read as 
follows:


Sec.  413.40   Ceiling on the rate of increase in hospital inpatient 
costs.

    (a) * * *
    (3) Net inpatient operating costs include the costs of certain 
preadmission services as specified in paragraph (c)(2) of this section, 
the costs of routine services, ancillary services, and intensive care 
services (as defined in Sec.  413.53(b)) incurred by a hospital in 
furnishing covered inpatient services to Medicare beneficiaries. Net 
inpatient operating costs exclude capital-related costs as described in 
Sec.  413.130, the costs of approved medical education programs as 
described in Sec. Sec.  413.75 through 413.83 and 413.85, and organ 
acquisition costs as specified in subpart L of this part incurred by 
approved transplant programs. These costs are identified and excluded 
from inpatient operating costs before the application of the ceiling.
* * * * *


Sec.  413.75   [Amended]

0
31. Section 413.75 is amended in paragraph (b), in the definition of 
``Rural track FTE limitation'', by removing the phrase ``urban hospital 
may include in its'' and adding in its place the phrase ``urban 
hospital or rural hospital may include in its''.
0
32. Section 413.77 is amended by revising paragraph (e)(1)(iii) and 
adding paragraphs (e)(1)(iv) and (v) to read as follows:


Sec.  413.77   Direct GME payments: Determination of per resident 
amounts.

* * * * *
    (e) * * *
    (1) * * *
    (iii) If, under paragraph (e)(1)(ii)(A) or paragraph (B) or 
(e)(iv)(B) of this section, there are fewer than three existing 
teaching hospitals with per resident amounts that can be used to 
calculate the weighted mean value per resident amount, for base periods 
beginning on or after October 1, 1997, the per resident amount equals 
the updated weighted mean value of per resident amounts of all 
hospitals located in the same census region as that term is used in 
subpart D of part 412 of this subchapter.
    (iv) A hospital that, as of December 27, 2020, has a per resident 
amount based on less than 1.0 FTE in any cost reporting period 
beginning before October 1, 1997, would receive a recalculated per 
resident amount when it trains at least 1.0 FTE in such program(s) for 
any cost reporting period beginning between December 27, 2020, and 
December 26, 2025. A hospital that, as of December 27, 2020, has a per 
resident amount based on no more than 3.0 FTEs in any cost reporting 
period beginning on or after October 1, 1997, and before December 27, 
2020, would receive a recalculated per resident amount when it trains 
more than 3.0 FTEs in such program(s) for any cost reporting period 
beginning between December 27, 2020 and December 26, 2025. The 
recalculated per resident amount is based on the lower of--
    (A) The hospital's actual cost per resident incurred in connection 
with the GME program(s) based on the cost and resident data from the 
hospital's base year cost reporting period, which is, for hospitals 
with previously less than 1.0

[[Page 25698]]

FTE, the cost reporting period beginning on or after December 27, 2020, 
and before December 25, 2025, in which it trains at least 1.0 FTE; and 
for hospitals with previously less than or equal to 3.0 FTEs, the cost 
reporting period beginning on or after December 27, 2020, and before 
December 27, 2025, in which it trains more than 3.0 FTEs; or
    (B) The updated weighted mean value of per resident amounts of all 
hospitals located in the same geographic wage area is calculated using 
all per resident amounts (including primary care and obstetrics and 
gynecology and nonprimary care) and FTE resident counts from the most 
recently settled cost reports of those teaching hospitals.
    (v) Effective for a cost reporting periods beginning on or after 
December 27, 2020, a per resident amount would be established if a 
hospital trains less than 1.0 FTE resident and this training results 
from the hospital's participation in a Medicare GME affiliation 
agreement under Sec.  413.79(f). Effective for a cost reporting period 
beginning on or after December 27, 2020, a per resident amount would 
only be established when the hospital trains at least 1.0 FTE and does 
not participate in a Medicare GME affiliation agreement under Sec.  
413.79(f) for that training.
* * * * *
0
32. Section 413.78 is amended by revising paragraph (b) to read as 
follows:


Sec.  413.78   Direct GME payments: Determination of the total number 
of FTE residents.

* * * * *
    (b)(1) No individual resident may be counted as more than one FTE 
based on the total time spent in training at all sites. A hospital 
cannot claim the time spent by residents training at another hospital, 
except as provided in paragraph (i) of this section. Except as provided 
in paragraphs (c), (d), and (e) of this section, if a resident spends 
time in more than one hospital or in a non-provider setting, the 
resident counts as partial FTE based on the proportion of time worked 
at the hospital to the total time worked. A part-time resident counts 
as a partial FTE based on the proportion of allowable time worked 
compared to the total time necessary to fill a full-time internship or 
residency slot.
    (2) Effective for a cost reporting period beginning on or after 
December 27, 2020, a hospital must report FTE residents on its Medicare 
cost report for a cost reporting period if it does not participate in a 
Medicare GME affiliation agreement (as defined under Sec.  413.75(b), 
and the hospital trains at least 1.0 FTE in an approved program or 
programs, or, if the hospital trains less than 1.0 FTE residents in an 
approved program or programs and this training results from the 
hospital's participation in a Medicare GME affiliation agreement (as 
defined under Sec.  413.75(b)).
* * * * *
0
34. Section 413.79 is amended by--
0
a. Revising paragraph (c)(2) introductory text;
0
b. Adding paragraph (c)(7);
0
c. Revising paragraph (d)(7);
0
d. Adding paragraphs (e)(1)(vi), (e)(6), and (f)(8);
0
e. Revising paragraphs (k) introductory text, (k)(1), (k)(2) 
introductory text, (k)(2)(i), and (k)(3);
0
f. Adding paragraph (k)(4)(i)(C);
0
g. Revising paragraph (k)(4)(ii) introductory text;
0
h. Adding (k)(4)(ii)(C);
0
i. In paragraph (k)(5)(i), removing the phrase ``An urban hospital may 
not include in its rural track FTE limitation or (assuming the urban 
hospital's FTE'' and adding in its place the phrase ``A hospital may 
not include in its rural track FTE limitation or (assuming the 
hospital's FTE'';
0
j. In paragraph (k)(5)(ii), removing the phrase ``The hospital'' and 
adding in its place the phrase ``Each hospital''; and
0
k. Adding paragraphs (k)(5)(iv) and (p).
    The revisions and additions read as follows:


Sec.  413.79   Direct GME payments: Determination of the weighted 
number of FTE residents.

* * * * *
    (c) * * *
    (2) Determination of the FTE resident cap. Subject to the 
provisions of paragraphs (c)(3) through (6) and (m) through (p) of this 
section and Sec.  413.81, for purposes of determining direct GME 
payment--
* * * * *
    (7) Determination of an increase in the otherwise applicable 
resident cap under section 126 of Public Law 116-260. For portions of 
cost reporting periods beginning on or after July 1, 2023, a hospital 
may receive an increase in its otherwise applicable FTE resident cap 
(as determined by CMS) if the hospital meets the requirements and 
qualifying criteria under section 1886(h)(9) of the Act and if the 
hospital submits an application to CMS within the timeframe specified 
by CMS.
    (d) * * *
    (7)(i) Subject to the provisions under paragraph (k) of this 
section, effective for cost reporting periods beginning on or after 
April 1, 2000 and before cost reporting periods beginning on or after 
October 1, 2022, FTE residents in a rural track program at an urban 
hospital are included in the urban hospital's rolling average 
calculation described in this paragraph (d).
    (ii) Subject to the provisions under paragraph (k) of this section, 
effective for rural track programs started in a cost reporting period 
beginning on or after October 1, 2022, FTE residents in a rural track 
program at an urban hospital or rural hospital are excluded from 
rolling average calculation described in this paragraph (d) during the 
cost reporting periods prior to the beginning of the applicable 
hospital's cost reporting period that coincides with or follows the 
start of the sixth program year of each rural track.
    (e) * * *
    (1) * * *
    (vi) In the case of a hospital that, as of December 27, 2020, has a 
FTE cap based on the training of less than 1.0 FTE in any cost 
reporting period beginning before October 1, 1997; or no more than 3.0 
FTEs based on a cost reporting period beginning on or after October 1, 
1997, and before December 27, 2020, if such a hospital begins training 
residents in a new approved program (as defined under Sec.  413.79(l)) 
in a program year beginning on or after December 27, 2020 and before 
December 26, 2025, such hospital with a previous FTE cap of less than 
1.0 FTE may receive a recalculated FTE cap when it begins to train at 
least 1.0 FTE in such new program(s); and such hospital with a previous 
FTE cap of no more than 3.0 FTEs may receive a recalculated FTE cap 
when it begins to train more than 3.0 FTEs in such new program(s). The 
recalculated FTE cap is equal to the sum of the products of three 
factors (limited to the number of accredited slots for each program):
    (A) The highest total number of FTE residents trained in any 
program year during the fifth year of the first new program's existence 
started in a program year beginning on or after December 27, 2020 and 
before December 26, 2025, at all of the hospitals to which the 
residents in the program rotate;
    (B) The number of years in which residents are expected to complete 
the program, based on the minimum accredited length for each type of 
program.
    (C) The ratio of the number of FTE residents in the new program 
that trained at the hospital over the entire 5-year period to the total 
number of FTE residents that trained at all hospitals over the entire 
5-year period.
* * * * *
    (6) Effective for a cost reporting period beginning on or after 
December

[[Page 25699]]

27, 2020, FTE resident caps are established when the hospital trains 
1.0 or more FTE residents in a new medical residency program (as 
defined under Sec.  413.79(l) of this subchapter).
    (f) * * *
    (8) FTE resident cap slots added under section 126 of Pub. L. 116-
260 may be used in a Medicare GME affiliation agreement beginning in 
the fifth year after the effective date of those FTE resident cap 
slots.
* * * * *
    (k) Residents training in rural track programs. Subject to the 
provisions of Sec.  413.81, an urban hospital that establishes a new 
residency program, or has an existing residency program, with a rural 
track (or an integrated rural track) may include in its FTE count 
residents in those rural tracks, in addition to the residents subject 
to its FTE cap specified under paragraph (c) of this section. An urban 
hospital (or, effective for a cost reporting period beginning on or 
after October 1, 2022, a rural hospital) with a rural track residency 
program may count residents in those rural tracks up to a rural track 
FTE limitation if the hospital complies with the conditions specified 
in paragraphs (k)(2) through (7) of this section.
    (1) If an urban hospital rotates residents to a separately 
accredited rural track program at a rural hospital(s) for two-thirds of 
the duration of the program for cost reporting periods beginning on or 
after April 1, 2000, and before October 1, 2003, or for more than one-
half of the duration of the program for cost reporting periods 
beginning on or after October 1, 2003, and before October 1, 2022, the 
urban hospital may include those residents in its FTE count for the 
time the rural track residents spend at the urban hospital, not to 
exceed its rural track FTE limitation. For cost reporting periods 
beginning on or after October 1, 2022, if an urban hospital rotates 
residents to a rural track program at a rural hospital(s) for more than 
one-half of the duration of the program, both the urban and the rural 
hospital may include those residents in their FTE counts for the time 
the rural track residents spend at the urban and rural hospital, 
respectively, not to exceed their rural track FTE limitations. The 
rural track FTE limitation is determined as follows:
    (i) For rural track programs started prior to October 1, 2012, for 
the first 3 years of the rural track's existence, the rural track FTE 
limitation for each urban hospital will be the actual number of FTE 
residents, subject to the rolling average at paragraph (d)(7) of this 
section, training in the rural track at the urban hospital. For rural 
track programs started on or after October 1, 2012, and before October 
1, 2022, prior to the start of the urban hospital's cost reporting 
period that coincides with or follows the start of the sixth program 
year of the rural track's existence, the rural track FTE limitation for 
each urban hospital will be the actual number of FTE residents, subject 
to the rolling average at paragraph (d)(7) of this section, training in 
the rural track at the urban hospital. For rural track programs started 
in a cost reporting period on or after October 1, 2022, before the 
start of the urban or rural hospital's cost reporting period that 
coincides with or follows the start of the sixth program year of the 
rural track's existence, the rural track FTE limitation for each 
hospital will be the actual number of FTE residents training in the 
rural track at the urban or rural hospital.
    (ii) For rural track programs started prior to October 1, 2012, 
beginning with the fourth year of the rural track's existence, the 
rural track FTE limitation is equal to the product of the highest 
number of residents, in any program year, who during the third year of 
the rural track's existence are training in the rural track at the 
urban hospital and are designated at the beginning of their training to 
be rotated to the rural hospital(s) for at least two-thirds of the 
duration of the program for cost reporting periods beginning on or 
after April 1, 2000, and before October 1, 2003, or for more than one-
half of the duration of the program for cost reporting periods 
beginning on or after October 1, 2003, and the number of years those 
residents are training at the urban hospital. For rural track programs 
started on or after October 1, 2012 and before October 1, 2022, 
beginning with the start of the urban hospital's cost reporting period 
that coincides with or follows the start of the sixth program year of 
the rural track's existence, the rural track FTE limitation is 
calculated in accordance with paragraph (e)(1) of this section. For 
rural track programs started on or after October 1, 2022, beginning 
with the start of the urban or rural hospital's cost reporting period 
that coincides with or follows the start of the sixth program year of 
the rural track's existence, the rural track FTE limitation is 
calculated in accordance with paragraph (e)(1) of this section.
    (2) If an urban hospital rotates residents to a separately 
accredited rural track program at a rural nonprovider site(s) for two-
thirds of the duration of the program for cost reporting periods 
beginning on or after April 1, 2000, and before October 1, 2003, or for 
more than one-half of the duration of the program for cost reporting 
periods beginning on or after October 1, 2003, the urban hospital may 
include those residents in its FTE count, subject to the requirements 
under Sec.  413.78(d) through (g). For cost reporting periods beginning 
on or after October 1, 2022, if an urban or rural hospital rotates 
residents to a rural track program at a rural nonprovider site for more 
than one-half of the duration of the program, the urban or rural 
hospital may include those residents in its FTE count, subject to which 
hospital meets the requirements under Sec.  413.78(g), not to exceed 
their rural track FTE limitations. The rural track FTE limitation is 
determined as follows:
    (i) For rural track programs started prior to October 1, 2012, for 
the first 3 years of the rural track's existence, the rural track FTE 
limitation for each urban hospital will be the actual number of FTE 
residents, subject to the rolling average specified in paragraph (d)(7) 
of this section, training in the rural track at the urban hospital and 
the rural nonprovider site(s). For rural track programs started on or 
after October 1, 2012, and before October 1, 2022, prior to the start 
of the urban hospital's cost reporting period that coincides with or 
follows the start of the sixth program year of the rural track's 
existence, the rural track FTE limitation for each urban hospital will 
be the actual number of FTE residents, subject to the rolling average 
specified in paragraph (d)(7) of this section, training in the rural 
track at the urban hospital and the rural nonprovider site(s). For 
rural track programs started in a cost reporting period on or after 
October 1, 2022, prior to the start of the urban or rural hospital's 
cost reporting period that coincides with or follows the start of the 
sixth program year of the rural track's existence, the rural track FTE 
limitation for each hospital will be the actual number of FTE residents 
training in the rural track at the hospital and the rural nonprovider 
site(s).
* * * * *
    (3) For rural track programs started prior to October 1, 2012, if 
an urban hospital rotates residents in the rural track program to a 
rural hospital(s) for less than two-thirds of the duration of the 
program for cost reporting periods beginning on or after April 1, 2000, 
and before October 1, 2003, or for one-half or less than one-half of 
the duration of the program for cost reporting periods beginning on or 
after October 1, 2003, the rural hospital may not include those 
residents in its FTE count (unless the rural track is a new program 
under

[[Page 25700]]

paragraph (e)(3) of this section, or the rural hospital's FTE count 
does not exceed that hospital's FTE cap), nor may the urban hospital 
include those residents when calculating its rural track FTE 
limitation. For rural track programs started on or after October 1, 
2012, if an urban hospital rotates residents in the rural track program 
to a rural hospital(s) for one-half or less than one-half of the 
duration of the program, the rural hospital may not include those 
residents in its FTE count (unless the rural track is a new program 
under paragraph (e)(3) of this section, or the rural hospital's FTE 
count does not exceed that hospital's FTE cap), nor may the urban 
hospital include those residents when calculating its rural track FTE 
limitation. For rural track programs started in a cost reporting period 
beginning on or after October 1, 2022, if less than or equal to 50 
percent of the duration of the training program occurs in a rural area, 
neither the urban or rural hospital may receive a rural track FTE 
limitation.
    (4) * * *
    (i) * * *
    (C) For rural track programs started in a cost reporting period 
beginning on or after October 1, 2022, if less than or equal to 50 
percent of the duration of the training program occurs in a rural area, 
neither the urban or rural hospital may receive a rural track FTE 
limitation.
    (ii) For rural track programs started on or after October 1, 2012 
and prior to October 1, 2022, if an urban hospital rotates residents in 
the rural track program to a rural nonprovider site(s) for one-half or 
less than one-half of the duration of the program, the urban hospital 
may include those residents in its FTE count, subject to the 
requirements under Sec.  413.78(g). The urban hospital may include in 
its FTE count those residents in the rural track, not to exceed its 
rural track limitation, determined as follows:
* * * * *
    (C) For rural track programs started in a cost reporting period 
beginning on or after October 1, 2022, if less than or equal to 50 
percent of the duration of the training program occurs in a rural area, 
neither the urban or rural hospital may receive a rural track FTE 
limitation.
    (5) * * *
    (iv) Effective for cost reporting periods beginning on or after 
October 1, 2022, in order for an urban or rural hospital to receive a 
rural track FTE limitation, greater than 50 percent of the rural track 
program must occur in a rural area.
* * * * *
    (p) Determination of an increase in the otherwise applicable 
resident cap under section 126 of the Consolidated Appropriations Act 
(Pub. L. 116-260). For portions of cost reporting periods beginning on 
or after July 1, 2023, a hospital may receive an increase in its 
otherwise applicable FTE resident cap (as determined by CMS) if the 
hospital meets the requirements and qualifying criteria under section 
1886(h)(9) of the Act and if the hospital submits an application to CMS 
within the timeframe specified by CMS.

Subpart H--Payment for End-Stage Renal Disease (ESRD) Services

0
35. The subpart heading for Subpart H is revised to read as set forth 
above.


Sec.  Sec.  413.200  through 413.203 [Removed and Reserved]

0
36. Sections 413.200 through 413.203 are removed and reserved.
0
37. Subpart L is added to read as follows:
Subpart L--Payment of Organ Acquisition Costs to Transplant Hospitals 
and Organ Procurement Organizations
Sec.
413.400 Definitions.
413.402 Organ acquisition costs.
413.404 Standard acquisition charge.
413.406 Acquisition of pancreata for islet cell transplant.
413.408 Counting of organs for transplant hospitals/hospital-based 
organ procurement organizations and calculation of Medicare's share 
of organ acquisition costs.
413.410 Counting of kidneys for independent organ procurement 
organizations and calculation of Medicare's share of kidney 
acquisition costs.
413.412 Intent to transplant, and counting en bloc, research, and 
discarded organs.
413.414 Medicare secondary payer and organ acquisition costs.
413.416 Organ acquisition charges for kidney-paired exchanges.
413.418 Donor community hospitals' charges to organ procurement 
organizations for organ acquisition costs.
413.420 Payment to independent organ procurement organizations and 
histocompatibility laboratories for kidney acquisition costs.

Subpart L--Payment of Organ Acquisition Costs to Transplant 
Hospitals and Organ Procurement Organizations


Sec.  413.400   Definitions.

    As used in this subpart:
    Histocompatibility laboratory means a laboratory meeting the 
requirements set forth in Sec.  493.1227 of this chapter and providing 
the services for the acquisition of kidneys or other organs for 
transplantation.
    Hospital-based organ procurement organization (HOPO) means an organ 
procurement organization that is considered a department of the 
transplant hospital and reports organ acquisition costs it incurs on 
the transplant hospital's Medicare cost report.
    Independent organ procurement organization (IOPO) means an organ 
procurement organization that files a Medicare cost report separate 
from a hospital and meets all of the following:
    (1) Is not subject to the control of a hospital with respect to the 
hiring, firing, training, and paying of employees.
    (2) Is not considered as a department of a hospital for insurance 
purposes (including malpractice insurance, general liability insurance, 
worker's compensation insurance, and employee retirement insurance).
    (3) Reports organ acquisition costs it incurs on the IOPO Medicare 
cost report.
    Organ, for organ acquisition payment purposes, means:
    (1) A human kidney, liver, heart, lung, pancreas, or intestine (or 
multivisceral organs when transplanted at the same time as an 
intestine).
    (2) Pancreata procured on or after October 1, 2004 for the purpose 
of acquiring pancreatic islet cells for transplantation into 
individuals who are participating in a National Institute of Diabetes 
and Digestive and Kidney Diseases clinical trial.
    Organ procurement organization (OPO) means an organization defined 
in Sec.  486.302 of this chapter. OPOs can be independent or hospital 
based.
    Standard acquisition charge (SAC) means a charge as defined in 
Sec.  413.404 of this chapter.
    Transplant hospital means a hospital that furnishes organ 
transplants and other medical and surgical specialty services required 
for the care of transplant patients.
    Transplant hospital/HOPO (TH/HOPO) refers to a transplant hospital, 
or a transplant hospital that operates a HOPO (as previously defined in 
this section) and performs organ procurement activities as one entity 
reported on the transplant hospital's Medicare cost report.
    Transplant program means an organ-specific transplant program 
within a transplant hospital (as defined in this section).


Sec.  413.402   Organ acquisition costs.

    (a) Costs related to organ acquisition. Costs recognized in 
paragraph (b) of this section are costs incurred in the acquisition of 
organs from a living donor or a cadaveric donor, by the hospital or an 
organ procurement organization, as appropriate.

[[Page 25701]]

    (b) Types of costs. Organ acquisition costs are as follows:
    (1) Tissue typing, including tissue typing furnished by independent 
laboratories.
    (2) Donor and beneficiary evaluation.
    (3) Other costs associated with excising organs, such as general 
routine and special care services provided to the donor.
    (4) Operating room and other inpatient ancillary services 
applicable to the donor.
    (5) Preservation and perfusion costs.
    (6) Organ Procurement and Transplantation Network registration 
fees.
    (7) Surgeons' fees for excising cadaveric organs (currently limited 
to $1,250 for kidneys).
    (8) Transportation of the excised organ to the transplant hospital.
    (9) Costs of organs acquired from other hospitals or organ 
procurement organizations.
    (10) Hospital costs normally classified as outpatient costs 
applicable to organ excisions (services include donor and recipient 
tissue typing, work-up, and related services furnished prior to 
inpatient admission).
    (11) Costs of services applicable to organ excisions which are 
rendered by residents and interns not in approved teaching programs.
    (12) All pre-admission services applicable to organ excisions, such 
as laboratory, electroencephalography, surgeons' fees for cadaveric 
excisions, and the costs of physicians' services.
    (c) Living kidney donor complications. (1) Living kidney donor 
complications related to the surgery to remove a kidney, which occur 
after the date of discharge, are not considered kidney acquisition 
costs.
    (2) Medicare covers costs incurred for living kidney donor 
complications only if they are directly attributable to a kidney 
donation for transplant into a Medicare beneficiary.
    (3) Living kidney donor complications are paid under Medicare Part 
A or Part B, as applicable to the services provided, with no donor 
liability for deductibles or coinsurance. Living kidney donor 
complications are billed under the Medicare Beneficiary Identifier of 
the transplant recipient.


Sec.  413.404   Standard acquisition charge.

    (a) General. (1) Procuring an organ is not a covered service when 
performed independent of a Medicare covered transplant, however, the 
reasonable costs to procure an organ are reimbursable when billed in 
connection with a Medicare covered transplant.
    (2) The SAC represents the average of the total actual costs 
associated with procuring either cadaveric donor organs or living donor 
organs, by organ type.
    (3) When a TH/HOPO or IOPO provides an organ to another transplant 
hospital or OPO, it bills its SAC to the transplant hospital, TH/HOPO 
or IOPO receiving the organ.
    (b) THs/HOPOs SACs. (1) A TH/HOPO must develop a SAC for each organ 
type (for example heart, liver, or lung).
    (2) When a TH/HOPO provides an organ to another transplant hospital 
or OPO, it must bill the receiving transplant hospital or OPO its SAC 
by organ type, or the hospital's standard departmental charges that are 
reduced to cost.
    (3) A transplant hospital must establish SACs for living donor 
organs. A TH/HOPO must establish SACs for cadaveric donor organs.
    (i) Living donor SAC for transplant hospitals--(A) Definition. The 
living donor SAC is an average cost that a transplant hospital incurs 
to procure an organ from a living donor.
    (B) Establishment of living donor SAC. A transplant hospital must 
establish a living donor SAC (living SAC) before the transplant 
hospital bills its first living donor transplant to Medicare.
    (C) Calculating the living donor SAC--(1) Initial living donor SAC. 
A transplant hospital calculates its initial living SAC for each living 
organ type as follows:
    (i) By estimating the reasonable and necessary costs they expect to 
incur for services furnished to living donors, and pre-admission 
services furnished to recipients of living donor organs during the 
hospital's cost reporting period.
    (ii) Dividing the estimated amount described in paragraph 
(b)(3)(i)(C)(1)(i) of this paragraph by the projected number of usable 
living donor organs to be procured by the transplant hospital during 
the transplant hospital's cost reporting period.
    (2) Subsequent living donor SAC. A transplant hospital calculates 
its subsequent living donor SAC for each living organ type as follows:
    (i) By using the transplant hospital's actual organ acquisition 
costs for the living donor organ type from the prior year's Medicare 
cost report, adjusted for any changes in the current year.
    (ii) Dividing the costs in paragraph (b)(3)(i)(C)(2)(i) of this 
section by the actual number of usable living organs procured by the 
transplant hospital during that prior cost reporting period.
    (D) Costs used to develop the living donor SAC. Costs that may be 
used to develop the living donor SAC include, but are not limited to 
the following:
    (1) Costs of tissue typing services, including those furnished by 
independent laboratories.
    (2) Costs of physician pre-admission transplant evaluation 
services.
    (3) Organ Procurement and Transplantation Network registration 
fees.
    (4) Costs for donor and recipient evaluation and workup furnished 
prior to admission for transplantation.
    (5) Other costs associated with procurement, for example, general 
routine and special care services related to the donor.
    (6) Costs of operating room and other inpatient ancillary services 
related to the donor.
    (7) Preservation and perfusion costs.
    (8) Transportation costs of the excised organ.
    (ii) Cadaveric donor SAC for THs/HOPOs--(A) Definition. The 
cadaveric donor SAC is an average cost that a TH/HOPO incurs to procure 
a cadaveric donor organ.
    (B) Calculating the cadaveric SAC--(1) Initial cadaveric donor SAC. 
A TH/HOPO calculates its initial cadaveric SAC for each cadaveric organ 
type as follows:
    (i) By estimating the reasonable and necessary costs they expect to 
incur to procure cadaveric organs, combined with the expected costs of 
acquiring cadaveric organs from OPOs or other transplant hospitals.
    (ii) Dividing the estimated amount described in paragraph 
(b)(3)(ii)(B)(1)(i) of this section by the projected number of usable 
cadaveric organs to be procured by the TH/HOPO within the transplant 
hospital's cost reporting period.
    (2) Subsequent cadaveric donor SAC. A TH/HOPO calculates its 
subsequent cadaveric donor SAC for each cadaveric organ type as 
follows:
    (i) By using the transplant hospital's actual organ acquisition 
costs for the cadaveric donor organ type from the prior year's Medicare 
cost report, adjusted for any changes in the current year.
    (ii) Dividing the costs in paragraph (b)(3)(ii)(B)(2)(i) of this 
section by the actual number of usable cadaveric organs procured by the 
TH/HOPO during that prior cost reporting period.
    (C) Costs to develop the cadaveric donor SAC. Costs that may be 
used to develop the cadaveric donor SAC include, but are not limited to 
the following:
    (1) Costs of organs acquired from other transplant hospitals or 
OPOs.
    (2) Costs of transportation of the excised organs.

[[Page 25702]]

    (3) Surgeons' fees for excising cadaveric organs (currently limited 
to $1,250 for kidneys).
    (4) Costs of tissue typing services, including those furnished by 
independent laboratories.
    (5) Preservation and perfusion costs.
    (6) General routine and special care service costs.
    (7) Operating room and other inpatient ancillary service costs.
    (c) Independent OPO SACs--(1) Non-renal SAC. An IOPO establishes 
non-renal SACs based on its costs of procuring non-renal organs for 
each organ type, by--
    (i) Estimating the reasonable and necessary costs it expects to 
incur for services furnished to procure cadaveric donor non-renal 
organs during the IOPO's cost reporting period; and
    (ii) Dividing the amount estimated in paragraph (c)(1)(i) of this 
section by the projected number of cadaveric donor non-renal organs the 
IOPO expects to procure within its cost reporting period.
    (2) Kidney SAC. (i) An IOPO's Medicare contractor establishes the 
kidney SAC based on an estimate of the reasonable and necessary costs 
the IOPO expects to incur to procure cadaveric kidneys during the 
IOPO's cost reporting period, divided by the projected number of usable 
cadaveric kidneys the IOPO expects to procure.
    (ii) The Medicare contractor develops the IOPO's initial kidney SAC 
based on the IOPO's budget information.
    (iii) The kidney SAC for subsequent years is computed using the 
IOPO's costs related to kidney acquisition that were incurred in the 
prior cost reporting period and dividing those costs by the number of 
usable cadaveric kidneys procured during that cost reporting period. 
These SACs are the basis for the interim payments by the transplant 
hospital to the IOPO, as set forth in Sec.  413.420(d).
    (iv) The IOPO's Medicare contractor may adjust the kidney SAC 
during the year, if necessary, for cost changes.
    (v) The IOPO cannot use or change its kidney SAC without the 
contractor's approval.
    (3) Billing SACs for organs generally. The IOPO uses its own organ 
SAC and not the SAC it paid to another IOPO when billing a transplant 
hospital receiving the organ. When an IOPO receives an organ from 
another IOPO, the receiving IOPO is responsible for paying the 
procuring IOPO's SAC.


Sec.  413.406   Acquisition of pancreata for islet cell transplant.

    (a) Medicare only covers and pays for reasonable costs of 
acquisition of pancreata for islet cell transplants into Medicare 
beneficiaries participating in a National Institute of Diabetes and 
Digestive and Kidney Diseases clinical trial of islet cell 
transplantation.
    (b) Pancreata procured for covered islet cell transplants must be 
assigned a full standard acquisition charge and be treated as solid 
organs for procurement purposes.


Sec.  413.408  Counting of organs for transplant hospitals/hospital-
based organ procurement organizations and calculation of Medicare's 
share of organ acquisition costs.

    (a) Counting and reporting of Medicare usable organs. THs/HOPOs, 
must accurately count and report the Medicare usable organs and total 
usable organs on their Medicare hospital cost reports to ensure that 
costs to acquire Medicare usable organs are accurately allocated to 
Medicare.
    (b) Medicare usable organs. For cost reporting periods beginning on 
or after October 1, 2021, for THs/HOPOs, Medicare usable organs include 
only the following:
    (1) Organs transplanted into Medicare beneficiaries (including 
kidneys for Medicare Advantage beneficiaries for dates of service on or 
after January 1, 2021).
    (2) Organs for which Medicare has a secondary payer liability for 
the organ transplant.
    (3) Pancreata procured for the purpose of acquiring pancreatic 
islet cells acquired for transplantation for Medicare beneficiaries 
participating in a National Institute of Diabetes and Digestive and 
Kidney Diseases clinical trial.
    (c) Total usable organs. For cost reporting periods beginning on or 
after October 1, 2021, for THs/HOPOs, total usable organs include all 
of the following:
    (1) Medicare usable organs.
    (2) Organs excised with the intention to be used for research.
    (3) Organs excised and either transplanted or furnished to other 
transplant hospitals or OPOs.
    (4) Organs obtained from another OPO or transplant hospital and 
either transplanted or furnished to other transplant hospitals or OPOs.
    (5) Organs sent to veterans' hospitals or organs sent outside the 
United States.
    (6) Organs transplanted into non-Medicare beneficiaries.
    (7) Organs for which the transplant was totally or partially paid 
by primary insurance other than Medicare.
    (8) Organs for which the transplant was covered by a Medicare 
Advantage plan for dates of service prior to January 1, 2021.
    (9) Kidneys sent to United States MRTCs with or without contractor-
approved a reciprocal sharing agreement with the HOPO in effect prior 
to March 3, 1988.
    (10) Pancreata procured for the purpose of acquiring pancreatic 
islet cells for transplantation into participants in a National 
Institute of Diabetes and Digestive and Kidney Diseases clinical trial.
    (d) TH/HOPO's total costs exclude procurement costs of organs sent 
to foreign transplant centers and organs transplanted into non-Medicare 
beneficiaries. A TH/HOPO's total costs for all organs are reduced by 
the costs associated with procuring organs sent to foreign transplant 
centers or transplanted in patients other than Medicare beneficiaries. 
THs/HOPOs must separate costs for procuring organs that are sent to 
foreign transplant centers and organs transplanted in patients other 
than Medicare beneficiaries from Medicare allowable costs prior to 
final cost settlement by the Medicare contractors. The separation of 
cost is achieved using the Medicare ratio set forth in Sec.  
413.408(e).
    (e) Calculation of Medicare's share of organ acquisition costs. For 
cost reporting periods beginning on or after October 1, 2021, 
Medicare's share of organ acquisition costs for a TH/HOPO is calculated 
by multiplying the total allowable organ acquisition costs by the ratio 
of Medicare usable organs (as specified in Sec.  413.408(b)), to total 
usable organs (as specified in Sec.  413.408(c)).


Sec.  413.410   Counting of kidneys for independent organ procurement 
organizations and calculation of Medicare's share of kidney acquisition 
costs.

    (a) Counting and reporting of the number of usable kidneys. IOPOs 
must accurately count and report Medicare usable kidneys and total 
usable kidneys on their Medicare OPO cost reports to ensure that costs 
to acquire Medicare usable kidneys are accurately allocated to 
Medicare.
    (b) Medicare usable kidneys. For cost reporting periods beginning 
on or after October 1, 2021, for IOPOs, Medicare usable kidneys include 
only kidneys sent to transplant hospitals, HOPOs and other IOPOs that 
are transplanted into Medicare beneficiaries.
    (c) Total usable kidneys. For cost reporting periods beginning on 
or after October 1, 2021, for IOPOs, total usable kidneys include all 
of the following:
    (1) Medicare usable kidneys.
    (2) Kidneys procured with the intention to be used for research.
    (3) Kidneys procured and furnished to other transplant hospitals or 
OPOs.

[[Page 25703]]

    (4) Kidneys procured from another OPO or transplant hospital and 
either transplanted or furnished to other transplant hospitals or OPOs.
    (5) Kidneys sent to veterans' hospitals or organs sent outside the 
United States.
    (6) Kidneys for which the transplant was covered by a Medicare 
Advantage plan for dates of service prior to January 1, 2021.
    (7) Kidneys sent to United States MRTCs with or without a 
contractor-approved reciprocal sharing agreement with the IOPO in 
effect prior to March 3, 1988.
    (d) IOPO's total costs exclude procurement costs of kidneys sent to 
foreign transplant centers and organs transplanted into non-Medicare 
beneficiaries. (1) An IOPO's total costs for all kidneys is reduced by 
the costs associated with procuring kidneys that are sent to foreign 
transplant centers or transplanted in patients other than Medicare 
beneficiaries.
    (2) IOPOs must separate costs for procuring kidneys that are sent 
to foreign transplant centers and kidneys transplanted in patients 
other than Medicare beneficiaries from Medicare allowable costs prior 
to final settlement by the Medicare contractors. The separation of cost 
is achieved using the Medicare ratio set forth in Sec.  413.410(e).
    (e) Calculation of Medicare's share of kidney acquisition costs. 
For cost reporting periods beginning on or after October 1, 2021, 
Medicare's share of kidney acquisition costs for an IOPO is calculated 
by multiplying the total allowable kidney acquisition costs by the 
ratio of Medicare usable kidneys, as specified in Sec.  413.410(b), to 
total kidneys, as specified in Sec.  413.410(c).


Sec.  413.412   Intent to transplant, and counting en bloc, research, 
and discarded organs.

    (a) Principle of intent to transplant. (1) For organ acquisition 
payment purposes, an organ is intended for transplant when the OPO or 
transplant hospital designates it for transplant prior to the time the 
donor enters the hospital's operating room for surgical excision/
recovery of the organ(s).
    (2) OPOs and transplant hospitals must identify the costs 
associated with the recovered and unrecovered organs and apportion 
those costs to the appropriate cost centers by organ type.
    (b) Counting en bloc organs. En bloc organs can be en bloc lungs or 
en bloc kidneys. For Medicare cost allocation purposes, OPOs and 
transplant hospitals count--
    (1) En bloc lungs or en bloc kidneys procured and transplanted en 
bloc (two organs transplanted as one unit) as one total usable organ. 
En bloc organs transplanted into a Medicare beneficiary count as one 
Medicare usable organ in accordance with Sec.  413.408(b) or one 
Medicare usable kidney in accordance with Sec.  413.410(b).
    (2) En bloc lungs and en bloc kidneys procured en bloc but 
separated and transplanted into two different recipients as two total 
usable organs. For each organ transplanted into a Medicare beneficiary, 
count each as one Medicare usable organ in accordance with Sec.  
413.408(b) or one Medicare usable kidney in accordance with Sec.  
413.410(b).
    (c) Counting of research organs. For Medicare cost allocation 
purposes, organs used for research are not counted as Medicare usable 
organs in Medicare's share of organ acquisition costs (except pancreata 
in accordance with Sec.  413.408(b)(3)).
    (1) OPOs and transplant hospitals--
    (i) Do not count organs designated for research activities prior to 
the time the donor entered the hospital's operating room for surgical 
removal of the organs as Medicare usable organs; and
    (ii) Count organs designated for research activities prior to the 
time the donor entered the hospital's operating room for surgical 
removal of the organs as total usable organs.
    (2) Do not count organs designated for transplant prior to the time 
the donor entered the hospital's operating room for surgical removal of 
the organs but subsequently determined to be unusable and donated to 
research, as Medicare usable organs or total usable organs.
    (d) Counting of discarded/unusable organs. An organ is not counted 
as a Medicare usable organ or a total usable organ if the excising 
surgeon determines, upon initial inspection or after removal of the 
organ, that the organ is not viable and not medically suitable for 
transplant and the organ is determined to be unusable and discarded. 
This includes organs that are determined to be unusable and 
subsequently donated to research in accordance with paragraph (c)(2) of 
this section.


Sec.  413.414   Medicare secondary payer and organ acquisition costs.

    (a) General principle. If a Medicare beneficiary has a primary 
health insurer other than Medicare and that primary health insurer has 
primary liability for the transplant and organ acquisition costs, the 
Medicare Program may share a liability for organ acquisition costs as a 
secondary payer in certain instances. To determine whether Medicare has 
liability as a secondary payer, it is necessary to review the 
transplant hospital's agreement with the primary insurer.
    (b) Medicare has no secondary payer liability for organ acquisition 
costs. If the primary insurer's agreement requires the transplant 
hospital to accept the primary insurer's payment as payment in full for 
the transplant and the associated organ acquisition costs, Medicare has 
zero liability as a secondary payer with no payment obligation for the 
transplantation costs or the organ acquisition costs, and the organ at 
issue is not a Medicare usable organ.
    (c) Medicare may have secondary payer liability for organ 
acquisition costs. When the primary insurer's agreement does not 
require the transplant hospital to accept the payment from the primary 
insurer as payment in full, and the payment the transplant hospital 
receives from the primary insurer for the transplant and organ 
acquisition costs is insufficient to cover the entire cost, Medicare 
may have a secondary payer liability for the organ acquisition costs.
    (1) To determine whether Medicare has a secondary payer liability 
for the organ acquisition costs, it is necessary for the transplant 
hospital to submit a bill to its Medicare contractor and to compare the 
total cost of the transplant, including the transplant DRG amount and 
the organ acquisition costs, to the payment received from the primary 
payer.
    (2) If the payment from the primary payer is greater than the cost 
of the transplant DRG and the organ acquisition costs, there is no 
Medicare liability and the transplant hospital must not count the organ 
as a Medicare usable organ.
    (3) If the payment from the primary payer is less than the 
transplant DRG and the organ acquisition costs, there is a Medicare 
secondary payer liability and all of the following must occur:
    (i) The transplant hospital must pro-rate the payment from the 
primary payer between the transplant DRG payment and the organ 
acquisition payment.
    (ii) The transplant hospital counts the organ as a Medicare usable 
organ.
    (iii) The portion of the payment applicable to organ acquisition is 
used on the cost report to reduce the Medicare organ acquisition costs.


Sec.  413.416   Organ acquisition charges for kidney-paired exchanges.

    (a) Initial living donor evaluations. When a recipient and donor 
elect to participate in a kidney paired exchange, the costs of the 
initial living donor evaluations are incurred by the originally 
intended recipient's

[[Page 25704]]

transplant hospital, regardless of whether the living donor actually 
donates to their originally intended recipient, a kidney paired 
exchange recipient, or does not donate at all.
    (b) Additional tests after a match. In a kidney paired exchange, 
regardless of whether an actual donation occurs, once the donor and 
recipient are matched, any additional tests requested by the 
recipient's transplant hospital and performed by the donor's transplant 
hospital, are billed to the recipient's transplant hospital as charges 
reduced to cost (using the donor's transplant hospital's cost to charge 
ratio) and included as acquisition costs on the recipient transplant 
hospital's Medicare cost report.
    (c) Procurement and transport of a kidney. When a donor's 
transplant hospital procures and sends a kidney to a recipient's 
transplant hospital all of the following are applicable:
    (1) All costs must be reasonable and necessary.
    (2)(i) The donor's transplant hospital bills the recipient's 
transplant hospital.
    (ii) The donor's transplant hospital bills its charges reduced to 
cost, or bills its applicable kidney SAC for the reasonable costs 
associated with procuring, packaging, and transporting the kidney.
    (3) The donor's transplant hospital records the costs described in 
paragraph (c)(2)(ii) of this section on its Medicare cost report as 
kidney acquisition costs and offsets any payments received from the 
recipient's transplant hospital against its kidney acquisition costs.
    (4) The recipient's transplant hospital records as part of its 
kidney acquisition costs--
    (i) The amounts billed by the donor's transplant hospital for the 
reasonable costs associated with procuring, packaging, and transporting 
the organ; and
    (ii) Any additional testing performed and billed by the donor's 
transplant hospital.
    (d) Donor's procurement occurs at recipient transplant hospital. In 
a kidney-paired exchange--
    (1) When a donor's transplant hospital does not procure a kidney, 
but the donor travels to the recipient's transplant hospital for the 
organ procurement, the reasonable costs associated with the organ 
procurement are included on the Medicare cost report of the recipient's 
transplant hospital; and
    (2) The travel expenses of the living donor are not allowable 
Medicare costs.


Sec.  413.418   Donor community hospitals' charges to organ procurement 
organizations for organ acquisition costs.

    (a) General. A donor community hospital (a Medicare-certified non-
transplant hospital) incurs organ acquisition costs for donor organ 
procurement services, authorized by the OPO following declaration of 
death and consent to donate.
    (b) Donor community hospitals. For cost reporting periods beginning 
on or after October 1, 2021, when a donor community hospital incurs 
costs for services furnished to a cadaveric donor, as authorized by the 
OPO, the donor community hospital must bill the OPO its customary 
charges that are reduced to cost by applying its most recently 
available hospital specific cost-to-charge ratio for the period in 
which the service was rendered.


Sec.  413.420   Payment to independent organ procurement organizations 
and histocompatibility laboratories for kidney acquisition costs.

    (a) Principle. (1) Covered services furnished after September 30, 
1978, by OPOs and histocompatibility laboratories in connection with 
kidney acquisition and transplantation are reimbursed under the 
principles for determining reasonable cost contained in this part.
    (2) Services furnished by IOPOs and histocompatibility 
laboratories, that have an agreement with the Secretary in accordance 
with paragraph (c) of this section, are paid directly by the transplant 
hospital using a kidney SAC (for an IOPO) or contractor-established 
rates (for a histocompatibility laboratory). (The reasonable costs of 
services furnished by HOPOs or laboratories are reimbursed in 
accordance with the principles contained in Sec. Sec.  413.60 and 
413.64.)
    (b) Definitions. Definitions relevant to this section can be found 
in Sec.  413.400 of this subpart.
    (c) Agreements with IOPOs and laboratories. (1) Any IOPO or 
histocompatibility laboratory that wishes to have the cost of its pre-
transplant services reimbursed under the Medicare program must file an 
agreement with CMS under which the IOPO or laboratory agrees to do all 
of the following:
    (i) To file a cost report in accordance with Sec.  413.24(f) within 
5 months following the close of the period covered by the report.
    (ii) To permit CMS to designate a contractor to determine the 
interim reimbursement rate payable by the transplant hospitals for 
services provided by the IOPO or laboratory and to make a determination 
of reasonable cost based upon the cost report filed by the IOPO or 
laboratory.
    (iii) To provide such budget or cost projection information as may 
be required to establish an initial interim reimbursement rate.
    (iv) To pay to CMS amounts that have been paid by CMS to transplant 
hospitals and that are determined to be in excess of the reasonable 
cost of the services provided by the IOPO or laboratory.
    (v) Not to charge any individual for items or services for which 
that individual is entitled to have payment made under section 1861 of 
the Act.
    (2) The initial cost report due from an IOPO or laboratory is for 
its first fiscal year during any portion of which it had an agreement 
with the Secretary under paragraphs (c)(1) and (2) of this section. The 
initial cost report covers only the period covered by the agreement.
    (d) Interim reimbursement. (1) Transplant hospitals with approved 
kidney transplant programs pay the IOPO or histocompatibility 
laboratory for their pre-transplantation services on the basis of an 
interim rate established by the contractor for that IOPO or laboratory.
    (2) The interim rate is based on a kidney SAC or contractor 
established rates, associated with procuring a kidney for 
transplantation, incurred by an IOPO or laboratory respectively, during 
its previous fiscal year. If there is not adequate cost data to 
determine the initial interim rate, the Medicare contractor determines 
it according to the IOPO's or laboratory's estimate of its projected 
costs for the fiscal year.
    (3) Payments made by transplant hospitals on the basis of interim 
rates are reconciled directly with the IOPO or laboratory after the 
close of its fiscal year, in accordance with paragraph (e) of this 
section.
    (4) Information on the interim rate for all IOPOs and 
histocompatibility laboratories must be disseminated to all transplant 
hospitals and contractors.
    (e) Retroactive adjustment--(1) Cost reports. Information provided 
in cost reports by IOPOs and histocompatibility laboratories must meet 
the requirements for cost data and cost finding specified in Sec.  
413.24. These cost reports must provide the following:
    (i) A complete accounting of the cost incurred by the IOPO or 
laboratory in providing covered services, the total number of Medicare 
beneficiaries who received those services.
    (ii) Any other data necessary to enable the contractor to make a 
determination of the reasonable cost of covered

[[Page 25705]]

services provided to Medicare beneficiaries.
    (2) Audit and adjustment. A cost report submitted by an IOPO or 
histocompatibility laboratory is reviewed by the contractor and a new 
interim reimbursement rate for kidney acquisition costs for the 
subsequent fiscal year is established based upon this review.
    (i) A retroactive adjustment in the amount paid under the interim 
rate is made in accordance with Sec.  413.64(f).
    (ii) If the determination of reasonable cost reveals an overpayment 
or underpayment resulting from the interim reimbursement rate paid to 
transplant hospitals, a lump sum adjustment is made directly between 
that contractor and the IOPO or laboratory.
    (f) Payment requirements. For services furnished on or after April 
1, 1988, no payment may be made for services furnished by an IOPO that 
does not meet the requirements of part 486, subpart G, of this chapter.
    (g) Appeals. If the amount in controversy is $1,000 or more, any 
IOPO or histocompatibility laboratory that disagrees with a 
contractor's cost determination under this section is entitled to a 
contractor hearing, in accordance with the procedures set forth in 
Sec. Sec.  405.1811 through 405.1833 of this chapter.

PART 425--MEDICARE SHARED SAVINGS PROGRAM

0
38. The authority for Part 425 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1306, 1395hh, and 1395jjj.

0
39. 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
40. The authority citation for Part 455 continues to read as follows:

    Authority:  42 U.S.C. 1302.

0
41. 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
42. The authority citation for part 495 continues to read as follows:

    Authority:  42 U.S.C. 1302 and 1395hh.

0
43. 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 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

[[Page 25706]]

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
44. Section 495.24 is amended by--
0
a. Revising paragraph (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.'';
0
h. Adding paragraph (e)(7)(ii)(C); and
0
i. Revising paragraphs (e)(8)(ii) introductory text, (e)(8)(ii)(A), 
(e)(8)(iii) introductory text, and (e)(8)(iii)(A), (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.
    (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.
* * * * *
    (7) * * *
    (ii) * * *
    (C) Beginning in 2022, the eligible hospital or CAH ensures the 
patient's health information, with an encounter date on or after 
January 1, 2016, is available for 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 CAHs CEHRT.
    (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

[[Page 25707]]

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 will receive 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
45. 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: April 23, 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 proposed prospective 
payment rates for Medicare hospital inpatient operating costs and 
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 proposed figures for the 
standardized amounts, offsets, and budget neutrality factors. 
Therefore, in this proposed rule, we are setting forth the rate-of-
increase percentage for updating the target amounts for certain 
hospitals excluded from the IPPS that would 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 proposed LTCH PPS standard Federal 
payment rate that would 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.

[[Page 25708]]

    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.G. of the preamble of this 
proposed 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 IV.A.2 of the preamble of this proposed 
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 proposing 
to make 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 proposed 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 proposed 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 
proposed rule are listed in section VI. of this Addendum and are 
available via the internet on the CMS website.

II. Proposed 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 proposing to use for determining the proposed 
prospective payment rates for FY 2022.
    In summary, the proposed 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 IV.A. of the 
preamble of this proposed rule for a complete discussion on the 
proposed FY 2022 inpatient hospital update. The table that follows 
shows these four scenarios:
[GRAPHIC] [TIFF OMITTED] TP10MY21.327

    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

[[Page 25709]]

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 proposed rule).
     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 proposing to 
apply 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 proposing to apply a uniform, 
national budget neutrality adjustment to the FY 2022 wage index for 
the rural floor.
    For FY 2022, we are proposing to not remove the FY 2021 Stem 
Cell Acquisition Budget Neutrality Factor from the prior year's 
standardized amount and to not apply a new factor. If we removed the 
prior year's adjustment, we would not satisfy budget neutrality. We 
believe 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 59032-59033). 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.

A. Calculation of the Proposed 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, we are proposing to rebase and revise the national 
labor-related and nonlabor-related shares (based on the proposed 
2018-based hospital market basket discussed in section IV.B.3. of 
the preamble of this proposed 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 proposed rule, 
we are proposing to use 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 proposing to apply 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 proposed 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 proposed rule and are available via the 
internet on the CMS website.

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, we are proposing to calculate 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, we are proposing to use the 
proposed 2018-based IPPS operating and capital market baskets for FY 
2022. As discussed in section IV.B. of the preamble of this proposed 
rule, in accordance with section 1886(b)(3)(B) of the Act, as 
amended by section 3401(a) of the Affordable Care Act, we are 
proposing to reduce the FY 2022 applicable percentage increase 
(which for this proposed rule is based on IGI's fourth quarter 2020 
forecast of the proposed 2018-based IPPS market basket) by the MFP 
adjustment, as discussed elsewhere in this proposed rule.
    Based on IGI's fourth quarter 2020 forecast of the hospital 
market basket increase (as discussed in Appendix B of this proposed 
rule), the forecast of the hospital market basket increase for FY 
2022 for this proposed rule is 2.5 percent. As discussed earlier, 
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 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 IV.B. of the 
preamble of this proposed 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

[[Page 25710]]

possible applicable percentage increases that would be applied to 
update the national standardized amount. The proposed 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 proposed rule.

4. Methodology for Calculation of the Average Standardized Amount

    As discussed in section I.F of the preamble of this proposed 
rule, we are proposing to use alternative data for the FY 2022 
ratesetting in situations where the latest data available that would 
typically be used for the proposed rule is significantly impacted by 
the COVID-19 PHE. We refer the reader to section I.F of the preamble 
of this proposed rule for further discussion of this proposal and 
our analysis of the best available data for purposes of FY 2022 
ratesetting. In this section, we discuss the data we are proposing 
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 this proposed rule, we are proposing to instead use 
the FY 2019 MedPAR claims data, including for purposes of 
calculating the proposed budget neutrality adjustments and proposed 
outlier fixed-loss cost threshold. As discussed in section I.F, we 
are also soliciting comments on an alternative to this proposal of 
using the same FY 2020 data that we would ordinarily use for 
purposes of FY 2022 ratesetting, which we may consider finalizing 
for FY 2022 based on consideration of comments received.
     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 December 2020 
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 proposing 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, we are proposing to use the 
December 2020 update of the PSF, consistent with our typical 
process. In the FY 2022 proposed rule impact file, we have indicated 
which PSF update the applicable fields were sourced from. As 
discussed in section I.F of this proposed rule, we are also 
soliciting comments on an alternative approach of using the same 
data that we would ordinarily use for purposes of the FY 2022 
rulemaking, which we may consider finalizing for FY 2022 based on 
consideration of comments received. In order to facilitate comments 
on this alternative approach, we are making available supporting 
data files, such as budget neutrality factors based on the FY 2020 
MedPAR file and related MS-DRG relative weighting factors. The 
supplemental data files can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We include 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.
    The methodology we used to calculate the proposed 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 proposed 
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 are proposing to adjust 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 
proposed 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.
     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 are proposing to 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

[[Page 25711]]

pass-through payment not paid under the IPPS. Revenue centers 081X-
089X are typically excluded from ratesetting, however, we are 
proposing to not remove 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, we are 
proposing to remove 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).
     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 would 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), we are proposing to include 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, we 
also are proposing 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.
     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 proposing to continue to apply a 
proposed 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 proposed 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, we are proposing to apply 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, would 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), 
we are proposing to include estimated empirically justified Medicare 
DSH payments that would 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 described by section 1886(r)(2) of the Act. That is, 
we are proposing to consider 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 IV.G. of the preamble to this proposed rule and later in 
this section, we are proposing to continue 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 
are proposing to include estimated uncompensated care payments in 
this comparison.
    Similarly, for MDHs, as discussed in section IV.G. of the 
preamble of this proposed 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, we are proposing to continue to take 
into consideration uncompensated care payments in the computation of 
payments under the Federal rate and the hospital-specific rate for 
MDHs.
     We are proposing to include 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 would be estimated based on the proposed 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 proposed rule.

a. Proposed 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 proposed rule, we normalized 
the recalibrated MS-

[[Page 25712]]

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 proposing to make 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 proposed rule, 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 proposed 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 proposal in section IV.I. of the preamble to this proposed 
rule, we applied the proposed 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, we are proposing to apply 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 IV.I. of the preamble of this proposed rule for a complete 
discussion on the proposed adjustor for certain cases that group to 
MS-DRG 018 and to section II.E.2.b. of the preamble of this proposed 
rule, for a complete discussion of the proposed 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 proposed budget 
neutrality adjustment factor and applied this factor to the 
standardized amount. As discussed in section IV. of this Addendum, 
we are proposing to apply 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 proposed FY 2022 budget neutrality 
factors.

b. Updated Wage Index--Proposed 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, we are 
proposing to adjust 100 percent of the wage index factor for 
occupational mix. We describe the occupational mix adjustment in 
section III.E. of the preamble of this proposed rule.
    To compute a proposed 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 proposed 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 proposed FY 2022 hospital readmissions 
payment adjustment and the estimated FY 2022 hospital VBP payment 
adjustment; and
     Aggregate payments using the proposed FY 2022 relative 
weights and the proposed FY 2022 pre-reclassified wage indexes, 
applied the proposed 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 proposed FY 2022 
hospital readmissions payment adjustments and estimated FY 2022 
hospital VBP payment adjustments applied previously.
    In addition, we applied the proposed 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 proposed 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 proposed budget neutrality 
factors.

c. Reclassified Hospitals--Proposed 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 proposed budget neutrality adjustment 
factor for FY 2022, we used FY 2019 discharge data to simulate 
payments and compared the following:
     Aggregate payments using the proposed FY 2022 labor-
related share percentage, the proposed FY 2022 relative weights, and 
the proposed 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 proposed FY 2022 labor-
related share percentage, the proposed FY 2022 relative weights, and 
the proposed 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 proposed rule, which is available via the internet on the 
CMS website. This table reflects reclassification crosswalks 
proposed for FY 2022, and applies the proposed

[[Page 25713]]

policies explained in section III. of the preamble of this proposed 
rule. Based on this comparison, we computed a proposed 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 proposed FY 2022 
budget neutrality factors.
    The proposed FY 2022 budget neutrality adjustment factor was 
applied to the proposed standardized amount after removing the 
effects of the FY 2021 budget neutrality adjustment factor. We note 
that the proposed 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 proposed rule.
    As discussed in the interim final rule with comment period 
titled ``Modification of Limitations on Redesignation by the 
Medicare Geographic Classification Review Board (MGCRB)'' (CMS-1762-
IFC), publicly available in conjunction with this proposed rule, we 
amended our 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. These regulatory 
changes aligned our policy with the decision in Bates County 
Memorial Hospital v. Azar, 464 F. Supp. 3d (D.D.C. 2020). For FY 
2022, there are approximately 22 hospitals that may, as a result of 
the settlement or other resolution of pending litigation, receive a 
higher wage index than they might otherwise have received based on 
the information currently available to us. If these hospitals do 
receive higher wage indexes for that reason, we intend to include 
any amounts they receive by reason of those higher wage indexes 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 FY 
2022, if these hospitals do receive a higher wage index at the time 
of the final rule than they might otherwise have received, we 
estimate the FY 2022 budget neutrality adjustment could increase by 
as much as approximately one-half of a percentage point compared to 
the budget neutrality adjustment that might otherwise have been 
calculated.

d. Proposed Rural Floor Proposed 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 proposed 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, we are proposing to 
calculate 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). 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 proposed FY 2022 rural 
Puerto Rico wage index is calculated based on the average of the 
proposed 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 proposed national 
rural floor budget neutrality adjustment factor. The national 
adjustment was applied to the national wage indexes to produce 
proposed rural floor budget neutral wage indexes. Please see the 
table later in this section for a summary of the proposed FY 2022 
budget neutrality factors.
    As further discussed in section III.G.2 of this proposed 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 proposing to apply the imputed 
floor after the application of the rural floor and would 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 further explained in 
section III.G.2 of this proposed 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 
proposed rule. We will include 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 proposed 
rule for a complete discussion regarding the imputed floor.

e. Proposed Rural Community Hospital Demonstration Program Adjustment

    In section V.L. of the preamble of this proposed 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.M. of the preamble of this proposed 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 proposed 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 $63,829,479.00. 
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

[[Page 25714]]

neutrality factors. We refer readers to section V.L. of the preamble 
of this proposed 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--Proposed Budget 
Neutrality Adjustment

    As discussed in section III.G.3. of the preamble of this 
proposed 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 proposed rule, consistent with our current 
methodology for implementing wage index budget neutrality under 
section 1886(d)(3)(E) of the Act, we are proposing to make 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 proposed budget neutrality adjustment factor 
for FY 2022, we used FY 2019 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the proposed FY 2022 labor-
related share percentage, the proposed FY 2022 relative weights, and 
the proposed 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 proposed FY 2022 labor-
related share percentage, the proposed FY 2022 relative weights, and 
the proposed FY 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 proposed FY 2022 budget neutrality adjustment factor was 
applied to the standardized amount.
    The following table is a summary of the proposed FY 2022 budget 
neutrality factors, as discussed in the previous sections.
[GRAPHIC] [TIFF OMITTED] TP10MY21.328

    In order to facilitate comments on the alternative approach 
discussed in section I.F of this proposed rule of using the same FY 
2020 data that we would ordinarily use for purposes of FY 2022 
ratesetting, and which we may consider finalizing for FY 2022 based 
on consideration of comments received, we are making available the 
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.

g. Proposed 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 proposing to implement the required +0.5 percent 
adjustment to the standardized amount. This is a permanent 
adjustment to the payment rates.

h. Proposed 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 proposing to incorporate 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.

[[Page 25715]]

(1) Proposed 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 would 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 would 
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 
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 Proposed 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, we are 
proposing to continue 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 proposed rule, we 
are proposing to determine a projection of outlier payment 
reconciliations for the FY 2022 outlier threshold calculation, by 
advancing the methodology by 1 year. Specifically, we are proposing 
to use 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 are proposing 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 are 
proposing 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 are targeting an amount higher than 5.1 percent for outlier 
payments for FY 2022 under our proposed methodology.
    For this 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 propose 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 may 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.
    For this 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 are proposing 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 this proposed rule, we provide the FY 2022 
outlier threshold as calculated

[[Page 25716]]

for this 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 would 
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 are proposing 
to determine an outlier adjustment by applying a factor to the 
standardized 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 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 include 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 is 0.949 (1-0.051).
    We are inviting 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.

(b) Proposed 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 
are proposing 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 are proposing 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 
proposal 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 are proposing 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 are proposing 
to use the following methodology, which generally parallels the 
proposed 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 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 this proposed rule and 
expect to use the March 2020 HCRIS extract for the FY 2022 final 
rule. Similar to the FY 2020 final rule, 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 
are proposing 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 this 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 are proposing 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. As 
previously noted, we may

[[Page 25717]]

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 this FY 2022 proposed rule, the estimated percentage of FY 
2022 capital outlier payments otherwise determined using the shared 
outlier threshold is 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 
results 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 are 
proposing 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 are inviting 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.

(2) Proposed 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 proposed FY 2022 
outlier threshold, we simulated payments by applying proposed 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 are proposing 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 proposing to remove 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 proposed FY 
2022 relative weights, consistent with our proposal discussed in 
section IV.I. of the preamble to this proposed rule, we applied the 
proposed 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 proposed rule, we are applying a proposed 
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, for this FY 2022 
proposed rule, we are proposing to use the FY 2019 MedPAR claims 
data, which is 3 years prior to FY 2022. Therefore, we are proposing 
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 are 
proposing 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 proposed rule. That is, for FY 
2022, we are proposing 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. Specifically, 
for this 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 propose that for the FY 2022 
IPPS/LTCH PPS final rule, we would continue to use the charge 
inflation estimate from the FY 2021 IPPS/LTCH PPS final rule. In 
addition, we are soliciting 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 proposed rule, and 
note 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

[[Page 25718]]

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 three 
years. Because we are proposing 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 this proposed rule of using the same 
data that we would ordinarily use for purposes of FY 2022 
ratesetting, and which we may consider finalizing for FY 2022 based 
on consideration of comments received, we are making 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 include 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, 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 this FY 2022 IPPS/LTCH PPS proposed 
rule, we are proposing 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 proposed approach 
of not using data that may have been significantly impacted by the 
COVID-19 PHE. We are proposing to apply 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 replace 
these CCRs with the statewide average CCR for the upcoming fiscal 
year. We also assign 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 do not apply the 
adjustment factors described later in this section to hospitals 
assigned the statewide average CCR. For FY 2022, we are also 
proposing 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.
    Ordinarily, for the proposed rule, we would use CCRs from the 
December 2020 update of the PSF and apply a proposed 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 are proposing 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 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 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 the proposed methodology, for this proposed rule, we 
calculated a proposed March 2019 operating national average case-
weighted CCR of 0.254027 and a proposed 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. 
Because we are proposing to use 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 this 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. Because we are 
proposing to use 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 in section I.F of this proposed rule and in section 
I.O of Appendix A of this proposed rule, we are soliciting comments 
on an alternative approach of using the same data we would 
ordinarily use for purposes of FY 2022 ratesetting, which we may 
consider finalizing for FY 2022 based on consideration of comments 
received, and are making available supplemental data files to 
facilitate comments on this alternative approach. As noted 
previously, we include 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, 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. 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 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 this proposed rule. 
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 proposed rule, sections 1886(q) and 1886(o) of the 
Act establish the Hospital Readmissions Reduction Program and the 
Hospital VBP Program, respectively. We do not believe that it is 
appropriate to include the proposed hospital VBP payment adjustments 
and the hospital readmissions payment adjustments in the proposed 
outlier threshold calculation or the proposed 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

[[Page 25719]]

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 are proposing to exclude the estimated hospital VBP payment 
adjustments and the estimated hospital readmissions payment 
adjustments from the calculation of the proposed outlier fixed-loss 
cost threshold.
    We note 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 are 
proposing 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 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 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 are proposing to 
include estimated FY 2022 uncompensated care payments in the 
computation of the proposed outlier fixed-loss cost threshold. 
Specifically, we are proposing 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 
proposed 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 proposing 
to incorporate an estimate of FY 2022 outlier reconciliation in the 
methodology for determining the outlier threshold. As noted 
previously, for this FY 2022 proposed rule, the ratio of outlier 
reconciliation dollars to total Federal Payments (Step 4) is a 
negative 0.013758 percent, which, when rounded to the second digit, 
is -0.01 percent. Therefore, for FY 2022, we are proposing 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 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 reflects 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 note that, if 
calculated without applying our proposed methodology for 
incorporating an estimate of outlier reconciliation in the 
determination of the outlier threshold, the proposed threshold would 
be $31,027. We are proposing 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 add-on payments for new 
technology, plus $30,967. As discussed further in section I.A of 
this proposed rule, we note that the estimate of the outlier 
threshold using the FY 2020 MedPAR file is $36,483.

(3) Other Proposed 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) would result in outlier payments 
that would equal 5.1 percent of operating DRG payments and we 
estimate that capital outlier payments would equal 5.34 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 proposing to reduce the FY 2022 
standardized amount by 5.1 percent to account for the projected 
proportion of payments paid as outliers.
    The proposed outlier adjustment factors that would be applied to 
the operating standardized amount and capital Federal rate based on 
the proposed FY 2022 outlier threshold are as follows:
[GRAPHIC] [TIFF OMITTED] TP10MY21.329

    We are proposing to apply 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 proposed 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 proposed statewide average capital CCRs. As 
previously stated, the proposed 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 proposed statewide average total CCRs used under the 
LTCH PPS as discussed in section V. of this Addendum.

[[Page 25720]]

    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 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 5.42 
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 proposed rule. We will 
provide an estimate of actual FY 2021 outlier payments in the FY 
2023 IPPS/LTCH PPS proposed rule.

5. Proposed 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 proposing to apply to all hospitals, except hospitals located in 
Puerto Rico, for FY 2022. The proposed 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 proposed 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 proposing to apply 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 proposed standardized 
amounts reflecting the proposed applicable percentage increases for 
FY 2022.
    The proposed 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 proposed FY 2022 national 
standardized amounts. The second through fifth columns display the 
changes from the FY 2021 standardized amounts for each proposed 
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 25721]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.330


[[Page 25722]]


BILLING CODE 4120-01-C

B. Proposed 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 proposed labor related and -nonlabor related- shares 
that we are proposing to use 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. Proposed 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 proposed rule, we are proposing to apply 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 proposing to apply 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 proposed rule, we 
discuss the data and methodology for the FY 2022 wage index.

2. Proposed 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 proposing to update 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 proposing to update 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 proposing to use 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 proposing to create 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 proposed 2018-based IPPS market 
basket is comprised of a different mix of commodities and services. 
Therefore, we are proposing to create 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 proposed 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 proposed rulemaking. In 
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38530), 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 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 proposing for FY 2022 to continue 
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 
proposing to establish 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 FY 2018 COLA factors. We note that 
the proposed FY 2022 COLA factors 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

[[Page 25723]]

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] TP10MY21.331

C. Calculation of the Proposed 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 proposed 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 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

[[Page 25724]]

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 
proposed applicable percentage increases to the hospital-specific 
rates applicable to SCHs and MDHs are the following:
[GRAPHIC] [TIFF OMITTED] TP10MY21.332

    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 proposed 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 proposed 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 would receive for its discharges beginning on or after 
October 1, 2021. We note that, in this proposed rule, for FY 2022, 
we are not proposing to make a documentation and coding adjustment 
to the hospital specific-rate. We refer readers to section II.D. of 
the preamble of this proposed rule for a complete discussion 
regarding our proposed 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. Proposed 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 are proposing to use 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 Proposed Federal Hospital Inpatient 
Capital-Related Prospective Payment Rate Update for FY 2022

    In the discussion that follows, we explain the factors that we 
are proposing to use to determine the capital Federal rate for FY 
2022. In particular, we explain why the proposed FY 2022 capital 
Federal rate would increase approximately 1.22 percent, compared to 
the FY 2021 capital Federal rate. As discussed in the impact 
analysis in

[[Page 25725]]

Appendix A to this FY 2022 IPPS/LTCH PPS proposed rule, we estimate 
that capital payments per discharge would increase approximately 0.5 
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 proposed 
rule, we are proposing 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 proposed 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 proposed 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 are proposing to use claims from the March 2020 
update of the FY 2019 MedPAR file. Similarly, for this proposed 
rule, we ordinarily would use provider data from the December 2020 
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 December 2020 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, we are proposing to use 
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. As discussed 
previously and in section I.O.1 of Appendix A, we are also 
considering an alternative approach that would use the FY 2020 data 
that we ordinarily would use in the FY 2022 IPPS ratesetting. To 
facilitate comments on this alternative approach, which we may 
consider finalizing for FY 2022 based on consideration of comments 
received, we are making available budget neutrality and other 
ratesetting adjustments calculated under this alternative approach. 
These data can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.

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 proposed update factor for FY 2022 under that 
framework is 0.7 percent based on a projected 1.0 percent increase 
in the proposed 2018-based CIPI, a proposed 0.0 percentage point 
adjustment for intensity, a proposed 0.0 percentage point adjustment 
for case-mix, a proposed 0.0 percentage point adjustment for the DRG 
reclassification and recalibration, and a proposed 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 
proposed rule, we describe the policy adjustments that we are 
proposing to apply 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 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 are projecting a 0.5 percent total increase in 
the case-mix index. We estimated that the real case-mix increase 
would 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 proposed 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 
proposed 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 proposed rule, we believe the FY 2020 MedPAR 
claims data were significantly impacted by the COVID-19 PHE. Due to 
these impacts, we are proposing to not evaluate the effects of the 
FY 2020 DRG reclassification and recalibration as part of our update 
for FY 2022. Therefore, we are proposing to make 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, we are proposing 
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

[[Page 25726]]

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 proposed rule, we are proposing to continue 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 proposing to use 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 we are 
proposing to make 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 proposed 0.7 percent capital update factor under the 
capital update framework for FY 2022, as shown in the following 
table.
[GRAPHIC] [TIFF OMITTED] TP10MY21.333

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 are 
proposing to incorporate the estimated outlier reconciliation 
payment amounts into the outlier threshold model, as we did for FY 
2021. (For more details on our proposal to incorporate outlier 
reconciliation payment amounts into the outlier threshold model, 
please see section II.A. of this Addendum to this proposed 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 
would equal 5.34 percent for inpatient capital-related payments 
based on the proposed 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 would decrease FY 2022 aggregate estimated 
capital outlier payments by 0.01 percent. Therefore, accounting for 
estimated capital outlier reconciliation, the estimated outlier 
payments for capital-related PPS payments would equal 5.33 percent 
(5.34 percent-0.01 percent) of inpatient capital-related payments 
based on the capital Federal rate in FY 2022. Accordingly, we are 
proposing to apply an outlier adjustment factor of 0.9467 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 would be slightly 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 proposed FY 2022 outlier 
adjustment of 0.9467 is a 0.01 percent change from the FY 2021 
outlier adjustment of 0.9466. Therefore, the proposed net change in 
the outlier adjustment to the capital Federal rate for FY 2022 is 
1.0001 (0.9467/0.9466) so that the proposed outlier adjustment would 
increase the FY 2022 capital Federal rate by approximately 0.01 
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 
proposed 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 proposed rule, 
this policy was applied in FYs 2020 and 2021, and will continue to 
apply in FY 2022.

[[Page 25727]]

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 proposed rule, we are not proposing to apply 
this policy in FY 2022.
    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 
are not proposing to change this policy in 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 proposed rule, we are proposing 
to no longer permanently apply the budget neutrality factor for the 
lowest quartile hospital wage index adjustment and the 5 percent cap 
on wage index decreases such that they would 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 out-
migration and Frontier state adjustments, which are not subject to 
budget neutrality. Therefore, in order to continue to exclude the 
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 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 proposed 
approach, prior to calculating the GAF budget neutrality factors for 
FY 2022, we are proposing to remove 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 are 
proposing to divide 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 proposed changes to the wage index and the 
continuation of the lowest quartile hospital wage index adjustment 
policy in FY 2022 discussed previously, which directly affects the 
GAF, we are proposing to continue to compute a budget neutrality 
factor for changes in the GAFs in two steps. We discuss our proposed 
2-step calculation of the proposed 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 proposed FY 2022 GAFs without incorporating the 
lowest quartile hospital wage index adjustment. To achieve budget 
neutrality for these proposed changes in the GAFs, we calculated an 
incremental GAF budget neutrality adjustment factor of 1.0000 for FY 
2022. Next, we compared estimated aggregate capital Federal rate 
payments based on the proposed FY 2022 GAFs with and without the 
lowest quartile hospital wage index adjustment. For this 
calculation, estimated aggregate capital Federal rate payments were 
calculated using the proposed FY 2022 MS-DRG classifications and 
relative weights and the proposed FY 2022 GAFs (both with and 
without the lowest quartile hospital wage index adjustment). (We 
note, for this calculation the proposed GAFs included the out-
migration and Frontier state adjustments. We further note that this 
calculation will include the imputed floor adjustment in the FY 2022 
final rule. As discussed in section III.X. of the preamble of this 
proposed rule, given the recent enactment of section 9831 of Pub. L. 
117-2 on March 11, 2021 (which provides for the application of the 
imputed floor adjustment in a non-budget neutral manner beginning in 
FY 2022), there was not sufficient time available to incorporate the 
imputed floor required by this provision into the calculation of the 
provider wage index for this proposed rule.) To achieve budget 
neutrality for the effects of the lowest quartile hospital wage 
index adjustment on the proposed FY 2022 GAFs, we calculated an 
incremental GAF budget neutrality adjustment factor of 0.9976. As 
discussed earlier in this section, we are proposing that the lowest 
quartile hospital wage index adjustment factor not be permanently 
built into the capital Federal rate. Consistent with this proposal, 
and unlike in previous rules, we present the calculated lowest 
quartile hospital wage index adjustment factor 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 
proposed 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 proposed FY 2022 GAFs (without the lowest quartile hospital wage 
index adjustment) to estimated aggregate capital Federal rate 
payments based on the proposed FY 2022 MS-DRG classifications and 
relative weights and the proposed FY 2022 GAFs (without the lowest 
quartile hospital wage index adjustment). The proposed incremental 
adjustment factor for DRG classifications and changes in relative 
weights is 1.0001.
    The proposed incremental adjustment factor for proposed MS-DRG 
classifications and changes in relative weights (1.0001) and for 
proposed changes in the FY 2022 GAFs due to the proposed update to 
the wage data, wage index reclassifications and redesignations, and 
application of the rural floor policy (1.0000) is 1.0001 (1.0001 x 
1.0000). 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 on the 
FY 2022 GAFs, as described previously, we calculated a proposed 
budget neutrality adjustment factor of 0.9976 for FY 2022.
    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.

[[Page 25728]]

    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 or the lowest quartile hospital 
wage index adjustment described previously have on the other payment 
parameters, such as the payments for DSH or IME.
    The proposed incremental GAF/DRG adjustment factor of 1.0001 
accounts for the proposed MS-DRG reclassifications and recalibration 
and for proposed changes in the GAFs that result from proposed 
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 proposed lowest quartile hospital wage index adjustment factor 
of 0.9976 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. However, these 
factors do not account for changes in payments due to changes in the 
DSH and IME adjustment factors.

4. Proposed 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 proposing to 
establish an update of 0.70 percent in determining the FY 2022 
capital Federal rate for all hospitals. As a result of this proposed 
update and the proposed budget neutrality factors discussed earlier, 
we are proposing to establish a national capital Federal rate of 
$471.89 for FY 2022. The proposed national capital Federal rate for 
FY 2022 was calculated as follows:
     The proposed FY 2022 update factor is 1.007; that is, 
the proposed update is 0.7 percent.
     The proposed FY 2022 GAF/DRG budget neutrality 
adjustment factor that is applied to the capital Federal rate for 
proposed changes in the MS-DRG classifications and relative weights 
and proposed 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 1.0001.
     The proposed FY 2022 lowest quartile hospital wage 
index budget neutrality adjustment 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 is 0.9976.
     The proposed FY 2022 outlier adjustment factor is 
0.9467.
    We are providing the following chart that shows how each of the 
proposed factors and adjustments for FY 2022 affects the computation 
of the proposed FY 2022 national capital Federal rate in comparison 
to the FY 2021 national capital Federal rate. The proposed FY 2022 
update factor has the effect of increasing the capital Federal rate 
by 0.70 percent compared to the FY 2021 capital Federal rate. The 
proposed GAF/DRG budget neutrality adjustment factor has the effect 
of increasing the capital Federal rate by 0.01 percent. The proposed 
FY 2022 lowest quartile hospital wage index budget neutrality 
adjustment factor has the effect of increasing the capital Federal 
rate by 0.49 percent compared to the FY 2021 capital Federal rate. 
The proposed FY 2022 outlier adjustment factor has the effect of 
increasing the capital Federal rate by 0.01 percent compared to the 
FY 2021 capital Federal rate. The combined effect of all the 
proposed changes would increase the national capital Federal rate by 
approximately 1.22 percent, compared to the FY 2021 national capital 
Federal rate.

[[Page 25729]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.334

B. Calculation of the Proposed 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 proposed 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 proposed fixed-loss 
amount of $30,967.
    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 proposed rule, we are proposing to rebase and revise 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 proposed rule.

2. Forecast of the CIPI for FY 2022

    Based on IHS Global Inc.'s fourth quarter 2020 forecast, for 
this proposed rule, we are forecasting the proposed 2018-based CIPI 
to increase 1.0 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 3.0 
percent increase in other capital expense prices in FY 2022, 
partially offset by a projected 3.7 percent decline in vintage-
weighted interest expense prices in FY 2022. The weighted average of 
these three factors produces the forecasted 1.0 percent increase for 
the proposed 2018-based CIPI in FY 2022. We are also proposing that 
if more recent data becomes available (for example, a more recent 
estimate of the increase in the 2018-based CIPI), we would use such 
data, if appropriate, to determine the FY 2022 increase in the 2018-
based CIPI for the final rule.

[[Page 25730]]

IV. Proposed 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. 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.)
    We are proposing to rebase and revise the IPPS operating basket 
to a 2018 base year. Therefore, we are proposing 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, 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 would be the FY 2022 percentage increase in the 
proposed 2018-based IPPS operating market basket.
    For this FY 2022 IPPS/LTCH PPS proposed rule, based on IGI's 
2020 fourth quarter forecast, we estimate 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, 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 would be 2.5 percent, in accordance with the 
applicable regulations at 42 CFR 413.40. However, we are proposing 
that if more recent data become 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.
    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 VII. of the 
preamble of this proposed rule and section V. of the Addendum to 
this proposed rule for the proposed 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.

V. Proposed Changes to the Payment Rates for the LTCH PPS for FY 2022

A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2022

1. Overview

    In section VIII. of the preamble of this proposed 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 
(which we refer to as ``the multifactor productivity (MFP) 
adjustment'') as discussed in section VIII.C.2 of the preamble of 
this proposed 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 proposed 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 Proposed FY 2022 LTCH PPS Standard Federal 
Payment Rate

    Consistent with our historical practice and Sec.  
412.523(c)(3)(xvii), for FY 2022 we are proposing to apply the 
annual update to the LTCH PPS standard Federal payment rate from the 
previous year. Furthermore, in determining the proposed LTCH PPS 
standard Federal payment rate for FY 2022, we also are proposing to 
make certain regulatory adjustments, consistent with past practices. 
Specifically, in determining the proposed FY 2022 LTCH PPS standard 
Federal payment rate, we are proposing to apply 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 
proposed rule.
    In this proposed rule, we are proposing to establish an annual 
update to the LTCH PPS standard Federal payment rate of 2.2 percent 
(that is, the most recent estimate of the LTCH PPS market basket 
increase of 2.4 percent less the MFP adjustment of 0.2 percentage 
point). Therefore, in accordance with Sec.  412.523(c)(3)(xvii), we 
are proposing to apply a factor of 1.022 to the FY 2021 LTCH PPS 
standard Federal payment rate of $ 43,755.34 to determine the 
proposed 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 proposing to establish an 
annual update to the LTCH PPS standard Federal payment rate of 0.2 
percent (that is, an update factor of 1.002) 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 proposing to apply an area wage level budget neutrality 
factor to the FY 2022 LTCH PPS standard Federal payment rate of 
1.002458, based on the best available data at this time, to ensure 
that any proposed changes to the area wage level adjustment (that 
is, the proposed annual update of the wage index and labor-related 
share) would not result in any change (increase or decrease) in 
estimated aggregate LTCH PPS standard Federal payment rate payments. 
Accordingly, we are proposing to establish an LTCH PPS standard 
Federal payment rate of $44,827.87 (calculated as $43,755.34 x 1.022 
x 1.002458) 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 proposing 
to establish an LTCH PPS standard Federal payment rate of $43,950.62 
(calculated as $43,755.34 x 1.002 x 1.002458) for FY 2022.

B. Proposed 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

[[Page 25731]]

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 proposed FY 2022 LTCH PPS standard Federal payment rate wage 
index values that would 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 proposed rule and available via the 
internet on the CMS website.

2. Proposed 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. These bulletins established 
revised delineations for Metropolitan Statistical Areas, 
Micropolitan Statistical Areas, and Combined Statistical Areas, and 
provided guidance on the use of the delineations of these 
statistical areas based on the standards published on June 28, 2010 
(75 FR 37246), and Census Bureau data. 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 proposing to adopt 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 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 proposed 
rule, under the authority of section 123 of the BBRA, as amended by 
section 307(b) of the BIPA, we are proposing to adopt 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 proposal to adopt 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 proposed rule, we are also 
proposing to use 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.

3. Proposed 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

[[Page 25732]]

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 proposed rule, consistent with our historical practice, 
we are proposing to establish 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 proposing to establish 
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 fourth quarter 2020 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 63.7 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 9.4 percent based 
on IHS Global Inc.'s fourth quarter 2020 forecast of the 2017-based 
LTCH market basket, we took 46 percent of 9.4 percent to determine 
the labor-related share of capital-related for FY 2022 of 4.3 
percent. Therefore, we are proposing to establish a total labor-
related share for FY 2022 of 68.0 percent (the sum of 63.7 percent 
for the operating cost and 4.3 percent for the labor-related share 
of capital-related cost).

4. Proposed 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 
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, we are proposing 
to continue to employ our historical practice of using the same data 
we are proposing to use to compute the proposed FY 2022 acute care 
hospital inpatient wage index, as discussed in section III. of the 
preamble of this proposed 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, we are proposing to compute the FY 2022 LTCH PPS 
standard Federal payment rate area wage index values consistent with 
the ``urban'' and ``rural'' geographic classifications (that is, the 
proposed 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. We are also proposing to continue 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, for FY 2022 we are proposing to continue 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 are proposing to use 
to determine the proposed 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 proposed 
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 
proposed 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 are proposing to use 
to determine the proposed FY 2022 LTCH PPS standard Federal payment 
rate area wage index values in this proposed rule, there are no 
rural areas without IPPS hospital wage data. Therefore, it is not 
necessary to use our established methodology to calculate a proposed 
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. Proposed 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), we are 
proposing to apply an

[[Page 25733]]

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, we are proposing to determine 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 proposed FY 2022 wage index values 
and the proposed FY 2022 labor-related share of 68.0 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 proposed rule and the labor-related share is 
discussed in section V.B.3. of this Addendum to this proposed 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 proposed FY 2022 updates to the area wage level adjustment 
(calculated in Step 2) to determine the proposed 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 proposed FY 2022 updates to the area wage 
level adjustment budget neutrality factor from Step 3 to determine 
the proposed FY 2022 LTCH PPS standard Federal payment rate after 
the application of the proposed 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 proposed 
FY 2022 LTCH PPS standard Federal payment rate area wage level 
adjustment budget neutrality factor.
    For this proposed rule, using the steps in the methodology 
previously described, we determined a proposed FY 2022 LTCH PPS 
standard Federal payment rate area wage level adjustment budget 
neutrality factor of 1.002458. Accordingly, in section V.A. of the 
Addendum to this proposed rule, we applied the proposed area wage 
level adjustment budget neutrality factor of 1.002458 to determine 
the proposed FY 2022 LTCH PPS standard Federal payment rate, in 
accordance with Sec.  412.523(d)(4).

C. Proposed 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) to 
correspond to the updated of the labor-related share of the IPPS 
market basket, which reflected 2014 cost shares. As discussed in 
this proposed 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 proposing to update 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 proposing to update 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 proposing to use 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 proposing to create 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 proposed 2018-based IPPS market 
basket is comprised of a different mix of commodities and services. 
Therefore, we are proposing to create 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 proposed 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 proposed 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 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, for FY 2022, we are 
proposing to continue to use such a cap, 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 
proposing to establish for

[[Page 25734]]

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 for FYs 2018 through 2021.
[GRAPHIC] [TIFF OMITTED] TP10MY21.335

D. Proposed 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 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. Proposed LTCH Total CCR Ceiling

    Ordinarily, for this FY 2022 proposed rule, we would use IPPS 
total CCR data from the December 2020 update of the Provider 
Specific File (PSF) for the purposes of calculating the proposed 
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 proposed 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

[[Page 25735]]

in section VIII.A.4. of the preamble of this proposed rule that 
these are the best available data at this time for the purposes of 
calculating the proposed LTCH total CCR ceiling for FY 2022. 
Therefore, in this proposed 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 proposing to 
establish an LTCH total CCR ceiling of 1.24 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. Consistent with our historical practice, 
we are proposing to use the best available data, if applicable, to 
determine the LTCH total CCR ceiling for FY 2022 in the final rule. 
(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).)

c. Proposed 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 proposed rule, we would use IPPS total CCR 
data from the December 2020 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 proposed 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 proposed 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 proposed 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 
proposing to establish LTCH PPS statewide average total CCRs for 
urban and rural hospitals that would 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 proposed 
rule (and available via the internet on the CMS website). Consistent 
with our historical practice, we also are proposing to use the best 
available data, if applicable, to determine the LTCH PPS statewide 
average total CCRs for FY 2022 in the final rule.
    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 are proposing to use 
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 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 
are proposing to use 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, we are proposing to continue 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 
proposing to use 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)).

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. Proposed 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. Proposed 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 this proposed rule, we are proposing to adjust our 
methodology for calculating the

[[Page 25736]]

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 
are proposing 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 proposed fixed-loss amount 
for FY 2022. We also are proposing to make a technical change to the 
methodology for determining the CCRs to use when calculating the 
proposed fixed-loss amount for FY 2022. Furthermore, we are 
proposing that these proposed 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 proposed 
technical changes are described in greater detail in sections 
V.D.3.b.(1). and V.D.3.b.(2). of the Addendum to this proposed rule.

(1) Proposed Charge Inflation Factor for Use in Determining the 
Proposed 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 
are proposing 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 proposed rule), we are 
proposing 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 claims data, instead 
of using estimates calculated from quarterly market basket update 
values. In this proposed rule, we describe the general methodology 
we are proposing 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 propose 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 this 
proposed 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 proposed 
charge inflation factor for FY 2022, we are proposing 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. As discussed in greater detail in section 
VIII.A.4. of the preamble of this proposed 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 proposed charge inflation factor for FY 2022.
    Therefore, for this 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 results 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 propose to inflate the billed charges obtained from the 
FY 2019 MedPAR file by this 3-year charge inflation factor of 
1.193455 when determining the proposed fixed-loss amount for LTCH 
PPS standard Federal payment rate cases for FY 2022.

(2) Proposed CCRs for Use in Determining the Proposed 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 
are proposing 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 proposed rule), we are proposing 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 are proposing 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,

[[Page 25737]]

including the specific data we propose 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 one 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).
    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 this proposed 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 reasons 
discussed in section VIII.A.4. of the preamble of this proposed 
rule. Ordinarily, for this FY 2022 proposed rule, we would use CCR 
data from the December 2020 update of the PSF when determining the 
CCRs used for calculating the proposed 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. As also discussed in 
section VIII.A.4. of the preamble of this proposed rule, we believe 
the utilization patterns reflected in these cost reports were 
significantly impacted by the COVID-19 PHE. Therefore, for the 
purposes of determining the CCRs used for calculating the proposed 
fixed-loss amount for FY 2022, we are proposing to use the March 
2020 PSF as the most recently available PSF and the March 2019 PSF 
as the PSF that was made available one year prior to the most 
recently available PSF, as described in our proposed 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 proposed rule, we believe 
these are the best available data at this time for the purposes of 
determining the CCRs used to calculate the proposed fixed-loss 
amount for FY 2022. In addition, we also are proposing 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. As discussed in greater detail in section 
VIII.A.4. of the preamble of this proposed 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 we proposed to use in this 
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 Version 39 of 
the GROUPER) to calculate the case-weighted average CCRs. For this 
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 results 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) Proposed Fixed-Loss Amount for LTCH PPS Standard Federal Payment 
Rate Cases for FY 2022

    In this proposed rule, we are proposing 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 this proposed rule, we believe 
the FY 2020 MedPAR claims were significantly impacted by COVID-19 
PHE. As a result, we are proposing 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, under the broad authority of section 123(a)(1) of the BBRA and 
section 307(b)(1) of the BIPA, we are proposing 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. We also are proposing to continue 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 proposed adjusted LTCH PPS 
standard Federal payment rate payment and the proposed fixed-loss 
amount for LTCH PPS standard Federal payment rate cases of $32,680).
    Consistent with our historical practice, we are proposing to use 
the best available LTCH claims data and CCR data, if applicable, 
when determining the fixed-loss amount for LTCH PPS standard Federal 
payment rate cases for FY 2022 in the final rule.

4. Proposed 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

[[Page 25738]]

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 proposed 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 proposed 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, we are proposing 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 proposed IPPS fixed-
loss amount. That is, we are proposing a fixed-loss amount for site 
neutral payment rate cases of $30,967, which is the same proposed FY 
2022 IPPS fixed-loss amount discussed in section II.A.4.j.(1). of 
the Addendum to this proposed rule. Accordingly, for FY 2022, we are 
proposing 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).
    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 are proposing to continue this policy.
    As discussed earlier, 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), 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 are proposing 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 proposed HCO budget neutrality adjustment would not be 
applied to the HCO portion of the site neutral payment rate amount 
(81 FR 57309).

E. Proposed 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 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

[[Page 25739]]

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).
    For FY 2022, as discussed in greater detail in section V.E.4.b. 
of the preamble of this proposed 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 72.14 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 54.11 percent (the product of 75 percent and 72.14 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 pursuant 
to 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 79.11 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 + 54.11 percent = 79.11 percent).
    Therefore, for FY 2022, we are proposing 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 are 
proposing that, if more recent data became available, we would use 
that data to determine this factor in the final rule.

F. Computing the Proposed 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 
proposed 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 proposed FY 2022 factors are shown in 
the chart in section V.C. of this Addendum) in accordance with Sec.  
412.525(b). In this proposed rule, we are proposing to establish an 
LTCH PPS standard Federal payment rate for FY 2022 of $44,827.87, as 
discussed in section V.A. of the Addendum to this proposed rule. We 
illustrate the methodology to adjust the proposed 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 proposed FY 2022 LTCH PPS wage index 
value of 1.0392 (obtained from Table 12A listed in section VI. of 
the Addendum to this proposed rule and available via the internet on 
the CMS website). The Medicare patient case is classified into 
proposed MS-LTC-DRG 189 (Pulmonary Edema & Respiratory Failure), 
which has a proposed relative weight for FY 2022 of 0.9448 (obtained 
from Table 11 listed in section VI. of the Addendum to this proposed 
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 proposed Federal 
prospective payment for this Medicare patient case in FY 2022, we 
computed the wage-adjusted Federal prospective payment amount by 
multiplying the unadjusted proposed FY 2022 LTCH PPS standard 
Federal payment rate ($44,827.87) by the proposed labor-related 
share (0.68 percent) and the proposed wage index value (1.0392). 
This wage-adjusted amount was then added to the nonlabor-related 
portion of the unadjusted proposed LTCH PPS standard Federal payment 
rate (0.32 percent; adjusted for cost of living, if applicable) to 
determine the adjusted proposed LTCH PPS standard Federal payment 
rate, which is then multiplied by the proposed MS-LTC-DRG relative 
weight (0.9448) to calculate the total adjusted proposed LTCH PPS 
standard Federal prospective payment for FY 2022 ($43,482.34). The 
table illustrates the components of the calculations in this 
example.
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VI. Tables Referenced in This Proposed Rule Generally Available Through 
the Internet on the CMS Website

    This section lists the tables referred to throughout the 
preamble of this proposed 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 
proposed 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 proposed rule 
should contact Michael Treitel at (410) 786-4552.
    The following IPPS tables for this proposed 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 Proposed rule Home Page'' or 
``Acute Inpatient -Files- for Download.'' We refer readers to 
section I.O. of the Appendix A of this proposed rule for a 
discussion of the supplemental data files based on the use of the FY 
2020 data that we would ordinarily use for FY 2022 ratesetting, 
which we are also making available on the CMS website.

Table 2.--Proposed Case-Mix Index and Wage Index Table by CCN--FY 
2022 Proposed Rule
Table 3.--Proposed Wage Index Table by CBSA--FY 2022 Proposed Rule
Table 4A.--Proposed List of Counties Eligible for the Out-Migration 
Adjustment under Section 1886(d)(13) of the Act--FY 2022 Proposed 
Rule
Table 4B.--Counties Redesignated under Section 1886(d)(8)(B) of the 
Act (LUGAR Counties)--FY 2022 Proposed Rule
Table 5.--Proposed 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 6G.1.--Proposed Secondary Diagnosis Order Additions to the CC 
Exclusions List- FY 2022
Table 6G.2.--Proposed Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2022
Table 6H.1.--Proposed Secondary Diagnosis Order Deletions to the CC 
Exclusions List--FY 2022
Table 6H.2.--Proposed Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2022
Table 6I.1.--Proposed Additions to the MCC List--FY 2022
Table 6I.2.--Proposed Deletions to the MCC List--FY 2022
Table 6J.1.--Proposed Additions to the CC List--FY 2022
Table 6P.--ICD-10-CM and ICD-10-PCS Codes for Proposed MS-DRG 
Changes--FY 2022 (Table 6P contains multiple tables, 6P.1a. through 
6P.3a that include the ICD-10-CM and ICD-10-PCS code lists relating 
to specific proposed MS-DRG changes. These tables are referred to 
throughout section II.D. of the preamble of this proposed rule.)
Table 7A.--Proposed Medicare Prospective Payment System Selected 
Percentile Lengths of Stay: FY 2019 MedPAR Update March 2020--
GROUPER Version 38 MS-DRGs
Table 7B.--Proposed Medicare Prospective Payment System Selected 
Percentile Lengths of Stay: FY 2019 MedPAR Update March 2020--
GROUPER Version 39 MS-DRGs
Table 8A.--Proposed FY 2022 Statewide Average Operating Cost-to-
Charge Ratios (CCRs) for Acute Care Hospitals (Urban and Rural)
Table 8B.--Proposed FY 2022 Statewide Average Capital Cost-to-Charge 
Ratios (CCRs) for Acute Care Hospitals
Table 16.--Proxy Hospital Value-Based Purchasing (VBP) Program 
Adjustment Factors That Would Apply for FY 2022 If Our Proposals to 
Revise the Scoring and Payment Methodology For That Program Year Are 
Not Finalized
Table 18.--Proposed FY 2022 Medicare DSH Uncompensated Care Payment 
Factor 3

    The following LTCH PPS tables for this FY 2022 proposed 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-P:

Table 8C.--Proposed FY 2022 Statewide Average Total Cost-to-Charge 
Ratios (CCRs) for LTCHs (Urban and Rural)
Table 11.--Proposed 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.--Proposed LTCH PPS Wage Index for Urban Areas for 
Discharges Occurring from October 1, 2021 through September 30, 2022
Table 12B.--Proposed LTCH PPS Wage Index for Rural Areas for 
Discharges Occurring from October 1, 2021 through September 30, 2022
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Appendix A: Economic Analyses

I. Regulatory Impact Analysis

A. Statement of Need

    This proposed rule is necessary in order to make payment and 
policy changes under the Medicare 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 proposed 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.
    We believe that the proposed changes in this proposed rule, such 
as the proposed updates to the IPPS and LTCH PPS rates, and the 
proposals 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 proposed changes would 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 proposed 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.
    We estimate that the proposed changes for FY 2022 acute care 
hospital operating and capital payments would redistribute amounts 
in excess of $100 million to acute care hospitals, and therefore, 
estimate that this rulemaking is ``economically significant'' as 
measured by the $100 million threshold. The proposed applicable 
percentage increase to the IPPS rates required by the statute, in 
conjunction with other proposed payment changes in this proposed 
rule, would result in an estimated $2.5 billion increase in FY 2022 
payments, primarily driven by: (a) A combined $2.2 billion increase 
in FY 2022 operating payments, including uncompensated care 
payments, and (b) a combined increase of $0.3 billion resulting from 
estimated changes in new technology add-on payments, 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 FY 2022 capital payments. These proposed 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 $52 million in 
FY 2022 relative to FY 2021.
    Our operating impact estimate includes the proposed 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 proposed rule. In addition, our 
operating payment impact estimate includes the proposed 2.3 percent 
hospital update to the standardized amount (which includes the 
estimated 2.5 percent market basket update reduced by the proposed 
0.2 percentage point for the multifactor productivity (MFP) 
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 proposed 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 proposed rule would affect payments to a substantial 
number of small rural hospitals, as well as other classes of 
hospitals, and the effects on

[[Page 25743]]

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 proposed 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 proposed changes in this proposed rule would 
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 
proposed changes would ensure that the outcomes of the prospective 
payment systems are reasonable and equitable, while avoiding or 
minimizing unintended adverse consequences.
    Because this proposed rule contains a range of policies, we 
refer readers to the section of the proposed rule where each policy 
is discussed. These sections include the rationale for our 
decisions, including the need for the proposed policy.

D. Limitations of Our Analysis

    The following quantitative analysis presents the projected 
effects of our proposed policy changes, as well as statutory changes 
effective for FY 2022, on various hospital groups. We estimate the 
effects of individual proposed 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 such variables as admissions, lengths of stay, case mix, changes 
to the Medicare population, or incentives. In addition, we discuss 
limitations of our analysis for specific proposed policies in the 
discussion of those proposed 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 proposed 
rule, consistent with our proposed use of the Provider Specific File 
(PSF), we included 3,198 IPPS acute care hospitals in our analysis. 
This represents approximately 54 percent of all Medicare-
participating hospitals. The majority of this impact analysis 
focuses on this set of hospitals. There also are approximately 1,417 
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 proposed changes to the 
prospective payment systems for these IPPS-excluded hospitals and 
units are not included in this proposed rule. The impact of the 
proposed 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 proposed 
rule, consistent with our proposed use of the PSF, there were 95 
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 proposed rate 
updates discussed in this proposed rule. The impacts of the proposed 
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 proposed update of the rate-of-
increase limit (or target amount) is the estimated FY 2022 
percentage increase in the proposed 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 2020 fourth quarter forecast of the 
proposed 2018-based IPPS market basket increase, we are estimating 
the proposed FY 2022 update to be 2.5 percent (that is, the estimate 
of the market basket rate-of-increase), as discussed in section 
IV.A. of the preamble of this proposed rule. We are proposing that 
if more recent data become available for the final rule, we would 
use such data, if appropriate, to calculate the IPPS operating 
market basket update for FY 2022. However, the Affordable Care Act 
requires an adjustment for multifactor productivity (proposed 0.2 
percentage point reduction for FY 2022), resulting in a proposed 2.3 
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 proposed 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 proposed 
update is the percentage increase in the proposed 2018-based IPPS 
operating market basket for FY 2022, estimated at 2.5 percent.
    The impact of the proposed 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 Proposed Policy Changes Under the 
IPPS for Operating Costs

1. Basis and Methodology of Estimates

    In this proposed rule, we are announcing proposed policy changes 
and payment rate updates for the IPPS for FY 2022 for operating 
costs of acute care hospitals. The proposed FY 2022 updates to the 
capital payments to acute care hospitals are discussed in section 
I.I. of this Appendix.
    Based on the overall proposed percentage change in payments per 
case estimated using our payment simulation model, we estimate that 
total FY 2022 operating payments would increase by 2.7 percent, 
compared to FY 2021. In addition to the proposed applicable 
percentage increase, this amount reflects the proposed +0.5 
percentage point permanent

[[Page 25744]]

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 would also affect 
overall payment changes.
    We have prepared separate impact analyses of the proposed 
changes to each system. This section deals with the proposed 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 proposed changes in this proposed rule. As discussed 
in Section I.A of this proposed rule, we believe that the FY 2019 
claims data is the best available data for purposes of the proposed 
FY 2022 ratesetting and this impact analysis reflects the use of 
that data. However, there are other proposed changes for which we do 
not have data available that would allow us to estimate the payment 
impacts using this model. For those proposed 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 
proposed changes in payments per case presented in this section are 
taken from the FY 2019 MedPAR file and are consistent with our 
proposed use of Provider-Specific File (PSF) data, as discussed 
previously in this proposed rule. Although the analyses of the 
proposed 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 proposed 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 proposed 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 proposed payments under the capital IPPS, and the impact 
of proposed 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 discuss the following proposed changes:
     The effects of the application of the proposed 
applicable percentage increase of 2.3 percent (that is, a 2.5 
percent market basket update with a proposed reduction of 0.2 
percentage point for the multifactor productivity adjustment), and a 
proposed 0.5 percentage point adjustment required under section 414 
of the MACRA to the IPPS standardized amount, and the proposed 
applicable percentage increase (including the market basket update 
and the proposed multifactor productivity adjustment) to the 
hospital-specific rates.
     The effects of the proposed changes to the relative 
weights and MS-DRG GROUPER.
     The effects of the proposed 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 proposed FY 2022 wage index.
     The effects of the geographic reclassifications by the 
MGCRB (as of publication of this proposed rule) that will be 
effective for FY 2022.
     The effects of the proposed rural floor with the 
application of the national budget neutrality factor to the wage 
index.
     The effects of the proposed 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 
proposed FY 2022 policies relative to payments based on FY 2021 
policies.
    To illustrate the impact of the proposed 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, we are proposing that, 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 would receive an applicable percentage increase of 1.675 
percent. At the time this impact was prepared, 65 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 proposed 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, we are 
proposing that hospitals that are identified as not meaningful EHR 
users and do submit quality information under section 
1886(b)(3)(B)(viii) of the Act would receive an applicable 
percentage increase of 0.425 percent. At the time this impact 
analysis was prepared, 105 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 
proposed 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 would receive a 
proposed applicable percentage increase of -0.2 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 proposed policy change, statutory or otherwise, is then 
added incrementally to this baseline, finally arriving at an FY 2022 
model incorporating all of the proposed changes. This simulation 
allows us to isolate the effects of each change.
    Our comparison illustrates the proposed 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 proposing to update the 
standardized amounts for FY 2022 using a proposed applicable 
percentage increase of 2.3 percent. This includes our forecasted 
IPPS operating hospital market basket increase of 2.5 percent with a

[[Page 25745]]

proposed 0.2 percentage point reduction for the multifactor 
productivity adjustment. Hospitals that fail to comply with the 
quality data submission requirements and are meaningful EHR users 
would receive a proposed update of 1.675 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 proposed update of 0.425 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 a proposed update of -0.2 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 2.3 percent, if the hospital submits quality data and 
is a meaningful EHR user.
    A second significant factor that affects the proposed 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 proposed 
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 3,198 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 739 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.
    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 1,965, and 1,233, 
respectively.
    The next three groupings examine the impacts of the proposed 
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 2,034 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 proposed changes 
on rural hospitals by special payment groups (SCHs, MDHs and RRCs). 
There were 555 RRCs, 304 SCHs, 148 MDHs, 151 hospitals that are both 
SCHs and RRCs, and 24 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.
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[[Page 25748]]


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BILLING CODE 4120-01-C

a. Effects of the Proposed Hospital Update and Other Proposed 
Adjustments (Column 1)

    As discussed in section IV.A. of the preamble of this proposed 
rule, this column includes the proposed hospital update, including 
the proposed 2.5 percent market basket update reduced by the 
proposed 0.2 percentage point for the multifactor productivity 
adjustment. In addition, as discussed in section II.D. of the 
preamble of this proposed rule, this column includes the FY 2022 
+0.5 percentage point adjustment required under section 414 of the 
MACRA. As a result, we are proposing to make a 2.8

[[Page 25749]]

percent update to the national standardized amount. This column also 
includes the proposed update to the hospital-specific rates which 
includes the proposed 2.5 percent market basket update reduced by 
the proposed 0.2 percentage point for the multifactor productivity 
adjustment. As a result, we are proposing to make a 2.3 percent 
update to the hospital-specific rates.
    Overall, hospitals would experience a 2.8 percent increase in 
payments primarily due to the combined effects of the proposed 
hospital update to the national standardized amount and the proposed 
hospital update to the hospital-specific rate. Hospitals that are 
paid under the hospital-specific rate would experience a 2.3 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 Proposed Changes to the MS-DRG Reclassifications and 
Relative Cost-Based Weights With Recalibration Budget Neutrality 
(Column 2)

    Column 2 shows the effects of the proposed changes to the MS-
DRGs and relative weights with the application of the proposed 
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 proposed 
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 proposed 
rule, the FY 2022 MS-DRG relative weights will be 100 percent cost-
based and 100 percent MS-DRGs. For FY 2022, we are proposing to 
calculate the MS-DRGs using the FY 2019 MedPAR data grouped to the 
proposed Version 39 (FY 2022) MS-DRGs. The methodology to calculate 
the proposed relative weights and the reclassification changes to 
the GROUPER are described in more detail in section II.G. of the 
preamble of this proposed rule.
    The ``All Hospitals'' line in Column 2 indicates that proposed 
changes due to the MS-DRGs and relative weights would result in a 
0.0 percent change in payments with the application of the proposed 
recalibration budget neutrality factor of 1.000098 to the 
standardized amount.

c. Effects of the Proposed Wage Index Changes (Column 3)

    Column 3 shows the impact of the proposed updated wage data 
using FY 2018 cost report data, with the application of the proposed 
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 proposed 
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 proposed payment parameters constant 
in this simulation. That is, Column 3 shows the proposed 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 proposed 
FY 2022 pre-reclassification wage index based on FY 2018 wage data 
with the proposed 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 
proposed 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 proposed 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 
proposing to calculate the proposed wage budget neutrality factor to 
ensure that payments under updated wage data and the proposed 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 proposed FY 2022 wage budget neutrality factor is 
1.000277 and the overall proposed 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 proposed 
labor-related share, combined with the proposed wage budget 
neutrality adjustment, would 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 2.5 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 proposed 2.5 percent increase in 
the national average hourly wage. Of the 3,140 hospitals with wage 
data for both FYs 2021 and 2022, 1,628 or 52 percent would 
experience an average hourly wage increase of 2.5 percent or more.
    The following chart compares the shifts in wage index values for 
hospitals due to proposed changes in the average hourly wage data 
for FY 2022 relative to FY 2021. These figures reflect proposed 
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 
proposed 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) 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 proposed pre-
reclassified wage index figures in the following chart may 
illustrate a somewhat larger or smaller proposed change than would 
occur in a hospital's payment wage index and total payment.
    The following chart shows the projected impact of proposed 
changes in the area wage index values for urban and rural hospitals.

[[Page 25750]]

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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 proposed 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 proposed 
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 proposing to apply an 
adjustment of 0.987018 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 proposed rule). As noted elsewhere in this proposed 
rule, concurrent with this proposed rule, CMS has made publicly 
available 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). Also as noted elsewhere in this proposed rule, if certain 
hospitals receive higher wage indexes as a result of settlement or 
other resolution of pending litigation, we intend to include any 
amounts they receive by reason of those higher wage indexes in the 
calculation of the budget neutrality factor. If these hospitals do 
receive a higher wage index at the time of the final rule than they 
might otherwise have received, we estimate the FY 2022 budget 
neutrality adjustment could increase by as much as approximately 
one-half of a percentage point compared to the budget neutrality 
adjustment that might otherwise have been calculated.
    Geographic reclassification generally benefits hospitals in 
rural areas. We estimate that the geographic reclassification would 
increase payments to rural hospitals by an average of 1.1 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 proposed 
rule and available via the internet on the CMS website reflects the 
reclassifications for FY 2022.

e. Effects of the Proposed 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 proposed 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 proposed 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 proposed FY 2022 rural floor budget neutrality factor 
to be applied to the wage index of 0.993988, which would reduce wage 
indexes by 0.6 percent.
    Column 5 shows the projected impact of the proposed 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 proposed post-reclassification FY 2022 wage 
index of providers before the rural floor adjustment and the 
proposed 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 287 hospitals would receive the rural floor in 
FY 2022. All IPPS hospitals in our model would have their wage 
indexes reduced by the proposed rural floor budget neutrality 
adjustment of 0.993988. We project that, in aggregate, rural 
hospitals would experience a 0.2 percent decrease in payments as a 
result of the application of the proposed 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 2.7 
percent increase in payments primarily due to the application of the 
rural floor in Massachusetts.

f. Effects of the Application of the Proposed Frontier State Wage Index 
and Proposed Out-Migration Adjustment (Column 6)

    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

[[Page 25751]]

neutral and is estimated to increase IPPS operating payments by 
approximately $68 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 
184 providers that would 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 would be approximately $40 million.

g. Effects of All FY 2022 Proposed Changes (Column 7)

    Column 7 shows our estimate of the proposed changes in payments 
per discharge from FY 2021 and FY 2022, resulting from all changes 
reflected in this proposed rule for FY 2022. It includes combined 
effects of the year-to-year change of the previous columns in the 
table.
    The proposed average increase in payments under the IPPS for all 
hospitals is approximately 2.7 percent for FY 2022 relative to FY 
2021 and for this row is primarily driven by the proposed changes 
reflected in Column 1. Column 7 includes the proposed annual 
hospital update of 2.8 percent to the national standardized amount. 
This proposed annual hospital update includes the proposed 2.5 
percent market basket update reduced by the proposed 0.2 percentage 
point multifactor productivity adjustment. As discussed in section 
II.D. of the preamble of this proposed 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 2.3 percent hospital update. As described in Column 
1, the proposed annual hospital update with the proposed +0.5 
percent adjustment for hospitals paid under the national 
standardized amount, combined with the proposed annual hospital 
update for hospitals paid under the hospital-specific rates, would 
result in a 2.7 percent increase in payments in FY 2022 relative to 
FY 2021. 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 proposed changes in payments per 
discharge from FY 2021 and FY 2022 in Column 7.
    Overall payments to hospitals paid under the IPPS due to the 
proposed applicable percentage increase and proposed changes to 
policies related to MS-DRGs, geographic adjustments, and outliers 
are estimated to increase by 2.7 percent for FY 2022. Hospitals in 
urban areas would experience a 2.7 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 2.9 percent in 
FY 2022.

3. Impact Analysis of Table II

    Table II presents the projected impact of the proposed 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 
proposed 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 proposed 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 proposed policy changes discussed 
previously that we are able to model using our IPPS payment 
simulation model, we are proposing to make various other changes in 
this proposed 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 proposed 
changes in this proposed rule. Generally, we have limited or no 
specific data available with which to estimate the impacts of these 
proposed changes using that payment simulation model. For those 
proposed 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 proposed changes 
are discussed in this section.

1. Effects of Proposed Policies Relating to New Medical Service and 
Technology Add-On Payments and New COVID-19 Treatments Add-on Payment 
(NCTAP)

a. Proposed FY 2022 Status of Technologies Approved for FY 2021 New 
Technology Add-On Payments

    In section II.F.4. of the preamble of this proposed rule, we are 
proposing to continue to make new technology add-on payments for 
BAROSTIM NEO System, BALVERSATM, Jakafi[supreg], 
FETROJA[supreg], Optimizer[supreg] System, RECARBRIOTM, 
Soliris[supreg], XENLETATM, 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 proposing 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: 
AndexXaTM, AZEDRA[supreg], 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 readers to section II.F. of the 
preamble of this proposed rule with regard to our proposal for a 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 
proposed 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 proposing to continue to make new 
technology add-on payments in FY 2022:
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b. Proposed FY 2022 Applications for New Technology Add-On Payments

    In sections II.F.5. and 6. of the preamble to this proposed 
rule, we discuss 37 technologies for which we received applications 
for add-on payments for new medical services and technologies for FY 
2022. We note that five applicants withdrew their application prior 
to the issuance of this proposed rule. As explained in the preamble 
to this proposed 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 proposed 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

[[Page 25755]]

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 
proposed rule, we are proposing to approve 14 of the 16 alternative 
pathway applications for FY 2022 new technology add-on payments. We 
note that for one technology, the 3-year anniversary date of the 
product's entry onto the U.S. market will occur in FY 2021, and 
therefore we do not believe that the device is eligible for new 
technology add-on payments for FY 2022. We also note that another 
technology does not appear to include any operating costs and 
therefore no new technology add-on payment would be made because, as 
discussed in prior rulemaking and noted previously, we only make new 
technology add-on payments for operating costs (72 FR 47307 and 
47308).
    Based on preliminary information from the applicants at the time 
of this proposed rule, we estimate that total payments for the 16 
technologies that applied under the alternative pathway, if 
approved, would be approximately $80 million for FY 2022. Total 
estimated FY 2022 payments for new technologies that are designated 
as a QIDP would be approximately $58 million, and total estimated FY 
2022 payments for new technologies that are part of the Breakthrough 
Device program would be approximately $22 million. We note that 
these estimated payments may be updated in the final rule based on 
revised or additional information CMS receives prior to the final 
rule.
    We have not yet determined whether any of the 21 technologies 
that applied under the traditional pathway discussed in section 
II.F.5. of the preamble of this proposed rule will meet the criteria 
for new technology add-on payments for FY 2022. Consequently, it is 
premature to estimate the potential payment impact of these 21 
technologies for any potential new technology add-on payments for FY 
2022. We note that, as in past years, if any of the 21 technologies 
that applied under the traditional pathway are found to be eligible 
for new technology add-on payments for FY 2022, in the FY 2022 IPPS/
LTCH PPS final rule, we would discuss the estimated payment impact 
for FY 2022.

c. Proposed Changes to FY 2022 New COVID-19 Treatments Add-On Payment 
(NCTAP)

    As discussed in section II.F. of the preamble of this proposed 
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 proposed rule we are proposing 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 are 
proposing 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.
    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 proposed 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 
proposed 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 Proposed Changes to Medicare DSH and Uncompensated 
Care Payments for FY 2022

a. Proposed Revision of the Regulations To Ensure Only Appropriate Days 
Are Counted in the Numerator of the Medicaid Fraction

    As discussed in section V.F. of the preamble of this proposed 
rule, we are proposing to revise the regulation governing the DSH 
calculation to ensure that the only section 1115 days that may be 
counted in the numerator of the Medicaid fraction are the days of 
patients for whom a section 1115 waiver provides inpatient hospital 
insurance coverage benefits directly to that patient on that day. To 
the extent that this proposal has an impact on expenditures, that 
impact is not estimable because we do not have information on the 
number of section 1115 days by hospital, which would be required to 
make an estimate.

b. Medicare DSH Uncompensated Care Payment Proposals for FY 2022

    As discussed in section V.E. of the preamble of this proposed 
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 proposed rule, we are proposing to establish the amount 
to be distributed as uncompensated care payments to DSH eligible 
hospitals, which for FY 2022 is $7,627,628,282.10. This figure 
represents 75 percent of the amount that otherwise would have been 
paid for Medicare DSH payment adjustments adjusted by a proposed 
Factor 2 of 72.14 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 will use 
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 proposing to use 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 proposed methodology for 
calculating Factor 3, we refer readers to section V.E.4. of the 
preamble of this proposed rule.
    To estimate the impact of the combined effect of proposed 
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 
proposed 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 absent section 3133 of the 
Affordable Care Act, adjusted by a proposed Factor 2 of 72.14 
percent and multiplied by a Factor 3 calculated using the 
methodology described previously.
    Our analysis included 2,378 hospitals that are projected to be 
eligible for DSH in FY 2022. It did not include hospitals that had 
terminated their participation from the Medicare program as of 
January 28, 2021, Maryland hospitals, new hospitals, MDHs, and SCHs 
that are expected to be paid based on their hospital-specific rates. 
The 27 hospitals participating in the Rural Community Hospital 
Demonstration Program were excluded from this analysis, as

[[Page 25756]]

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 proposed 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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    The changes in projected FY 2022 uncompensated care payments 
from payments in FY 2021 are driven by a proposed decrease in Factor 
1 and a proposed 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. The proposed Factor 1 has decreased 
from FY 2021 final rule's Factor 1 of $11.378 billion to this 
proposed rule's Factor 1 of $10.573 billion, while the proposed 
percent change in the percent of individuals who are uninsured 
(Factor 2) has decreased from 72.86 percent to 72.14 percent. Based 
on the proposed changes in these two factors, the impact analysis 
found that, across all projected DSH eligible hospitals, proposed FY 
2022 uncompensated care payments are estimated at approximately 
$7.628 billion, or a proposed decrease of approximately 7.99 percent 
from FY 2021 uncompensated care payments (approximately $8.290 
billion). While these proposed changes would 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 proposed changes in Factor 3. As seen in the previous table, a 
percent change of less than negative 7.99 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 7.99 percent 
indicates that a hospital type is projected to have a smaller 
decrease than the overall average. Similarly, a positive percent 
change indicates an increase in uncompensated care payments. 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.

[[Page 25758]]

    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 an 
11.27 percent decrease in uncompensated care payments, while urban 
hospitals are projected to receive a 7.79 percent decrease in 
uncompensated care payments.
    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 a 14.02 percent 
payment decrease, and rural hospitals with 100-249 beds are 
projected to receive a 9.86 percent decrease. These decreases for 
smaller rural hospitals are greater than the overall hospital 
average. However, larger rural hospitals with 250+ beds are 
projected to receive a smaller than average payment decrease of 1.57 
percent. This trend is consistent among urban hospitals, with the 
smallest urban hospitals, those with 0-99 and 100-249 beds, 
projected to receive a decrease in uncompensated care payments that 
is greater than the overall hospital average, at 9.61 and 10.42 
percent, respectively. In contrast, the largest urban hospitals with 
250+ beds are projected to receive a 6.80 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 an increase of 4.68 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 4.46 
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, as well as 
urban hospitals in Puerto Rico, 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 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 7.61 percent decrease in 
uncompensated care payments, hospitals in large urban areas are 
expected to see a decrease in uncompensated care payments of 8.47 
percent, while hospitals in other urban areas are expected to 
receive a decrease in uncompensated care payments of 5.99 percent. 
Rural hospitals are projected to receive the largest decrease of 
8.72 percent.
    Nonteaching hospitals are projected to receive a payment 
decrease of 7.55 percent, teaching hospitals with fewer than 100 
residents are projected to receive a payment decrease of 8.01 
percent, and teaching hospitals with 100+ residents have a projected 
payment decrease of 8.33 percent. All of these decreases closely 
approximate the overall hospital average. Proprietary and voluntary 
hospitals are projected to receive smaller than average decreases of 
6.40 and 7.34 percent respectively, while government hospitals are 
expected to receive a larger payment decrease of 9.94 percent. All 
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 15.17 and 
27.46 percent, respectively.

3. Effects of Proposed Reductions Under the Hospital Readmissions 
Reduction Program for FY 2022

    In section V.G. of the preamble of this proposed rule, we 
discuss our proposed 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 proposed rule illustrate the estimated financial 
impact of the Hospital Readmissions Reduction Program payment 
adjustment methodology by hospital characteristic. For the purpose 
of modeling the proposed FY 2022 payment adjustment factors for this 
proposed rule, we used the payment adjustment factors from the FY 
2021 Hospital Readmissions Reduction Program and the FY 2021 
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, 2016 and 
June 30, 2019 (that is, the FY 2021 Hospital Readmissions Reduction 
Program's performance period). 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 the FY 2022 IPPS/LTCH 
PPS final rule, we will 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 (that 
is, July 1, 2017 through June 30, 2020). 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) waiver which excluded data from January 1, 2020 through June 
30, 2020 from the Hospital Readmissions Reduction Program 
calculations.\1527\
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    \1527\ 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.
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    The results in the table include 2,986 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, 2016 
and June 30, 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, 82.17 percent of eligible 
hospitals characterized as non-teaching hospitals are expected to be 
penalized. Among teaching hospitals, 89.70 percent of eligible 
hospitals with fewer than 100 residents and 92.64 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 October 
1, 2018 and September 30, 2019 (FY 2019). For example, the penalty 
as a share of payments for urban hospitals is 0.68 percent. This 
means that total penalties for all urban hospitals are 0.68 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.

[[Page 25759]]

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[[Page 25760]]


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4. Effects of Proposed Changes Under the FY 2022 Hospital Value-Based 
Purchasing (VBP) Program

    In section V.H. of the preamble of this proposed 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 proposing 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 to change the 
scoring and payment methodologies for the FY 2022 program year, such 
that the hospital would 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 are proposing that we will calculate the measure 
rates for all of the measures we have selected for the FY 2022 
program year, but that we would not generate achievement or 
improvement points for any of the measures we are proposing to 
suppress. Additionally, we are proposing to not award domain scores 
for the Person and Community Engagement, Efficiency and Cost 
Reduction, and Safety domains. Therefore, we would not award 
hospitals a TPS, and would 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 would 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. If these proposals are finalized, 
the impact for every hospital under the Hospital VBP Program would 
be a net percentage payment adjustment of zero.
    We are also providing the estimated impact of the FY 2022 
program because those impacts would apply if the proposals, as 
previously discussed, are not finalized. We used TPSs from FY 2021 
to calculate the proxy adjustment factors used for this impact 
analysis. We note that these FY 2021 TPSs were calculated using 
measure data from before the COVID-19 PHE was declared, and that if 
our proposals are not finalized, actual TPSs for the FY 2022 program 
year could be more variable than the FY 2021 TPSs due to the impacts 
of the COVID-19 PHE on FY 2022 data. These are the most recently 
available scores that hospitals were given an opportunity to review 
and correct. The proxy adjustment factors use estimated annual base 
operating DRG payment amounts derived from the December 2020 update 
to the FY 2020 MedPAR file. The proxy adjustment factors can be 
found in Table 16 associated with this proposed rule (available via 
the internet on the CMS website). This impact analysis shows that, 
for the FY 2022 program year, the number of hospitals that would 
receive an increase in their base operating DRG payment amount is 
lower than the number of hospitals that would receive a decrease. On 
average, urban hospitals in the New England region and rural 
hospitals in the East South Central region would have the highest 
positive percentage change in base operating DRG. Hospitals in the 
Urban Middle Atlantic, Urban South Atlantic, Urban West South 
Central, Rural New England, Rural Middle Atlantic, Rural South 
Atlantic, and Rural West South Central regions would experience an 
average negative percent change in base operating DRG. All other 
regions, both urban and rural, would experience an average positive 
percent change in base operating DRG payment amounts.
    As DSH patient percent increases, the average percent change in 
the base operating DRG payment amounts would generally increase 
(excluding DSH Percent = 50-65, for which the average percent change 
in the base operating DRG payment amounts would be lower than the 
average percent change in the base operating DRG payment amounts for 
all

[[Page 25761]]

other categories). With respect to hospitals' Medicare utilization 
as a percent of inpatient days (MCR), as the MCR percent increases, 
the average percent change in the base operating DRG payment amounts 
would generally increase. On average, non-teaching hospitals would 
have a lower percentage change in their base operating DRG payment 
amounts compared to teaching hospitals; however, on average, both 
non-teaching hospitals and teaching hospitals would have a positive 
percentage change in their base operating DRG payment amounts.
[GRAPHIC] [TIFF OMITTED] TP10MY21.354


[[Page 25762]]


[GRAPHIC] [TIFF OMITTED] TP10MY21.355

    The actual FY 2022 program year's TPSs would not be reviewed and 
corrected by hospitals until after the FY 2022 IPPS/LTCH PPS final 
rule has been published. Therefore, the same historical universe of 
eligible hospitals and corresponding TPSs from the FY 2021 program 
year would be used for the updated impact analysis in the final 
rule, if the proposals, as previously described, for FY 2022 are not 
finalized.
    We note that we are also proposing to suppress the MORT-30-PN 
measure for the FY 2023 program year. If this proposal is finalized, 
we would calculate the measure rate for the MORT-30-PN program year,

[[Page 25763]]

however, we would not generate achievement or improvement points for 
that measure. At this time, we have not proposed to suppress any 
other measures for the FY 2023 program year. Therefore, we are not 
proposing any changes to the scoring methodology for the FY 2023 
program in this 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. We are also proposing to remove the CMS PSI 90 measure 
beginning with the FY 2023 program year. However, because we are 
proposing to remove this measure before it would be used in 
calculating a hospital's TPS under the Hospital VBP Program, we do 
not expect this proposal will have impacts for the FY 2023 program 
year.

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 two tables. These FY 2022 HAC 
Reduction Program 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 tables in this section present the estimated proportion 
of hospitals in the worst-performing quartile of Total HAC Scores by 
hospital characteristic. The first table shows the estimated 
proportion of hospitals in the worst-performing quartile of Total 
HAC Scores using the proposed one-year performance period for the 
HAI measures if the measure suppression policy proposed in section 
IX.I.3.d. of the preamble of this proposed rule is finalized and 
adopted for the FY 2022 program year. The second table shows the 
estimated proportion of hospitals in the worst-performing quartile 
of Total HAC Scores using the previously finalized two-year 
performance period for the HAI measures.
    The first 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, 2016 and 
December 31, 2017 and version 9.0 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, 2017 and December 31, 2017. 
These results are based on the FY 2020 Final Rule Impact Table and 
estimate the impacts of the measure suppression policy by excluding 
6 months of CMS PSI 90 data and 12 months of CDC measure data. For 
the second table, hospitals' CMS PSI 90 measure results are based on 
Medicare fee-for-service (FFS) discharges from July 1, 2018 through 
December 31, 2019 \1528\ and version 11.0 of the PSI software. 
Hospitals' measure results for CDC CLABSI, CAUTI, Colon and 
Abdominal Hysterectomy SSI, MRSA bacteremia, and CDI measures are 
derived from standardized infection ratios (SIRs) calculated with 
hospital surveillance data reported to the NHSN for infections 
occurring between January 1, 2018 and December 31, 2019. To analyze 
the results by hospital characteristic, we used the FY 2021 Final 
Rule Impact File. Both tables are based on historical data and may 
not reflect the actual impacts of the COVID-19 PHE.
---------------------------------------------------------------------------

    \1528\ Although the FY 2022 applicable period for the CMS PSI 90 
measure is July 1, 2018 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 public health emergency. CMS, ``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.
---------------------------------------------------------------------------

    While both tables are presented in this section and their format 
is the same, we use values from the first table in this text as an 
examples because the length of data periods match the measure 
suppression policy proposed in section IX.I.3.d. of the preamble of 
this proposed rule. The table includes 3,169 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, with regard to teaching status, 475 hospitals out of 1,988 
hospitals characterized as non-teaching hospitals would be subject 
to a payment reduction. Among teaching hospitals, 199 out of 891 
hospitals with fewer than 100 residents and 103 out of 260 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, 23.9 
percent of the 1,988 hospitals characterized as non-teaching 
hospitals, 22.3 percent of the 891 teaching hospitals with fewer 
than 100 residents, and 39.6 percent of the 260 teaching hospitals 
with 100 or more residents would be subject to a payment reduction.

[[Page 25764]]

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[[Page 25767]]


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6. Effects of the Proposed Changes to IME and Direct GME Payments

    The Consolidated Appropriations Act (CAA) of 2020 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, with 200 slots to be distributed in 5 
rounds over 5 years starting in FY 2023, with priority given to 
hospitals in 4 categories. Section 127 of the CAA, effective for 
cost reporting periods beginning on or after October 1, 2022, makes 
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, and the application of the 3-year rolling average to 
the payment calculation of these hospitals. Section 131 of the CAA 
makes 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, based on new programs started on 
or after enactment (December 27, 2020) and 5 years after (December 
26, 2025). We provide detailed proposals for implementing these 3 
CAA provisions in section V.J.2. of this proposed rule. Following is 
a table showing the estimated cost of implementation of these 3 CAA 
provisions:

[[Page 25768]]

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    In section V.J.2.d. of the preamble of this proposed rule, we 
also are proposing that, effective for cost reporting periods 
beginning on or after October 1, 2021, a cost report is rejected for 
teaching hospitals for lack of supporting documentation if it does 
not include the IRIS data that 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 FTE and IME FTE 
residents reported in the teaching hospital's cost report. This 
proposal would continue to require all teaching hospitals to submit 
the IRIS data under Sec.  413.24(f)(5) to have an acceptable cost 
report submission. However, this proposal would require that this 
data must correspond to 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 
teaching hospital's cost report. Providers are required under 
Sec. Sec.  413.20 and 413.24 to maintain data that substantiates 
their costs. IRIS is the source document for reporting FTEs in all 
teaching hospitals' cost reports. To enhance the contractors' 
ability to review duplicates and to ensure residents are not being 
double counted, we believe it is necessary and appropriate to 
require that the total unweighted and weighted 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 unweighted and 
weighted FTE counts for direct GME and IME reported on Worksheet E-4 
and Worksheet E, Part A. Because all teaching hospitals are already 
required to submit the IRIS data under Sec.  413.24(f)(5) to have an 
acceptable cost report submission, there are no additional burdens 
or expenses placed upon teaching hospitals as a result of our 
proposal to require that the supporting documents submitted (the 
IRIS data) correspond to the amounts reported in the cost report in 
order to have an acceptable cost report submission.

7. Effects of Implementation of the Rural Community Hospital 
Demonstration Program in FY 2022

    In section V.K. of the preamble of this proposed 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. Therefore, we 
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 propose to adopt the general 
methodology used in previous years, whereby we estimated the 
additional payments made by the program for each of the 
participating hospitals as a result of the demonstration, and then 
adjusted the national IPPS rates by an amount sufficient to account 
for the added costs of this demonstration. In other words, we have 
applied 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 proposed rule, the resulting amount applicable to FY 
2022 is $63,829,479, 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 not 
yet all available for the 18 hospitals that completed a cost 
reporting period beginning in FY 2016 according to the demonstration 
cost-based payment methodology. We are expecting to include in the 
FY2022 IPPS/LTCH PPS final rule the difference between the actual 
costs of the demonstration as determined from these cost repots and 
the estimated costs as determined in the FY 2016 final rule.

[[Page 25769]]

    For this proposed rule for FY 2022, the total amount that we are 
applying to the national IPPS rates is $63,829,479.

8. Effects of the Proposed Repeal of the Market-Based MS-DRG Relative 
Policy

    In section V.L. of the preamble of this proposed rule, we are 
proposing 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. We are also proposing to repeal the market-based MS-DRG 
relative weight methodology that was adopted effective for FY 2024, 
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, is effective 
beginning with the relative weights calculated for FY 2024. If we 
were to finalize our proposal to repeal the market-based MS-DRG 
relative weight methodology effective in FY 2024, we would continue 
calculating the MS-DRG relative weights using the current cost-based 
MS-DRG relative weight methodology for FY 2024 and subsequent fiscal 
years. If finalized, this proposed repeal of the market-based data 
collection and market-based relative weight methodology would not 
result in a payment impact to hospitals and would instead decrease 
burden for hospitals required to comply with the market-based MS-DRG 
relative weight data collection requirement.

9. Effects of Continued Implementation of the Frontier Community Health 
Integration Project (FCHIP) Demonstration

    In section VII.B.2. of the preamble of this proposed we discuss 
the implementation of the FCHIP demonstration, which allows 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). Thus, the FCHIP 
Demonstration will resume on July 1, 2021, 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 July 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, we will 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 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 proposing 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.

10. Effects of the Proposed 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 proposed rule, we 
discuss our proposals 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.
    All states require providers to enroll in Medicaid in order to 
process a Medicaid claim, including one for Medicare cost-sharing. 
However, some Medicare providers and suppliers have experienced 
difficulty enrolling in a State's Medicaid program and submitting 
claims 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 proposing to add 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

[[Page 25770]]

(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.
    There are three areas where this provision 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 
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 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 State plan rate. 
Lastly, states can pay at a negotiated rate.
    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. Given this, and that the states that would 
be impacted by this proposal are those that have not enrolled 
certain Medicare provider types, it seems plausible that these 
states would choose to elect lesser-of payment policies for these 
newly enrolled provider types, generally limiting new cost-sharing 
liability to zero. However, because states have the flexibility 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 State plan 
elections.

a. Updating State Medicaid Systems With Other Provider Types and Cost-
Sharing Logic

    To estimate the costs of this proposal, we note that Medicare 
LTCHs are an example of a Medicare-enrolled provider that is most 
notably not an explicit provider type in Medicaid. Therefore, we 
assume that 26 states will need to make systems changes to implement 
the proposal if finalized since this is the number of states named 
in the Select Specialty Hospital--Denver, et al. v. Azar case in 
which 77 LTCHs from 26 states appealed the denial of claims for 
Medicare bad debt because the LTCHs were unable to furnish a 
Medicaid remittance advice. While there may be other states or 
territories that do not enroll other provider types, such as 
Comprehensive Outpatient Rehabilitation Facilities (CORFs), we have 
less information on this circumstance and, for the purposes of this 
analysis, assume that the 26 states included in the LTCH litigation 
are the same states that may not be enrolling these other provider 
types. As such, we have estimated a one-time burden for 26 State and 
territory Medicaid programs to comply with the provider enrollment 
requirement as proposed. 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. Since we 
estimate that 26 states and territories would need to make changes, 
we project an aggregate burden of $1,111,469 (26 states * 960 hours 
of programming work * $44.53/hour) and a cost per State of 
approximately $42,749 (960 * $44.53 = $42,749). The cost and time 
attributable to this systems change will be influenced by whether 
the State is implementing other enrollment systems changes at the 
same time. Assuming the State implements this change in isolation, 
we estimate that this change could take 6 months. However, if a 
State makes this change as a part of a broader enrollment systems 
update, the work specific to proposal could be minimal. We note that 
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 proposed rule, we assume there will be 17 months 
between when we expect to publish a 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 proposed rule. States would have the ability to choose, in 
consultation with CMS, when in the 17-month implementation period 
they want to make this change. For the purposes of this impact 
analysis, we estimated a uniform distribution beginning in August 
2021 and ending in January 2023. As noted previously, the total cost 
impact over 17 months is $1,111,469, when apportioned uniformly over 
the 17 months, the resulting impacts are $322,326 and $789,143 for 
2021 and 2022 respectively corresponding to 5 months and 12 months 
in 2021 and 2022, respectively. We solicit comment on Medicaid costs 
of systems updates related to this proposal.

b. New Providers and Suppliers Enrolling in State Medicaid Systems

    Currently, there are 363 LTCHs across the United States, and our 
understanding is that at least half are in a Core Based Statistical 
Area (CBSA) in which the states currently enroll LTCHs. If half of 
LTCHs are able to newly enroll with their State Medicaid program, we 
estimate enrollment will take an average of three to six hours for 
an LTCH office manager, at a BLS mean hourly rate of $28.91 per 
hour, to complete so would cost between $86.73 and $173.46 for each 
LTCH (3 to 6 hours * $28.91/hr). Therefore, we estimate this will 
cost LTCHs between $15,611 and $31,223 ($86.73 to $173.46 * 180 
LTCHs) in aggregate. We assume that, on average, it will take states 
a similar amount of time to review and process these enrollment 
applications, though we know that some applications can be 
adjudicated quickly through automated processes, and others will 
need manual review. We estimate states will need to process 
enrollment applications for 180 LTCHs, across 26 states, for a total 
costs of between $15,611 and $31,223, or $600 to $1,200 per State 
($15,611 to $31,223/26 states). While this proposal may also impact 
other provider and supplier types, such as CORFs, we are uncertain 
how many of these provider types will be able to newly enroll in 
Medicaid as a result of this proposal. We solicit comment on the 
enrollment application and processing impacts related to this 
proposal.

c. Reducing Medicare Bad Debt Appeals

    This proposed rule will not affect existing bad debt appeals. 
However, we believe the proposed rule may reduce the number of 
future bad debt appeals by ensuring certain Medicare-enrolled 
providers, such as LTCHs, can enroll with State Medicaid programs, 
receive Medicaid Remittance Advice (RA), and claim Medicare bad 
debt. In eliminating these appeals, the proposal would eliminate 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 Medicare cost savings from avoiding future Medicare bad 
debt appeals. As noted previously, we are unable to estimate a 
reduction in Medicare bad debt payments that would result from an 
increase in State payment of Medicare LTCH cost-sharing because 
states have flexibility to choose their cost-sharing payment 
methodology for different provider types in their 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 resolution of the Select Specialty 
Hospital--Denver, et al. v. Azar case, which included claims from 77 
LTCHs in 26 states from 2005 to 2010, helps us better understand the 
potential appeal-related costs avoided if we finalize this proposal.
    Medicare Hospital Insurance Trust Fund Payments. After an 
adverse decision for CMS, the Federal government ultimately paid the 
plaintiffs a total of $23,649,492, which included the principle 
amount of $18,656,588 for the payment of bad debt claims that had 
been denied, plus associated

[[Page 25771]]

interest of $4,992,904. In determining the principle amount to be 
paid, it was difficult for CMS to retroactively determine State 
liability for cost-sharing, if any, in order to deduct that amount 
from the amount claimable as bad debt. If finalized, this proposal 
would help ensure that the amount paid for bad debt accurately 
reflects State liability. Additionally, by reducing the need for bad 
debt appeals and litigation, it would also eliminate costs 
associated with interest, should future cases be decided similarly 
to Select Specialty Hospital--Denver, et al. v. Azar.
    Litigation costs. In the Specialty Hospital--Denver, et al. v. 
Azar case, the plaintiffs sought $1,174,000 in total costs of 
attorney's 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 LTCHs.
    The Federal government also bears significant costs to process 
and defend these appeals and subsequent litigation: The MAC and the 
Federal Specialized Service prepare the documentation to present at 
the PRRB; the PRRB prepares the case for the hearing and prepares 
and issue 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; the 
Office of General Council prepares and files the appropriate 
documentation to hear the court case which may also involve 
components of the U.S. Department of Justice; and the Office of 
General Council defends the case, and if necessary, works with CMS 
to determine an appropriate settlement that the MAC then implements. 
Currently, there are at least 20 open cases before CMS for the same 
issue ruled on in the Select Specialty Hospital--Denver case, 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.
    If this proposal is not finalized, it is likely that appeals on 
this issue, and their associated costs for Medicare providers and 
for the Federal government described previously, would continue into 
the future. We solicit comment on the cost and savings related to 
appeals resulting from this proposed policy.
    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 maximum $31,223 in aggregate spending 
for providers and suppliers to enroll with State Medicaid programs, 
and the maximum $31,223 for states to process those applications, as 
well as the $1,111,469 in aggregate spending for states to update 
the State Medicaid systems, which will likely be eligible for 90/10 
FMAP, as described previously.

11. Effects of the Proposed Organ Acquisition Payment Policy

    In section X.B.2. of the preamble of this proposed rule, we are 
proposing to codify into the Medicare regulations some longstanding 
Medicare organ acquisition payment policies, with clarifications 
where necessary, and proposing to codify some new organ acquisition 
payment policies. Specifically, in section X.B.2.h. of the preamble 
of this proposed rule, we are proposing to revise and codify the 
Medicare organ counting policy to more accurately record and pay 
Medicare's share of organ acquisition costs. Additionally in section 
X.B.2.l. of the preamble of this proposed rule, we are proposing to 
revise and codify the policy for donor community hospital (Medicare-
certified non-transplant hospitals) charges for services provided to 
organ procurement organizations. In section X.B.2.m. of the preamble 
of this proposed rule, we are also proposing to make technical 
corrections, clarifications, conforming changes, and redesignations 
in the regulations. Finally, in section X.B.3. of the preamble of 
this proposed rule, we are soliciting comments on the existing cap 
on surgeon fees for cadaveric kidney excisions.
    As a result of our proposal to codify certain longstanding organ 
acquisition payment policies into the regulations, there would be no 
additional costs to the Medicare program and no increased burden 
placed upon transplant hospitals, OPOs or other stakeholders. 
Likewise, there would be no costs or savings to the Medicare program 
from the technical corrections, clarifications, conforming changes, 
or redesignations of some regulations. There would also be no costs 
or savings to the Medicare program from the comment solicitation 
related to surgeon fees.
    As a result of our proposal to revise and codify the Medicare 
usable organ counting policy to count only organs transplanted into 
Medicare beneficiaries so that Medicare more accurately records and 
pays its share of organ acquisition costs, we estimate an annual 
cost savings to the Medicare trust fund of $230 million in FY 2022, 
$1.74 billion over 5 years, and $4.150 billion over 10 years. OACT 
estimated these savings on a cash basis using IPPS cost data. These 
savings estimates also include effects associated with the impacts 
to Medicare Advantage plans. These effects which are unrelated to 
our proposal, include the changes resulting from the 21st Century 
Cures Act, which requires that kidney acquisition costs for Medicare 
Advantage beneficiaries be paid under Fee-for-service Medicare 
beginning January 1, 2021, rather than under Medicare Advantage 
(section 17006 of Pub. L. 114-255).
    As a result of our proposal to revise and codify the policy for 
donor community hospital charges for services provided to organ 
procurement organizations, we are currently unable to estimate a 
cost savings. Based on the Scientific Registry of Transplant 
Recipient data, we recognize that organs recovered from donor 
community hospitals comprised 62 percent of all transplanted organs 
in 2017 and 2018.\1529\ Under the current policy donor community 
hospitals bill customary charges or negotiated rates and not charges 
reduced to cost. Because our proposal requires donor community 
hospitals to reduce charges to cost, we anticipate a cost savings to 
the Medicare trust fund.
---------------------------------------------------------------------------

    \1529\ Scientific Registry of Transplant Recipients. Request for 
Information. Requested on 02/08/2021.
---------------------------------------------------------------------------

12. Effects of the Proposed Policy Changes to the Medicare Shared 
Savings Program

    In section X.C. of the preamble of this proposed rule, we 
describe our proposed changes to the Medicare Shared Savings Program 
(Shared Savings Program) established under section 1899 of the Act. 
The proposed 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 proposed 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 participation decisions made 
by ACOs in similar positions entering PY 2021.
    We estimate that the proposed 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 have otherwise have 
terminated their participation in the program absent the flexibility 
and reduced shared savings payouts to ACOs that would 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 
estimate the impact of this proposal over the single performance 
year for which it would

[[Page 25772]]

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 net. On one hand, the policy could allow certain 
ACOs to delay making more aggressive care delivery changes if they 
expect CMS to likely continue to offer risk-free participation in 
the program in future rulemaking, as would have been the case for 
two successive rules (the May 8, 2020 COVID-19 Interim Final Rule 
with Comment Period and this FY 2022 Medicare Hospital Inpatient 
Prospective Payment System proposed rule). On the other hand, the 
proposal 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 
decide whether or not to transition to performance-based risk for PY 
2022. These two scenarios illustrate potential countervailing longer 
run impacts from the proposal, and while we do not attempt to 
estimate a net impact across the mix of such possible scenarios for 
ACOs impacted by this proposal, we assert that the proposal 
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.

I. Effects of Proposed Changes in the Capital IPPS

1. General Considerations

    As discussed, in section III.A of the Addendum to this proposed 
rule, we are proposing to use 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 
proposed capital Federal rate for FY 2022. Consistent with these 
proposals, 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 proposed changes to the capital 
prospective payment system do not incorporate cost data, we used the 
March 2020 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 draw 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 proposed 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 
proposed capital IPPS payments in FY 2022 is as follows:

8(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 proposed rule, the proposed update 
to the capital Federal rate is 0.70 percent for FY 2022.
     In addition to the proposed FY 2022 update factor, the 
proposed FY 2022 capital Federal rate was calculated based on a 
proposed GAF/DRG budget neutrality adjustment factor of 1.0001, a 
proposed budget neutrality factor for the proposed lowest quartile 
hospital wage index adjustment of 0.9976, and a proposed outlier 
adjustment factor of 0.9467.

2. Results

    We used the payment simulation model previously described in 
section I.I. of Appendix A of this proposed rule to estimate the 
potential impact of the proposed changes for FY 2022 on total 
capital payments per case, using a universe of 3,198 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 2020 
update of HCRIS. In Table III, we present a comparison of estimated 
total payments per case for FY 2021 and estimated proposed total 
payments per case for FY 2022 based on the proposed FY 2022 payment 
policies. Column 2 shows estimates of payments per case under our 
model for FY 2021. Column 3 shows estimates of proposed payments per 
case under our model for FY 2022. Column 4 shows the proposed total 
percentage change in payments from FY 2021 to FY 2022. The change 
represented in Column 4 includes the proposed 0.70 percent update to 
the capital Federal rate and other proposed 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 proposed 0.70 percent update to the capital 
Federal rate for FY 2022, in conjunction with 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 78 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 primarily due to the proposed changes in 
GAFs, and are generally consistent with the projected changes in 
payments due to proposed changes in the wage index (and proposed 
policies affecting the wage index), as shown in Table I in section 
I.G. of this Appendix A.
    The net impact of these proposed changes is an estimated 0.5 
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 would increase by an estimated 0.5 
percent for hospitals in urban areas while payments to hospitals in 
rural areas would increase by 1.0 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 urban areas 
range from a 0.2 percent increase for the West South Central region 
to a 1.2 percent increase for the Pacific region. We estimate a 
decrease for the capital payments per case from FY 2021 to FY 2022 
of 0.4 percent for the Middle Atlantic urban region and 0.8 percent 
for the New England urban region, primarily due to changes in the 
GAFs and estimated decreases in DSH payments. However, all rural 
regions are expected to experience an increase in capital payments 
per case from FY 2021 to FY 2022, ranging from 0.6 percent for the 
West North Central rural region to 1.9 percent for the South 
Atlantic rural region. These regional differences are primarily due 
to the proposed changes in the GAFs and estimated changes in outlier 
and DSH payments.

[[Page 25773]]

    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. Voluntary hospitals are 
expected to experience an increase in capital IPPS payments of 0.6 
percent, and the projected increase in capital payments for 
proprietary and government hospitals is estimated to be 0.7 percent 
and 0.6 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 proposed rule for FY 2022, we show the proposed 
average capital payments per case for reclassified hospitals for FY 
2022. Urban reclassified hospitals are expected to experience an 
increase in capital payments of 0.1 percent; urban nonreclassified 
hospitals are expected to experience an increase in capital payments 
of 1.0 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. 
The estimated percentage increase for rural reclassified hospitals 
is 1.2 percent, and for rural nonreclassified hospitals, the 
estimated percentage increase in capital payments is 0.8 percent.

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J. Effects of Proposed Payment Rate Changes and Policy Changes 
Under the LTCH PPS

1. Introduction and General Considerations

    In section VII. of the preamble of this proposed rule and 
section V. of the Addendum to this proposed rule, we set forth the 
proposed annual update to the payment rates for the LTCH PPS for FY 
2022. In the preamble of this proposed rule, we specify the 
statutory authority for the provisions that are presented, identify 
the policies for FY 2022, and present rationales for our proposals 
as well as alternatives that were considered. In this section of 
Appendix A to this proposed rule, we discuss the impact of the 
proposed changes to the payment rate, factors, and other payment 
rate policies related to the LTCH PPS that are presented in the 
preamble of this proposed rule in terms of their estimated fiscal 
impact on the Medicare budget and on LTCHs.
    There are 363 LTCHs included in this impact analysis. We note 
that, although there are currently approximately 373 LTCHs, 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 VII.B.3.c. of 
the preamble of this proposed rule. Moreover, in the claims data 
used for this proposed 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 proposed payment rate, 
factors, and policies presented in this proposed rule, the proposed 
2.2 percent annual update to the LTCH PPS standard Federal payment 
rate, the proposed update to the MS-LTC-DRG classifications and 
relative weights, the proposed 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 proposed 
rule, we estimate that overall LTCH PPS payments in FY 2022 will 
increase by approximately 1.4 percent (or approximately $52 million) 
based on the proposed rates and factors presented in section VII. of 
the preamble and section V. of the Addendum to this proposed rule.
    Based on the FY 2019 LTCH cases that were used for the analysis 
in this proposed 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 proposed 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 proposed 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 proposed 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 1.2 percent (or 
approximately $41 million). This estimated increase in LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases in FY 2022 
is primarily due to the proposed 2.2 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, 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 proposed 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 proposed FY 2022 LTCH PPS payments of 
approximately $3.822 billion, resulting in an estimated overall 
increase in LTCH PPS payments of approximately $52 million. We note 
that the estimated $52 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 proposed rule.
    The LTCH PPS standard Federal payment rate for FY 2021 is 
$43,755.34. For FY 2022, we are proposing to establish an LTCH PPS 
standard Federal payment rate of $ 44,827.87 which reflects the 
proposed 2.2 percent annual update to the LTCH PPS standard Federal 
payment rate and the proposed budget neutrality factor for proposed 
updates to the area wage level adjustment of 1.002458 (discussed in 
section V.B.6. of the Addendum to this proposed 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 proposing to establish an 
LTCH PPS standard Federal payment rate of $43,950.62. This proposed 
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 proposed annual update of 2.2 percent to the LTCH PPS 
standard Federal payment rate is projected to result in an increase 
of 2.1 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 2.1 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 2.1 percent.
    For FY 2022, we are proposing to update 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 
proposed FY 2022 IPPS wage index). We also are proposing a labor-
related share of 68.0 percent for FY 2022, based on the most recent 
available data (IGI's fourth quarter 2020 forecast) on the relative 
importance of the labor-related share of operating and capital costs 
of the 2017-based LTCH market basket. We also are proposing to apply 
an area wage level budget neutrality factor of 1.002458 to ensure 
that the proposed changes to the area wage level adjustment would 
not

[[Page 25777]]

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 proposed 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) would 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 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 
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 proposed in section V.D.3.b. of the Addendum to 
this proposed 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 proposed methodology described in section 
V.D.3.b. of the Addendum to this proposed 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 proposed rule, based on 
the best available data, we believe that the provisions of this 
proposed 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.

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 1.5 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 363 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. Proposed 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 
$52 million. This estimated increase in payments reflects the 
projected increase in payments to LTCH PPS standard Federal payment 
rate cases of approximately $41 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 proposed 
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 
proposed 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 proposed provider impact analysis for the 
changes that affect LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases.

b. Proposed 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 
proposed 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 proposed rates, factors, and the policies in this FY 2022 
IPPS/LTCH PPS proposed rule (as discussed in section VII. of the 
preamble of this proposed rule and section V. of the Addendum to 
this proposed rule). As discussed elsewhere in this proposed 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:

[[Page 25778]]

     Location: Large urban/other urban/rural.
     Participation date.
     Ownership control.
     Census region.
     Bed size.

c. Proposed 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 
proposed 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 
proposed FY 2022 LTCH PPS standard Federal payment rate, we used the 
proposed FY 2022 standard Federal payment rate of $44,827.87 (or 
$43,950.62 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 proposed FY 
2022 LTCH PPS payments, we used the proposed FY 2022 LTCH PPS labor-
related share (68.0 percent), the proposed FY 2022 wage index values 
from Tables 12A and 12B listed in section VI. of the Addendum to 
this proposed rule (which are available via the internet on the CMS 
website), the proposed FY 2022 HCO fixed-loss amount for LTCH PPS 
standard Federal payment rate cases of $32,680 (as discussed in 
section V.D.3. of the Addendum to this proposed rule), and the 
proposed FY 2022 COLA factors (shown in the table in section V.C. of 
the Addendum to this proposed rule) to adjust the proposed FY 2022 
nonlabor-related share (32.0 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 
proposed in section V.D.3.b. of the Addendum to this proposed 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 proposed methodology described in section 
V.D.3.b. of the Addendum to this proposed 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 
proposed 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 proposed 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 proposed annual update to the standard Federal rate 
(as discussed in section V.A.2. of the Addendum to this proposed 
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 proposed 
corresponding budget neutrality factor (as discussed in section 
V.B.6. of the Addendum to this proposed 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 proposed 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 proposed rule, we have prepared the 
following summary of the impact (as shown in Table IV) of the LTCH 
PPS payment rate and proposed policy changes for LTCH PPS standard 
Federal payment rate cases presented in this proposed rule. The 
impact analysis in Table IV shows that estimated payments per 
discharge for LTCH PPS

[[Page 25781]]

standard Federal payment rate cases are projected to increase 1.2 
percent, on average, for all LTCHs from FY 2021 to FY 2022 as a 
result of the proposed payment rate and policy changes applicable to 
LTCH PPS standard Federal payment rate cases presented in this 
proposed rule. This estimated 1.2 percent increase in LTCH PPS 
payments per discharge was determined by comparing estimated 
proposed FY 2022 LTCH PPS payments (using the proposed payment rates 
and factors discussed in this proposed 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 proposing to update the LTCH PPS 
standard Federal payment rate for FY 2022 by 2.2 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 proposed budget neutrality 
factor for proposed changes to the area wage level adjustment of 
1.002458 (discussed in section V.B.6. of the Addendum to this 
proposed rule), based on the best available data at this time, to 
ensure that any proposed 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 proposed 2.2 percent annual update to the LTCH PPS standard 
Federal payment rate is projected to result in approximately a 2.1 
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 
proposed 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 1.2 percent. The projected increase for urban hospitals 
is 1.2 percent for urban hospitals, while the projected increase for 
rural hospitals is 1.5 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 1.2 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 1.2 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 0.8 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 1.0 percent and 1.2 percent in 
payments to LTCH PPS standard Federal payment rate cases, 
respectively. Government owned and operated LTCHs, meanwhile, are 
expected to experience a 1.4 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 1.7 percent. The remaining 
regions are projected to experience an increase in payments in the 
range of 0.7 to 1.6 percent. These regional variations are primarily 
due to the proposed 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 125-199 beds will 
experience the lowest increase in payments for LTCH PPS standard 
Federal payment rate cases, 0.9 percent. LTCHs with 75-124 beds are 
projected to experience the largest increase in payments of 1.3 
percent. The remaining bed size categories are projected to 
experience an increase in payments in the range of 1.0 to 1.2 
percent.

4. Effect on the Medicare Program

    As stated previously, we project that the provisions of this 
proposed 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 $41 million (or 
approximately 1.2 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 proposed 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 proposed 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 $52 million (or approximately 
1.4 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 proposed 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 Proposed Requirements for the Hospital Inpatient 
Quality Reporting (IQR) Program

    In section IX.C. of the preamble of this proposed rule, we 
discuss our current and proposed requirements 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 proposed rule, we are proposing 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 Hybrid HWM measure beginning with a one-year 
voluntary reporting period beginning July 1, 2022

[[Page 25782]]

through June 30, 2023, before requiring mandatory reporting of the 
measure for the reporting period that would run from July 1, 2023 
through June 30, 2024, affecting the FY 2026 payment determination 
and for subsequent years; (3) 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 payment determination followed by quarterly reporting 
deadlines affecting the FY 2024 payment determination and subsequent 
years; (4) adopt 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) remove the Death Among Surgical 
Inpatients with Serious Treatable Complications (CMS PSI-04) measure 
beginning with the FY 2023 payment determination; (6) remove two 
eCQMs (Anticoagulation Therapy for Atrial Fibrillation/Flutter eCQM 
and Discharged on Statin Medication eCQM) beginning with the FY 2026 
payment determination; (7) remove the Exclusive Breast Milk Feeding 
(PC-05) measure beginning with the FY 2026 payment determination; 
(8) remove the Admit Decision Time to ED Departure Time for Admitted 
Patients (ED-2) measure beginning with the FY 2026 payment 
determination; (9) revise 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''; (10) revise 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''; (11) 
require the 2015 Edition Cures Update of CEHRT for eCQMs and hybrid 
measures beginning with the FY 2025 payment determination; and (12) 
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 
beginning with validations affecting the FY 2024 payment 
determination.
    As shown in summary table in section XII.B.4.k. of the preamble 
of this proposed 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 proposed policies and updated 
burden estimates across a four 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 X.B.4 of the preamble of this proposed 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.8.e. and IX.C.8.f. of the preamble 
of this proposed rule, we are proposing 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 proposal 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 proposal 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 proposal. 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 
is 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 proposed rule we include proposals to adopt two new eCQMs 
and remove four eCQMs. 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 proposals, 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 requirements, such as 
maintaining measure specifications 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 proposed rule, we 
are proposing to adopt a COVID-19 HCP Vaccination 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 annual reporting beginning with the FY 
2024 payment determination and subsequent years. 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 currently 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).\1530\
---------------------------------------------------------------------------

    \1530\ 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 HCP Vaccination 
measure is not accounted for under the CDC PRA 0920-1317 or 0920-
0666, the cost and burden information is included here. We estimate 
that it would 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 \1531\ 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 hour x $36.62) and $45.78 (1.25 hours x $36.62) 
monthly and between $82.40 (2.25 hour 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). 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

[[Page 25783]]

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 HCP Vaccination 
measure to monitor, track, and provide transparency for the public 
on this important tool to combat COVID-19 outweigh the costs of 
reporting. We welcome comments on the estimated time to collect data 
and enter it into NHSN.
---------------------------------------------------------------------------

    \1531\ https://www.bls.gov/oes/current/oes436013.htm. The 
adjusted hourly wage rate of $36.62/hr includes an adjustment of 100 
percent of the median hourly wage to account for the cost of 
overhead, including fringe benefits.
---------------------------------------------------------------------------

    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.

L. Effects of Proposed Requirements for the PPS-Exempt Cancer 
Hospital Quality Reporting (PCHQR) Program

    In section IX.D. of the preamble of this proposed rule, we 
proposed 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 proposed rule, we are 
proposing 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, adopt 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 annual 
reporting periods beginning with the FY 2024 program year, and 
codify existing program policies. As stated in section XII.B.7. of 
the preamble of this proposed rule, we estimate the total burden 
reduction associated with the proposal to remove 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/hr). 
We do not estimate any changes in burden or cost in association with 
our other proposals for this program.
    In section IX.D.5. of the preamble of this proposed rule, we are 
proposing to adopt a COVID-19 HCP Vaccination Measure beginning with 
a shortened reporting period from October 1 to December 31, 2021, 
affecting the FY 2023 program year followed by annual reporting 
beginning with the FY 2024 program year and subsequent years. PCHs 
would 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 currently 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).\1532\
---------------------------------------------------------------------------

    \1532\ 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 HCP Vaccination 
measure is not accounted for under the CDC PRA 0920-1317 or 0920-
0666, the cost and burden information is included here. 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 \1533\ 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), three months would be required. For the CY 2021 reporting 
period/FY 2023 program year, PCHs would incur an additional burden 
between 2.25 hours (0.75 hours * 3 months) and 3.75 hours (1.25 
hours * 3 months) per PCH. For all 11 PCHs, the total burden would 
range from 24.75 hours (2.25 hours * 11 hospitals) and 41.25 hours 
(3.75 hours * 11 hospitals). Each PCH would incur an estimated cost 
of between $27.47 (0.75 hour * $36.62/hr) and $45.78 (1.25 hours * 
36.63/hr) monthly and between $82.40 (2.25 hours * $36.62/hr) and 
$137.33 (3.75 hours * $36.62/hr) 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 * 12 months) and 15 hours 
(1.25 hours/month * 12 months) per PCH and between 99 hours (9 
hours/hospital * 11 hospitals) and 165 hours (15 hours/hospital * 11 
hospitals) for all PCHs. Each PCH would incur an estimated cost of 
between $329.58 (9 hours x $36.62/hr) and $549.30 annually (15 hours 
x $36.62/hr). The estimated cost across all 11 PCHs would be between 
$906.40 ($82.40/hospital * 11 hospitals) and $1,510.63 ($137.33/
hospital * 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 * 11 hospitals) and $6,042.30 ($549.30/hospital * 
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 HCP Vaccination 
measure to monitor, track, and provide transparency for the public 
on this important tool to combat COVID-19 outweigh the costs of 
reporting. We welcome comments on the estimated time to collect data 
and enter it into the NHSN.
---------------------------------------------------------------------------

    \1533\ 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.
---------------------------------------------------------------------------

M. Effects of Proposed Requirements for the Long-Term Care Hospital 
Quality Reporting Program (LTCH QRP)

    In section IX.E.4. of the preamble of this proposed rule, we are 
proposing to add one measure to the Long-Term Care Hospital (LTCH) 
Quality Reporting Program (QRP), and update a measure adopted in the 
FY 2020 IPPS/LTCH final rule. We propose to add the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure and 
update the denominator for the Transfer of Health (TOH) Information 
to the Patient--Post-Acute Care (PAC) measure and also 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). In addition, 
we are proposing to publicly report 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 are 
seeking information on two issues: CMS' future plans 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.
    We note that the CDC would 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).\1534\ We refer readers to section 
XII.B.8, 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.
---------------------------------------------------------------------------

    \1534\ 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 Proposed Requirements Regarding the Promoting 
Interoperability Program

    In section IX.F.3.b. of the preamble of this rule, we are 
proposing the following 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 modify the Provide Patients Electronic 
Access to Their Health Information Measure to establish a data 
availability requirement beginning with encounters with a date of 
service on or after January 1, 2016, beginning

[[Page 25784]]

with the EHR reporting period in CY 2022; (3) 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; (4) 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); (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 the SAFER Guides, 
beginning with the EHR reporting period in CY 2022; (6) to remove 
attestation statements 2 and 3 from the Promoting Interoperability 
Program's prevention of information blocking requirement; and (7) 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 proposed changes.
    Next, in section VIII.D.3.b. of the preamble of this rule, we 
are proposing the following changes for CY 2023 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 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 proposals under the Hospital IQR Program. We 
are amending our regulation text as necessary to incorporate these 
proposed changes.
    Lastly, in section IX.F.3.b. of the preamble of this rule, we 
are proposing the following 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 four 
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 under the Hospital IQR Program. We 
are amending our regulation text as necessary to incorporate these 
proposed changes.
    For the EHR reporting period in CY 2022, the proposals 
summarized here are mainly extensions from or continuations of 
existing policies from last year's 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 
the update of 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, and we 
have updated number of registered respondents. 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 this rule includes 
proposals that would 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 
XXII.B. of the preamble of this proposed 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.

O. Alternatives Considered

    This proposed rule contains a range of policies. It also 
provides descriptions of the statutory provisions that are 
addressed, identifies the proposed 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

    As discussed in section II.A. of the preamble of this proposed 
rule, we are proposing to use 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 
proposing 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 section II.D. of the preamble of this 
proposed rule). Similarly, we are proposing 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 
proposed FY 2022 IPPS MS-DRG (as discussed in greater detail section 
II.X. of the preamble of this proposed rule) and proposed FY 2022 
MS-LTC-DRG relative weights (as discussed in greater detail section 
VI.B.of the preamble of this proposed rule). (As noted in section 
II.A. of the preamble of this proposed rule, the FY 2019 HCRIS data 
would contain many cost reports ending in FY 2020 based on each 
hospital's cost reporting period.) We have clearly identified 
throughout the preamble of this proposed rule where and how we are 
proposing to modify the IPPS and LTCH PPS ratesetting consistent 
with our proposed use of the FY 2019 data instead of the FY 2020 
data we would ordinarily use if that FY 2020 data is significantly 
impacted by the COVID-19 PHE.
    As an alternative to our proposed approach, we considered using 
the FY 2020 data we would ordinarily use in the FY 2022 IPPS and 
LTCH PPS ratesetting. For example, we considered proposing to use 
the FY 2020 MedPAR claims data and cost report data from the FY 2019 
HCRIS file for purposes of determining the proposed FY 2022 IPPS MS-
DRG relative weights and the LTCH PPS MS-LTC-DRG relative weights, 
as well as in determining the proposed FY 2022 budget neutrality 
factors and other proposed FY 2022 ratesetting.
    In order to facilitate comments on this alternative approach, 
which we may consider finalizing for FY 2022 based on consideration 
of comments received, we are making available the FY 2020 MedPAR 
file and the FY 2019 HCRIS file that we would ordinarily have 
provided in conjunction with this proposed rule. We are also making 
available the MS-DRG and MS-LTC-DRG relative weighting factors and 
length of stay information calculated using the FY 2020 data we 
would have ordinarily used. We are making available a file with the 
budget neutrality and other ratesetting adjustments calculated under 
this alternative approach. Finally, we are making available other 
proposed rule supporting data files based on the use of the FY 2020 
data that we ordinarily would have provided, including: The IPPS and 
LTCH PPS Impact Files; the AOR/BOR File; the Case Mix Index File; 
and, the Standardizing File.
    With the exception of the FY 2020 MedPAR file, and the routine 
updates to the PSF file and the HCRIS file, these IPPS specific 
files can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index, 
along with the data files and information for our proposed FY 2022 
IPPS ratesetting. The LTCH PPS specific files can be found on the 
CMS website at: https://www.cms.gov/medicare/medicare-fee-for-service-payment/longtermcarehospitalpps, along with the data files 
and information for our proposed FY 2022 LTCH PPS ratesetting. The 
FY 2020 MedPAR may be ordered in the same manner as the FY 2019 
MedPAR file, and will be packaged with the updated FY 2019 MedPAR 
file that contains the proposed V39 MS-DRG groupings used to develop 
this proposed 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 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.
    In section V.L. of the preamble of this proposed rule, we are 
proposing 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 proposing to repeal the market-based MS-DRG 
relative weight methodology adopted effective for FY 2024,

[[Page 25785]]

as finalized in the FY 2021 IPPS/LTCH PPS final rule. We also note 
that we are soliciting comment on alternative approaches or data 
sources that could be used in Medicare fee-for-service (FFS) 
ratesetting. We are also considering an alternative to our proposal, 
to instead 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 this 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. We refer readers to the frequently asked 
questions for more information: https://www.cms.gov/files/document/frequently-asked-questions-faqs-market-based-ms-drg-relative-weight-data-collection-and-change.pdf.
    We are inviting public comments on our proposal, as explained in 
section V.L. of the preamble to this proposed rule, to repeal both 
the market-based data collection requirement and the market-based 
relative weight methodology, and also on the alternative to maintain 
the market-based data collection requirement but delay the adoption 
of the market-based MS-DRG relative weight methodology to a date 
after FY 2024.
    If we were to finalize a delay in the implementation of the 
market-based MS-DRG relative weight methodology, we would remain 
open to adjusting the methodology, as finalized in the FY 2021 IPPS/
LTCH PPS final rule, through future rulemaking, prior to the new 
effective date. Should we finalize a delay in the effective date of 
the market-based MS-DRG relative weight methodology, we would 
conduct further analysis based on the median payer-specific 
negotiated charge data received on the Medicare cost report, and 
provide an opportunity for public comment on that analysis, prior to 
the new effective date for the market-based MS-DRG relative weight 
methodology.

P. Overall Conclusion

1. Acute Care Hospitals

    Acute care hospitals are estimated to experience an increase of 
approximately $2.507 billion in FY 2022, including operating, 
capital, and new technology changes, as well as increased GME 
payments as a result of section 131 of the Consolidated 
Appropriations Act of 2021 and increased payments as a result of the 
imputed floor provision in section 9831 of the American Rescue Plan 
Act of 2021, as modeled for this proposed rule. The estimated change 
in operating payments is approximately $2.157 billion (discussed in 
section I.G. and I.H. of this Appendix). The estimated change in 
capital payments is approximately $0.048 billion (discussed in 
section I.I. of this Appendix). The estimated change in new 
technology add-on payments is approximately $0.82 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. The estimated increase in 
payments as a result of our proposed implementation of section 9831 
of the American Rescue Plan Act of 2021 (discussed in section 
III.G.2. of this proposed rule) is $0.191 billion. The estimated FY 
2022 payments as a result of our proposed implementation of section 
131 of the Consolidated Appropriations Act of 2021 (discussed in 
section V.K.2.a. of this proposed rule) is $0.030 billion. 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 proposed MS-DRG and wage index changes, and for 
the wage index reclassifications under the MGCRB.
    We estimate that hospitals would experience a 0.5 percent 
increase in capital payments per case, as shown in Table III. of 
section I.I. of this Appendix. We project that there would be a $48 
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 proposed 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 proposed rates, factors, and policies presented in this proposed 
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 $52 million relative to FY 2021 primarily due to the 
proposal 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 welcome any public comments on 
the approach in estimating the number of entities that will review 
this proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of the proposed 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 welcome 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 this 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 
proposed rule is $110.74 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 
26.42 hours for the staff to review half of this proposed rule. For 
each IPPS hospital or LTCH that reviews this proposed rule, the 
estimated cost is $2,926 (26.42 hours x $110.74). Therefore, we 
estimate that the total cost of reviewing this proposed rule is 
$2,492,858 ($2,926 x 852 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 proposed 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 proposed changes 
to the IPPS presented in this proposed 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 proposed in this 
proposed rule are estimated at $2.507 billion.

[[Page 25786]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.365

B. LTCHs

    As discussed in section I.J. of this Appendix, the impact 
analysis of the proposed payment rates and factors presented in this 
proposed 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 $52 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 proposed 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 proposed payment rates and factors 
and other provisions presented in this proposed 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 policies for LTCHs in this 
proposed rule are estimated at $52 million.
[GRAPHIC] [TIFF OMITTED] TP10MY21.366

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 (having revenues of less than $8.0 million to $41.5 
million in any 1 year). (For details on the latest standards for 
health care providers, we refer readers to page 38 of the Table of 
Small Business Size Standards for NAIC 622 found on the SBA website 
at: https://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf.)
    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 proposed 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 is to consider effects 
economically ''significant'' if greater than 5 percent of providers 
reach a threshold of 3 to 5 percent or more of total revenue or 
total costs. We believe that the provisions of this proposed rule 
relating to IPPS hospitals will have an economically significant 
impact on small entities as explained in this Appendix. For example, 
the majority of the 3,198 IPPS hospitals included in the impact 
analysis shown in ``Table I.--Impact Analysis of Proposed Changes to 
the IPPS for Operating Costs for FY 2022,'' on average are expected 
to see increases in the range of 3 percent, primarily due to the 
proposed hospital rate update, as discussed in section I.G. of this 
Appendix. On average, the proposed rate update for these hospitals 
is estimated to be 2.8 percent.
    The majority of the 360 LTCH PPS hospitals included in the 
impact analysis shown in ``Table IV. Impact of Proposed 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 
1 percent, primarily due to the proposed 2.2 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 
discussed in section I.J. of this Appendix.
    This proposed rule contains a range of proposed policies. It 
provides descriptions of the statutory provisions that are 
addressed, identifies the proposed 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 proposed rule constitutes our regulatory 
flexibility analysis. We are soliciting public comments on our 
estimates and analysis of the impact of our proposals on small 
entities. Public comments that we receive and our responses will be 
presented in the final rule.

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 (313 hospitals) and 50-99 beds (254 
hospitals) are expected to experience an increase in payments from 
FY 2021 to FY 2022 of 4.0 percent and 2.6 percent, respectively, 
primarily driven by the proposed 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 proposed 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

[[Page 25787]]

payments from FY 2021 to FY 2022 of 1.5 percent, primarily due to 
the proposed 2.2 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 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 proposed 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 proposed 
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 proposed 
rule, we continue to seek comment on 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 this 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 proposed 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. Proposed FY 2022 Inpatient Hospital Update
    As discussed in section IV.A. of the preamble to this proposed 
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 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 multifactor 
productivity (MFP) 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 MFP 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 proposed rule, we are 
proposing to replace the 2014-based IPPS operating and capital market 
baskets with the rebased and revised proposed 2018-based IPPS operating 
and capital market baskets beginning in FY 2022.
    In this FY 2022 IPPS/LTCH PPS proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, we are proposing 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 is 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 this FY 2022 IPPS/LTCH PPS proposed rule, based on 
IGI's fourth quarter 2020 forecast, we are proposing a MFP adjustment 
of 0.2 percentage point for FY 2022. We are also proposing that if more 
recent data subsequently become available, we would use such data, if 
appropriate, to determine the FY 2022 market basket update and MFP 
adjustment for the FY 2022 IPPS/LTCH PPS final rule.
    Therefore, based on IGI's fourth quarter 2020 forecast of the 
proposed 2018-based IPPS market basket and the MFP 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 
are proposing four possible applicable percentage increases that could 
be applied to the standardized amount, as shown in the following table.

[[Page 25788]]

[GRAPHIC] [TIFF OMITTED] TP10MY21.367

B. Proposed 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 proposing the same four possible 
applicable percentage increases in the previous table for the hospital-
specific rate applicable to SCHs and MDHs.

C. Proposed 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 IV.A.1. of the preamble of this proposed 
rule.
    In addition, as discussed in section IV.A.2. of the preamble of 
this proposed 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 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, for this FY 2022 proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, as previously discussed, for Puerto 
Rico hospitals, we are proposing a market basket update of 2.5 percent 
and an MFP adjustment of 0.2 percent. Therefore, 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 are proposing 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, 
we are proposing 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 MFP 
adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we are proposing 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 MFP adjustment.
    As noted previously, we are proposing 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 MFP adjustment 
for the FY 2022 IPPS/LTCH PPS final rule.

D. Proposed 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

[[Page 25789]]

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 proposed rule, we are 
proposing to use the percentage increase in the proposed 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 proposed 2018-based IPPS operating market basket. For 
this proposed rule, the current estimate of the IPPS operating market 
basket percentage increase for FY 2022 is 2.5 percent. We are proposing 
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 MFP adjustment for the FY 2022 IPPS/LTCH PPS final rule.

E. Proposed 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 proposed rule, 
we are proposing to update the LTCH PPS standard Federal payment rate 
for FY 2022 by 2.2 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 (that is, the MFP adjustment). Furthermore, in accordance with 
the LTCHQR Program under section 1886(m)(5) of the Act, we are 
proposing to reduce 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 proposing to establish an 
update factor of 1.022 in determining the LTCH PPS standard Federal 
rate for FY 2022. For LTCHs that fail to submit quality data for FY 
2022, we are proposing to establish an annual update to the LTCH PPS 
standard Federal rate of 0.2 percent (that is, the proposed annual 
update for FY 2022 of 2.2 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 proposed update 
factor of 1.0020 in determining the LTCH PPS standard Federal rate for 
FY 2022. (We note that, as discussed in section VII.D. of the preamble 
of this proposed rule, the proposed update to the LTCH PPS standard 
Federal payment rate of 2.2 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 2.5 
percent.
    For FY 2022, consistent with policy set forth in section VII. of 
the preamble of this proposed rule, for LTCHs that submit quality data, 
we are recommending an update of 2.2 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 0.2 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 proposing an 
applicable percentage increase for FY 2022 of 2.3 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.

[[Page 25790]]

    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 proposed update to the 
capital rate is discussed in section III. of the Addendum to this 
proposed rule.

[FR Doc. 2021-08888 Filed 4-27-21; 4:45 pm]
BILLING CODE 4120-01-P