[Federal Register Volume 87, Number 90 (Tuesday, May 10, 2022)]
[Proposed Rules]
[Pages 28108-28746]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2022-08268]



[[Page 28107]]

Vol. 87

Tuesday,

No. 90

May 10, 2022

Part II





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Parts 412, 413, 482, 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 2023 Rates; 
Quality Programs and Medicare Promoting Interoperability Program 
Requirements for Eligible Hospitals and Critical Access Hospitals; 
Costs Incurred for Qualified and Non-Qualified Deferred Compensation 
Plans; and Changes to Hospital and Critical Access Hospital Conditions 
of Participation; Proposed Rule

  Federal Register / Vol. 87, No. 90 / Tuesday, May 10, 2022 / Proposed 
Rules  

[[Page 28108]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 412, 413, 482, 485, and 495

[CMS-1771-P]
RIN 0938-AU84


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 2023 Rates; 
Quality Programs and Medicare Promoting Interoperability Program 
Requirements for Eligible Hospitals and Critical Access Hospitals; 
Costs Incurred for Qualified and Non-Qualified Deferred Compensation 
Plans; and Changes to Hospital and Critical Access Hospital Conditions 
of Participation

AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of 
Health and Human Services (HHS).

ACTION: Proposed rule.

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SUMMARY: This proposed rule would: Revise the Medicare hospital 
inpatient prospective payment systems (IPPS) for operating and capital-
related costs of acute care hospitals; make changes relating to 
Medicare graduate medical education (GME) for teaching hospitals; 
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). In additon it 
would establish new requirements and revise existing requirements for 
eligible hospitals and critical access hospitals (CAHs) participating 
in the Medicare Promoting Interoperability Program; provide estimated 
and newly established performance standards for the Hospital Value-
Based Purchasing (VBP) Program; and propose updated policies for the 
Hospital Readmissions Reduction Program, Hospital Inpatient Quality 
Reporting (IQR) Program, Hospital VBP Program, Hospital-Acquired 
Condition (HAC) Reduction Program, PPS-Exempt Cancer Hospital Reporting 
(PCHQR) Program, and the Long-Term Care Hospital Quality Reporting 
Program (LTCH QRP). It would also revise the hospital and critical 
access hospital (CAH) conditions of participation (CoPs) for infection 
prevention and control and antibiotic stewardship programs; and codify 
and clarify policies related to the costs incurred for qualified and 
non-qualified deferred compensation plans. Lastly, this proposed rule 
would provide updates on the Rural Community Hospital Demonstration 
Program and the Frontier Community Health Integration Project.

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 17, 2022.

ADDRESSES: In commenting, please refer to file code CMS-1771-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 https://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-1771-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-1771-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 
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.
    Allison Pompey, (410) 786-2348, New Technology Add-On Payments and 
New COVID-19 Treatments Add-on Payments Issues.
    Mady Hue, [email protected], and Andrea Hazeley, 
[email protected], MS-DRG Classifications Issues.
    Siddhartha Mazumdar, (410) 786-6673, Rural Community Hospital 
Demonstration Program Issues.
    Jeris Smith, [email protected], Frontier Community Health 
Integration Project Demonstration Issues.
    Sophia Chan, [email protected], Hospital Readmissions 
Reduction Program--Administration Issues.
    Jennifer Robinson, [email protected], Hospital 
Readmissions Reduction Program--Measures Issues.
    Jennifer Tate, [email protected], Hospital-Acquired 
Condition Reduction Program--Administration Issues.
    Yuling Li, [email protected], Hospital-Acquired Condition 
Reduction Program--Measures Issues.
    Julia Venanzi, [email protected], Hospital Inpatient 
Quality Reporting and Hospital Value-Based Purchasing Programs--
Administration Issues.
    Melissa Hager, [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.
    Ora Dawedeit, [email protected], PPS-Exempt Cancer Hospital 
Quality Reporting--Administration Issues.
    Leah Domino, [email protected], PPS-Exempt Cancer Hospital 
Quality Reporting Program--Measure Issues.
    Christy Hughes, [email protected], Long-Term Care Hospital 
Quality Reporting Program--Data Reporting Issues.
    Elizabeth Holland, [email protected], Medicare 
Promoting Interoperability Program.
    CAPT Scott Cooper, USPHS, (410) 786-9465, and Dawn Linn, 
[email protected], Conditions of Participation Pandemic Reporting 
Requirements for Hospitals and Critical Access Hospitals.

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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: https://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 fiscal year (FY) 2023 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 2023 IPPS Proposed rule Home Page'' or ``Acute 
Inpatient--Files for Download.'' The LTCH PPS tables for this FY 2023 
proposed rule are available through the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the list item for Regulation 
Number CMS-1771-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 2023 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. Proposed Use of FY 2021 Data and Proposed Methodology 
Modifications for the FY 2023 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 2023 MS-DRG Documentation and Coding Adjustment
    D. Proposed Changes to Specific MS-DRG Classifications
    E. Recalibration of the FY 2023 MS-DRG Relative Weights
    F. Add-On Payments for New Services and Technologies for FY 2023
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 2023 Wage 
Index
    F. Analysis and Implementation of the Proposed Occupational Mix 
Adjustment and the Proposed FY 2023 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 2023 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 2023 Wage Index
IV. Proposed Payment Adjustment for Medicare Disproportionate Share 
Hospitals (DSHs) for FY 2023 (Sec.  412.106)
    A. General Discussion
    B. Eligibility for Empirically Justified Medicare DSH Payments 
and Uncompensated Care Payments
    C. Empirically Justified Medicare DSH Payments
    D. Uncompensated Care Payments
    E. Proposed Supplemental Payment for Indian Health Service and 
Tribal Hospitals and Puerto Rico Hospitals for FY 2023 and 
Subsequent Fiscal Years
    F. Counting Days Associated With Section 1115 Demonstrations in 
the Medicaid Fraction
V. Other Decisions and Changes to the IPPS for Operating Costs
    A. Proposed Changes in the Inpatient Hospital Updates for FY 
2022 (Sec.  412.64(d))
    B. Rural Referral Centers (RRCs)--Proposed Annual Updates to 
Case-Mix Index (CMI) and Discharge Criteria (Sec.  412.96)
    C. Proposed Payment Adjustment for Low-Volume Hospitals (Sec.  
412.101)
    D. Proposed Changes in the Medicare-Dependent, Small Rural 
Hospital (MDH) Program (Sec.  412.108)
    E. Proposed Indirect Medical Education (IME) Payment Adjustment 
Factor (Sec.  412.105)
    F. Proposed Payment for Indirect and Direct Graduate Medical 
Education Costs (Sec. Sec.  412.105 and 413.75 Through 413.83)
    G. Proposed Payment Adjustment for Certain Clinical Trial and 
Expanded Access Use Immunotherapy Cases (Sec. Sec.  412.85 and 
412.312)
    H. Hospital Readmissions Reduction Program: Proposed Updates and 
Changes (Sec. Sec.  412.150 Through 412.154)
    I. Hospital Value-Based Purchasing (VBP) Program: Proposed 
Policy Changes
    J. Hospital-Acquired Conditions (HAC) Reduction Program: 
Proposed Updates and Changes (Sec.  412.170)
    K. Rural Community Hospital Demonstration Program
VI. Proposed Changes to the IPPS for Capital-Related Costs
    A. Overview
    B. Additional Provisions
    C. Proposed Annual Update for FY 2023
VII. Proposed Changes for Hospitals Excluded From the IPPS
    A. Proposed Rate-of-Increase in Payments to Excluded Hospitals 
for FY 2023
    B. Critical Access Hospitals (CAHs)
VIII. Proposed Changes to the Long-Term Care Hospital Prospective 
Payment System (LTCH PPS) for FY 2023
    A. Background of the LTCH PPS
    B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-
LTC-DRG) Classifications and Relative Weights for FY 2023
    C. Proposed Changes to the LTCH PPS Payment Rates and Other 
Proposed Changes to the LTCH PPS for FY 2023
IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers
    A. Assessment of the Impact of Climate Change and Health Equity
    B. Overarching Principles for Measuring Healthcare Quality 
Disparities Across CMS Quality Programs--Request for Information
    C. Continuing to Advance to Digital Quality Measurement and the 
Use of Fast Healthcare Interoperability Resources (FHIR) in Hospital 
Quality Programs--Request for Information
    D. Advancing the Trusted Exchange Framework and Common 
Agreement-Request for Information
    E. Hospital Inpatient Quality Reporting (IQR) Program
    F. PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program
    G. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
    H. Proposed Changes to the Medicare Promoting Interoperability 
Program
X. Changes for Hospitals and Other Providers and Suppliers
    A. Codification of the Costs Incurred for Qualified and Non-
Qualified Deferred Compensation Plans
    B. Condition of Participation (CoP) Requirements for Hospitals 
and CAHs To Report Data Elements To Address Any Future Pandemics and 
Epidemics as Determined by the Secretary
    C. Request for Public Comments on IPPS Payment Adjustment for 
N95 Respirators That Are Wholly Domestically Made
XI. MedPAC Recommendations
XII. Other Required Information
    A. Publicly Available Files
    B. Collection of Information Requirements
    C. Response to Comments
    Addendum--Schedule of Standardized Amounts, Update Factors, and 
Rate-of-

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Increase Percentages Effective With Cost Reporting Periods Beginning 
on or After October 1, 2022 and Payment Rates for LTCHs Effective 
for Discharges Occurring on or After October 1, 2022

I. Executive Summary and Background

A. Executive Summary

1. Purpose and Legal Authority
    This FY 2023 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 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 2023 proposed rule, we are proposing 
to implement a permanent policy to cap wage index decreases as well as 
continuing policies to address wage index disparities impacting low 
wage index hospitals. We also are proposing to make changes relating to 
Medicare graduate medical education (GME) for teaching hospitals and 
new technology add-on payments.
    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 proposing updated policies for the Hospital Readmissions 
Reduction Program, Hospital Inpatient Quality Reporting (IQR) Program, 
Hospital Value-Based Purchasing (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. We are also requesting feedback across 
programs on health impacts due to climate change and on overarching 
principles in measuring healthcare quality disparities in hospital 
quality programs and value-based purchasing programs. We are also 
seeking feedback on advancing the Trusted Exchange Framework and Common 
Agreement (TEFCA). 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 Program and 
HAC Reduction Program. In addition to these measure suppressions for 
the Hospital VBP Program, we are proposing to implement a special 
scoring methodology for FY 2023 that results in each hospital receiving 
a value-based incentive payment amount that matches their 2 percent 
reduction to the base operating DRG payment amount. Similarly, we are 
also proposing to suppress all six measures in the HAC Reduction 
Program for the FY 2023 program year. If finalized as proposed, for the 
FY 2023 program year, hospitals participating in the HAC Reduction 
Program will not be given a measure score, a Total HAC score, nor will 
hospitals receive a payment penalty. We are also providing estimated 
and newly established performance standards for the Hospital VBP 
Program. For the Hospital Readmissions Reduction Program, we are 
proposing to resume the use of the one affected measure under the 
proposed measure suppression policy for the FY 2024 applicable period 
following suppression of this measure for the FY 2023 applicable 
period, and incorporating measure updates to the six condition/
procedure measures addressed by the Hospital Readmission Reduction 
Program to account for patient history of COVID-19.
    Under various statutory authorities, we either discuss continued 
program implementation or propose to make changes to the Medicare IPPS, 
the LTCH PPS, other related payment methodologies and programs for FY 
2023 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 (Pub. L. (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

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account for certain excess readmissions. section 15002 of the 21st 
Century Cures Act directs the Secretary to compare hospitals with 
respect to the number of their Medicare-Medicaid dual-eligible 
beneficiaries (dual-eligibles) in determining the extent of excess 
readmissions.
     Section 1886(r) of the Act, as added by section 3133 of 
the Affordable Care Act, which provides for a reduction to 
disproportionate share hospital (DSH) payments under section 
1886(d)(5)(F) of the Act and for a new uncompensated care payment to 
eligible hospitals. Specifically, section 1886(r) of the Act requires 
that, for fiscal year 2014 and each subsequent fiscal year, subsection 
(d) hospitals that would otherwise receive a DSH payment made under 
section 1886(d)(5)(F) of the Act will receive two separate payments: 
(1) 25 percent of the amount they previously would have received under 
section 1886(d)(5)(F) of the Act for DSH (``the empirically justified 
amount''), and (2) an additional payment for the DSH hospital's 
proportion of uncompensated care, determined as the product of three 
factors. These three factors are: (1) 75 percent of the payments that 
would otherwise be made under section 1886(d)(5)(F) of the Act; (2) 1 
minus the percent change in the percent of individuals who are 
uninsured; and (3) a hospital's uncompensated care amount relative to 
the uncompensated care amount of all DSH hospitals expressed as a 
percentage.
     Section 1886(m)(5) of the Act, which requires the 
Secretary to reduce by two percentage points the annual update to the 
standard Federal rate for discharges for a long-term care hospital 
(LTCH) during the rate year for LTCHs that do not submit data in the 
form, manner, and at a time, specified by the Secretary.
     Section 1886(m)(6) of the Act, as added by section 
1206(a)(1) of the Pathway for Sustainable Growth Rate (SGR) Reform Act 
of 2013 (Pub. L. 113-67) and amended by section 51005(a) of the 
Bipartisan Budget Act of 2018 (Pub. L. 115-123), which provided for the 
establishment of site neutral payment rate criteria under the LTCH PPS, 
with implementation beginning in FY 2016. Section 51005(b) of the 
Bipartisan Budget Act of 2018 amended section 1886(m)(6)(B) by adding 
new clause (iv), which specifies that the IPPS comparable amount 
defined in clause (ii)(I) shall be reduced by 4.6 percent for FYs 2018 
through 2026.
     Section 1899B of the Act, as added by section 2(a) of the 
Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT 
Act) (Pub. L. 113-185), which provides for the establishment of 
standardized data reporting for certain post-acute care providers, 
including LTCHs.
     Section 1861(e) of the Act provides the specific statutory 
authority for the hospital CoPs; section 1820(e) of the Act provides 
similar authority for CAHs. The hospital provision at section 
1861(e)(9) of the Act authorizes the Secretary to issue any regulations 
he or she deems necessary to protect the health and safety of patients 
receiving services in those facilities; the CAH provision at section 
1820(e)(3) of the Act authorizes the Secretary to issue such other 
criteria as he or she may require.
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 Pub. L. 110-90 until FY 2013. Prior to the ATRA, 
this amount could not have been recovered under Pub. L. 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 2023, we are proposing to make an adjustment of 
+ 0.5 percent to the standardized amount.
b. Proposed Use of FY 2021 Data and Proposed Methodology Modifications 
for the FY 2023 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 proposal to return to 
our historical practice of using the most recent data available for 
purposes of FY 2023 ratesetting, including the FY 2021 MedPAR claims 
and FY 2020 cost report data, with certain proposed modifications to 
our usual ratesetting methodologies to account for the anticipated 
decline in COVID-19 hospitalizations of Medicare beneficiaries at IPPS 
hospitals and LTCHs as compared to FY 2021. As discussed in greater 
detail in section I.F of the preamble of this proposed rule, we believe 
that it is reasonable to assume that some Medicare beneficiaries will 
continue to be hospitalized with COVID-19 at IPPS hospitals and LTCHs 
in FY 2023. Given this expectation, we believe it is appropriate to use 
FY 2021 data, as the most recent available data during the period of 
the COVID-19 PHE, for purposes of the FY 2023 IPPS and LTCH PPS 
ratesetting. However, as also discussed in greater detail in section 
I.F. of the preamble of this proposed rule, we believe it is reasonable 
to assume based on the information available at this time that there 
will be fewer COVID-19 hospitalizations in FY 2023 than in FY 2021. 
Therefore, we are proposing to use the FY 2021 data for purposes of the 
FY 2023 IPPS and LTCH PPS ratesetting but with modifications to our 
usual ratesetting methodologies to account for the anticipated decline 
in COVID-19 hospitalizations of Medicare beneficiaries at IPPS 
hospitals and LTCHs as compared to FY 2021. As discussed in section 
I.O. of Appendix A of this proposed rule, we are also requesting 
comments on, as an alternative to our proposed approach, the use of the 
FY 2021 data for purposes of FY 2023 ratesetting without the proposed 
modifications to our usual methodologies for the calculation of the FY 
2023 MS-DRG and MS-LTC-DRG relative weights or the usual methodologies 
used to determine the FY 2023 outlier fixed-loss amount for IPPS cases 
and LTCH PPS standard Federal payment rate cases.
c. Proposed Continuation of the Low Wage Index Hospital Policy
    To help mitigate wage index disparities between high wage and low

[[Page 28112]]

wage hospitals, in the FY 2020 IPPS/LTCH PPS rule (84 FR 42326 through 
42332), we adopted a policy to increase the wage index values for 
certain hospitals with low wage index values (the low wage index 
hospital policy). This policy was adopted in a budget neutral manner 
through an adjustment applied to the standardized amounts for all 
hospitals. We also indicated our intention 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. We are 
proposing for the low wage index hospital policy to continue for FY 
2023, and are also proposing to apply this policy in a budget neutral 
manner by applying an adjustment to the standardized amounts.
d. Proposed Permanent Cap on Wage Index Decreases
    Consistent with section 1886(d)(3)(E) of the Act, we adjust the 
IPPS 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 and update the wage index 
annually based on a survey of wages and wage-related costs of short-
term, acute care hospitals. As described in section III.N. of the 
preamble of this proposed rule, we have further considered the comments 
we received during the FY 2022 rulemaking recommending a permanent 5 
percent cap policy to prevent large year-to-year variations in wage 
index values as a means to reduce overall volatility for hospitals. 
Under the authority at sections 1886(d)(3)(E) and 1886(d)(5)(I)(i) of 
the Act, for FY 2023 and subsequent years, we are proposing to apply a 
5-percent cap on any decrease to a hospital's wage index from its wage 
index in the prior FY, regardless of the circumstances causing the 
decline. That is, we are proposing that a hospital's wage index for FY 
2023 would not be less than 95 percent of its final wage index for FY 
2022, and that for subsequent years, a hospital's wage index would not 
be less than 95 percent of its final wage index for the prior FY. We 
are also proposing to apply this proposed wage index cap policy in a 
budget neutral manner through a national adjustment to the standardized 
amount under our authority in sections 1886(d)(3)(E) and 
1886(d)(5)(I)(i) of the Act.
e. Proposed DSH Payment Adjustment and Additional Payment for 
Uncompensated Care
    Under section 1886(r) of the Act, which was added by section 3133 
of the Affordable Care Act, starting in FY 2014, Medicare 
disproportionate share hospitals (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 
2023. 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 
conjunction with more recently available data in the calculation of 
Factor 2. For FY 2023, we are proposing to use the two most recent 
years of audited data on uncompensated care costs from Worksheet S-10 
of the FY 2018 cost reports and the FY 2019 cost reports to calculate 
Factor 3 in the uncompensated care payment methodology for all eligible 
hospitals. In addition, for FY 2024 and subsequent fiscal years, we are 
proposing to use a three-year average of the data on uncompensated care 
costs from Worksheet S-10 for the three most recent fiscal years for 
which audited data are available. Beginning in FY 2023, we are 
proposing to discontinue the use of low-income insured days as a proxy 
for uncompensated care to determine Factor 3 for Indian Health Service 
(IHS) and Tribal hospitals and hospitals located in Puerto Rico. In 
addition, we are proposing certain methodological changes for 
calculating Factor 3 for FY 2023 and subsequent fiscal years.
    We recognize that our proposal to discontinue the use of the low-
income insured days proxy to calculate uncompensated care payments for 
Indian Health Service (IHS) and Tribal hospitals and hospitals located 
in Puerto Rico could result in a significant financial disruption for 
these hospitals. Accordingly, we are proposing to use our exceptions 
and adjustments authority under section 1886(d)(5)(I) to establish a 
new supplemental payment for IHS and Tribal hospitals and hospitals 
located in Puerto Rico, beginning in FY 2023.
    Additionally, we are proposing to revise our regulation governing 
the calculation of the Medicaid fraction of the DSH calculation. Under 
this proposal, we would revise our regulation to explicitly reflect our 
interpretation of the language ``regarded as'' ``eligible for medical 
assistance under a State plan approved under title XIX'' in section 
1886(d)(5)(F)(vi) of the Act to mean patients who receive health 
insurance authorized by a section 1115 demonstration or patients who 
pay for all or substantially all of the cost of such health insurance 
with premium assistance authorized by a section 1115 demonstration, 
where state expenditures to provide the health insurance or premium 
assistance may be matched with funds from Title XIX. Moreover, of the 
groups we ``regard as'' Medicaid eligible, we propose to include in the 
Medicaid fraction only the days of those patients who obtain health 
insurance directly or with premium assistance that provides essential 
health benefits (EHB) as set forth in 42 CFR part 440, subpart C, for 
an Alternative Benefit Plan (ABP), and for patients obtaining premium 
assistance, only the days of those patients for which the premium 
assistance is equal to or greater than 90 percent of the cost of the 
health insurance, provided the patient is not also entitled to Medicare 
Part A.
f. Proposed Changes to GME Payments Based on Milton S. Hershey Medical 
Center, et al. v. Becerra Litigation
    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME payments 
to teaching hospitals when those hospitals' weighted full-time 
equivalent (FTE) counts exceed their direct GME FTE cap. In Milton S. 
Hershey Medical Center, et al. v. Becerra, the court ordered CMS to 
recalculate reimbursement owed, holding that CMS's regulation 
impermissibly modified the statutory weighting factors. The plaintiffs 
in these consolidated cases alleged that as far back as 2005, the 
proportional reduction that CMS applied to the weighted FTE count when 
the weighted FTE count exceeded the FTE cap conflicted with the 
Medicare statute, and it was an arbitrary and capricious exercise of 
agency discretion under the Administrative Procedure Act. The court 
held that the

[[Page 28113]]

proportional reduction methodology impermissibly modified the weighting 
factors statutorily assigned to residents and fellows. The court 
granted the motion for summary judgment to plaintiffs' motions, denied 
defendant's, and remanded to the Agency so that it could recalculate 
plaintiffs' reimbursement payments consistent with the court's opinion.
    After reviewing the statutory language regarding the direct GME FTE 
cap and the court's opinion, we have decided to propose a modified 
policy to be applied prospectively for all teaching hospitals, as well 
as retroactively to the providers and cost years in Hershey and certain 
other providers as described in greater detail in section V.F.2. of the 
preamble of this proposed rule. The proposed modified policy would 
address situations for applying the FTE cap when a hospital's weighted 
FTE count is greater than its FTE cap, but would not reduce the 
weighting factor of residents that are beyond their initial residency 
period to an amount less than 0.5. Specifically, effective for cost 
reporting periods beginning on or after October 1, 2022, we are 
proposing that the hospital's unweighted number of FTE residents 
exceeds the FTE cap, and the number of weighted FTE residents also 
exceeds that FTE cap, the respective primary care and obstetrics and 
gynecology weighted FTE counts and other weighted FTE counts are 
adjusted to make the total weighted FTE count equal the FTE cap. If the 
number of weighted FTE residents does not exceed that FTE cap, then the 
allowable weighted FTE count for direct GME payment is the actual 
weighted FTE count.
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 2023 IPPS/LTCH PPS proposed rule, we are discussing 
the following policies: (1) Proposal to resume use of the Hospital 30-
Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) following 
Pneumonia Hospitalization measure (NQF #0506) for the FY 2024 program 
year; (2) modification of the Hospital 30-Day, All-Cause, Risk-
Standardized Readmission Rate (RSRR) following Pneumonia 
Hospitalization measure (NQF #0506) to exclude COVID-19 diagnosed 
patients from the measure denominator, beginning with the Hospital 
Specific Reports (HSRs) for the FY 2023 program year; and (3) 
modification of all six condition/procedure specific measures to 
include a covariate adjustment for patient history of COVID-19 within 
one year prior to the index admission beginning with the FY 2023 
program year. We are also seeking comment on updating the to 
incorporate provider performance for socially at-risk populations.
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) Suppress the Hospital 
Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and 
five Hospital Acquired Infection (HAI) measures, for the FY 2023 
Program year; and (2) update the baseline periods for certain measures 
for the FY 2025 program year. We are also proposing to revise the 
scoring and payment methodology for the FY 2023 program year such that 
hospitals will not receive Total Performance Scores (TPSs). 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 note that we are 
also announcing technical updates to the measures in the Clinical 
Outcomes Domain.
i. Hospital-Acquired Condition (HAC) Reduction Program
    We are proposing changes to the HAC Reduction program, which was 
established under Section 1886(p) of the Act, to provide an incentive 
to hospitals to reduce the incidence of hospital-acquired conditions. 
We refer readers to the FY 2022 IPPS/LTCH PPS final rule for further 
details on our measure suppression policy (86 FR 45301 through 45304). 
In this FY 2023 IPPS/LTCH PPS proposed rule, we are proposing to: (1) 
Suppress the CMS PSI 90 measure and the five CDC NHSN HAI measures from 
the calculation of measure scores and the Total HAC Score, thereby not 
penalizing any hospital under the HAC Reduction Program FY 2023 program 
year; (2) publicly and confidentially report CDC NHSN HAI measure 
results but not calculate or report measure results for the CMS PSI 90 
measure for the HAC Reduction Program FY 2023 program year; (3) 
suppress CY 2021 CDC NHSN HAI measures data from the FY 2024 HAC 
Reduction Program Year; (4) update the measure specification to the 
minimum volume threshold for the CMS PSI 90 measure beginning with the 
FY 2023 program year; (5) update the measure specifications to risk-
adjust for COVID-19 diagnosis in the CMS PSI 90 measure beginning with 
the FY 2024 HAC Reduction Program Year; (6) request information from 
stakeholders on the potential adoption of two digital National 
Healthcare Safety Network (NHSN) measures: The NHSN Healthcare-
associated Clostridioides difficile Infection Outcome measure and NHSN 
Hospital-Onset Bacteremia & Fungemia Outcome measure; (7) request 
information on overarching principles for measuring healthcare quality 
disparities across CMS Quality Programs; (8) update the NHSN CDC HAI 
data submission requirements for newly opened hospitals beginning in 
the FY 2024 HAC Reduction Program Year; and (9) clarify the removal of 
the no mapped location policy beginning with the FY 2023 program year.
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.
    In this FY 2023 IPPS/LTCH PPS proposed rule, we are proposing 
several changes to the Hospital IQR Program. We are proposing the 
adoption of 10 new measures: (1) Hospital Commitment to Health Equity 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination; (2) Screening for Social Drivers of Health beginning 
with voluntary reporting for the CY 2023 reporting period and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (3) Screen Positive Rate for Social Drivers of Health 
beginning with voluntary reporting for the CY 2023 reporting period and 
mandatory reporting beginning with the CY 2024 reporting

[[Page 28114]]

period/FY 2026 payment determination; (4) Cesarean Birth electronic 
clinical quality measure (eCQM) with inclusion in the measure set 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination, and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination; (5) Severe Obstetric 
Complications eCQM with inclusion in the measure set beginning with the 
CY 2023 reporting period/FY 2025 payment determination, and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (6) Hospital-Harm--Opioid-Related Adverse Events eCQM 
(NQF #3501e) beginning with the CY 2024 reporting period/FY 2026 
payment determination; (7) Global Malnutrition Composite Score eCQM 
(NQF #3592e) beginning with the CY 2024 reporting period/FY 2026 
payment determination; (8) Hospital-Level, Risk Standardized Patient-
Reported Outcomes Performance Measure Following Elective Primary Total 
Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (NQF #3559) 
beginning with two voluntary periods, followed by mandatory reporting 
for the reporting period which runs from July 1, 2025 through June 30, 
2026, impacting the FY 2028 payment determination; (9) Medicare 
Spending Per Beneficiary (MSPB) Hospital (NQF #2158) beginning with the 
FY 2024 payment determination; and (10) Hospital-Level Risk-
Standardized Complication Rate (RSCR) Following Elective Primary THA/
TKA (NQF #1550) beginning with the FY 2024 payment determination. We 
are proposing refinements to two current measures beginning with the FY 
2024 payment determination: (1) Hospital[hyphen]Level, 
Risk[hyphen]Standardized Payment Associated with an Episode-of-Care for 
Primary Elective THA/TKA; and (2) Excess Days in Acute Care (EDAC) 
After Hospitalization for Acute Myocardial Infarction (AMI) (NQF 
#2881). We are also requesting comment on the potential future 
development and inclusion of two National Healthcare Safety Network 
(NHSN) measures: (1) Healthcare-Associated Clostridioides difficile 
Infection Outcome; and (2) Hospital-Onset Bacteremia & Fungemia 
Outcome.
    We are proposing changes to current policies related to eCQMs and 
hybrid measures: (1) A proposal to modify the eCQM reporting and 
submission requirements to increase the number of eCQMs to be reported 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (2) a proposal to remove the zero denominator 
declarations and case threshold exemption policies for hybrid measures 
beginning with the FY 2026 payment determination; (3) a proposal for 
the data submission and reporting requirements for patient-reported 
outcome-based performance measures (PRO-PMs) beginning with the FY 2026 
payment determination; and (4) a proposal to modify the eCQM validation 
policy to increase the requirement from 75 percent to 100 percent of 
requested medical records, beginning with the FY 2025 payment 
determination.
    With respect to public reporting, we are proposing to establish a 
hospital designation related to maternity care to be publicly-reported 
on a public-facing website beginning in Fall 2023, and are also seeking 
comments on other potential associated activities regarding this 
designation. Additionally, we are seeking comments on ongoing ways we 
can advance digital quality measurement and use of Fast Healthcare 
Interoperability Resources (FHIR).
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 FY 2023 IPPS/LTCH PPS proposed rule, we are proposing to 
adopt a patient safety exception into the measure removal policy. We 
are also proposing to begin public display of the 30-Day Unplanned 
Readmissions for Cancer Patients measure (NQF #3188) (PCH-36), the 
Proportion of Patients Who Died from Cancer Receiving Chemotherapy in 
the Last 14 Days of Life measure (NQF #0210) (PCH-32), the Proportion 
of Patients Who Died from Cancer Not Admitted to Hospice measure (NQF 
#0215) (PCH-34), the Proportion of Patients Who Died from Cancer 
Admitted to the ICU in the Last 30 Days of Life measure (NQF #0213) 
(PCH-33), and the Proportion of Patients Who Died from Cancer Admitted 
to Hospice for Less Than Three Days measure (NQF #0216) (PCH-35). In 
addition, along with the Hospital IQR and HAC Reduction Programs, we 
are requesting comment on the potential adoption of two digital 
National Healthcare Safety Network (NHSN) measures: The NHSN 
Healthcare-associated Clostridioides difficile Infection Outcome 
measure and NHSN Hospital-Onset Bacteremia and Fungemia Outcome 
measure.
l. Medicare Promoting Interoperability Program
    For CY 2023, we are proposing several changes to the Medicare 
Promoting Interoperability Program. Specifically, we are proposing: (1) 
To require and modify the Electronic Prescribing Objective's Query of 
Prescription Drug Monitoring Program (PDMP) measure while maintaining 
the associated points at 10 points beginning with the EHR reporting 
period in CY 2023; (2) to expand the Query of PDMP measure to include 
Schedule II, III, and IV drugs beginning with the CY 2023 EHR reporting 
period; (3) to add a new Health Information Exchange (HIE) Objective 
option, the Enabling Exchange under the Trusted Exchange Framework and 
Common Agreement (TEFCA) measure (requiring a yes/no response), as an 
optional alternative to fulfill the objective, beginning with the CY 
2023 EHR reporting period; (4) to modify the Public Health and Clinical 
Data Exchange Objective by adding an Antibiotic Use and Antibiotic 
Resistance (AUR) measure in addition to the current four required 
measures (Syndromic Surveillance Reporting, Immunization Registry 
Reporting, Electronic Case Reporting, and Electronic Reportable 
Laboratory Result Reporting beginning in the CY 2023 EHR reporting 
period; (5) to consolidate the current options from three to two levels 
of active engagement for the Public Health and Clinical Data Exchange 
Objective and to require the reporting of active engagement for the 
measures under the objective beginning with the CY 2023 EHR reporting 
period; (6) to modify the scoring methodology for the Medicare 
Promoting Interoperability Program beginning in CY 2023; (7) to 
institute public reporting of certain Medicare Promoting 
Interoperability Program data beginning with the CY 2023 EHR reporting 
period; (8) to remove regulation text for the objectives and measures 
in the Medicare Promoting Interoperability Program from paragraph (e) 
under 42 CFR 495.24 and add new paragraph (f) beginning in CY 2023; and 
(9) to adopt two new eCQMs in the Medicare Promoting Interoperability 
Program's eCQM measure set beginning with the CY 2023 reporting period, 
two new eCQMs in the Medicare Promoting Interoperability Program's eCQM 
measure set beginning with the CY 2024 reporting period, and modify the 
eCQM data reporting and submission requirements to increase the number 
of eCQMs required to be reported and the total number of eCQMs

[[Page 28115]]

to be reported beginning with the CY 2024 reporting period, which is in 
alignment with the eCQM updates proposed for the Hospital IQR Program.
m. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
To Report Data Elements To Address Any Future Pandemics and Epidemics 
as Determined by the Secretary
    In this proposed rule, we would revise the hospital and CAH 
infection prevention and control CoP requirements to continue COVID-19 
reporting requirements commencing either upon the conclusion of the 
current COVID-19 PHE declaration or the effective date of this proposed 
rule, whichever is later, and lasting until April 30, 2024 (unless the 
Secretary determines an earlier end date). We also propose additional 
requirements to address future PHEs related to epidemics and pandemics. 
Specifically, when the Secretary has declared a PHE, we propose to 
require hospitals and CAHs to report specific data elements to the 
CDC's National Health Safety Network (NHSN), or other CDC-supported 
surveillance systems, as determined by the Secretary. The proposed 
requirements of this section would apply to local, state, and national 
PHEs as declared by the Secretary. Additionally, we are proposing that 
the hospital (or CAH) provide the information specified on a daily 
basis, unless the Secretary specifies a lesser frequency contingent 
upon the state of the PHE and ongoing risks.
n. Comment Solicitation on IPPS and Outpatient Prospective Payment 
System (OPPS) Payment Adjustments for Wholly Domestically Made National 
Institute for Occupational Safety and Health (NIOSH)-Approved Surgical 
N95 Respirators
    As discussed in section X.C. of the preamble of this proposed rule, 
the Biden-Harris Administration has made it a priority to ensure 
America is prepared to continue to respond to COVID-19, and to combat 
future pandemics. A significant action to improve hospital preparedness 
and readiness for future threats might be to provide payment 
adjustments to hospitals to recognize the additional resource costs 
they incur to acquire NIOSH-approved surgical N95 respirators that are 
wholly domestically made. These surgical respirators, which faced 
severe shortage at the onset of the COVID-19 pandemic, are essential 
for the protection of beneficiaries and hospital personnel that 
interface with patients. The Department of Health and Human Services 
(HHS) recognizes that procurement of surgical N95 respirators that are 
wholly domestically made, while critical to pandemic preparedness and 
protecting health care workers and patients, can result in additional 
resource costs for hospitals.
    We are interested in feedback and comments on the appropriateness 
of payment adjustments that would account for these additional resource 
costs. We believe such a payment adjustment could help achieve a 
strategic policy goal, namely, sustaining a level of supply resilience 
for surgical N95 respirators that is critical to protect the health and 
safety of personnel and patients in a public health emergency. We are 
considering such payment adjustments to apply to 2023 and potentially 
subsequent years. We realize there may be different ways a payment 
adjustment to recognize the additional resource costs hospitals incur 
when purchasing wholly domestically made NIOSH-approved surgical N95 
respirators could be implemented and seek comment on two potential 
frameworks and alternative approaches.
3. Summary of Costs and Benefits
    The following table provides a summary of the costs, savings, and 
benefits associated with the major provisions described in section 
I.A.3. of the preamble of this proposed rule.
BILLING CODE 4120-01-P

[[Page 28116]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.000


[[Page 28117]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.001


[[Page 28118]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.002

BILLING CODE 4120-01-C

[[Page 28119]]

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 and, as we are proposing beginning in FY 2023 for IHS and 
Tribal hospitals and hospitals located in Puerto Rico, the proposed new 
supplemental payment.
    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). As section 50205 of the Bipartisan 
Budget Act extended the MDH program through FY 2022 only, for FY 2023, 
beginning on October 1, 2022, the MDH program will no longer be in 
effect absent a change in law. Because the MDH program is not 
authorized by statute beyond September 30, 2022, beginning October 1, 
2022, all hospitals that previously qualified for MDH status under 
section 1886(d)(5)(G) of the Act will no longer have MDH status and 
will be paid based on the IPPS Federal rate.
    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

[[Page 28120]]

institutions (RNHCIs) are also excluded from the IPPS. Various sections 
of the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33), the 
Medicare, Medicaid and SCHIP [State Children's Health Insurance 
Program] Balanced Budget Refinement Act of 1999 (BBRA, Pub. L. 106-
113), and the Medicare, Medicaid, and SCHIP Benefits Improvement and 
Protection Act of 2000 (BIPA, Pub. L. 106-554) provide for the 
implementation of PPSs for IRF hospitals and units, LTCHs, and 
psychiatric hospitals and units (referred to as inpatient psychiatric 
facilities (IPFs)). (We note that the annual updates to the LTCH PPS 
are included 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.

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 2023 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 2023.
    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 
the following:
     Proposed changes to MS-DRG classifications based on our 
yearly review for FY 2023.
     Proposed adjustment to the standardized amounts under 
section 1886(d) of the Act for FY 2023 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, 
including a proposed 10 percent cap on decreases in an MS-DRG relative 
weight from one fiscal year to the next.
     A discussion of the proposed FY 2023 status of new 
technologies approved for add-on payments for FY 2022, a presentation 
of our evaluation and analysis of the FY 2023 applicants for add-on 
payments for high-cost new medical services and technologies (including 
public input, as directed by Pub. L. 108-173, obtained in a town hall 
meeting) for applications not submitted under an alternative pathway, 
and a discussion of the proposed status of FY 2023 new technology 
applicants under the alternative pathways for certain medical devices 
and certain antimicrobial products.
     A proposal to use National Drug Codes (NDCs) to identify 
cases involving use of therapeutic agents approved for new technology 
add-on payments.
     A proposal to publicly post online future applications for 
new technology add-on payments. Specifically, beginning with the FY 
2024 application cycle, we are proposing to post online the completed 
application forms and certain related materials and updated application 
information submitted subsequent to the initial application submission 
for new technology add-on payments, with the exception of certain cost 
and volume information and certain additional materials (as discussed 
more fully in section II.F.9. of this proposed rule), no later than the 
issuance of the proposed rule.

[[Page 28121]]

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 2023 wage index update using wage data 
from cost reporting periods beginning in FY 2019.
     Calculation, analysis, and implementation of the proposed 
occupational mix adjustment to the wage index for acute care hospitals 
for FY 2023 based on the 2019 Occupational Mix Survey.
     Proposed application of the rural, imputed and frontier 
State floors, and continuation of the low wage index hospital policy.
     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 adjustment to the wage index for acute care 
hospitals for FY 2023 based on commuting patterns of hospital employees 
who reside in a county and work in a different area with a higher wage 
index.
     Proposed permanent cap on annual wage index decreases.
     Proposed labor-related share for the proposed FY 2023 wage 
index.
3. 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 2023.
     Proposed updated national and regional case-mix values and 
discharges for purposes of determining RRC status.
     Proposed payment adjustment for low-volume hospitals for 
FY 2023 and subsequent years.
     The statutorily required IME adjustment factor for FY 
2023.
     Proposed changes to the methodologies for determining 
Medicare DSH payments and the additional payments for uncompensated 
care.
     Proposed new supplemental payment for IHS/Tribal and 
Puerto Rico hospitals.
     Proposed revisions to the regulations regarding the 
counting of days associated with section 1115 demonstrations in the 
Medicaid fraction.
     Discussion of statutory expiration of the MDH program at 
the end of FY 2022.
     Proposed requirements for payment adjustments under the 
Hospital Readmissions Reduction Program for FY 2023.
     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 2023.
     Discussion of and proposed changes relating to the 
implementation of the Rural Community Hospital Demonstration Program in 
FY 2023.
     Proposed GME payment change in response to Milton S. 
Hershey Medical Center et al v. Becerra litigation.
     Proposed nursing and allied health education program 
Medicare Advantage (MA) add-on rates and direct GME MA percent 
reductions for CYs 2020 and 2021.
     Proposal to allow Medicare GME affiliation agreements 
within certain rural track full-time equivalent limitations.
     Proposed payment adjustment for certain clinical trial and 
expanded access use immunotherapy cases.
4. Proposed FY 2023 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 2023.
5. 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 2023.
     Proposed continued implementation of the Frontier 
Community Health Integration Project (FCHIP) Demonstration.
6. 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 2023.
7. 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).
     For the Long Term Care Hospital Quality Reporting Program 
(LTCH QRP), we are requesting information on CMS' overarching 
principles for measuring healthcare disparities across CMS Quality 
Programs, including the LTCH QRP. We are also requesting information on 
the potential adoption of one future National Healthcare Safety Network 
(NHSN) digital quality measure (dQM) for the LTCH QRP, as well as 
quality measure concepts under consideration for future years.
     Proposed changes to requirements pertaining to eligible 
hospitals and CAHs participating in the Medicare Promoting 
Interoperability Program.
8. Other Proposals and Comment Solicitations Included in This Proposed 
Rule
    Section X. of the preamble to this proposed rule includes the 
following:
     Proposals to codify policies related to the costs incurred 
for qualified and non-qualified deferred compensation plans.
     Proposed changes pertaining to the CoPs at 42 CFR part 482 
for hospitals, and at 42 CFR part 485, subpart F, for CAHs.
     Solicitation of comments on the appropriateness of payment 
adjustments that would account for the additional resource costs for 
hospitals for the procurement of wholly domestically made NIOSH-
approved surgical N95 respirators.
9. 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.

[[Page 28122]]

10. 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 2023 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 2023 for certain hospitals 
excluded from the IPPS.
11. 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 2023 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 
2023. 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.
12. 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 and other entities.
13. 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 2023 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.
14. 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 2022 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 2022 
report or to obtain a copy of the report, contact MedPAC at (202) 220-
3700 or visit MedPAC's website at https://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 digital health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) to facilitate collaboration with industry 
stakeholders to develop Health Level Seven International[supreg] (HL7) 
Fast Healthcare Interoperability Resources[supreg] (FHIR) standards. 
These standards could support the exchange and reuse of patient 
assessment data derived from the post-acute care (PAC) setting 
assessment tools, such as Minimum Data Set (MDS), Inpatient 
Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI), Long 
Term Care Hospital (LTCH) Continuity Assessment Record and Evaluation 
(CARE) Data Set (LCDS), Outcome and Assessment Information Set (OASIS), 
and other sources.1 2 The PACIO Project has focused on HL7 
FHIR implementation guides for functional status, cognitive status and 
new use cases on advance directives, re-assessment timepoints, and 
Speech, Language, Swallowing Cognitive communications and Hearing 
(SPLASCH).\3\ We encourage PAC provider and health internet technology 
(IT) vendor participation as the efforts advance. The CMS Data Element 
Library (DEL) continues to be updated and serves as a 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).\4\ The DEL furthers CMS' goal of data standardization and 
interoperability. Standards in the DEL can be referenced on the CMS 
website (https://del.cms.gov/DELWeb/pubHome) and in the ONC 
Interoperability Standards Advisory (ISA). The 2022 ISA is available at 
https://www.healthit.gov/isa/sites/isa/files/inline-files/2022-ISA-Reference-Edition.pdf.
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    \1\ HL7 FHIR Release 4. Available at: https://www.hl7.org/fhir/.
    \2\ HL7 FHIR. PACIO Functional Status Implementation Guide. 
Available at: https://paciowg.github.io/functional-status-ig/.
    \3\ PACIO Project. Available at: http://pacioproject.org/about/.
    \4\ CMS Data Element Library Fact Sheet. Available at: https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet.
    \5\ Public Law 114-255, sections 4001 through 4008. Available 
at: https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm.
    \6\ The Trusted Exchange Framework (TEF): Principles for Trusted 
Exchange (Jan. 2022). Available at: https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \7\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022). Available at: https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted 
December 13, 2016) required HHS and ONC to take steps further 
interoperability for providers in settings across the care 
continuum.\5\ Specifically, section 4003(b) of the Cures Act required 
ONC to take steps to advance interoperability through the development 
of a trusted exchange framework and common agreement aimed at 
establishing a universal floor of interoperability across the country. 
On January 18, 2022, ONC announced a significant milestone by releasing 
the Trusted Exchange Framework \6\ and Common Agreement Version 1.\7\ 
The Trusted Exchange Frameworkis a set of non-binding principles for 
health information exchange, and the Common Agreement is a contract 
that advances those principles. The Common Agreement and the 
incorporated by reference Qualified Health Information Network 
Technical Framework Version 1 establish the technical infrastructure 
model and governing approach for different health information networks 
and their users to securely share clinical

[[Page 28123]]

information with each other, all under commonly agreed to terms. The 
technical and policy architecture of how exchange occurs under the 
Trusted Exchange Framework and the Common Agreement follows a network-
of-networks structure, which allows for connections at different levels 
and is inclusive of many different types of entities at those different 
levels, such as health information networks, healthcare practices, 
hospitals, public health agencies, and Individual Access Services (IAS) 
Providers.\8\ For more information, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \8\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' The Common Agreement 
defines ``IAS Provider'' as: ``Each QHIN, Participant, and 
Subparticipant that offers Individual Access Services.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    We invite providers to learn more about these important 
developments and how they are likely to affect hospitals.

F. Proposed Use of FY 2021 Data and Proposed Methodology Modifications 
for the FY 2023 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. The cost report data source is the Medicare hospital cost 
report data files from the most recent quarterly Healthcare Cost Report 
Information System (HCRIS) release. Our goal is always to use the best 
available data overall for ratesetting. Ordinarily, the best available 
MedPAR data is 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. Ordinarily, the best available 
cost report data is based on the cost reports beginning 3 fiscal years 
prior to the fiscal year that is the subject of the rulemaking. 
However, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44789 through 
44793), we finalized our proposal to use FY 2019 data for the FY 2022 
ratesetting for circumstances where the FY 2020 data (the most recently 
available data at the time of rulemaking) was significantly impacted by 
the COVID-19 PHE.
    As we discussed in the FY 2022 IPPS/LTCH PPS final rule, the FY 
2020 MedPAR claims file and the FY 2019 HCRIS dataset both contained 
data that was significantly impacted by the COVID-19 PHE, primarily in 
that the utilization of services at IPPS hospitals and LTCHs was 
generally markedly different for certain types of services in FY 2020 
than would have been expected in the absence of the PHE. However, the 
most recent vaccination and hospitalization data from the CDC at the 
time of development of that rule supported our belief at the time that 
the risk of COVID-19 in FY 2022 would be significantly lower than the 
risk of COVID-19 in FY 2020 and there would be fewer COVID-19 
hospitalizations for Medicare beneficiaries in FY 2022 than there were 
in FY 2020. Therefore, we finalized our proposal to use FY 2019 data 
for the FY 2022 ratesetting for circumstances where the FY 2020 data 
was significantly impacted by the COVID-19 PHE, based on the belief 
that FY 2019 data from before the COVID-19 PHE would be a better 
overall approximation of the FY 2022 inpatient experience at both IPPS 
hospitals and LTCHs. For example, we used the FY 2019 MedPAR claims 
data for purposes where we ordinarily would have used the FY 2020 
MedPAR claims data. We also used cost report data from the FY 2018 
HCRIS file for purposes where we ordinarily would have used the FY 2019 
HCRIS file (since the FY 2019 cost report data from HCRIS contained 
many cost reports ending in FY 2020 based on each hospital's cost 
reporting period).
    Similar to our analysis of the FY 2020 MedPAR claims file and the 
FY 2019 HCRIS dataset for the FY 2022 IPPS/LTCH PPS rulemaking, the FY 
2021 MedPAR claims file and the FY 2020 HCRIS dataset also both contain 
data that was significantly impacted by the virus that causes COVID-19, 
primarily in that the utilization of services at IPPS hospitals and 
LTCHs was again generally markedly different for certain types of 
services in FY 2021 than would have been expected in the absence of the 
virus that causes COVID-19. Specifically, the share of admissions at 
IPPS hospitals and LTCHs for MS-DRGs and MS-LTC-DRGs associated with 
the treatment of COVID-19 continued to remain significantly higher than 
levels prior to the COVID-19 PHE. For example, in FY 2019, the share of 
IPPS cases and LTCH PPS standard Federal payment rate cases grouped to 
MS-DRG and MS-LTC-DRG 177 (Respiratory infections and inflammations 
with MCC) was approximately 1 percent and 2 percent, respectively. In 
comparison, in FY 2021, the share of IPPS cases and LTCH PPS standard 
Federal payment rate cases grouped to MS-DRG 177 was approximately 6 
percent and 8 percent, respectively. However, as we discuss further in 
this section, in light of the expected continued impact on 
hospitalizations of the virus that causes COVID-19, we believe it is 
appropriate to use the FY 2021 data reflecting this impact for this FY 
2023 IPPS/LTCH PPS rulemaking, with some proposed modifications to our 
usual ratesetting methodologies to account for the anticipated decline 
in COVID-19 hospitalizations of Medicare beneficiaries at IPPS 
hospitals and LTCHs as compared to FY 2021.
    The CDC graph below illustrates new inpatient hospital admissions 
of patients with confirmed COVID-19 from August 1, 2020 through 
February 15, 2022. (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/02182022/images/hospitalizations_02182022.jpg?_=35767, 
accessed February 22, 2022)

[[Page 28124]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.003

    The low point of the graph (late June 2021) approximately coincides 
with the time of the development of the FY 2022 IPPS/LTCH PPS final 
rule and generally supports, in conjunction with the other factors 
discussed in that rulemaking (including the most recent vaccination 
data from the CDC), our assumption in the final rule that the FY 2022 
time period would be more similar to the time period prior to the PHE. 
However, as can be seen in the graph, the virus that causes COVID-19 
has continued to significantly impact hospitalizations for the time 
period subsequent to the development of the FY 2022 IPPS/LTCH PPS final 
rule. As the CDC has noted, the most recent increase in 
hospitalizations has been primarily associated with the Omicron variant 
of the virus.\9\ The CDC has stated that new variants will continue to 
emerge. Viruses constantly change through mutation and sometimes these 
mutations result in a new variant of the virus. The CDC and other 
public health organizations monitor all variants of the virus that 
causes COVID-19 in the United States and globally. Scientists monitor 
all variants but may classify certain ones as variants being monitored, 
variants of interest, variants of concern and variants of high 
consequence. Some variants spread more easily and quickly than other 
variants, which may lead to more cases of COVID-19. Even if a variant 
causes less severe disease in general, an increase in the overall 
number of cases could cause an increase in hospitalizations. (see 
https://www.cdc.gov/coronavirus/2019-ncov/variants/about-variants.html, 
accessed February 25, 2022)
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    \9\ https://www.cdc.gov/coronavirus/2019-ncov/variants/omicron-variant.html.
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    Given the effects of the virus that causes COVID-19 in the Medicare 
FY 2020 data, the Medicare FY 2021 data, and the CDC hospitalization 
data, coupled with the expectation for future variants, we believe that 
it is reasonable to assume that some Medicare beneficiaries will 
continue to be hospitalized with COVID-19 at IPPS hospitals and LTCHs 
in FY 2023. Accordingly, we believe it is appropriate to use FY 2021 
data, specifically the FY 2021 MedPAR claims file and the FY 2020 HCRIS 
dataset (which contains data from many cost reports ending in FY 2021 
based on each hospital's cost reporting period) as the most recent 
available data during the period of the COVID-19 PHE, for purposes of 
the FY 2023 IPPS and LTCH PPS ratesetting. However, we also believe it 
is reasonable to assume based on the information available at this time 
that there will be fewer COVID-19 hospitalizations in FY 2023 than in 
FY 2021 given the more recent trends in the CDC hospitalization data 
since the Omicron variant peak in January, 2022. Accordingly, because 
we anticipate Medicare inpatient hospitalizations for COVID-19 will 
continue in FY 2023 but at a lower level, we are proposing to use FY 
2021 data for purposes of the FY 2023 IPPS and LTCH PPS ratesetting but 
with modifications to our usual ratesetting methodologies to account 
for the anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals and LTCHs as compared to FY 2021.
    First, we are proposing to modify the calculation of the FY 2023 
MS-DRG and MS-LTC-DRG relative weights. We observed that COVID-19 cases 
were impacting the relative weights as calculated using the FY 2021 
MedPAR data for a few COVID-19-related MS-DRGs and MS-LTC-DRGs. As an 
example, for MS-DRG and MS-LTC-DRG 870 (Septicemia or Severe Sepsis 
with MV >96 hours), the MS-DRG and MS-LTC-DRG relative weights 
calculated using the FY 2021 MedPAR data are approximately 9 and 3 
percent higher, respectively, compared to their relative weights if 
calculated excluding COVID-19 cases. Because this MS-DRG contains a mix 
of COVID-19 cases and non-COVID-19 cases with different average costs, 
the relative weight for this MS-DRG is dependent on that mix of cases. 
As noted previously, we believe it is reasonable to assume that there 
will be fewer COVID-19 hospitalizations among Medicare beneficiaries in 
FY 2023 than there were in FY 2021; however it is not possible to know 
precisely how COVID-19 hospitalizations in FY 2023 will compare to FY 
2021. We believe that averaging the relative weights as calculated with 
and without the COVID-19 cases reflected in the FY 2021 MedPAR data 
would reflect a reasonable estimation of the case mix for FY 2023 based 
on the information available at this time, and more accurately estimate 
the relative resource use for the cases treated in FY 2023. Therefore, 
we are proposing to calculate the relative weights for FY 2023 by first 
calculating two sets of weights, one including and one excluding COVID-
19 claims, and then averaging the two sets of relative weights to 
determine the proposed FY 2023 relative weight values. We believe this 
proposed modification to our relative weight setting methodology would 
appropriately reduce, but not remove entirely, the effect of COVID-19 
cases on the relative weight calculations, consistent with our 
expectation that Medicare inpatient hospitalizations for COVID-19 will 
continue in FY 2023 at a lower level as compared to FY 2021,

[[Page 28125]]

and provide a more accurate estimate of relative resource use for FY 
2023 than if we were to calculate the proposed relative weights using 
all applicable cases in the FY 2021 data. The proposal for modifying 
the methodology for determining the FY 2023 IPPS MS-DRG relative 
weights is discussed in greater detail in section II.E. of the preamble 
of this proposed rule. The proposal for modifying the methodology for 
determining the FY 2023 LTCH PPS MS-LTC-DRG relative weights is 
discussed in greater detail in section VIII.B. of the preamble of this 
proposed rule.
    We also are proposing to modify our methodologies for determining 
the FY 2023 outlier fixed-loss amount for IPPS cases and LTCH PPS 
standard Federal payment rate cases. The methodologies for determining 
both of these outlier fixed-loss amounts include calculating and 
applying a charge inflation factor to increase charges from the claim 
year to the rulemaking year, as well as calculating and applying CCR 
adjustment factors to adjust CCRs used to make payments in the current 
year to the rulemaking year. The charge inflation factors calculated 
using the two most recently available years of MedPAR claims data (FY 
2020 and FY 2021) that would ordinarily be used for this FY 2023 
proposed rule to inflate the charges on the FY 2021 MedPAR claims were 
abnormally high as compared to recent historical levels prior to the 
PHE (for example, for the IPPS, approximately 10 percent based on the 
FY 2020 and FY 2021 MedPAR claims data as compared to approximately 6 
percent based on the FY 2018 and FY 2019 MedPAR claims data). 
Furthermore, the IPPS operating and capital CCR adjustment factors 
calculated based on the percentage changes in the CCRs from the 
December 2020 update of the PSF to the December 2021 update of the PSF 
that would ordinarily be used for this FY 2023 proposed rule to adjust 
the CCRs from the December 2021 update of the PSF were also abnormally 
high as compared to recent historical levels prior to the PHE (for 
example, for the IPPS operating CCR adjustment factor, a factor of 
approximately 1.03 based on the December 2020 and December 2021 updates 
to the PSF as compared to a factor of approximately 0.97 based on the 
March 2019 and March 2020 updates to the PSF). We believe these 
abnormally high charge inflation and CCR adjustment factors as compared 
to historical levels were partially due to the high number of COVID-19 
cases with higher charges that were treated in IPPS hospitals and LTCHs 
in FY 2021. As we previously stated, we believe there will be fewer 
COVID-19 cases in FY 2023 than in FY 2021. Therefore, we do not believe 
it is reasonable to assume charges and CCRs will continue to increase 
at these abnormally high rates. Consequently, when determining the FY 
2023 outlier fixed-loss amounts for IPPS cases and LTCH PPS standard 
Federal payment rate cases, we are proposing to inflate the charges on 
the FY 2021 MedPAR claims using charge inflation factors computed by 
comparing the average covered charge per case in the March 2019 MedPAR 
file of FY 2018 to the average covered charge per case in the March 
2020 MedPAR file of FY 2019, which is the last 1-year period prior to 
the COVID-19 PHE. We also are proposing to adjust the CCRs from the 
December 2021 update of the PSF by comparing the percentage change in 
the national average case-weighted CCR from the March 2019 update of 
the PSF to the national average case-weighted CCR from the March 2020 
update of the PSF, which is the last 1-year period prior to the COVID-
19 PHE. We believe using the charge inflation factors and CCR 
adjustment factors derived from data prior to the COVID-19 PHE would 
provide a more reasonable approximation of the increase in costs that 
will occur from FY 2021 to FY 2023 because we do not believe the charge 
inflation that has occurred during the PHE will continue as the number 
of higher cost COVID-19 cases declines. The proposal for modifying the 
methodology for determining the FY 2023 outlier fixed-loss amounts for 
IPPS cases is discussed in greater detail in section II.A.4. of the 
addendum to this proposed rule. The proposal for modifying the 
methodology for determining the FY 2023 outlier fixed-loss amounts for 
LTCH PPS standard Federal payment rate cases is discussed in greater 
detail in section V.D.3. of the addendum to this proposed rule.
    As discussed in section I.O. of Appendix A of this proposed rule, 
we are also requesting comments on, as an alternative to our proposed 
approach, the use of the FY 2021 data for purposes of FY 2023 
ratesetting without these proposed modifications to our usual 
methodologies for the calculation of the FY 2023 MS-DRG and MS-LTC-DRG 
relative weights or the usual methodologies used to determine the FY 
2023 outlier fixed-loss amount for IPPS cases and LTCH PPS standard 
Federal payment rate cases. We note that the FY 2023 outlier fixed-loss 
amount would be significantly higher under this alternative approach. 
In order to illustrate the effect of our proposed modifications on the 
relative weights and fixed loss amount, we are making available 
supplemental information, including the relative weights and fixed loss 
amount calculated without the proposed modifications to our usual 
methodologies, as described in section I.O. of Appendix A of this 
proposed rule. 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.

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 2022 IPPS/LTCH PPS final 
rules (75 FR 50053 through 50055; 76

[[Page 28126]]

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, 85 FR 58445 through 
58596, 86 FR 44795 through 44961, respectively).

C. Proposed FY 2023 MS-DRG Documentation and Coding Adjustment

1. Background on the Prospective MS-DRG Documentation and Coding 
Adjustments for FY 2008 and FY 2009 Authorized by Public Law 110-90 and 
the Recoupment or Repayment Adjustment Authorized by Section 631 of the 
American Taxpayer Relief Act of 2012 (ATRA)
    In the FY 2008 IPPS final rule with comment period (72 FR 47140 
through 47189), we adopted the MS-DRG patient classification system for 
the IPPS, effective October 1, 2007, to better recognize severity of 
illness in Medicare payment rates for acute care hospitals. The 
adoption of the MS-DRG system resulted in the expansion of the number 
of DRGs from 538 in FY 2007 to 745 in FY 2008. By increasing the number 
of MS-DRGs and more fully taking into account patient severity of 
illness in Medicare payment rates for acute care hospitals, MS-DRGs 
encourage hospitals to improve their documentation and coding of 
patient diagnoses.
    In the FY 2008 IPPS final rule with comment period (72 FR 47175 
through 47186), we indicated that the adoption of the MS-DRGs had the 
potential to lead to increases in aggregate payments without a 
corresponding increase in actual patient severity of illness due to the 
incentives for additional documentation and coding. In that final rule 
with comment period, we exercised our authority under section 
1886(d)(3)(A)(vi) of the Act, which authorizes us to maintain budget 
neutrality by adjusting the national standardized amount, to eliminate 
the estimated effect of changes in coding or classification that do not 
reflect real changes in case-mix. Our actuaries estimated that 
maintaining budget neutrality required an adjustment of -4.8 percentage 
points to the national standardized amount. We provided for phasing in 
this -4.8 percentage point adjustment over 3 years. Specifically, we 
established prospective documentation and coding adjustments of -1.2 
percentage points for FY 2008, -1.8 percentage points for FY 2009, and 
-1.8 percentage points for FY 2010.
    On September 29, 2007, Congress enacted the TMA [Transitional 
Medical Assistance], Abstinence Education, and QI [Qualifying 
Individuals] Programs Extension Act of 2007 (Pub. L. 110-90). Section 
7(a) of Public Law 110-90 reduced the documentation and coding 
adjustment made as a result of the MS-DRG system that we adopted in the 
FY 2008 IPPS final rule with comment period to -0.6 percentage point 
for FY 2008 and -0.9 percentage point for FY 2009.
    As discussed in prior year rulemakings, and most recently in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56780 through 56782), we 
implemented a series of adjustments required under sections 7(b)(1)(A) 
and 7(b)(1)(B) of Public Law 110-90, based on a retrospective review of 
FY 2008 and FY 2009 claims data. We completed these adjustments in FY 
2013 but indicated in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53274 
through 53275) that delaying full implementation of the adjustment 
required under section 7(b)(1)(A) of Public Law 110-90 until FY 2013 
resulted in payments in FY 2010 through FY 2012 being overstated, and 
that these overpayments could not be recovered under Public Law 110-90.
    In addition, as discussed in prior rulemakings and most recently in 
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38008 through 38009), 
section 631 of the American Taxpayer Relief Act of 2012 (ATRA) amended 
section 7(b)(1)(B) of Public Law 110-90 to require the Secretary to 
make a recoupment adjustment or adjustments totaling $11 billion by FY 
2017. This adjustment represented the amount of the increase in 
aggregate payments as a result of not completing the prospective 
adjustment authorized under section 7(b)(1)(A) of Public Law 110-90 
until FY 2013.
2. Adjustments Made for FYs 2018, 2019, 2020, 2021, and 2022 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), FY 2021 IPPS/LTCH PPS final rule (85 FR 58444 and 
58445), and the FY 2022 IPPS/LTCH PPS final rule (86 FR 44794 and 
44795), 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, FY 2021, and FY 2022, 
respectively. We indicated the FY 2018, FY 2019, FY 2020, FY 2021, and 
FY 2022 adjustments were permanent adjustments to payment rates. We 
also stated that we plan to propose a future adjustment required under 
section 414 of the MACRA for FY 2023 in future rulemaking.
3. Proposed Adjustment for FY 2023
    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 2023. This would constitute a 
permanent adjustment to payment rates. This proposed 0.5 percentage 
point positive adjustment is the final adjustment prescribed by section 
414 of the MACRA. Along with the 0.4588 percentage point positive 
adjustment for FY 2018, and the 0.5 percentage point positive 
adjustments for FY 2019, FY 2020, FY 2021, and FY 2022, this final 
proposed adjustment will result in combined positive adjustment of 
2.9588 percentage points (or the sum of the adjustments for FYs 2018 
through 2023) to the standardized amount.

[[Page 28127]]

D. Proposed Changes to Specific MS-DRG Classifications

1. Discussion of Changes to Coding System and Basis for Proposed FY 
2023 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 2023 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 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. In the FY 2022 IPPS/LTCH PPS 
proposed rule, we stated that while we continue to believe that a 
change in the deadline from November 1 to October 20 would provide 
hospitals sufficient time to assess potential impacts and inform future 
MS-DRG recommendations, we were maintaining the deadline of November 1 
for FY 2023 MS-DRG classification change requests. As discussed in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 44795), we received public 
comments expressing support for a future change to the deadline for 
requesting updates to the MS-DRG classifications from November 1 to 
October 20, and we noted in response that we may consider any changes 
to the deadline or frequency for submissions of requests for MS-DRG 
classification changes for future fiscal years. Beginning with FY 2024 
MS-DRG classification change requests, we are changing the deadline to 
request changes to the MS-DRGs to October 20th of each year to allow 
for additional time for the review and consideration of any proposed 
updates. As previously discussed, we continue to believe such a change 
would allow hospitals sufficient time to assess potential impacts and 
inform future MS-DRG recommendations, while also providing CMS the 
additional time needed for evaluation of the requested changes, 
analysis of claims data, and consideration of any proposed updates.
    We are also changing the process for submitting requested updates 
to the MS-DRG classifications, beginning with the FY 2024 MS-DRG 
classification change requests. CMS is in the process of implementing a 
new electronic application intake system, Medicare Electronic 
Application Request Information SystemTM (MEARIS\TM\), that 
will be available for users to begin gaining familiarity with a new 
approach and process to submit new technology add-on payment 
applications, requests for ICD-10-PCS procedure codes, and other 
requests. To simplify and streamline the process for submission of 
standardized applications and requests that inform payment policy under 
the IPPS, we will also be using this new system for submission of MS-
DRG classification change requests. We believe that submission of MS-
DRG reclassification requests through MEARIS\TM\ will not only help CMS 
to track such requests, but it will also create efficiencies for 
requestors when compared to the previous submission process.
    Accordingly, beginning with the FY 2024 MS-DRG classification 
change requests, CMS will only accept such requests submitted via 
MEARIS\TM\, and will no longer consider any such requests that are sent 
via email. We anticipate that, beginning April 5, 2022, MEARIS\TM\ will 
be available for users to begin gaining familiarity with this new 
approach for submitting MS-DRG classification change requests. 
MEARIS\TM\, including the mechanism for submitting MS-DRG 
classification change requests, can be accessed at https://mearis.cms.gov. We encourage users to register and begin using this 
system to provide feedback on their experience with this initial 
version. We note that within MEARIS\TM\, we have built in several 
resources to support users, including a ``Resources'' section 
(available at https://mearis.cms.gov/public/resources) and technical 
support available under ``Useful Links'' at the bottom of the 
MEARIS\TM\ site. Questions regarding the MEARIS\TM\ system can be 
submitted to CMS using the form available under ``Contact'' at https://mearis.cms.gov/public/resources?app=msdrg.
    We also note that, as discussed in section II.D.17. of the preamble 
of this proposed rule, effective January 5, 2022, MEARIS\TM\ was made 
available for users to begin gaining familiarity with a new approach 
and process to submit ICD-10-PCS procedure code requests.
    As noted previously, interested parties had to submit MS-DRG 
classification change requests for FY 2023 by November 1, 2021. As we 
have discussed in prior rulemaking, 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 submit any comments and 
suggestions for FY 2024 by October 20, 2022 via the new electronic 
intake system, Medicare Electronic Application Request Information 
SystemTM (MEARISTM) at https://mearis.cms.gov/public/home.
    As we did for the FY 2022 IPPS/LTCH PPS proposed rule, for this FY 
2023 IPPS/LTCH PPS proposed rule we are providing a test version of the 
ICD-10

[[Page 28128]]

MS-DRG GROUPER Software, Version 40, 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 2023. Therefore, it includes the new diagnosis and 
procedure codes that are effective for FY 2023 as reflected in Table 
6A.--New Diagnosis Codes--FY 2023 and Table 6B.--New Procedure Codes--
FY 2023 associated with this proposed rule and does not include the 
diagnosis codes that are invalid beginning in FY 2023 as reflected in 
Table 6C.--Invalid Diagnosis Codes--FY 2023 associated with this 
proposed rule. We note that at the time of the development of this 
proposed rule there were no procedure codes designated as invalid for 
FY 2023, and therefore, there is no Table 6D--Invalid Procedure Codes--
FY 2023 associated with 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. Because 
the diagnosis codes no longer valid for FY 2023 are not reflected in 
the test software, we are making available a supplemental file in Table 
6P.1a that includes the mapped Version 40 FY 2023 ICD-10-CM codes and 
the deleted Version 39.1 FY 2022 ICD-10-CM 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 40.
    The test version of the ICD-10 MS-DRG GROUPER Software, Version 40, 
the draft version of the ICD-10 MS-DRG Definitions Manual, Version 40, 
and the supplemental mapping files in Table 6P.1a of the FY 2022 and FY 
2023 ICD-10-CM diagnosis 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 2023. 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 the FY 2021 MedPAR data for purposes of this FY 2023 IPPS 
rulemaking, with certain proposed modifications to the relative weight 
and outlier methodologies. For this FY 2023 IPPS/LTCH PPS proposed 
rule, our MS-DRG analysis was based on ICD-10 claims data from the 
September 2021 update of the FY 2021 MedPAR file, which contains 
hospital bills received from October 1, 2020 through September 30, 
2021, for discharges occurring through September 30, 2021. In our 
discussion of the proposed MS-DRG reclassification changes, we refer to 
these claims data as the ``September 2021 update of the FY 2021 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 our belief 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 the FY 2022 IPPS/LTCH PPS final rule (86 FR 44798), we finalized 
a delay in applying this technical criterion to existing MS-DRGs until 
FY 2023 or future rulemaking, in light of the PHE. Commenters 
recommended that a complete analysis of the MS-DRG changes to be 
proposed for future rulemaking in connection with the expanded three-
way severity split criteria be conducted and made available to enable 
the public an opportunity to review and consider the redistribution of 
cases, the impact to the relative weights, payment rates, and hospital 
case mix to allow meaningful comment prior to implementation.
    In our analysis of the MS-DRG classification requests for FY 2023 
that we received by November 1, 2021, 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 28129]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.004

    In general, once the decision has been made to propose to make 
further modifications to the MS-DRGs as described previously, such as 
creating a new base MS-DRG, or in our evaluation of a specific MS-DRG 
classification request to split (or subdivide) an existing base MS-DRG 
into severity levels, all five criteria must be met for the base MS-DRG 
to be split (or subdivided) by a CC subgroup. We note that in our 
analysis of requests to create a new MS-DRG, we typically evaluate the 
most recent year of MedPAR claims data available. For example, we 
stated earlier that for this FY 2023 IPPS/LTCH PPS proposed rule, our 
MS-DRG analysis was based on ICD-10 claims data from the September 2021 
update of the FY 2021 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 2 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 are 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 2023 IPPS/LTCH PPS proposed rule, using the September 
2021 update of the FY 2021 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 2023. 
Findings from our analysis indicated that approximately 41 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 123 MS-DRGs (41 MS-DRGs 
x 3 severity levels = 123) and the creation of 75 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.1b for the 
list of the 123 MS-DRGs that would be subject to deletion and the list 
of the 75 new MS-DRGs that would be proposed for creation for FY 2023 
under this policy if the NonCC subgroup criteria were applied.
    In light of the ongoing public health emergency (PHE), we continue 
to have concerns about the impact of implementing this volume of MS-DRG 
changes at this time, and believe it may be appropriate to continue to 
delay application of the NonCC subgroup criteria to existing MS-DRGs to 
maintain more stability in the current MS-DRG structure and until such 
time additional analyses can be performed to assess impacts, as 
discussed in response to comments in the FY 2022 IPPS/LTCH PPS final 
rule. Therefore, we are proposing not to apply the NonCC subgroup 
criteria to existing MS-DRGs with a three-way severity level split for 
FY 2023, and to instead maintain the current structure of the 41 MS-
DRGs that currently have a three-way severity level split (total of 123 
MS-DRGs) that would otherwise be subject to these criteria. We intend 
to address the application of the NonCC subgroup criteria to existing 
MS-DRGs with a three-way severity level split in future rulemaking.
2. Pre-MDC: MS-DRG 018 Chimeric Antigen Receptor (CAR) T-Cell and Other 
Immunotherapies
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44798 through 
44806), we finalized our proposal to assign procedure codes describing 
CAR T-cell, non-CAR T-cell, and other immunotherapies to Pre-MDC MS-DRG

[[Page 28130]]

018 and to revise the title for Pre-MDC MS-DRG 018 to ``Chimeric 
Antigen Receptor (CAR) T-cell and Other Immunotherapies'' to reflect 
this assignment. In that discussion, we noted that a few commenters 
recommended we continue to work with stakeholders on ways to improve 
the predictability and stability of hospital payments for these 
complex, novel cell therapies and that we should continue to monitor 
and assess the appropriateness of therapies assigned to MS-DRG 018, if 
they continue to be aligned on resource use, and whether additional 
refinements or MS-DRGs may be warranted in the future.
    We also noted that the process of code creation and proposed 
assignment to the most appropriate MS-DRG exists independently, 
regardless of whether there is an associated application for a new 
technology add-on payment for a product or technology submitted for 
consideration in a given fiscal year. Specifically, requests for a new 
code(s) or updates to existing codes are addressed through the ICD-10 
Coordination and Maintenance Committee meetings, held annually in the 
spring and fall, where code proposals are presented and the public is 
provided the opportunity to comment. All codes finalized from the fall 
meeting are subsequently proposed for assignment under the ICD-10 MS-
DRGs through rulemaking. We refer the reader to section II.D.17 of the 
preamble of this proposed rule for additional information regarding the 
ICD-10 Coordination and Maintenance Committee meeting process.
    There were no requests or proposals for new procedure codes to 
describe the administration of a CAR T-cell or another type of gene or 
cellular therapy discussed at the September 14-15, 2021 ICD-10 
Coordination and Maintenance Committee meeting. For the March 8-9, 2022 
ICD-10 Coordination and Maintenance Committee meeting, there were 
topics included on the agenda and in the related meeting materials that 
included proposals for new procedure codes to describe the 
administration of a CAR T-cell or another type of gene or cellular 
therapy product. The agenda and related meeting materials for these 
specific topics are available via the internet on the CMS website at 
https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44805) and 
noted previously, the process of code creation and proposed assignment 
to the most appropriate MS-DRG exists independently, regardless of 
whether there is an associated application for a new technology add-on 
payment for a product or technology submitted for consideration in a 
given fiscal year. We also clarified that the assignment of a procedure 
code to a MS-DRG is not dependent upon a product's Food and Drug 
Administration (FDA) approval. Similarly, the creation of a code to 
describe a technology that is utilized in the performance of a 
procedure or service does not require FDA approval of the technology.
    Because the diagnosis and procedure code proposals that are 
presented at the March meeting for an October 1 implementation 
(upcoming FY) are not finalized in time to include in Table 6A.--New 
Diagnosis Codes and Table 6B.--New Procedure Codes in association with 
the proposed rule, as noted in prior rulemaking, we use our established 
process to examine the MS-DRG assignment for the predecessor codes to 
determine the most appropriate MS-DRG assignment. Specifically, we 
review the predecessor code and MS-DRG assignment most closely 
associated with the new 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 or 
treatment of the condition. We have noted in prior rulemaking that this 
process does not automatically result in the new procedure code being 
assigned to the same MS-DRG or to have the same designation (O.R. 
versus Non-O.R.) as the predecessor code.
    In response to commenters' recommendation that we continue to 
assess the appropriateness of the therapies assigned to Pre-MDC MS-DRG 
018, we are providing the results of our data analysis using the 
September 2021 update of the FY 2021 MedPAR file for cases reporting 
the administration of a CAR T-cell or other immunotherapy in Pre-MDC 
MS-DRG 018 and the number of cases reporting a secondary diagnosis of 
Z00.6 (Encounter for examination for normal comparison and control in 
clinical research program). We note that if a procedure code that is 
assigned to the logic for Pre-MDC MS-DRG 018 is not listed it is 
because there were no cases found. We also note there were no cases 
reporting diagnosis code Z00.6 as a principal diagnosis. Our findings 
are shown in the following table.

[[Page 28131]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.005

    The data show that there is a wide range in the volume of cases (4 
cases versus 435 cases), average length of stay (11.3 days versus 20.3 
days), and average costs ($157,950 versus $310,561) reporting the 
administration of CAR T-cell therapies in MS-DRG 018. This is to be 
expected since these therapies continue to evolve and the ICD-10-PCS 
coding to identify and describe these therapies also continues to be 
refined through the ICD-10 Coordination and Maintenance Committee 
meeting process. As additional claims data becomes available for these 
therapies, we will continue to evaluate to determine if further 
modifications to Pre-MDC MS-DRG 018 are warranted.
    In response to our statement in the FY 2022 IPPS/LTCH PPS final 
rule that we plan to continue engaging with stakeholders on additional 
options for consideration in this field of cellular and gene therapies, 
we received additional feedback and suggestions, including 
recommendations for Town Hall meetings/listening sessions to discuss 
the interconnectedness of these issues; exploration of what was 
described as a different set and kind of MS-DRGs that would reward 
providers for controlling patient care costs, without consideration of 
product costs outside of their control; and evaluation of the creation 
and assignment of multiple MS-DRGs for cell and gene therapy cases: One 
to cover patient care costs, the other to cover product costs across 
therapeutic product categories.
    We appreciate this additional feedback and will continue to 
consider these issues and suggestions in connection with future 
rulemaking. We also intend to continue engaging with stakeholders by 
sharing updates from our analysis of claims data as we examine and 
explore potential refinements for these therapies under the IPPS.
a. Laser Interstitial Thermal Therapy (LITT)
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44812 through 
44814), we finalized the reassignment of 31 ICD-10-PCS procedure codes 
describing laser interstitial thermal therapy (LITT) of various body 
parts to more clinically appropriate MS-DRGs, as shown in Table 6P.2b 
associated with the FY 2022 IPPS/LTCH PPS final rule and available via 
the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS, including the 
reassignment of procedure codes D0Y0KZZ (Laser interstitial thermal 
therapy of brain) and D0Y1KZZ (Laser interstitial thermal therapy of 
brain stem), which were reassigned from MS-DRG 023 (Craniotomy with 
Major Device Implant or Acute Complex CNS Principal Diagnosis with MCC 
or Chemotherapy Implant or Epilepsy with Neurostimulator), MS-DRG 024 
(Craniotomy with Major Device Implant or Acute Complex CNS Principal 
Diagnosis without MCC), and MS-DRGs 025, 026, and 027 (Craniotomy and 
Endovascular Intracranial Procedures with MCC, with CC, and without CC/
MCC, respectively) to MS-DRGs 040, 041, and 042 (Peripheral, Cranial 
Nerve and Other Nervous System Procedures with MCC, with CC and without 
CC/MCC, respectively).
    We also finalized the redesignation of these two LITT procedures 
(codes D0Y0KZZ and D0Y1KZZ) and the reassignment from extensive O.R. 
procedures in MS-DRGs 981, 982 and 983 (Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) to non-extensive O.R procedures in MS-DRGs 987, 989, and 
989 (Non-Extensive O.R. Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) (86 FR 44889).
    For FY 2023, we received two requests from the manufacturers of the 
LITT technology (Medtronic and Monteris[supreg] Medical) to reverse the 
MS-DRG reassignment for the ICD-10 procedure codes that identify LITT 
of the brain and brain stem (codes D0Y0KZZ and D0Y1KZZ) from the MS-
DRGs for peripheral, cranial nerve and other nervous system procedures 
(MS-DRGs 040, 041, and 042) back to the MS-DRGs for craniotomy and 
endovascular procedures (MS-DRGs 023, 024, 025, 026, and 027). The 
first

[[Page 28132]]

requestor acknowledged that the technique utilized in the performance 
of LITT procedures for the brain and brain stem are minimally invasive 
and do not involve a craniotomy however, the requestor also stated the 
procedures assigned to MS-DRGs 025, 026, and 027 are not exclusive to 
craniotomies. The requestor further stated that these LITT procedures 
involve a twist drill or burr hole and are similar to other non-
craniotomy procedures in MS-DRGs 025, 026, and 027 including 
radioactive elements and neurostimulator leads that involve inserting 
these devices into the brain.
    In its review of the other procedures assigned to MS-DRGs 040, 041, 
and 042, the requestor stated that there are distinct clinical 
differences between the invasiveness of LITT that involves 
instrumentation being placed deeply within the brain tissue and the 
non-invasiveness of stereotactic radiosurgery that does not involve 
entering the brain with instrumentation. The requestor also indicated 
LITT utilizes a different modality via direct thermal ablation compared 
to stereotactic radiosurgery that utilizes externally-generated 
ionizing radiation.
    The requestor performed its own data analysis for LITT procedures 
of the brain and brain stem using MedPAR data from FY 2019 through FY 
2022 impact files. According to the requestor, its findings demonstrate 
that the costs of the cases reporting LITT of the brain or brain stem 
are better aligned with MS-DRGs 025, 026, and 027 compared to MS-DRGs 
040, 041, and 042.
    The second requestor similarly discussed the steps and resources 
involved in the performance of LITT procedures for the brain and brain 
stem, provided its detailed analysis on the indications for LITT (brain 
tumors and epileptic foci), compared LITT to other procedures in MS-
DRGs 025, 026, and 027 and stated that the majority of the procedures 
currently assigned to MS-DRGs 040, 041, 042 are not performed for the 
treatment of brain cancer or epilepsy. The requestor stated that the 
LITT procedure is on the inpatient only list and is only performed on 
Medicare beneficiaries in the inpatient hospital setting. The requestor 
provided the top 10 principal diagnoses associated with LITT of brain 
cases it found based on its analysis, and identified the diagnoses for 
which there were less than 10 cases with an asterisk, as reflected in 
the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.006

    The requestor asserted that the statement in the FY 2022 IPPS/LTCH 
PPS final rule that the technique to perform the LITT procedure on 
brain and brain stem structures is considered minimally invasive and 
does not involve a craniotomy, and that therefore, continued assignment 
to the craniotomy MS-DRGs is not clinically appropriate, 
mischaracterizes both the LITT procedures and universe of services 
assigned to MS-DRGs 023 through 027. The requestor acknowledged that 
the craniotomy procedures listed in the logic for MS-DRGs 023 through 
027 include open procedures but stated the logic also lists less 
invasive procedures including percutaneous and percutaneous endoscopic 
procedures. The requestor asserted that open procedures are a minority 
of the ICD-10-PCS codes assigned to these MS-DRGs.
    In addition, the requestor stated that LITT and craniotomy are in 
fact very clinically similar; in that both procedures are intended to 
remove and destroy the targeted tumor and lesion with a different 
surgical tool used (scalpel versus heated ablation probe). According to 
the requestor, brain LITT procedures involve insertion of laser probes 
into the brain which requires opening both the skull and dura, similar 
to a craniotomy. The requestor also stated that craniotomy and LITT 
share several procedural characteristics and provided the following 
list.
     Require an operating room;
     Performed under general anesthesia;
     Require creation of burr holes and invasive skull 
fixation;
     Require a sterile field, incision, opening of the skull 
and dura;
     Cause tissue to be immediately destroyed or excised;
     Carry a risk of immediate intracranial bleeding;
     Require closure of the scalp wound;
     Risk intracranial infection; and
     Require a hospital stay of one or more nights.
    In contrast, the requestor stated that procedures assigned to MS-
DRGs 040, 041, and 042 are primarily nerve procedures or excision or 
detachment procedures performed on parts of the body other than the 
head, including the upper and lower extremities. According to the 
requestor, none of the procedures in MS-DRGs 040, 041, and 042 require 
drilling into the patient's skull, a step which is integral to LITT. 
The requestor provided the following top 10 principal

[[Page 28133]]

diagnoses associated with cases it found in MS-DRGs 040, 041, and 042 
during its analysis and stated that most of the procedures assigned to 
MS-DRGs 040, 041, and 042 are not typically performed in the treatment 
of brain cancer or epilepsy.
[GRAPHIC] [TIFF OMITTED] TP10MY22.007

    However, the requestor stated an exception is stereotactic 
radiosurgery (SRS) procedures performed on the brain and brain stem 
that are assigned to MS-DRGs 040, 041, and 042 and are used to treat 
brain cancer. According to the requestor, craniotomy, LITT and SRS are 
all image-guided procedures used to treat a variety of brain disorders 
including tumors and epilepsy, although it stated that is where any 
similarity between LITT and SRS ends and where the procedural 
similarities between craniotomy and LITT begin.
    The requestor stated SRS is a non-invasive procedure that gradually 
destroys or inactivates tissues in or around the brain and is typically 
performed on an outpatient basis while inpatient SRS treatment is rare. 
According to the requestor, SRS does not require an operating room, is 
rarely done under general anesthesia (children and highly 
claustrophobic individuals being an exception), and does not require 
(but can use) rigid skull fixation. In addition, the requestor stated 
that because it is non-invasive, there is no need for a sterile field, 
incision, opening/closing of the skull, opening/closing of the dura, 
suturing/stapling the wound, and produces essentially no risk of 
immediate intracranial bleeding or delayed infection. According to the 
requestor, LITT is much more invasive than SRS using a head frame and 
involves and requires the same surgical skill and hospital resources as 
craniotomies.
    Following the submission of the two FY 2023 MS-DRG classification 
change requests for LITT, these same two requestors (the manufacturers 
of the LITT technology) submitted a joint code proposal requesting an 
overall change to how LITT is classified within the ICD-10-PCS 
classification and for consideration as an agenda topic to be discussed 
at the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting. The proposal was presented and discussed at the March 8-9, 
2022 ICD-10 Coordination and Maintenance Committee meeting. 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 the request, including a recording of the discussion and the 
related meeting materials. Public comments in response to the code 
proposal were due by April 8, 2022.
    Because the diagnosis and procedure code proposals that are 
presented at the March ICD-10-CM Coordination and Maintenance Committee 
meeting for an October 1 implementation (upcoming FY) are not finalized 
in time to include in Table 6A.--New Diagnosis Codes and Table 6B.--New 
Procedure Codes in association with the proposed rule, as we have noted 
in prior rulemaking and discuss further in this section, we use our 
established process to examine the MS-DRG assignment for the 
predecessor codes to determine the most appropriate MS-DRG assignment. 
Specifically, we review the predecessor code and MS-DRG assignment most 
closely associated with the new 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 have noted in prior 
rulemaking that this process does not automatically result in the new 
procedure code being assigned to the same MS-DRG or to have the same 
designation (O.R. versus Non-O.R.) as the predecessor code. Under this 
established process, the MS-DRG assignment for the upcoming fiscal year 
for any new diagnosis or procedure codes finalized after the March 
meeting would be reflected in Table 6A.--New Diagnosis Codes and Table 
6B.--New Procedure Codes associated with the final rule for that fiscal 
year. However, in light of the unique circumstances relating to these 
procedures, for which there is a pending proposal to reclassify LITT 
within ICD-10-PCS and for new procedure codes discussed at the March 
meeting, as well as an MS-DRG reclassification request to reassign the 
existing codes describing these procedures, we address in this section 
first, the code proposal discussed at the March meeting and the 
possible MS-DRG assignments for any new codes that may be approved, and 
then secondly, the requested reassignment of the existing codes, in the 
event the new codes are not approved.
    To summarize, as discussed at the March meeting, the code proposal 
is to reclassify LITT procedures from the Radiation Therapy section of 
ICD-10-PCS (Section D) to the Medical and Surgical section of ICD-10-
PCS. Specifically, the proposal is to reclassify LITT procedures to the 
root operation Destruction. In ICD-10-PCS, the root operation 
Destruction is defined as physical eradication of all or a portion

[[Page 28134]]

of a body part by the direct use of energy, force, or a destructive 
agent. According to the requestors, LITT is misclassified to section 
D--Radiation Therapy in ICD-10-PCS possibly because of terminology that 
was used for predicate devices, whose indications included the phrase 
``interstitial irradiation or thermal therapy'' in describing LITT's 
method of action. The requestors stated LITT is thermal therapy, 
destroying soft tissue using heat generated by a laser probe at the 
target site and that the LITT procedure does not use ionizing 
radiation, which is what the term ``radiation'' commonly refers to in 
the general medical sense. The requestors also stated that by itself, 
radiation is a broad term and provided an example that the spectrum of 
electromagnetic radiation technically encompasses low energy non-
ionizing radio waves, microwaves, and infrared to high energy ionizing 
X-rays and gamma rays while ionizing radiation creates ions in the 
cells it passes through by removing electrons, a process which kills or 
alters the cells over time.
    The requestors further stated that only certain medical uses of 
radiation are classified to section D--Radiation Therapy. For instance, 
section D--Radiation Therapy categorizes treatments using ionizing 
radiation, including beam radiation, brachytherapy, and stereotactic 
radiosurgery. All of these deliver concentrated ionizing radiation to 
eradicate abnormal cells, most commonly neoplasms. Other treatments 
classified to section D--Radiation Therapy, such as hyperthermia, are 
used as adjuncts to ionizing radiation. The requestors asserted that 
while LITT eradicates abnormal cells, it does so with heat, not 
ionizing radiation and rather than a radiation therapy procedure, LITT 
is a surgical procedure. According to the requestors, LITT would be 
more appropriately classified as an ablation procedure with the root 
operation Destruction.
    The original request for a new code(s) to describe the LITT 
technology was initially discussed at the September 24-25, 2008 ICD-9-
CM Coordination and Maintenance Committee meeting. At that time, the 
requestor sought an April 1, 2009 implementation date. Public comments 
opposed an April 1, 2009 implementation date, therefore, effective 
October 1, 2009 (FY 2010), ICD-9-CM procedure codes were created to 
identify procedures performed utilizing the LITT technology. The 
following table lists the ICD-9-CM procedure codes describing LITT and 
their respective MDC and MS-DRG assignments under the ICD-9 based MS-
DRGs. We refer the reader to the ICD-9 and ICD-10 MS-DRG Definitions 
Manual Files V33 (available via the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download-Items/FY2016-
Final-Rule-Correction-Notice-Files (in the Downloads section) for 
complete documentation of the GROUPER logic for ICD-9.
[GRAPHIC] [TIFF OMITTED] TP10MY22.008

    The requestors maintain that although LITT was used to treat a 
variety of anatomic sites when it was first introduced, its current 
primary use is intracranial, specifically to treat brain tumors and 
epileptic foci. However, the requestors stated it is also used to treat 
radiation necrosis, an inflammatory response from prior treatment with 
ionizing radiation.
    Currently, in the U.S. there are only two LITT systems in use, 
VisualaseTM MRI-Guided Laser Ablation (Medtronic) and the 
Neuroblate[supreg] System (Monteris[supreg] Medical). The requestors 
also stated that over the last six years, the Indications for Use (IFU) 
for one of the two U.S. approved LITT technologies (Neuroblate[supreg]) 
has been updated to reflect the system's current use in the brain and 
to align with the intended neurosurgical patient population. The 
requestor indicated applications in the spine are also anticipated in 
the future within the central nervous system.
    As previously noted, the deadline for receipt of public comments 
for the proposed reclassification of LITT procedures that was presented 
at the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting along with the corresponding proposal for new procedure codes 
was April 8, 2022, and the final code decisions on these proposals are 
not yet available for inclusion in Table 6B.--New Procedure Codes 
associated with this FY 2023 IPPS/LTCH PPS proposed rule. However, as 
discussed in prior rulemaking (86 FR 44805), codes that are finalized 
after the March meeting are reviewed and subject to our established 
process of initially reviewing the predecessor codes MS-DRG assignment 
and designation, while considering

[[Page 28135]]

other relevant factors (for example, severity of illness, treatment 
difficulty, complexity of service and the resources utilized in the 
diagnosis and/or treatment of the condition) as previously described. 
The codes that are finalized after the March meeting are specifically 
identified with a footnote in Tables 6A.--New Diagnosis Codes and Table 
6B.--New Procedure Codes that are made publicly available in 
association with the final rule via the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. The public may provide feedback on these finalized 
assignments, which is then taken into consideration for the following 
fiscal year.
    Accordingly, as previously discussed, the MS-DRG assignment for any 
new procedure codes describing LITT, if finalized following the March 
meeting, would be reflected in Table 6B.--New Procedure Codes 
associated with the final rule for FY 2023. However, in light of the 
unique circumstances with respect to these procedures, for which there 
is both a proposal for reclassifying LITT from the Radiation Therapy 
section of the procedure code classification to the Medical/Surgical 
section with new ICD-10-PCS procedure code(s) and a separate MS-DRG 
reclassification request on the existing procedure codes, we are 
providing the opportunity for public comment on possible MS-DRG 
assignments for the requested new procedure codes describing LITT that 
may apply based on the application of our established process and 
analysis, in the event the new codes are finalized for FY 2023. We note 
that while we discuss the potential MS-DRG assignments for new 
procedure codes describing LITT, stakeholders may use current coding 
information to consider the potential MS-DRG assignments for any other 
procedure codes that may be finalized after the March meeting and 
submit public comments for consideration. Specifically, in the ICD-10 
Coordination and Maintenance Committee meeting materials (available via 
the internet on the CMS website at https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials), for each procedure code proposal we 
provide the current coding that is applicable within the classification 
and that should be reported in the absence of a more unique code, or 
until such time a new code is created and becomes effective. The 
procedure code(s) listed in current coding are generally, but not 
always, the same code(s) that are considered as the predecessor code(s) 
for purposes of MS-DRG assignment. As previously noted, our process for 
determining the MS-DRG assignment for a new procedure code does not 
automatically result in the new procedure code being assigned to the 
same MS-DRG or having the same designation (O.R. versus Non-O.R.) as 
the predecessor code. However, this current coding information can be 
used in conjunction with the GROUPER logic, as set forth in the ICD-10 
MS-DRG Definitions Manual and publicly available via the internet on 
our CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software 
to review the MS-DRG assignment of the current code(s) and examine the 
potential MS-DRG assignment of the proposed code(s), to assist in 
formulating any public comments for submission to CMS for 
consideration.
    We note that, unlike the typical code request for a new or revised 
procedure code that involves a new technology or a new approach to 
performing an existing procedure, the circumstances for this particular 
request are distinct in that the code request would reclassify LITT 
within the ICD-10-PCS classification from section D--Radiation Therapy 
to the root operation Destruction in the Medical and Surgical section 
of ICD-10-PCS. Therefore, in light of the unique considerations with 
respect to the requested reclassification of the LITT procedures in 
connection with the pending code proposal, we believe it is appropriate 
to utilize the assignments and designations of the procedure codes 
describing Destruction of the respective anatomic body site as 
predecessor codes rather than the current codes describing LITT from 
the Radiation Therapy section of ICD-10-PCS in considering potential 
MS-DRG assignment for the requested new LITT procedure codes.
    As previously discussed, under our established process for 
determining the MS-DRG assignment for newly approved procedure codes, 
we examine the MS-DRG assignment for the predecessor codes to determine 
the most appropriate MS-DRG assignment for the new codes. Specifically, 
we review the predecessor code and MS-DRG assignment most closely 
associated with the new 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. As we have noted in prior rulemaking, 
this process does not automatically result in the new procedure code 
being assigned to the same MS-DRG or to have the same designation (O.R. 
versus Non-O.R.) as the predecessor code.
    Applying this established review process to the proposed codes for 
the LITT procedures, we believe that, based on the predecessor codes, 
and as previously noted, the potential assignments and designations 
would align with the assignments and designations of the procedure 
codes describing Destruction of the respective anatomic body site. For 
example, as discussed earlier in this section of this proposed rule, 
the code request involved reclassifying LITT procedures from section 
D--Radiation Therapy to the root operation Destruction in the Medical 
and Surgical section of ICD-10-PCS. The root operation Destruction is 
appropriate to identify and report procedures, such as ablation, that 
are performed on various body parts. The code request also involved 
creating what is referred to as a qualifier value, to uniquely describe 
LITT as the modality. The qualifier value is the seventh character or 
digit, in a valid ICD-10-PCS procedure code.
    The following ICD-10-PCS table illustrates an example of the 
proposed procedure codes for LITT of the brain and brain stem, and 
cervical, thoracic, and lumbar spinal cord body parts, including the 
qualifier value that was presented and discussed at the March 8-9, 2022 
ICD-10 Coordination and Maintenance Committee meeting.

[[Page 28136]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.009

    We note that the code proposal presented only provided the body 
part value 0 Brain, for reporting any LITT procedures performed on the 
brain, as well as, the brain stem, consistent with the current 
available body part option in Table 005, Destruction of Central Nervous 
System and Cranial Nerves, where the predecessor code is located. The 
predecessor code(s) and associated MS-DRG assignments for the proposed 
new procedure code(s) describing LITT of the brain and spinal cord 
under MDC 01 are identified as follows.
[GRAPHIC] [TIFF OMITTED] TP10MY22.010

    As shown in the table, the procedure codes describing destruction 
of brain with an open, percutaneous or percutaneous endoscopic approach 
are assigned to MS-DRGs 023 through 027 (craniotomy and endovascular 
procedures) and the procedure codes describing destruction of cervical, 
thoracic or lumbar spinal cord with an open, percutaneous or 
percutaneous endoscopic approach are assigned to MS-DRG 028 (Spinal 
Procedures with MCC), MS-DRG 029 (Spinal Procedures with CC or Spinal 
Neurostimulators), and MS-DRG 030 (Spinal Procedures without CC/MCC).
    We refer the reader to Table 6P.2a associated with this proposed 
rule (and available via the internet at https://www.cms.gov/medicare/
medicare-fee-for-service-payment/acuteinpatientpps) to review the 
potential MDCs, MS-DRGs, and O.R. versus Non-O.R. designations 
identified based on this analysis of the proposed new procedure codes 
describing LITT as presented and discussed at the meeting. We note that 
Table 6P.2a also includes the predecessor codes that we utilized to 
inform this analysis. If finalized, the new procedure codes would be 
included in the FY 2023 code update files that are made available in 
late May/early June via the internet on the CMS website at https://www.cms.gov/medicare/coding/icd10. Additionally, if finalized, the new 
procedure codes describing LITT would be displayed in Table 6B.--New 
Procedure Codes, and the existing codes describing LITT would be 
deleted and reflected in Table 6D.--Invalid Procedure Codes, in 
association with the FY 2023 IPPS/LTCH PPS final rule. We refer the 
reader to section II.D.14. for further information regarding the files.
    As previously discussed, we also received requests to reassign the 
existing ICD-10 procedure codes that identify LITT of the brain and 
brain stem (codes D0Y0KZZ and D0Y1KZZ). In the event there is not 
support for the proposed reclassification of LITT procedures and the 
corresponding new procedure codes as presented at the March 8-9, 2022 
ICD-10 Coordination and Maintenance Committee meeting, we are also 
providing the results of our analysis of these existing codes and our 
proposed MS-DRG assignments for FY 2023, if those existing codes are 
retained.
    We examined claims data from the September 2021 update of the FY 
2021 MedPAR file for MS-DRGs 023, 024, 025, 026, and 027, in addition 
to MS-DRGs 040, 041, and 042 for cases reporting LITT of the brain 
(code D0Y0KZZ) or brain stem (code D0Y1KZZ). We note that if a 
procedure code is not listed it is because there were no cases found 
reporting that procedure code. Our findings are shown in the following 
tables.

[[Page 28137]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.011

[GRAPHIC] [TIFF OMITTED] TP10MY22.012

    As shown, we found a total of 123 cases reporting LITT of the brain 
across MS-DRGs 023, 025, 026, and 027. There were no cases found in MS-
DRG 024. The cases reporting LITT of the brain grouped to these MS-DRGs 
because another O.R. procedure that is assigned to the respective MS-
DRG was also reported. We refer the reader to Table 6P.2b for the list 
of the other O.R. procedures we identified that were also reported with 
LITT of the brain.
    For MS-DRGs 040, 041, and 042, we found a total of 54 cases 
reporting LITT of the brain and 2 cases reporting LITT of the brain 
stem. While the average costs of the cases reporting LITT of the brain 
were higher compared to all the cases in their respective MS-DRGs, the 
average length of stay was shorter. For example, the data demonstrates 
a shorter average length of stay (8.1 days versus 9.9 days) and higher 
average costs ($40,458 versus $30,212) for the 14 cases reporting LITT 
of brain in MS-DRG 040 compared to all the cases in MS-DRG 040. There 
were no cases found to report LITT of brain stem in MS-DRG 040. For MS-
DRG 041, we found 16 cases reporting LITT of brain with an average 
length of stay of 3.4 days and average costs of $23,278 and 1 case 
reporting LITT of brain stem with an average length of stay of 1 day 
and average costs of $10,222. The average length of stay for all the 
cases in MS-DRG 041 is 5 days with average costs of $19,090. The data 
demonstrates a shorter average length of stay (3.4 days and 1 day, 
respectively, versus 5 days) for the 16 cases reporting LITT of brain 
and the 1 case reporting LITT of brain stem. The data also demonstrates 
higher average costs ($23,278 versus $19,090) for the 16 cases 
reporting LITT of brain, and lower average costs for the 1 case 
reporting LITT of brain stem ($10,222 versus $19,090), as compared to 
the average costs of all cases in MS-DRG 041. For MS-DRG 042, we found 
24 cases reporting LITT of brain with an average length of stay of 1.7 
days and average costs of $22,426 and 1 case reporting LITT of brain 
stem with an average length of stay of 2 days and average costs of 
$32,668. The average length of stay for all the cases in MS-DRG 042 is 
2.9 days with average costs of $15,451. The data demonstrates a shorter 
average length of stay (1.7 days

[[Page 28138]]

and 2 days, respectively, versus 2.9 days) for the 24 cases reporting 
LITT of brain and the 1 case reporting LITT of brain stem. The data 
also demonstrate higher average costs ($22,426 and $32,668, 
respectively versus $15,451) for the 24 cases reporting LITT of brain 
and the 1 case reporting LITT of brain stem, compared to all the cases 
in MS-DRG 042.
    Based on the findings from our analysis, we considered whether 
other factors, such as the reporting of secondary MCC and CC diagnoses, 
may have contributed to the higher average costs for these cases. 
Specifically, we conducted additional analyses of the claims data from 
the September 2021 update of the FY 2021 MedPAR file to determine what 
secondary MCC diagnoses were also reported for the 14 cases reporting 
LITT of brain in MS-DRG 040 and what secondary CC diagnoses were 
reported for the 17 cases (16 for LITT of brain and 1 for LITT of brain 
stem) in MS-DRG 041. Our findings are shown in the following tables.
[GRAPHIC] [TIFF OMITTED] TP10MY22.013

[GRAPHIC] [TIFF OMITTED] TP10MY22.014


[[Page 28139]]


    We note that we did not find any other O.R. procedures reported on 
the claims in addition to the procedures for LITT of brain or brain 
stem for MS-DRGs 040, 041 and 042.
    The data shows that at least one of the listed secondary MCC 
diagnoses was reported with each claim for LITT of brain identified in 
MS-DRG 040 and the average length of stay for these cases ranged from 9 
days to 48 days and the average costs of these cases ranged from 
$41,486 to $80,745. We note that this data reflects the frequency with 
which each of the listed diagnoses was reported on a claim with LITT of 
brain. Therefore, multiple MCCs from this list of diagnoses may have 
been reported on a single claim. In addition, while the logic for case 
assignment to MS-DRG 040 requires at least one secondary MCC diagnosis, 
we conducted additional detailed analyses for MS-DRG 040, as shown in 
Table 6P.2f, to determine whether there were also secondary CC 
diagnoses reported in conjunction with one or more of the listed MCC 
diagnoses that may be contributing to the higher average costs for 
cases reporting LITT of brain in MS-DRG 040 in comparison to all the 
cases in MS-DRG 040. We found that 6 of the 14 cases reporting at least 
one or more secondary MCC diagnosis also reported one or more secondary 
CC diagnosis, which would appear to support that the severity of 
illness for these patients, as identified by the secondary MCC and CC 
diagnoses, may be more directly related to the higher average costs for 
these patients than the LITT procedure itself.
    Similarly, the data for MS-DRG 041 show the frequency with which 
each of the listed secondary CC diagnoses was reported with LITT of 
brain or brain stem. Results from the analysis for the 17 cases (16 for 
LITT of brain and 1 for LITT of brain stem) show the average length of 
stay for these cases ranged from 1 day to 29 days and the average costs 
ranged from $9,101 to $57,999. These data analysis findings for MS-DRG 
041 also appear to support our belief that the severity of illness for 
these patients, as identified by the listed secondary CC diagnoses, may 
be more directly related to the higher average costs for these patients 
than the LITT procedure itself.
    As stated previously, we did not find any other O.R. procedures 
reported on the claims in addition to the procedures for LITT of brain 
or brain stem for MS-DRGs 040, 041 and 042. Since the logic for case 
assignment to MS-DRG 042 is not based on the reporting requirement of 
any CC or MCC diagnoses, we conducted a detailed analysis of the claims 
data to determine what other factors may be contributing to the higher 
average costs and shorter average length of stay for these cases in 
comparison to all the cases in MS-DRG 042. We refer the reader to Table 
6P.2g associated with this proposed rule for the findings from our 
analysis. As shown in the data, the majority of the cases (15 of 25) 
had a principal diagnosis of epilepsy, 8 cases had a principal 
diagnosis related to malignant neoplasm of the brain or brain 
structures, 1 case had a principal diagnosis of hemangioma of 
intracranial structures and 1 case had a principal diagnosis of 
unspecified convulsions. The data also demonstrate that 16 of the 25 
cases reported in MS-DRG 042 include patients who were under the age of 
65, with ages ranging from 32 years old to 64 years old. We note that 
patients diagnosed with epilepsy are eligible for coverage since it is 
a condition that qualifies under certain criteria. It is not entirely 
clear if the age of these patients had any impact on the average length 
of stay since the average length of stay of the 24 cases reporting LITT 
of brain was 1.7 days and the 1 case reporting LITT of brain stem was 2 
days.
    As stated previously, the logic for case assignment to MS-DRG 042 
is not dependent on the reporting of any CC or MCC diagnoses, however, 
based on the diagnoses reflected in the claims data for MS-DRG 042, it 
is possible that conditions such as obesity and chronic conditions 
requiring the long-term use of certain therapeutic agents may be 
contributing factors to the consumption of resources, separately from 
the LITT procedure. We found 17 of the 25 cases reporting LITT of brain 
or brain stem to also report one or both of these conditions.
    We also reviewed the number of cases of LITT of the brain or brain 
stem procedures reported in the data since the transition to ICD-10. 
Specifically, we examined the claims data for cases reporting LITT of 
brain or brain stem as a standalone procedure or with another procedure 
in the FY 2016 through FY 2021 MedPAR data files across all MS-DRGs. 
The findings from our analysis are shown in table 6P.2e associated with 
this proposed rule.
    The data demonstrates that since the implementation of ICD-10, a 
shift in the reporting of LITT of brain and brain stem procedures has 
occurred. For example, the FY 2016, FY 2017 and FY 2018 MedPAR data 
reflect that the number of cases for which LITT of brain or brain stem 
procedures were reported as a standalone procedure is higher in 
comparison to the number of cases reported with another procedure. 
Conversely, the FY 2019, FY 2020, and FY 2021 MedPAR data reflect that 
the number of cases for which LITT of brain or brain stem procedures 
were reported as a standalone procedure is lower in comparison to the 
number of cases reported with another procedure. The data also reflect 
that the average length of stay is shorter and the average costs are 
lower for cases reporting LITT of brain or brain stem as a standalone 
procedure in comparison to the average length of stay and average costs 
for cases reported with another procedure across the FY 2016 through FY 
2021 MedPAR data files. Lastly, the data demonstrate that overall, the 
number of cases for which LITT of brain or brain stem procedures was 
performed had remained fairly stable at over 100 cases with increases 
in the FY 2017, FY 2020 and FY 2021 MedPAR data files of 156, 154 and 
185 cases, respectively.
    We also analyzed claims data from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting LITT of other anatomic sites 
across all MS-DRGs. Although the requestors indicated that LITT is 
primarily performed on intracranial lesions, as shown in Table 6P.2c 
associated with this proposed rule, we identified a small number of 
cases reporting LITT of the lung, rectum, liver, breast, and prostate, 
for a total of 29 cases where LITT was performed on other body parts/
anatomic sites.
    For example, we found a total of 5 cases reporting LITT of lung 
across 5 different MS-DRGs. Of these 5 cases, 2 cases had a longer 
average length of stay and higher average costs in comparison to all 
the cases in their respective MS-DRG. Specifically, for MS-DRG 163 
(Major Chest Procedures with MCC), we found 1 case reporting LITT of 
lung with an average length of stay of 17 days and average costs of 
$41,467. The average length of stay for all cases in MS-DRG 163 is 10.7 
days with average costs of $38,367. The data demonstrates a difference 
of 6.3 days (17-10.7=6.3) for the average length of stay and a 
difference of $3,100 in average costs ($41,467-$38,367=$3,100) for the 
1 case reporting LITT of lung in MS-DRG 163 compared to all the cases 
in MS-DRG 163. For MS-DRG 167 (Other Respiratory System O.R. Procedures 
with CC), we found 1 case reporting LITT of lung with an average length 
of stay of 7 days and average costs of $22,975. The average length of 
stay for all cases in MS-DRG 167 is 4.6 days with average costs of 
$15,397. The data demonstrates a difference of 2.4 days (7-4.6=2.4) for 
the average length of stay and a difference of $7,578 in average costs 
($22,975-$15,397=$7,578) for the 1

[[Page 28140]]

case reporting LITT of lung in MS-DRG 167 compared to all the cases in 
MS-DRG 167. The data for the remaining 3 cases reporting LITT of lung 
demonstrated a shorter average length of stay and lower average costs 
in comparison to all the cases in their respective MS-DRGs.
    We found 1 case reporting LITT of rectum in MS-DRG 357 (Other 
Digestive System O.R. Procedures with CC) with a shorter average length 
of stay (4 days versus 5.6 days) and lower average costs ($3,069 versus 
$18,065) as compared to all the cases in MS-DRG 357. We also found 1 
case reporting LITT of liver in MS-DRG 405 (Pancreas Liver and Shunt 
Procedures with MCC) with a longer average length of stay (20 days 
versus 12.3 days) and higher average costs ($49,0695 versus $43,771) as 
compared to all the cases in MS-DRG 405.We also found 1 case reporting 
LITT of right breast in MS-DRG 580 (Other Skin Subcutaneous Tissue and 
Breast Procedures with CC) with a longer average length of stay (19 
days versus 5.4 days) and higher average costs ($32,064 versus $13,767) 
as compared to all the cases in MS-DRG 580.
    Lastly, we found 21 cases reporting LITT of prostate across 14 MS-
DRGs. Of those 21 cases, 6 cases had a longer average length of stay or 
higher average costs, or both, in comparison to the average length of 
stay and average costs of all the cases in their respective MS-DRG. For 
example, in MS-DRG 650 (Kidney Transplant with Hemodialysis with MCC) 
we found 1 case reporting LITT of prostate with an average length of 
stay of 36 days and average costs of $67,238. The average length of 
stay for all cases in MS-DRG 650 is 8.1 days with average costs of 
$38,139. The data demonstrates a difference of 27.9 days (36-8.1=27.9) 
for the average length of stay and a difference of $29,099 in average 
costs ($67,238-$38,139= $29,099) for the 1 case reporting LITT of 
prostate in MS-DRG 650 compared to all the cases in MS-DRG 650. We also 
found 1 case reporting LITT of prostate in MS-DRG 659 (Kidney and 
Ureter Procedures for Non-Neoplasm with MCC) with an average length of 
stay of 26 days. The average length of stay for all cases in MS-DRG 659 
is 7.8 days, demonstrating a difference of 18.2 days (26-7.8=18.2). We 
found 1 case reporting LITT of prostate in MS-DRG 712 (Testes 
Procedures without CC/MCC) with average costs of $15,669. The average 
costs for all cases in MS-DRG 712 is $10,482, demonstrating a 
difference of $5,187 ($15,669-$10,482=$5,187). We found 1 case 
reporting LITT of prostate in MS-DRG 987 with an average length of stay 
of 23 days and average costs of $35,465. The average length of stay for 
all cases in MS-DRG 987 is 10.9 days with average costs of $26,657. The 
data demonstrates a difference of 12.1 days (23-10.9=12.1) for the 
average length of stay and a difference of $8,808 in average costs 
($35,465-$26,657= $8,808) for the 1 case reporting LITT of prostate in 
MS-DRG 987 compared to all the cases in MS-DRG 987. Lastly, we found 2 
cases reporting LITT of prostate in MS-DRG 988 (Non-Extensive O.R. 
Procedures Unrelated to Principal Diagnosis with CC) with average costs 
of $17,126. The average costs for all cases in MS-DRG 988 is $13,670, 
demonstrating a difference of $3,456 ($17,126-$13,670= $3,456) for the 
2 cases reporting LITT of prostate in MS-DRG 988.
    We refer the reader to Table 6P.2c for the detailed findings from 
our analysis. We note that if the procedure code describing LITT of a 
specific anatomic site is not listed it is because there were no cases 
found.
    We note that for the 10 cases previously described, for which LITT 
of a different anatomic site from the brain or brain stem was reported 
and had a longer average length of stay or higher average costs, or 
both, in comparison to the average length of stay and average costs of 
all the cases in their respective MS-DRG, that with the exception of 
MS-DRG 712, all the other MS-DRGs include a ``with MCC'' or ``with CC'' 
designation, or were reported in a surgical MS-DRG. We believe that 
these other factors may have contributed to the longer average length 
of stay and higher average costs for these cases, therefore we 
conducted additional analyses of the claims data to determine what 
diagnoses or procedures were also reported. We refer the reader to 
Table 6P.2d associated with this proposed rule for the findings from 
our detailed analysis of these 10 cases.
    As shown in Table 6P.2d, the data demonstrate that a number of MCC 
and/or CC secondary diagnoses were reported for each of the 10 cases 
and that the surgical procedures that were reported in addition to the 
LITT procedure seem to have contributed to the longer average length of 
stay and higher average costs for those cases when compared to the 
average length of stay and average costs for all the cases in their 
respective MS-DRG. For example, in case number 1 there are 2 diagnoses 
that are designated as MCC conditions and 5 diagnoses that that are 
designated as CC conditions with procedure codes describing a kidney 
transplant, hemodialysis, and insertion of a ureteral stent that were 
reported along with LITT of prostate. For case number 3 there are 4 
diagnoses that are designated as MCC conditions and 6 diagnoses that 
are designated as CC conditions with procedure codes describing 
bronchoscopic treatment of a bronchial tumor with and without stents, 
as well as the use of mechanical ventilation. Overall, the data appear 
to indicate that the performance of the LITT procedure was not the 
underlying reason for, or main driver of, the increase in resource 
utilization for those cases.
    As noted, the requestors indicated that LITT is primarily being 
performed on intracranial lesions. However, as summarized, we 
identified a limited number of cases reporting LITT procedures for 
other anatomic sites. We are interested in comments regarding the use 
of and experience with LITT for these other anatomic sites.
    Based on our analysis of the FY 2021 MedPAR claims data for cases 
reporting LITT of brain or brain stem (codes D0Y0KZZ and D0Y1KZZ) in 
MS-DRGs 040, 041, and 042, we agree with the requestors that the 
average costs of these cases are higher as compared to the average 
costs of all cases assigned to MS-DRGs 040, 041, and 042. For the 
reasons summarized, we also believe that other factors, including the 
reporting of secondary MCC and CC diagnoses, may be contributing to the 
higher average costs for these cases. As discussed in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 44813), we examined procedure codes D0Y0KZZ 
and D0Y1KZZ describing LITT of brain and brain stem, respectively, and 
stated that the technique to perform the LITT procedure on these 
structures is considered minimally invasive and does not involve a 
craniotomy, therefore, continued assignment to the craniotomy MS-DRGs 
is not clinically appropriate. Our clinical advisors continue to 
maintain that LITT is a minimally invasive procedure, requiring only a 
tiny incision for purposes of a burr hole and that patients are often 
only kept overnight (as reflected in the detailed claims data). 
However, we also recognize that craniotomy and LITT share common 
procedural characteristics including use of an operating room, carry 
risk of immediate intracranial bleeding or infection, and cause tissue 
to be immediately destroyed or excised. While the data do not 
demonstrate that the LITT procedure is the underlying reason for the 
higher average costs and consumption of resources for the small number 
of cases reporting LITT of brain (54 cases) or brain stem (2 cases) 
that we found in MS-DRGs 040, 041, and 042,

[[Page 28141]]

the data do demonstrate that the patients receiving this treatment 
therapy have brain tumors or epilepsy combined with multiple 
comorbidities or chronic conditions necessitating long-term use of 
medications, or both, and we note the indications for LITT (brain 
tumors and epileptic foci) are better aligned with MS-DRGs 025, 026, 
and 027 as compared to MS-DRGs 040, 041, and 042.
    As we discuss further in this section, we intend to more fully 
evaluate the logic for the procedures specifically involving a 
craniotomy, as well as the overall structure of MS-DRGs 023 through 
027, and we believe that reassignment of cases reporting LITT of brain 
or brain stem to MS-DRGs 025, 026, and 027 would be an appropriate 
first step in connection with these efforts. For example, while we 
recognize the distinctions between open craniotomy procedures and 
minimally invasive percutaneous intracranial procedures, we also 
recognize that the current logic for MS-DRGs 025 through 027 also 
includes other endovascular intracranial procedures performed using 
percutaneous or percutaneous endoscopic approaches, and we believe that 
further review of the clinical coherence of the procedures assigned to 
these MS-DRGs may be warranted. Our clinical advisors note that while 
the typical patient treated with LITT usually has a single small scalp 
incision through which a hole approximately the diameter of a straw is 
drilled, with no extensive surgical exposure, that LITT can still be 
employed for another subset of more complex patients, including 
patients with primary brain malignancies and those with larger 
metastatic lesions or multiple lesions. For this subset of more complex 
patients, a longer post-operative stay with direct medical supervision 
may be necessary. As such, we believe reassigning these procedures to 
MS-DRGs 025 through 027 for FY 2023 would be appropriate as we consider 
restructuring MS-DRGs 023 through 027, including how to better align 
the clinical indications with the performance of specific intracranial 
procedures. Accordingly, for these reasons, in the event there is not 
support for the proposed reclassification of LITT procedures and the 
corresponding new procedure codes as presented at the March 8-9, 2022 
ICD-10 Coordination and Maintenance Committee meeting, we are proposing 
to reassign the existing procedure codes describing LITT of the brain 
or brain stem from MS-DRGs 040, 041, and 042 to MS-DRGs 025, 026, and 
027 for FY 2023. We are also proposing to maintain the MS-DRG 
assignments for the existing procedure codes describing LITT of other 
anatomic sites as finalized and displayed in Table 6P.2b in association 
with the FY 2022 IPPS/LTCH PPS final rule, for FY 2023. We note that we 
did not receive any comments or requests to reconsider those finalized 
MS-DRG assignments for FY 2023.
    As noted, in connection with our analysis of cases reporting LITT 
procedures performed on the brain or brain stem in MDC 01, we have 
started to examine the logic for case assignment to MS-DRGs 023 through 
027 to determine where further refinements could potentially be made to 
better account for differences in the technical complexity and resource 
utilization among the procedures that are currently assigned to those 
MS-DRGs. Specifically, we are in the process of evaluating procedures 
that are performed using an open craniotomy (where it is necessary to 
surgically remove a portion of the skull) versus a percutaneous burr 
hole (where a hole approximately the size of a pencil is drilled) to 
obtain access to the brain in the performance of a procedure. We are 
also reviewing the indications for these procedures, for example, 
malignant neoplasms versus epilepsy to consider if there may be merit 
in considering restructuring the current MS-DRGs to better recognize 
the clinical distinctions of these patient populations in the MS-DRGs. 
We believe it is worthwhile to also compare the claims data for 
epilepsy patients who are treated with a neurostimulator implant versus 
a LITT procedure, as well as the claims data for patients with a 
diagnosis of epilepsy or malignant neoplasms who undergo a LITT 
procedure. Our analysis also includes reviewing the claims data with 
regard to the cases that reflect a procedure that is generally 
performed with another O.R. procedure versus a standalone procedure.
    As we continue this analysis of the claims data with respect to MS-
DRGs 023 through 027, we are also seeking public comments and feedback 
on other factors that should be considered in the potential 
restructuring of these MS-DRGs. As previously described, we are 
examining procedures by their approach (open versus percutaneous), 
clinical indications, and procedures that involve the insertion or 
implantation of a device. We recognize the logic for MS-DRGs 023 
through 027 has grown more complex over the years and believe there is 
opportunity for further refinement. We refer the reader to the ICD-10 
MS-DRG Definitions Manual, version 39.1, 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 
023 through 027. Feedback and other suggestions may be submitted by 
October 20, 2022 and directed to the new electronic intake system, 
Medicare Electronic Application Request Information SystemTM 
(MEARISTM), discussed in section II.D.1.b of the preamble of 
this proposed rule at https://mearis.cms.gov/public/home.
b. Vagus Nerve Stimulation
    We received a request to review the MS-DRG assignment for cases 
that identify patients who receive an implantable vagus nerve 
stimulation system for heart failure. The vagus nerve, also called the 
X cranial nerve or the 10th cranial nerve, is the longest and most 
complex of the cranial nerves. There is one vagus nerve on each side of 
the body that runs from the brain through the face and thorax to the 
abdomen. According to the requestor, cranial nerve stimulation (CNS), 
which includes vagus nerve stimulation, is a well-established therapy 
for various indications including epilepsy, treatment resistant 
depression (TRD) and obstructive sleep apnea (OSA), and is now being 
investigated and studied for use in patients with heart failure.
    According to the requestor, heart failure, or the heart's inability 
to pump an adequate supply of blood and oxygen to support the other 
organs of the body, is an autonomic nervous system dysfunction. The 
brain controls the function of the heart through the sympathetic branch 
and the parasympathetic branches of the autonomic nervous system. In 
heart failure, there is an imbalance in the autonomic nervous system. 
The vagus nerve stimulation system for heart failure is comprised of an 
implantable pulse generator, an electrical lead, and a programming 
computer system. The pulse generator, which is usually implanted just 
under the skin of the pectoral region, sends the energy to the vagus 
nerve through the lead. The lead is a flexible insulated wire that is 
guided under the skin from the chest up to the neck and is implanted 
onto the vagus nerve and transmits tiny electrical impulses from the 
generator to the nerve. These electrical impulses to the vagus nerve 
are intended to activate the parasympathetic branch of the autonomic 
nervous system to restore balance.

[[Page 28142]]

    The requestor stated that cases reporting a procedure code 
describing the insertion of a neurostimulator lead onto the vagus nerve 
and a procedure code describing the insertion of a stimulator generator 
with a principal diagnosis code describing epilepsy, TRD or OSA are 
assigned to surgical MS-DRGs 040, 041 and 042 (Peripheral Cranial Nerve 
and Other Nervous System Procedures with MCC, with CC or Peripheral 
Neurostimulator, and without CC/MCC, respectively) in MDC 01 (Diseases 
and Disorders of the Nervous System). However, when the same codes 
describing the insertion of a neurostimulator lead onto the vagus nerve 
and the insertion of a stimulator generator are reported with a 
principal diagnosis of heart failure, the cases instead are assigned to 
surgical MS-DRGs 252, 253 and 254 (Other Vascular Procedures with MCC, 
with CC, without MCC respectively) in MDC 05 (Diseases and Disorders of 
the Circulatory System).
    The requestor stated that the treatment of autonomic nervous system 
dysfunction is the underlying therapeutic objective of cranial nerve 
stimulation for heart failure, and therefore the diagnosis of heart 
failure is more clinically coherent with other diagnoses in MDC 01. As 
a result, the requestor, who is developing the VITARIA[supreg] System, 
an active implantable neuromodulation system that uses vagus nerve 
stimulation to deliver autonomic regulation therapy (ART) for an 
indicated use that includes patients who have moderate to severe heart 
failure, submitted a request to reassign cases reporting a procedure 
code describing the insertion of a neurostimulator lead onto the vagus 
nerve and a procedure code describing the insertion of a stimulator 
generator with a principal diagnosis code describing heart failure, 
from MS-DRGs 252, 253 and 254 in MDC 05 to MS-DRGs 040, 041 and 042 in 
MDC 01. This requestor also submitted an application for new technology 
add-on payment for FY 2023. We refer readers to section II.F.6. of the 
preamble of this proposed rule for a discussion regarding the 
application for new technology add-on payments for the VITARIA[supreg] 
System for FY 2023.
    According to the requestor, the following ICD-10-PCS procedure code 
pair identifies the insertion of a vagus nerve stimulation system for 
heart failure:
[GRAPHIC] [TIFF OMITTED] TP10MY22.015

    The requestor performed its own analysis of Medicare claims from 
2020 and stated that it found that patients enrolled in their pivotal 
clinical trials had an average length of stay of 6.38 days. According 
to the requestor this finding indicates a resource coherence more 
similar to cases assigned to MS-DRGs 040, 041 and 042, whose average 
lengths of stay ranges from 2 to 8 days, when compared to the average 
lengths of stay of 1 to 3 days for cases assigned to MS-DRGs 252 and 
253. The requestor stated their own analysis of 2019 and 2020 Medicare 
claims data also showed that fewer than 11 cases with procedure codes 
describing the implantation of a vagus nerve stimulation system map to 
MS-DRGs 252, 253 and 254 annually but it is expected that Medicare 
patients will receive vagus nerve stimulation system for heart failure 
on an inpatient basis. Because of the shared clinical and resource 
similarity of the procedure to implant the VITARIA[supreg] system to 
other CNS procedures, regardless of indication, the requestor stated 
that CNS procedures for the treatment of heart failure should also be 
assigned to MS-DRGs 040, 041 and 042. The requestor also noted that the 
title of MS-DRGs 252, 253 and 254 is ``Other Vascular Procedures with 
MCC, with CC, without MCC respectively''. Since no vascular access is 
involved in the procedure to implant vagus nerve stimulation systems, 
the requestor stated MS-DRGs 252, 253 and 254 are not appropriate 
mappings for these procedures.
    The ICD-10-CM diagnosis codes that describe heart failure are found 
in the following table. These diagnosis codes are all currently 
assigned to MDC 05.
BILLING CODE 4120-01-P

[[Page 28143]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.016

    The ICD-10-PCS codes that identify the insertion of a 
neurostimulator lead onto the vagus nerve are listed in the following 
table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.018


[[Page 28144]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.019

    The ICD-10-PCS codes that identify the insertion of a stimulator 
generator are listed in the following table.

[[Page 28145]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.020


[[Page 28146]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.021

BILLING CODE 4120-01-C
    Our analysis of this grouping issue confirmed that, when a 
procedure code describing the insertion of a neurostimulator lead onto 
the vagus

[[Page 28147]]

nerve and a procedure code describing the insertion of a stimulator 
generator are reported with a principal diagnosis code describing heart 
failure, these cases group to surgical MS-DRGs 252, 253 and 254 (Other 
Vascular Procedures with MCC, with CC, without MCC respectively).
    We note that cases involving the use of a peripheral 
neurostimulator and a diagnosis from MDC 01 are assigned to MS-DRG 041 
only. The GROUPER logic for MS-DRGs 040, 041, and 042 is reflected in 
the logic table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.022

    We refer the reader to the ICD-10 MS-DRG Version 39.1 Definitions 
Manual (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 the listed MS-DRGs.
    We examined claims data from the September 2021 update of the FY 
2021 MedPAR file for MS-DRGs 252, 253 and 254 to identify the subset of 
cases within MS-DRGs 252, 253 and 254 reporting a procedure code 
describing the insertion of a neurostimulator lead onto the vagus nerve 
and a procedure code describing the insertion of a stimulator generator 
with a principal diagnosis of heart failure. We found zero cases in MS-
DRGs 252, 253 and 254 reporting a procedure code describing the 
insertion of a neurostimulator lead onto the vagus nerve and a 
procedure code describing the insertion of a stimulator generator with 
a principal diagnosis of heart failure. In an attempt to further 
examine this issue, we then examined claims data from the September 
2021 update of the FY 2021 MedPAR file for MS-DRGs 252, 253 and 254 to 
identify the subset of cases within MS-DRGs 252, 253 and 254 reporting 
a procedure code describing the insertion of a neurostimulator lead 
onto the vagus nerve and a procedure code describing the insertion of a 
stimulator generator with a secondary diagnosis of heart failure and 
similarly found zero cases.
    The results of the claims analysis demonstrate that there is not 
sufficient claims data in the MedPAR file on which to assess the 
resource use of cases reporting a procedure code describing the 
insertion of a neurostimulator lead onto the vagus nerve and a 
procedure code describing the insertion of a stimulator generator with 
a principal or secondary diagnosis of heart failure as compared to 
other cases assigned to MS-DRGs 252, 253, and 254.
    In reviewing the requestor's concerns regarding clinical coherence, 
our clinical advisors acknowledge that heart failure is a complex 
syndrome involving autonomic nervous system dysfunction, however our 
clinical advisors disagree with assigning the diagnosis codes 
describing heart failure to MDC 01 (Diseases and Disorders of the 
Nervous System). Our clinical advisors note the concept of clinical 
coherence requires that the patient characteristics included in the 
definition of each MS-DRG relate to a common organ system or etiology. 
As the listed diagnosis codes describe heart failure, these diagnosis 
codes are appropriately assigned to MDC 05 (Diseases and Disorders of 
the Circulatory System). Our clinical advisors also state it would not 
be appropriate to move these diagnoses into MDC 01 because it could 
inadvertently cause cases reporting these same MDC 05 diagnoses with a 
circulatory system procedure to be assigned to an unrelated MS-DRG 
because 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''.
    To further examine the impact of moving the diagnoses describing 
heart failure into MDC 01, we analyzed claims data for cases reporting 
a circulatory system O.R. procedure and a principal diagnosis of heart 
failure. Our findings are reflected in the following table.
BILLING CODE 4120-01-P

[[Page 28148]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.023


[[Page 28149]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.024

BILLING CODE 4120-01-C
    As shown in the table, if we were to move diagnosis codes 
describing heart failure to MDC 01, 20,199 cases would be assigned to 
the surgical class referred to as ``unrelated operating room 
procedures'' as an unintended consequence because the surgical 
procedure reported on the claim would be considered unrelated to the 
MDC to which the case was assigned based on the principal diagnosis.
    In response to the requestor's concerns regarding the title of MS-
DRGs 252, 253 and 254, we note that, as stated in the ICD-10 MS-DRG 
Definitions Manual, ``In each MDC there is usually a medical and a 
surgical class referred to as ``other medical diseases'' and ``other 
surgical procedures,'' respectively. The ``other'' medical and surgical 
classes are not as precisely 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. There are, however, also 
patients who receive surgical procedures which are completely unrelated 
to the MDC to which the patient was assigned. An example of such a 
patient would be a patient with a principal diagnosis of pneumonia 
whose only surgical procedure is a destruction of prostate 
(transurethral prostatectomy in ICD-9-CM). Such patients are assigned 
to a surgical class referred to as ``unrelated operating room 
procedures.'' '' We further note that MS-DRGs 252, 253, and 254 (Other 
Vascular Procedures with MCC, with CC, and without CC/MCC, 
respectively) are examples of the ``other'' surgical class, therefore 
it is expected that there will be procedures not as precisely 
clinically aligned within the definition (logic) of these MS-DRGs.
    Considering that there is no data in the FY 2021 MedPAR file to 
support a reassignment of these cases based on resource consumption, 
the analysis of clinical coherence as discussed previously, and the 
impact that moving the diagnoses describing heart failure into MDC 01 
from MDC 05 would have on heart failure cases, we do not believe a 
reassignment of these cases is appropriate at this time. We can

[[Page 28150]]

continue to evaluate the clinical coherence and resource consumption 
costs that impact this subset of cases and their current MS-DRG 
assignment as data become available for future rulemaking.
    In summary for the reasons stated previously, we are not proposing 
to reassign cases reporting a procedure code describing the insertion 
of a neurostimulator lead onto the vagus nerve and a procedure code 
describing the insertion of a stimulator generator with a principal 
diagnosis of heart failure from MS-DRG 252, 253 and 254 to MS-DRGs 040, 
041 and 042.
    As we examined the GROUPER logic that would determine an assignment 
of a case to MS-DRGs 252, 253 and 254, we noted the logic for MS-DRGs 
252, 253 and 254 includes ICD-10-PCS procedure codes that describe the 
insertion of the stimulator generator. We refer the reader to the ICD-
10 MS-DRG Version 39.1 Definitions Manual (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 the 
listed MS-DRGs. During our review of the stimulator generator insertion 
procedures assigned to these MS-DRGs, we identified the following 24 
procedure codes that describe the insertion of a stimulator generator, 
differentiated by device type (for example single array or multiple 
array), that do not exist in the logic for MS-DRGs 252, 253 and 254.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.025


[[Page 28151]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.026

BILLING CODE 4120-01-C
    For clinical consistency with the other procedure codes describing 
the insertion of the stimulator generator currently assigned to these 
MS-DRGs, we are proposing to add the 24 ICD-10-PCS codes listed 
previously 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) effective October 1, 2022 for FY 
2023.
    Also, as we examined the GROUPER logic that would determine an 
assignment of a case to MS-DRG 041, we note the logic for case 
assignment to MS-DRG 041 as displayed in the ICD-10 MS-DRG Version 39.1 
Definitions Manual, 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.html contains 
code combinations or ``clusters'' representing the insertion of a 
neurostimulator lead and the insertion of a stimulator generator that 
are captured under a list referred to as ``Peripheral 
Neurostimulators.'' During our review of the procedure code clusters in 
this list, we noted that ICD-10-PCS procedure code clusters describing 
the insertion of a neurostimulator lead and the insertion of the 
stimulator generator differentiated by device type (for example single 
array or multiple array), approach and anatomical site placement are 
captured. However, procedure code clusters describing the insertion of 
stimulator generator, that is not differentiated by device type, and a 
neurostimulator lead were inadvertently excluded. We refer the reader 
to Table 6P.3a (which is available via the internet on the CMS website 
at https://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) for the list of the 108 ICD-10-PCS code 
clusters that were inadvertently excluded and do not exist in the logic 
for MS-DRG 041.
    For clinical consistency, our clinical advisors supported the 
addition of the 108 procedure code clusters to the GROUPER logic list 
referred to as ``Peripheral Neurostimulators'' for MS-DRG 041 that 
describe the insertion of stimulator generator, not differentiated by 
device type, and a neurostimulator lead. Therefore, we are proposing to 
add the 108 ICD-10-PCS code clusters listed in Table 6P.3a that 
describe the insertion of a stimulator generator, that is not 
differentiated by device type, and a neurostimulator lead to MS-DRG 
041, effective October 1, 2022 for FY 2023.
4. MDC 02 (Diseases and Disorders of the Eye): Retinal Artery Occlusion
    We received a request to reassign cases reporting diagnosis codes 
describing central retinal artery occlusion, and the closely allied 
condition branch retinal artery occlusion, from MS-DRG 123 
(Neurological Eye Disorders) in MDC 02 (Diseases and Disorders of the 
Eye) to MS-DRGs 061, 062, and 063 (Ischemic Stroke Precerebral 
Occlusion or Transient Ischemia with Thrombolytic Agent with MCC, with 
CC, and without CC/MCC, respectively) in MDC 01 (Diseases and Disorders 
of the Nervous System).
    Retinal artery occlusion refers to blockage of the retinal artery 
that carries oxygen to the nerve cells in the retina at the back of the 
eye, often by an embolus or thrombus. A blockage in the main artery in 
the retina is called central retinal artery occlusion (CRAO). A 
blockage in a smaller artery is called branch retinal artery occlusion 
(BRAO). According to the requestor, in the current mapping to MS-DRG 
123, diagnoses of CRAO and BRAO are being captured inappropriately as 
eye disorders in MDC 02. Instead, the requestor stated that CRAO and 
BRAO are forms of acute ischemic stroke which occur when a vessel 
supplying blood to the brain is obstructed.
    The requestor stated the retina is a core component of the central 
nervous system and there is growing recognition that damage to it is a 
vascular neurological problem and not an ophthalmological one. Patients 
with CRAO or BRAO are typically very sick, have an underlying 
condition, and are at imminent risk for further events including heart 
attack or brain stroke. A diagnosis of CRAO or BRAO requires an urgent, 
structured and multidisciplinary team-based examination to evaluate and 
treat other diagnoses that may be present such as high blood pressure, 
dyslipidemia, diabetes mellitus, obesity, obstructive sleep apnea and 
smoking to ameliorate the risks of a subsequent, potentially lethal, 
cardiovascular event.
    The requestor further stated new evidence outlines treatment of 
patients with CRAO with acute stroke protocols, specifically with 
intravenous thrombolysis (IV tPA) or hyperbaric oxygen therapy (HBOT), 
to improve outcomes. According to the requestor, BRAO is less commonly 
treated with IV tPA than CRAO but also requires an urgent and thorough 
diagnostic workup as with any other form of stroke. The requestor 
stated the current assignment of these conditions to MS-DRG 123 does 
not properly recognize disease complexity and allocation of resources 
for care for these cases. The requestor stated that patients with CRAO 
or BRAO more closely resemble patients currently mapped to MS-DRGs 061, 
062, and 063 in terms of in resource intensity and criticality and that 
in instances where HBOT is the chosen treatment modality, any revised 
MS-DRG mapping should include the ICD-10-PCS codes for HBOT.

[[Page 28152]]

    The ICD-10-CM codes that describe CRAO and BRAO are found in the 
following table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.027

    Thrombolytic therapy is identified with the following ICD-10-PCS 
procedure codes.
[GRAPHIC] [TIFF OMITTED] TP10MY22.028

    The requestor identified three ICD-10-PCS codes that they stated 
describe HBOT.
[GRAPHIC] [TIFF OMITTED] TP10MY22.029

    During our review of this issue, we included the three procedure 
codes as identified by the requestor as describing HBOT, as well as the 
similar procedure code 5A05221 (Extracorporeal hyperbaric oxygenation, 
continuous) that also describes HBOT, differing only in duration.
    Our analysis of this grouping issue confirmed that, when a 
procedure code describing the administration of a thrombolytic agent or 
a procedure code describing HBOT is reported with principal diagnosis 
code describing CRAO or BRAO, these cases group to medical MS-DRG 123. 
To begin our analysis, we examined claims data from the September 2021 
update of the FY 2021 MedPAR file for MS-DRG 123 to (1) identify cases 
reporting a principal diagnosis code describing CRAO or BRAO without a 
procedure code describing the administration of a thrombolytic agent or 
a procedure code describing HBOT; (2) identify cases reporting 
diagnosis codes describing CRAO or BRAO with a procedure code 
describing HBOT; and (3) identify cases reporting diagnosis codes 
describing CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent. Our findings are shown in the 
following table:

[[Page 28153]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.030

BILLING CODE 4120-01-C
    As shown in the table, we identified a total of 2,642 cases within 
MS-DRG 123 with an average length of stay of 2.5 days and average costs 
of $6,457. Of these 2,642 cases, there are 774 cases that reported a 
principal diagnosis code describing CRAO or BRAO without a procedure 
code describing the administration of a thrombolytic agent or a 
procedure code describing HBOT with an average length of stay of 2.2 
days and average costs of $5,482. There are nine cases that reported a 
principal diagnosis code describing CRAO or BRAO with a procedure code 
describing HBOT with an average length of stay of 2 days and average 
costs of $6,491. There are 47 cases that reported a principal diagnosis 
code describing CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent with an average length of stay 
of 2.3 days and average costs of $14,335.
    The data analysis shows that the 774 cases in MS-DRG 123 reporting 
a principal diagnosis code describing CRAO or BRAO without a procedure 
code describing the administration of a thrombolytic agent or a 
procedure code describing HBOT have average costs lower than the 
average costs in the FY 2021 MedPAR file for MS-DRG 123 ($5,482 
compared to $6,457), and the average length of stay is shorter (2.2 
days compared to 2.5 days). For the nine cases in MS-DRG 123 reporting 
a principal diagnosis code describing CRAO or BRAO with a procedure 
code describing HBOT, the average length of stay is shorter (2 days 
compared to 2.5 days) and the average costs ($6,491 compared to $6,457) 
are slightly higher than the average length of stay and average costs 
compared to all cases in that MS-DRG. For the 47 cases in MS-DRG 123 
reporting a principal diagnosis code describing CRAO or BRAO with a 
procedure code describing the administration of a thrombolytic agent, 
the average length of stay is slightly shorter (2.3 days compared to 
2.5 days) and the average costs are higher ($14,335 compared to $6,457) 
than the average length of stay and average costs compared to all cases 
in that MS-DRG.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for MS-DRGs 061, 062, and 063. Our findings are 
shown in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.031

    Because MS-DRG 123 is a base DRG and there is a three-way split 
within MS-DRGs 061, 062, and 063, we also analyzed the 47 cases 
reporting a principal diagnosis code describing CRAO or BRAO with a 
procedure code describing the administration of a thrombolytic agent 
and the nine cases reporting a principal diagnosis code describing CRAO 
or BRAO with a procedure code describing HBOT for the presence or 
absence of a secondary diagnosis designated as a complication or 
comorbidity (CC) or a major complication or comorbidity (MCC).

[[Page 28154]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.032

    This data analysis shows the cases in MS-DRG 123 reporting a 
principal diagnosis code describing CRAO or BRAO with a procedure code 
describing the administration of a thrombolytic agent or with a 
procedure code describing HBOT when distributed based on the presence 
or absence of a secondary diagnosis designated as a CC or an MCC have 
average costs lower than the average costs in the FY 2021 MedPAR file 
for MS-DRGs 061, 062, and 063 respectively, and the average lengths of 
stay are shorter. Accordingly, we do not believe the data adequately 
support a potential reassignment of these cases to MS-DRGs 061, 062, 
and 063 respectively.
    Our clinical advisors reviewed this issue and the related data 
analysis and do not believe that the small subset of patients with a 
diagnosis of CRAO or BRAO receiving a thrombolytic agent or hyperbaric 
oxygen therapy warrant a separate MS-DRG or reassignment at this time. 
Our clinical advisors noted the average costs for cases of patients 
with a diagnosis of CRAO or BRAO receiving HBOT are only slightly 
higher than the average costs for all cases in MS-DRG 123 ($6,491 
compared to $6,457). The average costs for cases of patients with a 
diagnosis of CRAO or BRAO receiving a thrombolytic agent are higher 
than the average costs for all cases in MS-DRG 123 however 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) it is unclear to what degree the 
higher average costs for these cases are attributable to the severity 
of illness of the patient and other circumstances of the admission as 
opposed to the administration of a thrombolytic agent, as the claims 
data reflects a wide variance with regard to average costs for these 
cases.
    Our clinical advisors further note that ischemia is defined as a 
condition in which the blood vessels become blocked, and blood flow is 
stopped or reduced. The condition has many potential causes, including 
a blockage caused by a blood clot, or due to buildup of deposits, such 
as cholesterol. Ischemia can occur anywhere in the body, and the 
different names for the condition depend on the organ or body part 
affected such as the brain (cerebral ischemia), heart (ischemic heart 
disease, myocardial ischemia, or cardiac ischemia), and intestines 
(mesenteric ischemia or bowel ischemia), legs (critical limb ischemia--
a form of peripheral artery disease), and skin (cutaneous ischemia), 
while they are similar in that they all involve a blocked blood vessel.
    In ICD-10 the body or organ system is the axis of the 
classification and diagnosis codes describing ischemia affecting other 
body parts are classified by the body or organ system affected. For 
example, codes describing myocardial ischemia are assigned to MDC 05 
(Diseases and Disorders of the Circulatory System) and codes describing 
mesenteric ischemia are assigned to MDC 06 (Diseases and Disorders of 
the Digestive System). Our clinical advisors disagree with assigning 
the diagnosis codes describing CRAO and BRAO to MDC 01. Our clinical 
advisors note the concept of clinical coherence generally requires that 
the patient characteristics included in the definition of each MS-DRG 
relate to a common organ system or etiology and that a specific medical 
specialty should typically provide care to the patients in the DRG. 
While closely related, the eyes and the brain are different organs. Our 
clinical advisors state that because the diagnosis codes used to report 
CRAO and BRAO describe ischemia affecting the retina, these diagnosis 
codes are appropriately assigned to MDC 02 (Diseases and Disorders of 
the Eye). The retina is a collection of cells at the back of the eye 
where the processing of visual information begins. Due to the retina's 
vital role in vision, damage to it can cause permanent blindness. The 
presence of CRAO or BRAO requires input from an ophthalmologist and 
treatment for these diagnoses would be expected to utilize different 
resources than a diagnosis of cerebral ischemia which may or may not 
involve visual impairment. Other possible interventions for CRAO or 
BRAO included attempting to lower the intraocular pressure with 
medication or by using a small-gauge needle to remove fluid to try to 
dislodge the embolus or ocular massage to dislodge the clot, which are 
not interventions generally performed for a diagnosis of acute ischemic 
stroke.
    To explore other mechanisms to address this request, we also 
reviewed claims data to consider the option of adding another severity 
level to the current structure of MS-DRG 123 (Neurological Eye 
Disorders) and assigning the cases with a principal diagnosis of CRAO 
or BRAO with a procedure code describing the administration of a 
thrombolytic agent to the highest level. This option would involve 
modifying the current base MS-DRG to a two-way severity level split or 
to a three-way severity level split of ``with MCC or thrombolytic 
agent, with CC, and without CC/MCC.'' Therefore, it would include 
proposing new MS-DRGs if the data and our clinical advisors supported 
creation of new MS-DRGs. However, as displayed in the data findings in 
the table that follows, the data did not support this option. We 
applied the five criteria as described in section II.D.1.b. of the 
preamble of this

[[Page 28155]]

proposed rule to determine if it would be appropriate to subdivide 
cases currently assigned to MS-DRG 123 into severity levels. This 
analysis generally includes two years of MedPAR claims data to compare 
the data results from one 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. 
However, as discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25092), our MS-DRG analysis last year was based on ICD-10 claims data 
from the March 2020 update of the FY 2019 MedPAR file, which contains 
hospital claims received from October 1, 2018 through March 31, 2020, 
for discharges occurring through September 30, 2019 and the ICD-10 
claims data from the September 2020 update of the FY 2020 MedPAR file, 
which contains hospital claims received from October 1, 2019 through 
September 30, 2020, for discharges occurring through September 30, 2020 
given the potential impact of the PHE for COVID-19. Therefore, for this 
FY 2023 IPPS/LTCH PPS proposed rule, we reviewed the claims data for 
base MS-DRG 123 using the March 2020 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 2022. We also reviewed the claims data for base MS-DRG 
123 using the September 2021 update of the FY 2021 MedPAR file, which 
were used in our analysis of claims data for MS-DRG reclassification 
requests for FY 2023. Our findings are shown in the table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.033

    We applied the criteria to create subgroups for the three-way 
severity level split. We refer the reader to section II.D.1.b. of the 
preamble of this FY 2023 IPPS/LTCH PPS proposed rule, for related 
discussion regarding our finalization of the expansion of the criteria 
to include the NonCC subgroup and our proposal to continue to delay 
application of the NonCC subgroup criteria to existing MS-DRGs with a 
three-way severity level split to maintain more stability in the 
current MS-DRG structure. We found that the criterion that there be at 
least 500 cases for each subgroup was not met, as shown in the table 
based on the data in the FY 2019, FY 2020, and FY 2021 MedPAR files. 
Specifically, for the ``with MCC'', ``with CC'', and ``without CC/MCC'' 
split, there were only 376 cases in the ``with MCC'' subgroup based on 
the data in the FY 2019 MedPAR file, only 345 cases in the ``with MCC'' 
subgroup based on the data in the FY 2020 MedPAR file and only 374 
cases in the ``with MCC'' subgroup based on the data in the FY 2021 
MedPAR file.
    We then applied the criteria to create subgroups for the two-way 
severity level splits. For the ``with MCC'' and ``without MCC'' (CC + 
NonCC) split, the criterion that there be at least 500 cases for each 
subgroup failed due to low volume each year, specifically, for the 
``with MCC'' subgroup as previously described. For the ``with CC/MCC'' 
and ``without CC/MCC'' (NonCC) split, we found that the criterion that 
there be at least a $2,000 difference in average costs between the 
``with CC/MCC'' and ``without CC/MCC'' subgroups also failed. In the FY 
2019 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $6,282 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $4,832, for a 
difference of only $1,450 ($6,282 minus $4,832 = $1,450). In the FY 
2020 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $6,573 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $5,122, for a 
difference of only $1,451 ($6,573 minus $5,122 = $1,451). In the FY 
2021 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $7,176 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $5,364, for a 
difference of only $1,812 ($7,176 minus $5,364 = $1,812). Our data 
analysis indicates that the current base MS-DRG 123 maintains the 
overall accuracy of the IPPS, and that the claims data do not support a 
three-way or a two-way severity level split for MS-DRG 123.
    Lastly, we explored reassigning cases with a principal diagnosis of 
CRAO or BRAO that receive the administration of a thrombolytic agent to 
other MS-DRGs within MDC 02. However, our review did not support 
reassignment of these cases to any other medical MS-DRGs as these cases 
would not be clinically coherent with the cases assigned to those other 
MS-DRGs.
    Therefore, based on the various data analyses we performed to 
explore the possible reassignment of cases with a principal diagnosis 
of CRAO or BRAO with a procedure code describing the administration of 
a thrombolytic agent or a procedure code describing hyperbaric oxygen 
therapy, and the clinical analysis as previously discussed, for FY 2023 
we are not proposing any MS-DRG changes for cases with a principal 
diagnosis of CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent or a procedure code describing 
hyperbaric oxygen therapy.
5. MDC 04 (Diseases and Disorders of the Respiratory System): Acute 
Respiratory Distress Syndrome (ARDS)
    We received a request to reassign cases reporting diagnosis code 
J80 (Acute respiratory distress syndrome) as the principal diagnosis 
from MS-DRG 204 (Respiratory Signs and Symptoms) to MS-DRG 189 
(Pulmonary Edema and Respiratory Failure).
    According to the requestor, when a patient presents with the 
condition of acute respiratory failure that progresses to acute 
respiratory distress syndrome (ARDS) during the hospital stay, official 
coding guidance instructs to only report the diagnosis code for ARDS 
(code J80). The requestor stated that in the American Hospital 
Association's (AHA) Coding Clinic for ICD-10-CM and ICD-10-PCS, Fourth 
Quarter 2020 publication, for a patient who is admitted in acute 
hypoxic respiratory failure that progresses to ARDS, the advice is to 
assign code J80, Acute respiratory distress syndrome. Additionally, in 
the ICD-10-CM Tabular List of Diseases, per the Excludes 1 note under 
category J96 (Respiratory failure, not elsewhere

[[Page 28156]]

classified) only code J80 should be assigned when respiratory failure 
and ARDS are both documented. The same publication also maintained that 
ARDS is a life-threatening form of respiratory failure and is not an 
unrelated condition. Therefore, when acute respiratory failure is 
documented along with ARDS, only one code is reported to capture the 
highest level of severity.
    The requestor also conveyed the Fourth Quarter 2020 publication's 
reference to previously published advice from the Fourth Quarter 2017 
publication that stated, ``Acute respiratory distress syndrome (ARDS) 
is a life-threatening condition. ARDS is a rapidly progressive disorder 
that has symptoms of dyspnea, tachypnea, and hypoxemia. Fluid builds up 
in the alveoli and lowers the amount of oxygen that is circulated 
through the bloodstream. Low levels of oxygen in the blood threatens 
organ function. ARDS is often associated with sepsis, pneumonia, trauma 
and aspiration. The majority of people who develop ARDS are already in 
the hospital in critical condition from some other health complication. 
The focus of treatment is getting oxygen to the organs.''
    We examined claims data from the September 2021 update of the FY 
2021 MedPAR file for all cases in MS-DRG 204 and the cases reporting 
ARDS (code J80) as a principal diagnosis. Our findings are shown in the 
following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.034

    As shown in the table, the data demonstrate a longer average length 
of stay (7.6 days versus 2.8 days) and higher average costs ($15,077 
versus $6,780) for the 96 cases reporting ARDS (code J80) as a 
principal diagnosis when compared to all 5,241 cases in MS-DRG 204.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for all cases in MS-DRG 189. Our findings are shown 
in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.035

    The data analysis supports that cases reporting ARDS (code J80) are 
more appropriately aligned with the average length of stay and average 
costs of the cases in MS-DRG 189 in comparison to MS-DRG 204 when ARDS 
is reported as a principal diagnosis. We also agree that, consistent 
with the coding clinic advice, ARDS is a life-threatening form of 
respiratory failure and the conventions of the ICD-10-CM classification 
as displayed in the Tabular List of Diseases Excludes note, support the 
concept that cases reporting ARDS as a principal diagnosis are more 
clinically coherent with the other conditions currently assigned to MS-
DRG 189.
    For these reasons, we are proposing to reassign cases reporting 
ARDS (code J80) as a principal diagnosis from MS-DRG 204 to MS-DRG 189 
effective FY 2023.
6. MDC 05 (Diseases and Disorders of the Circulatory System)
a. Percutaneous Transluminal Coronary Angioplasty (PTCA) Logic
    We identified a replication issue from the ICD-9 based MS-DRGs to 
the ICD-10 based MS-DRGs for procedure code 02UG3JE (Supplement mitral 
valve created from left atrioventricular valve with synthetic 
substitute, percutaneous approach) that was created effective October 
1, 2016 (FY 2017), to identify and describe further interventions that 
may occur for a patient who had previously undergone cardiac valve 
surgery to correct a congenital anomaly, such as repair of a complete 
common atrioventricular canal defect.
    We used our established process in the assignment of new procedure 
code 02UG3JE to the most appropriate MS-DRG(s) for FY 2017. Procedure 
code 02UG3JE was proposed for assignment to the same MS-DRGs as its 
predecessor code. The predecessor code for procedure code 02UG3JE as 
shown in the 2017 ICD-10-PCS conversion table (available via the 
internet on the CMS web page at https://www.cms.gov/Medicare/Coding/ICD10/2017-ICD-10-PCS-and-GEMs) is 02UG3JZ (Supplement mitral valve 
with synthetic substitute, percutaneous approach). The ICD-9-CM 
comparable translation for this code (02UG3JZ) is procedure code 35.97 
(Percutaneous mitral valve repair with implant), which identifies the 
use of the MitraClip[supreg] technology that has been discussed 
extensively in prior rulemaking.
    In the FY 2017 rulemaking, using our established process, new 
procedure code 02UG3JE was proposed and finalized for assignment to the 
following MS-DRGs for FY 2017, as also shown in Table 6B.--New 
Procedure Codes in association with the FY 2017 IPPS/LTCH PPS proposed 
and final rules (available via the internet on the CMS web page at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download). We note that the 
listed MS-DRGs also reflect the MS-DRGs that the predecessor code 
(02UG3JZ) was assigned to at the time of the proposed rule.

[[Page 28157]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.036

    However, as also discussed in the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 56809 through 56813), in connection with replication efforts 
between the ICD-9 and ICD-10 based MS-DRGs and the surgical hierarchy, 
the predecessor procedure code (02UG3JZ) was reassigned from MS-DRGs 
273 and 274 to MS-DRG 228 (Other Cardiothoracic Procedures with MCC) 
and revised MS-DRG 229 (Other Cardiothoracic Procedures without MCC), 
and was removed from the PTCA logic for MS-DRGs 231 and 232. However, 
these proposed and finalized MS-DRG changes for procedure code 02UG3JZ 
were not considered for purposes of the MS-DRG assignments for new 
procedure code 02UG3JE, which were instead finalized as proposed based 
on the existing MS-DRG assignments for the predecessor code, and code 
02UG3JE continued to remain on the PTCA list in the GROUPER logic for 
MS-DRGs 231 and 232.
    Our clinical advisors stated that procedure code 02UG3JE does not 
describe a PTCA procedure. We analyzed claims data from the September 
2021 update of the FY 2021 MedPAR file for cases in MS-DRGs 231 and 232 
to determine if there were any cases reported with procedure code 
02UG3JE, and there were no such cases found.
    Accordingly, because the procedure described by procedure code 
02UG3JE is not clinically consistent with a PTCA procedure and it was 
initially assigned to the list for PTCA procedures in the GROUPER logic 
as a result of replication in the transition from ICD-9 to ICD-10 based 
MS-DRGs, we are proposing to remove procedure code 02UG3JE from the 
list for PTCA procedures in the GROUPER logic for MS-DRGs 231 and 232 
effective FY 2023. We are also proposing to maintain the MS-DRG 
assignment for procedure code 02UG3JE in MS-DRGs 266 and 267 
(Endovascular Cardiac Valve Replacement and Supplement Procedures with 
and without MCC, respectively) for FY 2023.
b. Neuromodulation Device Implant for Heart Failure 
(BarostimTM Baroreflex Activation Therapy)
    The BAROSTIM NEOTM System is the first neuromodulation 
device system designed to trigger the body's main cardiovascular reflex 
to target symptoms of heart failure. The system consists of an 
implantable pulse generator (IPG) that is implanted subcutaneously in 
the upper chest below the clavicle, a stimulation lead that is sutured 
to either the right or left carotid sinus to activate the baroreceptors 
in the wall of the carotid artery and a wireless programmer system that 
is used to non-invasively program and adjust BAROSTIM NEOTM 
therapy via telemetry. The BAROSTIM NEOTM System is 
indicated for the improvement of symptoms of heart failure in a subset 
of patients with symptomatic New York Heart Association (NYHA) class II 
and III heart failure with low cardiac ejection fractions who do not 
benefit from guideline directed pharmacologic therapy or qualify for 
Cardiac Resynchronization Therapy (CRT).
    The BAROSTIM NEOTM System was approved for new 
technology add-on payments for FY 2021 (85 FR 58716 through 58717) and 
FY 2022 (86 FR 44974). We refer readers to section II.F.4.a. of the 
preamble of this proposed rule for a discussion regarding the proposed 
FY 2023 status of technologies approved for FY 2022 new technology add-
on payments, including the BAROSTIM NEOTM System.
    For this FY 2023 IPPS/LTCH PPS proposed rule, we received a request 
to (1) reassign the ICD-10-PCS procedure codes that describe the 
implantation of the BAROSTIM NEOTM System from MS-DRGs 252, 
253 and 254 (Other Vascular Procedures with MCC, with CC, without MCC 
respectively) to MS-DRGs 222, 223, 224, 225, 226, and 227 (Cardiac 
Defibrillator Implant with and without Cardiac Catheterization with and 
without AMI/HF/Shock with and without MCC, respectively) and (2) 
reassign the procedure code that describes the placement of a BAROSTIM 
NEOTM IPG alone from MS-DRGs 252, 253 and 254 to MS-DRG 245 
(AICD Generator Procedures).
    The following ICD-10-PCS procedure codes uniquely identify the 
implantation of the BAROSTIM NEOTM System: 0JH60MZ 
(Insertion of stimulator generator into chest subcutaneous tissue and 
fascia, open approach) in combination with 03HK3MZ (Insertion of 
stimulator lead into right internal carotid artery, percutaneous 
approach) or 03HL3MZ (Insertion of stimulator lead into left internal 
carotid artery, percutaneous approach). The requestor noted that ICD-
10-PCS codes 0JH60MZ, 03HK3MZ and 03HL3MZ are individually assigned to 
MDC 05 in MS-DRGs 252, 253, and 254 but not mapped to the logic of 
these MS-DRGs in a code combination or code cluster. According to the 
requestor this means that cases with a principal diagnosis from MDC 05 
with procedure codes describing the implantation of a BAROSTIM 
NEOTM system (0JH60MZ with 03HL3MZ or 03HK3MZ); with 
procedure codes describing placement of the stimulator generator alone 
(0JH60MZ); or with procedure codes describing the placement of a 
carotid sinus lead only (03HL3MZ or 03HK3MZ) are all assigned to MS-
DRGs 252, 253, and 254, despite the significant differences in the 
clinical coherence and resources required to perform these distinct 
procedures.

[[Page 28158]]

    The requestor stated that cases reporting procedure codes 
describing the implantation of a BAROSTIM NEOTM system are 
more clinically similar to, and have costs that are more closely 
aligned to, cases within MS-DRGs 222, 223, 224, 225, 226, and 227. The 
requestor stated that according to its own analysis, the population of 
Medicare patients surgically treated with procedures assigned to MS-
DRGs 222, 223, 224, 225, 226, and 227 is essentially identical to the 
population treated with the BAROSTIM NEOTM System. According 
to the requestor, this congruent patient population accounts for 
essentially all cases assigned to MS-DRGs 222, 223, 224, 225, 226, and 
227. The requestor stated their analysis demonstrated that over 80% of 
the cases in MS-DRGs 222, 223, 224, 225, 226, and 227 had a diagnosis 
of heart failure, compared to only 30% of cases with a diagnosis of 
heart failure assigned to MS-DRGs 252, 253, and 254. The requestor 
stated that the subset of patients that have an indication for the 
implantation of a BAROSTIM NEOTM system also have 
indications for the implantation of Implantable Cardioverter 
Defibrillators (ICD), Cardiac Resynchronization Therapy Defibrillators 
(CRT-D) and/or Cardiac Contractility Modulation (CCM) devices, all of 
which also require the permanent implantation of a programmable, 
electrical pulse generator and at least one electrical lead. The 
requestor specifically highlighted that the procedure code combinations 
describing the implantation of a cardiac contractility modulation (CCM) 
device system, which consists of a programmable implantable pulse 
generator (IPG) and three leads, one of which is implanted into the 
right atrium and the other two leads which are inserted into the right 
ventricle is assigned to MS-DRGs 222, 223, 224, 225, 226, and 227, and 
the codes describing the insertion of contractility modulation device 
generator alone are assigned to MS-DRG 245. The requestor stated that 
the average resource utilization required to implant the BAROSTIM 
NEOTM System demonstrates a significant disparity compared 
to all procedures within MS-DRGs 252, 253, and 254 and noted that the 
cost of the BAROSTIM NEOTM implantable device is $35,000, 
which is in range with the cost of the other cardiac implantable 
devices (for example ICD, CRT-D, and CCM) assigned to MS-DRGs 222, 223, 
224, 225, 226, and 227.
    The requestor stated that the majority of the procedures assigned 
to MS-DRGs 252, 253, and 254 are primarily designed to identify, 
diagnose, clear and restructure veins and arteries, excluding those 
that require implantable devices. Furthermore, the requestor stated the 
surgical procedures within MS-DRGs 252, 253, and 254 are not intended 
to treat or improve the function of the heart, nor treat the symptoms 
of heart failure.
    The requestor acknowledged that there are very few cases within the 
publicly available Medicare inpatient claims data that potentially 
includes procedure codes describing the implantation of a BAROSTIM 
NEOTM system. The requestors' own analysis revealed fewer 
than 11 cases with procedure codes describing the implantation of a 
BAROSTIM NEOTM system in the combined FY 2019 and FY 2020 
MedPAR data and noted that during much of this time period, the 
BAROSTIM NEOTM System was only implanted as part of a 
controlled clinical trial. The requestor stated that this incomplete 
data should not be used to determine initial MS-DRG assignments, 
especially for new FDA designated `breakthrough' medical technologies 
like the BAROSTIM NEOTM system. Rather, the requestor stated 
that CMS should use available information and expert knowledge to make 
initial MS-DRG assignments, while waiting for a substantial number of 
Medicare covered, post-approved claims from a disperse set of hospitals 
to reconsider MS-DRG assignments as necessary. The requestor cautioned 
that upon new technology add-on payments expiration, and if the 
inadequate MS-DRG assignment for these procedures continues, inpatient 
admissions to implant the BAROSTIM NEOTM system will be paid 
less than outpatient admissions to perform the same procedures.
    The ICD-10-CM diagnosis codes that describe heart failure are found 
in the following table. These diagnosis codes are all currently 
assigned to MDC 05.
BILLING CODE 4120-01-P

[[Page 28159]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.037

    First, we examined claims data from the September 2021 update of 
the FY 2021 MedPAR file for MS-DRGs 252, 253 and 254 to identify cases 
reporting a diagnosis of heart failure and procedure codes describing 
the implantation of the BAROSTIM NEOTM system with or 
without a procedure code describing the performance of a cardiac 
catheterization as MS-DRGs 222, 223, 224, 225, 226, and 227 are defined 
by the performance of cardiac catheterization. Our findings are shown 
in the following table.

[[Page 28160]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.038

    As shown in the table, the data analysis performed indicates that 
the two cases in MS-DRG 252 reporting procedure codes describing the 
implantation of a BAROSTIM NEOTM system have an average 
length of stay that is shorter than the average length of stay for all 
the cases in MS-DRG 252 (4.5 days versus 7.6 days) and higher average 
costs when compared to all the cases in MS-DRG 252 ($67,588 versus 
$27,488). These two cases did not also report a procedure code 
describing the performance of a cardiac catherization. The one case in 
MS-DRG 253 reporting procedure codes describing the implantation of a 
BAROSTIM NEOTM system had a length of stay that is shorter 
than the average length of stay for all the cases in MS-DRG 253 (1 day 
versus 5.2 days) and lower costs when compared to all the cases in MS-
DRG 253 ($19,237 versus $21,978). This case did not also report a 
procedure code describing the performance of a cardiac catherization. 
We found zero cases in MS-DRG 254 reporting procedure codes describing 
the implantation of a BAROSTIM NEOTM system.
    Our clinical advisors reviewed this data and note that is it is 
difficult to detect patterns of complexity and resource intensity based 
on the three cases that reported procedure codes describing the 
implantation of a BAROSTIM NEOTM system. The claims data 
also reflect a wide variance with regard to the length of stay and 
average costs for the three cases that did report the implantation of a 
BAROSTIM NEOTM system. The results of the claims analysis 
demonstrate we do not have sufficient claims data on which to base and 
evaluate any proposed changes to the current MS-DRG assignment. Our 
clinical advisors also expressed concern in equating the implantation 
of a BAROSTIM NEOTM system to the placement of ICD, CRT-D, 
and CCM devices as these devices all differ in terms of technical 
complexity and anatomical placement of the electrical lead(s). Our 
clinical advisors note there is no intravascular component or vascular 
puncture involved when implanting a BAROSTIM NEOTM system. 
Our clinical advisors also note the placement of ICD, CRT-D, and CCM 
devices generally involve a lead being affixed to the myocardium, being 
threaded through the coronary sinus or crossing a heart valve and are 
procedures that involve a greater level of complexity than affixing the 
stimulator lead to either the right or left carotid sinus when 
implanting a BAROSTIM NEOTM system.
    Next, to evaluate the request to reassign the procedure code that 
describes the placement of a BAROSTIM NEOTM IPG alone from 
MS-DRGs 252, 253 and 254 to MS-DRG 245 (AICD Generator Procedures), we 
examined claims data from the September 2021 update of the FY 2021 
MedPAR file for all cases in MS-DRGs 252, 253 and 254 and compared the 
results to cases with a procedure code describing placement of the 
stimulator generator alone. Our findings are shown in the following 
table. 
[GRAPHIC] [TIFF OMITTED] TP10MY22.039


[[Page 28161]]


BILLING CODE 4120-01-C
    As shown in the table, the data analysis performed indicates that 
the 12 cases in MS-DRG 252 reporting a procedure code describing 
placement of the stimulator generator alone have an average length of 
stay that is longer than the average length of stay for all the cases 
in MS-DRG 252 (8.8 days versus 7.6 days) and higher average costs when 
compared to all the cases in MS-DRG 252 ($56,622 versus $27,488). The 
four cases in MS-DRG 253 reporting a procedure code describing 
placement of the stimulator generator alone have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 253 (2.5 days versus 5.2 days) and higher average costs when 
compared to all the cases in MS-DRG 253 ($30,451 versus $21,978). We 
found zero cases in MS-DRG 254 reporting a procedure code describing 
placement of the stimulator generator alone.
    Our clinical advisors reviewed this data, and found, similar to the 
analysis of the data from the three cases that reported procedure codes 
describing the implantation of a BAROSTIM NEOTM system, that 
it is difficult to detect patterns of complexity and resource intensity 
based on the few cases that reported procedure codes describing 
placement of the stimulator generator alone. The claims data similarly 
reflects a wide variance with regard to the length of stay and average 
costs for these cases that did report the placement of the stimulator 
generator alone, indicating there may have been other factors 
contributing to the higher costs. When reviewing the consumption of 
hospital resources for this small 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 as the 
patients tended to have a major complication or co-morbid (MCC) 
condition reported based on the MS-DRG assigned.
    We recognize the average costs of the small numbers of cases 
reporting a procedure code describing placement of the stimulator 
generator alone 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.
    In response to the requestor's concerns regarding procedures 
currently assigned to MS-DRGs 252, 253 and 254, as discussed in section 
II.D.3.b. of the preamble of this proposed rule, we note that MS-DRGs 
252, 253, and 254 (Other Vascular Procedures with MCC, with CC, and 
without CC/MCC, respectively) are examples of the ``other'' surgical 
class, and therefore it is expected that there will be procedures not 
as precisely clinically aligned within the definition (logic) of these 
MS-DRGs. In regard to the concern about the implications for 
reimbursement when these procedures are performed in the outpatient 
setting as opposed to the inpatient setting, we note that the goals of 
reviewing the MS-DRG assignments of particular procedures are to better 
clinically represent the resources involved in caring for these 
patients and to enhance the overall accuracy of the system.
    In response to the requestor's statement that CMS should use 
available information and expert knowledge to make initial MS-DRG 
assignments, while waiting for a substantial number of Medicare 
covered, post-approved claims from a disperse set of hospitals to 
reconsider MS-DRG assignments as necessary, we note that we use 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 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 or treatment of the 
condition. We note that this process will 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. Members of the 
public have the opportunity to provide feedback on the assignment and 
designation of the codes if they disagree. We refer the reader to 
section II.D.17 of this proposed rule for a more detailed discussion of 
this process. We note that when BAROSTIM NEOTM applied for 
new technology add-on payment, it was noted that the technology could 
be uniquely identified using a combination of existing ICD-10-PCS codes 
that were already assigned to MS-DRGs, and this circumstance generally 
would not provide a basis for MS-DRG reassignment.
    Lastly, our clinical advisors expressed concern regarding making 
proposed MS-DRG changes based on a specific, single technology 
(BAROSTIM NEOTM system), identified by only one unique 
procedure code combination versus considering proposed changes based on 
a group of related procedure codes that can be reported to describe 
that same type or class of technology, which is more consistent with 
the intent of the MS-DRGs.
    We believe that as the number of cases reporting procedure codes 
describing the implantation of neuromodulation devices for heart 
failure increases, a better view of the associated costs and lengths of 
stay on average will be reflected in the data for purposes of assessing 
any reassignment of these cases. Our clinical advisors stated that it 
would not be appropriate to reassign cases for patients from MS-DRGs 
252, 253 and 254 to MS-DRGs 222, 223, 224, 225, 226, and 227 in the 
absence of additional data to better determine the resource utilization 
for this subset of patients to help inform whether a reassignment would 
be clinically warranted. Therefore, for the reasons stated previously, 
we are proposing to maintain the assignment of cases reporting 
procedure codes that describe the implantation of a neuromodulation 
device in MS-DRGs 252, 253 and 254 for FY 2023. We are also proposing 
to maintain the assignment of cases reporting a procedure code 
describing placement of a stimulator generator alone in MS-DRGs 252, 
253 and 254 for FY 2023.
    During our review of this issue, as we examined the GROUPER logic 
that would determine an assignment of a case to MS-DRGs 222, 223, 224, 
225, 226, and 227, we found two diagnosis codes describing heart 
failure that are not currently in 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). These diagnosis codes are listed in the following 
table.

[[Page 28162]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.040

    As a result, when either of these codes are coded as a principal 
diagnosis, 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 procedure code 
combination describing the implantation of a cardiac defibrillator and 
a procedure describing the performance of a cardiac catherization 
procedure. We refer the reader to the ICD-10 MS-DRG Definitions Manual 
Version 39.1, 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.
    Our clinical advisors reviewed this issue and believe that cases 
reporting diagnosis code I97.130 or I97.131 as a principal diagnosis 
are associated with a severity of illness on par with cases reporting a 
principal diagnosis of a type of heart failure. To code postprocedural 
heart failure in ICD-10-CM, instructional notes at category I50 direct 
to ``code first heart failure following surgery'' (that is, I97.130 and 
I97.131) with a second code from subcategory of I50 listed after the 
postprocedural heart failure code to specify the type of heart failure. 
Our clinical advisors recommend adding diagnosis codes I97.130 and 
I97.131 to the logic list of principal diagnoses that describe heart 
failure for clinical consistency, recognizing that coding guidelines 
instruct to code I97.130 and I97.131 before the codes from subcategory 
of I50 that specify the type of heart failure, as the codes from 
subcategory of I50 are currently in the listed principal diagnoses in 
the GROUPER logic for MS-DRGs 222 and 223. Therefore, we are proposing 
to modify the GROUPER logic to allow cases reporting diagnosis code 
I97.130 or I97.131 as a principal diagnosis to group to MS-DRGs 222 and 
223 when reported with qualifying procedures.
c. Cardiac Mapping
    We identified a replication issue from the ICD-9 based MS-DRGs to 
the ICD-10 based MS-DRGs for procedure code 02K80ZZ (Map conduction 
mechanism, open approach). Cardiac mapping describes the creation of 
detailed maps to detect how the electrical signals that control the 
timing of the heart rhythm move between each heartbeat to identify the 
location of rhythm disorders. Cardiac mapping is generally performed 
during open-heart surgery or performed via cardiac catherization.
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49363 through 
49369), we discussed a request to remove the cardiac ablation and other 
specified cardiovascular procedures from the following MS-DRGs, and to 
create new MS-DRGs to classify these procedures:
     MS-DRG 246 (Percutaneous Cardiovascular Procedure with 
Drug- Eluting Stent with MCC or 4+ Vessels/Stents);
     MS-DRG 247 (Percutaneous Cardiovascular Procedure with 
Drug-Eluting Stent without MCC);
     MS-DRG 248 (Percutaneous Cardiovascular Procedure with 
Non-Drug-Eluting Stent with MCC or 4+ Vessels/Stents);
     MS-DRG 249 (Percutaneous Cardiovascular Procedure with 
Non- Drug-Eluting Stent without MCC);
     MS-DRG 250 (Percutaneous Cardiovascular Procedure without 
Coronary Artery Stent with MCC); and
     MS-DRG 251 (Percutaneous Cardiovascular Procedure without 
Coronary Artery Stent without MCC).
    The requestor recommended that CMS assign the following ICD-9-CM 
procedure codes that identify and describe cardiac ablation procedures 
and the other percutaneous intracardiac procedures to the newly created 
MS-DRGs:
     35.52 (Repair of atrial septal defect with prosthesis, 
closed technique);
     35.96 (Percutaneous balloon valvuloplasty);
     35.97 (Percutaneous mitral valve repair with implant);
     37.26 (Catheter based invasive electrophysiologic 
testing);
     37.27 (Cardiac mapping);
     37.34 (Excision or destruction of other lesion or tissue 
of heart, endovascular approach);
     37.36 (Excision, destruction, or exclusion of left atrial 
appendage (LAA)); and
     37.90 (Insertion of left atrial appendage device).
    We stated we agreed that creating these new MS-DRGs would better 
reflect utilization of resources and clinical cohesiveness for 
intracardiac procedures in comparison to intracoronary procedures. 
Therefore, after consideration of the public comments we received, we 
finalized our proposal to create MS-DRGs 273 (Percutaneous Intracardiac 
Procedures with MCC) and MS-DRG 274 (Percutaneous Intracardiac 
Procedures without MCC) for the FY 2016 ICD-10 MS-DRGs Version 33 and 
finalized the assignment of the procedures performed within the heart 
chambers using intracardiac techniques to the two new MS-DRGs.
    In the FY 2016 rulemaking, we stated that the comparable ICD-10-PCS 
code translations for ICD-9-CM procedure code 37.27 (Cardiac mapping) 
were ICD-10-PCS codes 02K83ZZ (Map conduction mechanism, percutaneous 
approach) and 02K84ZZ (Map conduction mechanism, percutaneous 
endoscopic approach). However, code 02K80ZZ (Map Conduction Mechanism, 
Open Approach), which is also a comparable ICD-10-PCS code translation 
for ICD-9-CM procedure code 37.27, was inadvertently excluded. 
Consequently, procedure code 02K80ZZ continued to remain in the GROUPER 
logic for MS-DRGs 246, 247, 248, 249, 250 and 251.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58477), we finalized 
a revision to the titles for MS-DRGs 273 and 274 to ``Percutaneous and 
Other Intracardiac Procedures with and without MCC, respectively'' to 
better reflect the procedures assigned to them.
    In the ICD-10 MS-DRGs Definitions Manual Version 39.1, procedure 
code 02K80ZZ is currently recognized as a non-O.R. procedure that 
affects the MS-DRG to which it is assigned. Our clinical advisors 
reviewed this grouping issue and stated that procedure code 02K80ZZ 
does not describe a percutaneous cardiovascular procedure. Our clinical 
advisors support the reassignment of code 02K80ZZ for clinical 
coherence, noting the procedure should be appropriately grouped along 
with other procedure codes that describe cardiac mapping currently 
assigned to MS-DRGs 273 and 274. Accordingly, because the procedure 
described by procedure code 02K80ZZ is not clinically consistent with 
percutaneous cardiovascular procedures

[[Page 28163]]

and it was initially assigned MS-DRGs 246, 247, 248, 249, 250 and 251 
as a result of replication in the transition from ICD-9 to ICD-10 based 
MS-DRGs, we are proposing the reassignment of procedure code 02K80ZZ 
from MS-DRGs 246, 247, 248, 249, 250 and 251 to MS-DRGs 273 and 274 
(Percutaneous and Other Intracardiac Procedures with and without MCC, 
respectively) in MDC 05 effective FY 2023.
    As discussed in section II.D.1.b. of the preamble of this proposed 
rule, we are providing a test version of the ICD-10 MS-DRG GROUPER 
Software, Version 40, so that the public can better analyze and 
understand the impact of the proposals included in this proposed rule. 
We note that at the time of the development of the test software this 
issue was unable to be addressed and therefore, it does not reflect the 
proposed reassignment of procedure code 02K80ZZ from MS-DRGs 246, 247, 
248, 249, 250 and 251 to MS-DRGs 273 and 274 (Percutaneous and Other 
Intracardiac Procedures with and without MCC, respectively) in MDC 05 
for Version 40.
d. Surgical Ablation
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44836 through 
44848), we discussed a two-part request we received to review the MS-
DRG assignments for cases involving the surgical ablation procedure for 
atrial fibrillation. The first part of the request was to create a new 
classification of surgical ablation MS-DRGs to better accommodate the 
costs of open concomitant surgical ablations. 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

    As discussed in the FY 2022 IPPS/LTCH PPS final rule, we examined 
claims data from the March 2020 update of the FY 2019 MedPAR file and 
the September 2020 update of the FY 2020 MedPAR file for cases 
reporting procedure code combinations describing open concomitant 
surgical ablations. We refer the reader to Table 6P.1o associated with 
the FY 2022 final rule (which is available via the internet on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for data analysis findings of cases 
reporting procedure code combinations describing open concomitant 
surgical ablations. We stated our analysis showed while the average 
lengths of stay and average costs of cases reporting procedure code 
combinations describing open concomitant surgical ablations are higher 
than all cases in their respective MS-DRG, we found variation in the 
volume, length of stay, and average costs of the cases. We also stated 
findings from our analysis indicated that MS-DRGs 216, 217, 218 
(Cardiac Valve and Other Major Cardiothoracic Procedures with Cardiac 
Catheterization with MCC, with CC, and without CC/MCC, respectively) as 
well as approximately 31 other MS-DRGs would be subject to change based 
on the three-way severity level split criterion finalized in FY 2021. 
We refer the reader to section II.D.1.b. of this FY 2023 IPPS/LTCH PPS 
proposed rule, for related discussion regarding our proposal to 
continue to delay application of the NonCC subgroup criteria to 
existing MS-DRGs with three-way severity level split to maintain more 
stability in the current MS-DRG structure.
    In the FY 2022 final rule, we finalized our proposal to revise the 
surgical hierarchy for the MS-DRGs in MDC 05 (Diseases and Disorders of 
the Circulatory System) to sequence MS-DRGs 231-236 (Coronary Bypass) 
above MS-DRGs 228 and 229 (Other Cardiothoracic Procedures with and 
without MCC, respectively), effective October 1, 2021. In addition, we 
also finalized the assignment of cases with a procedure code describing 
coronary bypass and a procedure code describing open ablation to MS-
DRGs 233 and 234 and changed the titles of these MS-DRGs to ``Coronary 
Bypass with Cardiac Catheterization or Open Ablation with and without 
MCC, respectively'' to reflect this reassignment for FY 2022.
    In response to this final policy, for this FY 2023 IPPS/LTCH PPS 
proposed rule, we received a request to again review the MS-DRG 
assignment of cases involving open concomitant surgical ablation 
procedures. The requestor stated they continue to believe that the 
average hospital costs for surgical ablation for atrial fibrillation 
demonstrates a cost disparity compared to all procedures within their 
respective MS-DRGs. The requestor asked that that when open surgical 
ablation is performed with MVR, or AVR or MVR/AVR + CABG that these 
procedures are either (1) assigned to a different family of MS-DRGs or 
(2) assigned to MS-DRGs 216 and 217 (Cardiac Valve and Other Major 
Cardiothoracic Procedures with Cardiac Catheterization with MCC and 
with CC, respectively) similar to what CMS did with CABG and open 
ablation procedures in the FY 2022 rulemaking to better accommodate the 
added cost of open concomitant surgical ablation.
    The change to the surgical hierarchy in MDC 05 and the assignment 
of cases with a procedure code describing coronary bypass and a 
procedure code describing open ablation to MS-DRGs 233 and 234 is 
recent, only becoming effective October 1, 2021. We believe more time 
is needed before considering to again review the MS-DRG assignment of 
cases reporting procedure code combinations describing open concomitant 
surgical ablations as the data from the September 2021 update of the FY 
2021 MedPAR file does not reflect our FY 2022 finalization. In 
addition, our clinical advisors continue to state that in open 
concomitant surgical ablation procedures, the CABG, MVR, and AVR 
components of the procedure are more technically complex than the open 
surgical ablation procedure. They also state that the finalized 
revision to the surgical hierarchy leads to a grouping that is more 
coherent and better accounts for the resources expended to address the 
more complex procedures from other cases redistributed during the 
hierarchy change. As noted, we believe that additional time is needed 
to allow for further analysis of the claims data to reflect our FY 2022 
finalization, and also to determine to what extent the patient's co-
morbid conditions are also contributing to costs and to identify other 
contributing factors that might exist with respect to the increased 
length of stay and costs of this subset of cases in these MS-DRGs, as 
discussed in the FY 2022 IPPS/LTCH PPS final rule.
7. MDC 06 (Diseases and Disorders of the Digestive System): 
Appendicitis
    We received a request to reconsider the MS-DRG assignment for 
diagnosis code K35.20 (Acute appendicitis with generalized peritonitis, 
without abscess). According to the requestor, when this code is 
reported in combination with any one of the corresponding procedure 
codes that describe an appendectomy, the case is grouping to MS-DRGs 
341, 342, and 343 (Appendectomy without Complicated Principal Diagnosis 
with MCC, with CC, and without CC/MCC, respectively). Alternatively, 
the requestor stated that when diagnosis code K35.32 (Acute

[[Page 28164]]

appendicitis with perforation and localized peritonitis, without 
abscess) is reported in combination with any one of the corresponding 
procedure codes that describe an appendectomy, the case is grouping to 
MS-DRGs 338, 339, and 340 (Appendectomy with Complicated Principal 
Diagnosis with MCC, with CC, and without CC/MCC, respectively).
    The requestor asserted that the difference in MS-DRG assignment 
suggests that localized peritonitis is more severe or requires an 
additional level of care over and above that for generalized 
peritonitis. The requestor stated that clinically, both localized and 
generalized peritonitis, when treated with an appendectomy require the 
same level of patient care, including extensive intraoperative 
irrigation at the surgical site, direct inspection or imaging of the 
abdomen to look for possible abscess, use of intravenous antibiotics, 
and prolonged inpatient monitoring. The requestor added that 
generalized peritonitis can be thought of as a progression of the 
localized peritonitis condition and that patients progress from 
localized to generalized peritonitis and not vice versa.
    We note that this topic has been discussed previously in our FY 
2019 (83 FR 41230) and FY 2021 rulemakings (85 FR 32500 through 32503) 
and (85 FR 58484 through 58488). Effective FY 2019 (October 1, 2018) 
diagnosis code K35.2 (Acute appendicitis with generalized peritonitis) 
was expanded to K35.20 (Acute appendicitis with generalized 
peritonitis, without abscess); and K35.21 (Acute appendicitis with 
generalized peritonitis, with abscess). In addition, code K35.3 (Acute 
appendicitis with localized peritonitis) was expanded to K35.30 (Acute 
appendicitis with localized peritonitis, without perforation or 
gangrene); K35.31 (Acute appendicitis with localized peritonitis and 
gangrene, without perforation); K35.32 (Acute appendicitis with 
perforation and localized peritonitis, without abscess); and K35.33 
(Acute appendicitis with perforation and localized peritonitis, with 
abscess).
    We finalized the severity level designations for these new 
diagnosis codes in the FY 2019 IPPS/LTCH PPS final rule and stated our 
clinical advisors believed that the new diagnosis codes for acute 
appendicitis described as ``with abscess'' or ``with perforation'' were 
clinically qualified for the MCC severity level designation, while 
acute appendicitis ``without abscess'' or ``without perforation'' were 
clinically qualified for the CC severity level designation because 
cases with abscess or perforation would be expected to require more 
clinical resources and time to treat while those cases ``without 
abscess'' or ``without perforation'' are not as severe clinical 
conditions.
    As discussed in our FY 2021 rulemaking, we received the request to 
add K35.20 (Acute appendicitis with generalized peritonitis, without 
abscess) to the list of complicated principal diagnoses so that all 
ruptured/perforated appendicitis codes in MDC 06 group to MS-DRGs 338, 
339, and 340 (Appendectomy with Complicated Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) as K35.20 is the only 
ruptured appendicitis code not included in the list of complicated 
principal diagnosis codes. At that time, we noted that the inclusion 
term at subcategory K35.2 (Acute appendicitis with generalized 
peritonitis) is: ``Appendicitis (acute) with generalized (diffuse) 
peritonitis following rupture or perforation of the appendix''. The 
requestor stated that code K35.20 (Acute appendicitis with generalized 
peritonitis, without abscess) describes a generalized, more extensive 
form of peritonitis than code K35.32 (Acute appendicitis with 
perforation and localized peritonitis, without abscess). We noted that 
our clinical advisors agreed that the presence of an abscess would 
clinically determine whether a diagnosis of acute appendicitis would be 
considered a complicated principal diagnosis. As diagnosis code K35.20 
is described as ``without'' an abscess, our clinical advisors 
recommended that K35.20 not be added to the list of complicated 
principal diagnoses for MS-DRGS 338, 339, and 340. We also proposed to 
remove diagnosis code K35.32 (Acute appendicitis with perforation and 
localized peritonitis, without abscess) from the complicated principal 
diagnosis list.
    In response to that proposal, some commenters disagreed. A 
commenter stated that when ruptured appendicitis results in generalized 
peritonitis, resources are greater because the infection is not walled 
off, not localized, and has spread to two or more compartments within 
the abdominal cavity. According to the commenter, clinical literature 
supports the statement that generalized peritonitis is a more morbid 
(severe) presentation than just perforation or localized abscess. After 
consideration of the comments received and for the reasons discussed in 
the FY 2021 final rule, we did not finalize our proposals in that final 
rule. We concurred that the expansion of diagnosis codes K35.2 and 
K35.3 to introduce additional clinical concepts effective October 1, 
2018 significantly changed the scope and complexity of the diagnosis 
codes for this subset of patients. We also stated NCHS' staff 
acknowledged the clinical concerns based on the manner in which 
diagnosis codes K35.2 and K35.3 were expanded and confirmed that they 
would consider further review of these newly expanded codes with 
respect to the clinical concepts.
    We communicated with the CDC/NCHS staff regarding this repeat 
request submitted for FY 2023 consideration. The CDC/NCHS staff 
included these codes describing appendicitis on the agenda and a 
proposal for further revisions was presented for discussion at the 
March 8-9, 2022 ICD-10 Coordination and Maintenance Committee meeting. 
Specifically, the CDC/NCHS staff proposed to expand current diagnosis 
codes K35.20 and K35.21, making them sub-subcategories and creating new 
diagnosis codes to identify and describe acute appendicitis with 
generalized peritonitis, with perforation and without perforation, and 
unspecified as to perforation, as shown in the following table.

[[Page 28165]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.041

    We refer the reader to the CDC website at https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm for additional detailed information 
regarding the proposal, including a recording of the discussion and the 
related meeting materials.
    We note that the deadline for submitting public comments on the 
diagnosis code proposals discussed at the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting is May 9, 2022 and 
according to the CDC/NCHS staff, the diagnosis code proposals are being 
considered for an October 1, 2023 implementation (FY 2024). Any future 
proposed changes to the MS-DRGs for Appendectomy would be dependent on 
the diagnosis code revisions that are finalized by the CDC/NCHS. Since 
it is not clear what code changes may be finalized, including whether 
public comments would support the proposed changes or provide 
alternative options for consideration, we believe it is appropriate to 
delay any possible MS-DRG modifications for future rulemaking. 
Therefore, we are not proposing a change to the MS-DRG assignment or 
the current structure for MS-DRGs 338, 339, 340, 341, 342, and 343 at 
this time. Although we are not proposing a change to the MS-DRG 
assignments for FY 2023, we are making available the findings from our 
data analysis for the listed MS-DRGs and the associated diagnosis codes 
which may help inform future comments. We refer the reader to Table 
6P.4a (which is available via the internet on the CMS website at 
https://www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps).
8. MDC 07 (Diseases and Disorders of the Hepatobiliary System and 
Pancreas): Laparoscopic Cholecystectomy with Common Bile Duct 
Exploration
    We received a request to review the MS-DRG assignment when 
procedure code 0FC94ZZ (Extirpation of matter from common bile duct, 
percutaneous endoscopic approach) that describes a common bile duct 
exploration with gallstone removal procedure using a laparoscopic 
approach, is reported with a laparoscopic cholecystectomy. The 
procedure codes describing a laparoscopic cholecystectomy are
[GRAPHIC] [TIFF OMITTED] TP10MY22.042

    According to the requestor, when a laparoscopic cholecystectomy is 
reported with any one of the listed procedure codes with a common bile 
duct exploration and gallstone removal procedure that is performed 
laparoscopically and reported with procedure code 0FC94ZZ, the 
resulting assignment is MS-DRGs 417, 418 and 419 (Laparoscopic 
Cholecystectomy without C.D.E. with MCC, with CC, and without CC/MCC, 
respectively). This MS-DRG assignment does not recognize that a common 
bile duct exploration (C.D.E.) was performed. However, the requestor 
stated that when procedure code 0FC90ZZ (Extirpation of matter from 
common bile duct, open approach) that describes a common bile duct 
exploration with gallstone removal procedure using an open approach is 
reported with any one of the listed procedure codes describing a 
laparoscopic cholecystectomy, the resulting assignment is MS-DRGs 411, 
412, and 413 (Cholecystectomy with C.D.E. with MCC, with CC, and 
without CC/MCC, respectively). The requestor stated that this MS-DRG 
assignment appropriately recognizes that a common bile duct exploration 
was performed. The requestor questioned why only the common bile duct 
exploration with gallstone removal procedure performed using an open 
approach (code 0FC90ZZ) grouped appropriately when reported with the 
laparoscopic cholecystectomy.
    We reviewed procedure code 0FC94ZZ and found that it is currently 
designated as a non-O.R. procedure, therefore, the GROUPER logic does 
not recognize this procedure for purposes of MS-DRG assignment. We also 
note that MS-DRGs 411, 412, and 413 include cholecystectomy procedures 
performed by either an open or a percutaneous endoscopic (laparoscopic) 
approach. We refer the reader to the V39.1 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/MS-DRG-Classifications-and-Software for complete 
documentation of the GROUPER logic for MS-DRGs 411, 412, 413, 417, 418 
and 419.
    We analyzed claims data from the September 2021 update of the FY 
2021 MedPAR file for all cases in MS-DRGs 411, 412, 413, 417, 418, and 
419. Because the logic for MS-DRGs 411, 412, and 413 includes 
cholecystectomy

[[Page 28166]]

procedures performed by either an open or percutaneous endoscopic 
(laparoscopic) approach, we also analyzed the cases reported with each 
approach separately. The findings from our analysis are shown in the 
following tables.
[GRAPHIC] [TIFF OMITTED] TP10MY22.043

[GRAPHIC] [TIFF OMITTED] TP10MY22.044

[GRAPHIC] [TIFF OMITTED] TP10MY22.045

    In MS-DRG 411, we found a total of 116 cases with an average length 
of stay of 8.5 days and average costs of $29,332. Of those 116 cases, 
there were 56 cases reporting an open cholecystectomy, with an average 
length of stay of 10.7 days and average costs of $36,135 and 60 cases 
reporting a laparoscopic cholecystectomy, with an average length of 
stay of 6.5 days and average costs of $22,982. The data show that the 
cases reporting an open cholecystectomy have a longer average length of 
stay (10.7 days versus 6.5 days) and higher average costs ($36,135 
versus $22,982) compared to the cases reporting a laparoscopic 
cholecystectomy. The data also show that the cases reporting an open 
cholecystectomy have a longer average length of stay (10.7 days versus 
8.5 days) and higher average costs ($36,135 versus $29,332) compared to 
all the cases in MS-DRG 411. Similar findings are demonstrated for MS-
DRGs 412 and 413, where the data show that the cases reporting an open 
cholecystectomy have a longer average length of stay and higher average 
costs compared to the cases reporting a laparoscopic cholecystectomy, 
and also, when compared to all the cases in their respective MS-DRGs.
    We then analyzed claims data from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting procedure code 0FC94ZZ in MS-
DRGs 417, 418, and 419 to assess how often it was reported. The 
findings from our analysis are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.046


[[Page 28167]]


    We found a total of 231 cases across MS-DRGs 417, 418, and 419 with 
an average length of stay of 4.6 days and average costs of $15,348 
reporting procedure code 0FC94ZZ. In our review of the cases reporting 
a laparoscopic cholecystectomy across MS-DRGs 411, 412, and 413, we 
found a total of 178 cases with an average length of stay of 5.3 days 
and average costs of $18,206.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting procedure code 0FC94ZZ across 
all the MS-DRGs without another O.R. procedure reported, to assess the 
number of cases and which MS-DRGs procedure code 0FC94ZZ was found. The 
findings from our analysis are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.047

    The data analysis shows procedure code 0FC94ZZ was reported in a 
total of 32 cases across 7 MS-DRGs with an average length of stay of 
5.9 days and average costs of $16,087. While procedure code 0FC94ZZ is 
designated as non-O.R., we also analyzed the average length of stay and 
average costs of the cases found within each of the 7 MS-DRGs reporting 
procedure code 0FC94ZZ against all the cases in their respective MS-
DRGs, to determine if there was any indication that the performance of 
the procedure described by procedure code 0FC94ZZ may have had any 
impact. For instance, as shown in the table, for MS-DRG 438 we found 2 
cases reporting procedure code 0FC94ZZ with an average length of stay 
of 14 days and average costs of $26,092. In the September 2021 update 
of the FY 2021 MedPAR file, the total number of cases for MS-DRG 438 is 
10,240 with an average length of stay of 6.4 days and average costs of 
$13,341. The 2 cases reporting procedure code 0FC94ZZ have 
approximately twice the average length of stay (14 days versus 6.4 
days) and approximately twice the average costs ($26,092 versus 
$13,341) compared to all the cases for MS-DRG 438. In the absence of 
additional analysis, it is unknown if these differences can be 
attributed to other factors, such as the MCCs that were reported in 
these cases. Similar findings were found for MS-DRGs 441, 445, 446, and 
871. We will consider if further detailed analysis may be warranted for 
these cases.
    Our clinical advisors agreed that procedure code 0FC94ZZ describes 
a common bile duct exploration procedure with removal of a gallstone 
and should be added to the logic for case assignment to MS-DRGs 411, 
412, and 413 for clinical coherence with the other procedures that 
describe a common bile duct exploration. Therefore, for FY 2023, we are 
proposing to redesignate procedure code 0FC94ZZ from a non-O.R. 
procedure to an O.R. procedure and add it to the logic list for common 
bile duct exploration (CDE) in MS-DRGs 411, 412, and 413 
(Cholecystectomy with C.D.E. with MCC, with CC, and without CC/MCC, 
respectively) in MDC 07 to appropriately reflect when this procedure is 
performed and improve the clinical coherence of the patients assigned 
to these MS-DRGs.
    In addition, we note that MS-DRGs 414, 415, and 416 
(Cholecystectomy Except By Laparoscope without C.D.E. with MCC, with CC 
and without CC/MCC, respectively) also reflect cholecystectomy 
procedures, however, the logic is specifically defined for open 
cholecystectomy procedures without a common bile duct exploration 
procedure performed. Since MS-DRGs 411, 412, and 413 reflect cases 
where an open or laparoscopic cholecystectomy is performed with a 
common bile duct exploration procedure, MS-DRGs 414, 415, and 416 
reflect cases where only an open cholecystectomy is performed without a 
common bile duct exploration procedure, and MS-DRGs 417, 418, and 419 
reflect cases where only a laparoscopic cholecystectomy is performed 
without a common bile duct exploration procedure, we believe there may 
be an opportunity to further refine these MS-DRGs once additional 
analysis is performed for consideration in future rulemaking. For 
example, we could consider proposing to restructure these 
cholecystectomy MS-DRGs to reflect the following two concepts, if 
supported by the data, and relatedly, to determine if severity levels 
are also supported according to the existing criteria.
     Open Cholecystectomy with or without C.D.E.; and
     Laparoscopic Cholecystectomy with or without C.D.E.
    We are interested in receiving feedback from the public on this and 
any alternative recommendations or options to further refine these MS-
DRGs by October 20, 2022 for future consideration. Feedback and other 
suggestions should be directed to the new electronic intake system, 
Medicare Electronic Application Request Information SystemTM 
(MEARISTM), discussed in section II.D.1.b. of the preamble 
of this proposed rule at https://mearis.cms.gov/public/home.
9. MDC 10 (Diseases and Disorders of the Endocrine System): Eladocagene 
Exuparvovec Gene Therapy
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44895), we finalized 
the redesignation of code XW0Q316 (Introduction of eladocagene 
exuparvovec into cranial cavity and brain, percutaneous approach, new 
technology group 6) from a Non-O.R. procedure to 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,

[[Page 28168]]

and 989 (Non-Extensive O.R. Procedure Unrelated to Principal Diagnosis 
with MCC, with CC and without MCC/CC, respectively). We received a 
request to reconsider this assignment for FY 2023. According to the 
requestor, the clinical characteristics and costs of cases assigned to 
MS-DRGs 628 through 630 are significantly different from those 
associated with the administration of eladocagene exuparvovec. The 
requestor performed its own analysis, using deep brain stimulation for 
epilepsy and selective dorsal rhizotomy for cerebral palsy as proxies, 
and stated that based on its findings for the initial cost analysis and 
clinical comparison, that MS-DRG 23 (Craniotomy with Major Device 
Implant or Acute Complex CNS Principal Diagnosis with MCC or 
Chemotherapy Implant or Epilepsy with Neurostimulator), MS-DRG 24 
(Craniotomy with Major Device Implant or Acute Complex CNS Principal 
Diagnosis without MCC) and MS-DRGs 25, 26, and 27 (Craniotomy and 
Endovascular Intracranial Procedures with MCC, with CC, and without CC/
MCC, respectively) may be more appropriate. However, the requestor also 
stated that while the clinical aspects of eladocagene exuparvovec cases 
are similar to those of MS-DRGs 23 through 27, the costs are much 
higher and neither MS-DRGs 628, 629, 630 or MS-DRGs 23 through 27 are 
appropriate. Therefore, the requestor stated its belief that assigning 
eladocagene exuparvovec cases to new MS-DRGs is warranted.
    Eladocagene exuparvovec is a gene therapy for the treatment of 
patients with aromatic L-amino acid decarboxylase (AADC) deficiency, a 
rare genetic and fatal condition identified with ICD-10-CM diagnosis 
code E70.81. Patients with AADC deficiency are generally observed to 
have onset of symptoms in the first year of life, most notably 
hypotonia (muscle weakness), followed by movement disorders, 
developmental delay and autonomic signs, such as hyperhidrosis (profuse 
sweating unrelated to heat or exercise). It is understood that the 
long-term implications of this disease are severe, resulting in severe 
deficits and limitations in life expectancy. Because the condition is 
primarily diagnosed in the pediatric population, we would not expect to 
find any meaningful volume of cases in the MedPAR data.
    We analyzed claims data from the September 2021 update of the FY 
2021 MedPAR file for MS-DRGs 628, 629, and 630 for cases reporting 
procedure code XW0Q316 and did not find any cases. We then extended our 
analysis to all MS-DRGs and found 1 case reporting the administration 
of this therapy in MS-DRG 829 (Myeloproliferative Disorders or Poorly 
Differentiated Neoplasms with Other Procedures with CC/MCC) with an 
average length of stay of 2 days and average costs of $1,544. As we 
have discussed elsewhere we generally prefer not to create a new MS-DRG 
unless it would include a substantial number of cases. However, as 
discussed in section II.D.19.b. of the preamble of this proposed rule, 
we are seeking public comment on possible mechanisms through which we 
can address rare diseases and conditions that are represented by low 
volumes in our claims data. We believe this topic, relating to the 
administration of treatment to address the rare genetic and fatal 
condition of AADC deficiency, is appropriately aligned with and should 
be considered as part of that effort. Therefore, we are maintaining the 
current structure for MS-DRGs 628, 629, and 630 for FY 2023, but will 
continue to consider this request in connection with our evaluation of 
possible mechanisms to address rare diseases and conditions in the MS-
DRG structure, as discussed later in this rule.
10. MDC 15 Newborns and Other Neonates With Conditions Originating in 
Perinatal Period: MS-DRG 795 Normal Newborn
    We received a request to review the MS-DRG assignment of newborn 
encounters with diagnosis codes describing contact with and (suspected) 
exposure to COVID-19 when the condition is ruled out after clinical 
evaluation and negative workup. The requestor expressed concern that a 
newborn encounter coded with a principal diagnosis code from category 
Z38 (Liveborn infants according to place of birth and type of 
delivery), followed by codes Z05.1 (Observation and evaluation of 
newborn for suspected infectious condition ruled out) and Z20.822 
(Contact with and (suspected) exposure to COVID-19) is assigned to MS-
DRG 794 (Neonate with Other Significant Problems). The requestor stated 
that this assignment appears to be in error and that the assignment 
should instead be to MS-DRG 795 (Normal Newborn).
    Our analysis of this grouping issue confirmed that, when a 
principal diagnosis code from category Z38 (Liveborn infants according 
to place of birth and type of delivery), followed by codes Z05.1 
(Observation and evaluation of newborn for suspected infectious 
condition ruled out) and Z20.822 (Contact with and (suspected) exposure 
to COVID-19), the case is assigned to MS-DRG 794.
    As we examined the GROUPER logic that would determine an assignment 
of cases to MS-DRG 795, we note the ``only secondary diagnosis'' list 
under MS-DRG 795 includes the following five ICD-10-CM diagnosis codes 
from ICD-10-CM category Z20. We refer the reader to the ICD-10 MS-DRG 
Version 39.1 Definitions Manual (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 the MS-DRG 795.
[GRAPHIC] [TIFF OMITTED] TP10MY22.048

    In reviewing the ICD-10-CM diagnosis code classification and the 
GROUPER logic list, we note that the 13 ICD-10-CM diagnosis codes, also 
from category Z20, listed in the following table were inadvertently 
omitted from the ``only secondary diagnosis'' list under MS-DRG 795.

[[Page 28169]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.049

    We reviewed section I.C.21.c.1 of the 2022 ICD-10-CM Official 
Guidelines for Coding and Reporting which state ``category Z20 
indicates contact with, and suspected exposure to, communicable 
diseases. These codes are for patients who are suspected to have been 
exposed to a disease by close personal contact with an infected 
individual or are in an area where a disease is epidemic . . . Contact/
exposure codes may be used as a first-listed code to explain an 
encounter for testing, or, more commonly, as a secondary code to 
identify a potential risk.'' Per the Excludes1 note at category Z20, 
when applicable, diagnoses of current infectious or parasitic disease 
are coded instead of codes from category Z20.
    Our clinical advisors reviewed this issue and agree that patients 
exposed to communicable diseases that are worked up or treated 
prophylactically or both, and for whom those conditions are later 
determined after study to not be present, are distinct from patients 
with identified signs or symptoms of a suspected problem or diagnosed 
with having that communicable disease. Our clinical advisors supported 
adding the 13 diagnosis codes listed previously to the logic of MS-DRG 
795 for clinical consistency with the five other diagnosis codes 
describing contact with, and suspected exposure to, communicable 
diseases currently assigned to the ``only secondary diagnosis'' list 
under MS-DRG 795.
    After review of the coding guidelines and conventions, and 
discussion with our clinical advisors, we agree with the requestor that 
in these circumstances, these encounters should not map to MS-DRG 794 
(Neonate with Other Significant Problems) and should instead be 
assigned to MS-DRG 795 (Normal Newborn). Therefore, we are proposing to 
add the 13 diagnosis codes listed previously that describe contact with 
and (suspected) exposure to communicable diseases to the ``only 
secondary diagnosis'' list under MS-DRG 795 (Normal Newborn). Under 
this proposal, cases with a principal diagnosis described by an ICD-10-
CM code from category Z38 (Liveborn infants according to place of birth 
and type of delivery), following by codes Z05.1 (Observation and 
evaluation of newborn for suspected infectious condition ruled out) and 
Z20.822 (Contact with and (suspected) exposure to COVID-19) will be 
assigned to MS-DRG 795.
    As we examined the GROUPER logic that would determine an assignment 
of cases to MS-DRGs in MDC 15, we noted the logic for MS-DRG 790 
(Extreme Immaturity or Respiratory Distress Syndrome Neonate) includes 
ICD-10-CM diagnosis codes that describe extremely low birth weight 
newborn, extreme immaturity of newborn and respiratory distress 
syndrome of newborn. We refer the reader to the ICD-10 MS-DRG Version 
39.1 Definitions Manual (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 790. During our 
review of the diagnosis codes assigned to these MS-DRGs, we identified 
three diagnosis codes that do not exist in the logic for MS-DRG 790. 
The three diagnosis codes and their current MS-DRG assignments are 
listed in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.050

    Our clinical advisors reviewed this grouping issue and noted that 
while virtually every neonate under 1000 grams, which is the definition 
of extremely low birth weight (ELBW), will have a weight documented 
somewhere

[[Page 28170]]

in the medical record, in the rare instance that it is not, if the 
diagnosis documented by the provider is ``ELBW'' the neonate would be 
in a higher risk category. Our clinical advisors also note that whereas 
weight is measured with high precision, gestational age is more 
complicated. With the exception of in vitro fertilization, gestational 
age is an estimate. Our clinical advisors state similar to 
documentation of ``ELBW'', if the diagnosis documented by the provider 
is ``extreme immaturity of newborn'' the neonate would be in a higher 
risk category. These diagnoses describe conditions that require 
advanced care and resources similar to other conditions already 
assigned to the logic of MS-DRG 790 even in cases where the birth 
weight, or weeks of gestation, are unspecified.
    For clinical consistency, our clinical advisors supported the 
addition of these three diagnosis codes to the GROUPER logic list for 
MS-DRG 790. Therefore, we are proposing to reassign ICD-10-CM diagnosis 
codes P07.00, P07.20 and P07.26 to MS-DRG 790, effective October 1, 
2022 for FY 2023.
11. Review of Procedure Codes in MS-DRGs 981 Through 983 and 987 
Through 989
    We annually conduct a review of procedures producing assignment to 
MS-DRGs 981 through 983 (Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) or MS-DRGs 987 through 989 (Non-Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) on the basis of volume, by procedure, to see if it would 
be appropriate to move cases reporting these procedure codes out of 
these MS-DRGs into one of the surgical MS-DRGs for the MDC into which 
the principal diagnosis falls. The data are arrayed in two ways for 
comparison purposes. We look at a frequency count of each major 
operative procedure code. We also compare procedures across MDCs by 
volume of procedure codes within each MDC. We use this information to 
determine which procedure codes and diagnosis codes to examine.
    We identify those procedures occurring in conjunction with certain 
principal diagnoses with sufficient frequency to justify adding them to 
one of the surgical MS-DRGs for the MDC in which the diagnosis falls. 
We also consider whether it would be more appropriate to move the 
principal diagnosis codes into the MDC to which the procedure is 
currently assigned.
    In addition to this internal review, we also consider requests that 
we receive to examine cases found to group to MS-DRGs 981 through 983 
or MS-DRGs 987 through 989 to determine if it would be appropriate to 
add procedure codes to one of the surgical MS-DRGs for the MDC into 
which the principal diagnosis falls or to move the principal diagnosis 
to the surgical MS-DRGs to which the procedure codes are assigned.
    Based on the results of our review of the claims data from the 
September 2021 update of the FY 2021 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.
a. Embolization of Portal and Hepatic Veins
    We received a request to reassign cases with a principal diagnosis 
from MDC 07 (Diseases and Disorders of the Hepatobiliary System and 
Pancreas) when reported with procedures involving the embolization of a 
hepatic or portal vein 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 423, 424, and 425 (Other 
Hepatobiliary or Pancreas Procedures with MCC, with CC, and without CC/
MCC, respectively) in MDC 07.
    In ICD-10-PCS, the root operation selected to code embolization 
procedures is dependent on the objective of the procedure. If the 
objective of an embolization procedure is to completely close a vessel, 
the root operation Occlusion is coded. ICD-10-PCS procedure codes 
06L43DZ (Occlusion of hepatic vein with intraluminal device, 
percutaneous approach) or 06L83DZ (Occlusion of portal vein with 
intraluminal device, percutaneous approach) may be reported to describe 
embolization procedures to completely close off a hepatic or portal 
vein with an intraluminal device. If the objective of an embolization 
procedure is to narrow the lumen of a vessel, the root operation 
Restriction is coded. ICD-10-PCS procedure codes 06V43DZ (Restriction 
of hepatic vein with intraluminal device, percutaneous approach) or 
06V83DZ (Restriction of portal vein with intraluminal device, 
percutaneous approach) may be reported to describe embolization 
procedures to narrow or partially occlude a hepatic or portal vein with 
an intraluminal device.
    These four ICD-10-PCS procedure codes, as well as their MDC 
assignments, are listed in the table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.051

    Our analysis of this grouping issue confirmed that when a procedure 
code describing the percutaneous occlusion or restriction of the 
hepatic or portal vein with intraluminal device is reported with a 
principal diagnosis from MDC 07, these cases group to MS-DRGs 981, 982, 
and 983 (Extensive O.R. Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively). 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 an MS-DRG assignment to a surgical class referred to as 
``unrelated operating room procedures''.
    To understand the resource use for the subset of cases reporting 
procedure codes 06L43DZ, 06L83DZ, 06V43DZ or 06V83DZ with a principal 
diagnosis from MDC 07 that are currently

[[Page 28171]]

grouping to MS-DRGs 981, 982, and 983, we examined claims data from the 
September 2021 update of the FY 2021 MedPAR file for the average length 
of stay and average costs for these cases. Our findings are shown in 
the following table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.052

    We also examined the data for cases in MS-DRGs 423, 424, and 425, 
and our findings are shown in the following table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.053

    While the claims analysis based on the September 2021 update of the 
FY 2021 MedPAR file identified only 34 cases for which these procedures 
were reported with a principal diagnosis from MDC 07 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 423, 424, and 
425, given the clinical indications for hepatic or portal vein 
embolization procedures, such as to induce regrowth on one side of the 
liver in advance of a planned hepatic resection on the other side, we 
believe it is clinically appropriate to add these procedure codes 
describing the percutaneous occlusion or restriction of the hepatic or 
portal vein with intraluminal device to MS-DRGs 423, 424, and 425 in 
MDC 07. Our clinical advisors state that these procedures are clearly 
related to the principal diagnoses as they are procedures performed for 
hepatobiliary diagnoses, namely hepatocellular carcinoma and liver 
metastases, so it is clinically appropriate for the procedures to group 
to the same MDC as the principal diagnoses. Our clinical advisors also 
stated the procedures describing the percutaneous occlusion or 
restriction of the hepatic or portal vein with intraluminal device are 
consistent with the existing procedure codes included in the logic for 
case assignment to MS-DRGs 423, 424, and 425.
    Therefore, we are proposing to add ICD-10-PCS procedure codes 
06L43DZ, 06L83DZ, 06V43DZ and 06V83DZ to MDC 07 in MS-DRGs 423, 424 and 
425. Under this proposal, cases reporting procedure codes 06L43DZ, 
06L83DZ, 06V43DZ or 06V83DZ in conjunction with a principal diagnosis 
code from MDC 07 would group to MS-DRGs 423, 424 and 425.
b. Percutaneous Excision of Hip Muscle
    We received a request to examine cases reporting a procedure 
describing percutaneous biopsies of muscle. The requestor stated that 
when procedures describing the percutaneous excision of the left hip 
muscle for diagnostic purposes are reported with a principal diagnosis 
from MDC 06 (Diseases and Disorders of the Digestive System) such as 
K68.12 (Psoas muscle abscess), the cases are assigned to MS-DRGs 981, 
982, and 983 (Extensive O.R. Procedure Unrelated to Principal Diagnosis 
with MCC, with CC, and without CC/MCC, respectively). However, when 
procedures describing the percutaneous excision of the retroperitoneum 
for diagnostic purposes are reported with the same principal diagnosis 
of psoas muscle abscess, the cases are assigned to medical MS-DRGs 371, 
372, and 373 (Major Gastrointestinal Disorders and Peritoneal 
Infections with MCC, with CC, and without CC/MCC, respectively).

[[Page 28172]]

The requestor stated the cases at their facility with a principal 
diagnosis of psoas muscle abscess when reported with a procedure 
describing a biopsy of the left muscle had an average length of stay 
comparable to other cases assigned to MS-DRGs 371, 372, and 373. The 
requestor provided ICD-10-PCS procedure code 0KBP3ZX (Excision of left 
hip muscle, percutaneous approach, diagnostic) in its request and asked 
that CMS evaluate the assignment of procedure code 0KBP3ZX because 
procedures describing the percutaneous excision of the left hip muscle 
for diagnostic purposes appear to be related to a diagnosis of psoas 
muscle abscess.
    To analyze this request, we first identified the similar ICD-10-PCS 
procedure codes that also describe the excision of hip muscle. 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. The four ICD-10-PCS procedure codes that describe the 
excision of hip muscle, as well as their MDC assignments, are listed in 
the table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.054

    Our analysis of this grouping issue confirmed that when procedure 
codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX or 0KBP3ZZ are reported with a 
principal diagnosis from MDC 06, such as K68.12, these cases group to 
MS-DRGs 981, 982, and 983. As noted in the previous discussion, 
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 the claims data from the September 2021 update of the 
FY 2021 MedPAR file to identify cases reporting procedure codes 
0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, or 0KBP3ZZ with a principal diagnosis of 
K68.12 (Psoas muscle abscess) that are currently grouping to MS-DRGs 
981, 982, and 983. Our findings are shown in this table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.055

    As shown, in our analyses of the claims data for MS-DRGs 981 
through 983, we found a total of seven cases reporting procedures 
describing excision of hip muscle with a principal diagnosis of K68.12 
in the September 2021 update of the FY 2021 MedPAR file.
    To further evaluate this issue, we examined claims data from the 
September 2021 update of the FY 2021 MedPAR file for cases reporting 
any one of the four procedure codes (0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, or 
0KBP3ZZ) in MS-DRGs 981 through 983 with a principal diagnosis from MDC 
06. Our findings are shown in the following table.

[[Page 28173]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.056

    As shown, in our analyses of the claims data for MS-DRGs 981 
through 983, we found a total of 14 cases reporting procedures 
describing excision of hip muscle with a principal diagnosis from MDC 
06 in the September 2021 update of the FY 2021 MedPAR file.
    We also examined the data for cases in MS-DRGs 371, 372, and 373, 
and our findings are shown in the following table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.057

    We reviewed these procedures and our clinical advisors state that 
procedures that describe the percutaneous excision of hip muscle are 
not surgical in nature and would not be the main reason for inpatient 
hospitalization or be considered the principal driver of resource 
expenditure. Our clinical advisors state although a correlation cannot 
usually be made between procedures performed in general anatomic 
regions, such as the retroperitoneum, and procedures performed in 
specific body parts, such as muscle, because procedures coded with 
general anatomic region body parts represent a broader range of 
procedures that cannot be coded to a specific body part, they agree 
that in this instance procedures that describe the percutaneous 
excision of hip muscle should have the same designation as the ICD-10-
PCS procedure codes that describe the percutaneous excision of the 
retroperitoneum that are currently designated as non-O.R. procedures.
    Our clinical advisors reviewed this analysis and believe that, for 
clinical coherence and consistency, it would be appropriate to 
designate ICD-10-PCS codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ as 
non-O.R. procedures.
    Therefore, we are proposing to remove codes 0KBN3ZX, 0KBN3ZZ, 
0KBP3ZX, and 0KBP3ZZ from the FY 2023 ICD-10 MS-DRGs Version 40 
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. Cases 
reporting procedure codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ in 
conjunction with a principal diagnosis code from MDC 06 would group to 
MS-DRGs 371, 372, and 373.
    In addition, we also conduct an internal review and 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 September 2021 update of the FY 2021 MedPAR file we did 
not identify any cases for reassignment. We also did not receive any 
requests suggesting reassignment. Therefore, for FY 2023 we are not 
proposing to move any cases reporting procedure codes from MS-DRGs 981 
through 983 to MS-DRGs 987 through 989 or vice versa.
12. 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

[[Page 28174]]

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.14. of the preamble of this proposed rule, we 
are making Table 6B.--New Procedure Codes--FY 2023 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 39.1 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 multiyear 
project during which we will also review the process for determining 
when a procedure is considered an operating room procedure. For 
example, we may restructure the current O.R. and non O.R. designations 
for procedures by leveraging the detail that is now available in the 
ICD-10 claims data. We refer readers to the discussion regarding the 
designation of procedure codes in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38066) where we stated that the determination of when a 
procedure code should be designated as an O.R. procedure has become a 
much more complex task. This is, in part, due to the number of various 
approaches available in the ICD-10-PCS classification, as well as 
changes in medical practice. While we have typically evaluated 
procedures on the basis of whether or not they would be performed in an 
operating room, we believe that there may be other factors to consider 
with regard to resource utilization, particularly with the 
implementation of ICD-10.
    We discussed in the FY 2020 IPPS/LTCH PPS proposed rule that as a 
result of this planned review and potential restructuring, procedures 
that are currently designated as O.R. procedures may no longer warrant 
that designation, and conversely, procedures that are currently 
designated as non-O.R. procedures may warrant an O.R. type of 
designation. We intend to consider the resources used and how a 
procedure should affect the MS-DRG assignment. We may also consider the 
effect of specific surgical approaches to evaluate whether to subdivide 
specific MS DRGs based on a specific surgical approach. We plan to 
utilize our available MedPAR claims data as a basis for this review and 
the input of our clinical advisors. As part of this comprehensive 
review of the procedure codes, we also intend to evaluate the MS-DRG 
assignment of the procedures and the current surgical hierarchy because 
both of these factor into the process of refining the ICD-10 MS-DRGs to 
better recognize complexity of service and resource utilization.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58540 through 
58541), we provided a summary of the comments we had received in 
response to our request for feedback on what factors or criteria to 
consider in determining whether a procedure is designated as an O.R. 
procedure in the ICD-10-PCS classification system for future 
consideration. In consideration of the ongoing PHE, we continue to 
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.
    We received the following requests regarding changing the 
designation of specific ICD-10-PCS procedure codes from non-O.R. to 
O.R. procedures. We summarize these requests in this section of this 
rule and address why we are not considering a change to the designation 
of these codes at this time.
     We received a request to change the designation of all 
ICD-10-PCS procedure codes that describe diagnostic and therapeutic 
percutaneous endoscopic procedures performed on thoracic and abdominal 
organs, from non-O.R. to O.R. According to the requestor, thoracoscopic 
and laparoscopic procedures are always performed in the operating room 
under general anesthesia. We believe additional time is needed to fully 
examine the numerous ICD-10-PCS codes in the classification that 
describe diagnostic and therapeutic percutaneous endoscopic procedures 
performed on thoracic and abdominal organs as there are over 19,000 
ICD-10-PCS codes in the classification that describe procedures 
performed using a percutaneous endoscopic approach. As we have signaled 
in prior rulemaking, the designation of an O.R. procedure encompasses 
more than the physical location of the hospital in which the procedure 
may be performed. We also examine if, and in what way, the performance 
of the procedure affects the resource expenditure in those admissions 
in the inpatient setting, in addition to examining other clinical 
factors such as procedure complexity, and need for anesthesia 
administration as well as other types of sedation. We will continue to 
evaluate the ICD-10-PCS procedure codes that describe diagnostic and 
therapeutic percutaneous endoscopic procedures performed on

[[Page 28175]]

thoracic and abdominal organs as we conduct a comprehensive, systematic 
review of the ICD-10-PCS procedure codes.
     In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44892 
through 44895), CMS finalized the proposal to remove the 22 codes that 
describe the open drainage of subcutaneous tissue and fascia listed in 
the following table from the ICD-10 MS-DRGs Version 39.1 Definitions 
Manual in Appendix E-Operating Room Procedures and Procedure Code/MS-
DRG Index as O.R. procedures. Under this finalization, these procedures 
no longer impact MS-DRG assignment.
[GRAPHIC] [TIFF OMITTED] TP10MY22.058

    In the FY 2022 final rule, we noted that the designation of the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia as O.R. procedures was a result of a replication error in 
transitioning to ICD-10. This replication error led to ICD-10-PCS 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia being listed as comparable translations for ICD-9-CM code 
83.09 (Other incision of soft tissue), which was designated as a non-
extensive O.R. procedure under the ICD-9-CM MS- DRGs Version 32, as 
opposed to being listed as comparable translations for ICD-9-CM code 
86.04 (Other incision with drainage of skin and subcutaneous tissue) 
which was designated as a non- O.R. procedure under the ICD-9-CM MS-
DRGs Version 32. We stated in the FY 2022 final rule that designating 
the 22 procedure codes that describe the open drainage of subcutaneous 
tissue and fascia as non-O.R. procedures would result in a more 
accurate replication of the comparable procedure, under the ICD-9-CM 
MS-DRGs Version 32 which was 86.04, not 83.09 and is more aligned with 
current shifts in treatment practices.
    For this FY 2023 IPPS/LTCH PPS proposed rule, we received a request 
to re-examine this change in designation. According to the requestor, 
open procedures for the drainage of subcutaneous tissue and fascia are 
indeed typically performed in the operating room under general 
anesthesia and involve making incisions through the subcutaneous tissue 
into fascia for therapeutic drainage, breaking up of loculations, and 
irrigation. While our clinical advisors do not disagree with the 
requestor that these procedures can involve making incisions through 
the subcutaneous tissue into fascia, they continue to state procedures 
describing the open drainage of subcutaneous tissue and fascia can now 
be safely performed in the outpatient setting and when performed during 
a hospitalization, they are typically performed in conjunction with 
another O.R. procedure. For the reasons discussed in the FY 2022 final 
rule, our clinical advisors state that the non-O.R. designation of the 
22 procedure codes that describe the open drainage of subcutaneous 
tissue and fascia as finalized in the FY 2022 final rule better 
reflects the associated technical complexity and hospital resource use 
of these procedures.
13. Proposed Changes to the MS-DRG Diagnosis Codes for FY 2023
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

[[Page 28176]]

that are considered CCs. Historically, we developed this list using 
physician panels that classified each diagnosis code based on whether 
the diagnosis, when present as a secondary condition, would be 
considered a substantial complication or comorbidity. A substantial 
complication or comorbidity was defined as a condition that, because of 
its presence with a specific principal diagnosis, would cause an 
increase in the length-of-stay by at least 1 day in at least 75 percent 
of the patients. However, depending on the principal diagnosis of the 
patient, some diagnoses on the basic list of complications and 
comorbidities may be excluded if they are closely related to the 
principal diagnosis. In FY 2008, we evaluated each diagnosis code to 
determine its impact on resource use and to determine the most 
appropriate CC subclassification (NonCC, CC, or MCC) assignment. We 
refer readers to sections II.D.2. and 3. Of the preamble of the FY 2008 
IPPS final rule with comment period for a discussion of the refinement 
of CCs in relation to the MS-DRGs we adopted for FY 2008 (72 FR 47152 
through 47171).
b. Overview of Comprehensive CC/MCC Analysis
    In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described 
our process for establishing three different levels of CC severity into 
which we would subdivide the diagnosis codes. The categorization of 
diagnoses as a MCC, a CC, or a NonCC was accomplished using an 
iterative approach in which each diagnosis was evaluated to determine 
the extent to which its presence as a secondary diagnosis resulted in 
increased hospital resource use. We refer readers to the FY 2008 IPPS/
LTCH PPS final rule (72 FR 47159) for a complete discussion of our 
approach. Since the comprehensive analysis was completed for FY 2008, 
we have evaluated diagnosis codes individually when assigning severity 
levels to new codes and when receiving requests to change the severity 
level of specific diagnosis codes.
    We noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235 
through 19246) that with the transition to ICD-10-CM and the 
significant changes that have occurred to diagnosis codes since the FY 
2008 review, we believed it was necessary to conduct a comprehensive 
analysis once again. Based on this analysis, we proposed changes to the 
severity level designations for 1,492 ICD-10-CM diagnosis codes and 
invited public comments on those proposals. As summarized in the FY 
2020 IPPS/LTCH PPS final rule, many commenters expressed concern with 
the proposed severity level designation changes overall and recommended 
that CMS conduct further analysis prior to finalizing any proposals. 
After careful consideration of the public comments we received, as 
discussed further in the FY 2020 final rule, we generally did not 
finalize our proposed changes to the severity designations for the ICD-
10-CM diagnosis codes, other than the changes to the severity level 
designations for the diagnosis codes in category Z16- (Resistance to 
antimicrobial drugs) from a NonCC to a CC. We stated that postponing 
adoption of the proposed comprehensive changes in the severity level 
designations would allow further opportunity to provide additional 
background to the public on the methodology utilized and clinical 
rationale applied across diagnostic categories to assist the public in 
its review. We refer readers to the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42150 through 42152) for a complete discussion of our response 
to public comments regarding the proposed severity level designation 
changes for FY 2020.
    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/Downloads/10082019ListingSessionTrasncriptandQandAsandAudioFile.zip 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 mathematical data generated using 
claims from the FY 2018 MedPAR file 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.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58550 through 
58554), we discussed our 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 or management of care or both.
     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.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25175 through 
25180), as another interval step in our comprehensive review of the 
severity designations of ICD-10-CM diagnosis codes, we requested public 
comments on a potential change to the severity level designations for 
``unspecified'' ICD-10-CM diagnosis codes that we were considering 
adopting for FY 2022. Specifically, we noted we were considering 
changing the severity level designation of ``unspecified'' diagnosis 
codes to a NonCC where there are other codes available in that code 
subcategory that further specify the anatomic site. As summarized in 
the FY 2022 IPPS/LTCH PPS final rule, many commenters expressed concern 
with the potential severity level designation changes overall and 
recommended that CMS delay any possible change to the designation of 
these codes to give hospitals and their physicians time to prepare. 
After careful consideration of the public comments we received, we 
maintained the severity level designation of the ``unspecified'' 
diagnosis codes currently designated as a CC or MCC where there are 
other codes available in that code subcategory that further specify the 
anatomic site for

[[Page 28177]]

FY 2022. We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 
FR 44916 through 44926) for a complete discussion of our response to 
public comments regarding the potential severity level designation 
changes. Instead, for FY 2022, we finalized a new Medicare Code Editor 
(MCE) code edit for ``unspecified'' codes, effective with discharges on 
and after April 1, 2022. We stated we believe finalizing this new edit 
would provide additional time for providers to be educated while not 
affecting the payment the provider is eligible to receive. We refer the 
reader to section II.D.14.e. of the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 44940 through 44943) for the complete discussion.
    As this new edit will be effective beginning with discharges on and 
after April 1, 2022, our clinical advisors believe at this time, it is 
appropriate to not propose to change the designation of any ICD-10-CM 
diagnosis codes, including the unspecified codes that are subject to 
the ``Unspecified Code'' edit, as we continue our comprehensive CC/MCC 
analysis to allow stakeholders the time needed to become acclimated to 
the new edit.
    We continue to solicit feedback regarding the guiding principles, 
as well as other possible ways we can incorporate meaningful indicators 
of clinical severity. We have made available on the CMS website updated 
impact on resource use files so that the public can review the 
mathematical data for the impact on resource use generated using claims 
from the FY 2019 MedPAR file, the FY 2020 MedPAR file and the FY 2021 
MedPAR files. The link to these files is posted on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software. 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. We also continue to be interested 
in receiving feedback on how we might otherwise foster the 
documentation and reporting of the most specific diagnosis codes 
supported by the available medical record documentation and clinical 
knowledge of the patient's health condition to more accurately reflect 
each health care encounter and improve the reliability and validity of 
the coded data.
    For new diagnosis codes approved for FY 2023, 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 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 section II.D.14 of this proposed rule for the discussion of 
the proposed changes to the ICD-10-CM and ICD-10-PCS coding systems for 
FY 2023.
c. Requested Changes to Severity Levels
    For this FY 2023 IPPS/LTCH PPS proposed rule, we received several 
requests to change the severity level designations of specific ICD-10-
CM diagnosis codes, including a request to analyze a subset of the 
social determinants of health (SDOH) 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. However, we refer 
the reader to section II.D.13.d for further discussion related to the 
diagnosis codes describing social determinants of health. 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.
d. Request for Information on Social Determinants of Health Diagnosis 
Codes
    For this FY 2023 IPPS/LTCH PPS proposed rule, we are soliciting 
public comments on how the reporting of diagnosis codes in categories 
Z55-Z65 may improve our ability to recognize severity of illness, 
complexity of illness, and/or utilization of resources under the MS-
DRGs as described further in this section. Consistent with the 
Administration's goal of advancing health equity for all, including 
members of historically underserved and under-resourced communities, as 
described in the President's January 20, 2021 Executive Order 13985 on 
``Advancing Racial Equity and Support for Underserved Communities 
Through the Federal Government,'' \10\ we are also interested in 
receiving feedback on how we might otherwise foster the documentation 
and reporting of the diagnosis codes describing social and economic 
circumstances to more accurately reflect each health care encounter and 
improve the reliability and validity of the coded data including in 
support of efforts to advance health equity.
---------------------------------------------------------------------------

    \10\ 86 FR 7009 (January 25, 2021). Available at: 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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    Social determinants of health (SDOH) are the conditions in the 
environments where people are born, live, learn, work, play, worship, 
and age that affect a wide range of health, functioning, and quality-
of-life outcomes and risks.\11\ These circumstances or determinants 
influence an individual's health status and can contribute to wide 
health disparities and inequities. While SDOH do not describe current 
illnesses or injuries at the individual level, they are widely 
recognized as important potential predictors of risk for developing 
medical conditions like heart disease, diabetes, and obesity. In ICD-
10-CM, the Z codes found in Chapter 21 represent reasons for 
encounters, and are provided for occasions when circumstances other 
than a disease, injury or external cause classifiable to categories 
A00-Y89 are recorded as `diagnoses' or `problems'. The subset of Z 
codes that describe the social determinants of health are found in 
categories Z55-Z65 (Persons with potential health hazards related to 
socioeconomic and psychosocial circumstances). These codes describe a 
range of issues related--but not limited--to education and literacy, 
employment, housing, ability to obtain adequate amounts of food or safe 
drinking water, and occupational exposure to toxic agents, dust, or 
radiation. Effective October 1, 2021, the Centers for Disease Control 
and Prevention (CDC) National Center for Health Statistics (NCHS) added 
11 new diagnosis codes describing SDOH to provide additional 
information regarding determinants such as housing, food insecurity, 
and transportation. In addition, section I.B.14 of the FY 2022 ICD-10-
CM Official Guidelines for Coding and Reporting was updated to provide 
clarification of the term ``clinician'' in reporting codes related to 
social determinants of health and clarified the documentation that can 
be

[[Page 28178]]

utilized to assign SDOH codes when included in the official medical 
record. In this context, ``clinicians'' other than the patient's 
provider refer to ``healthcare professionals permitted, based on 
regulatory or accreditation requirements or internal hospital policies, 
to document in a patient's official medical record.'' \12\
---------------------------------------------------------------------------

    \11\ Available at: https://health.gov/healthypeople/objectives-and-data/social-determinants-health.
    \12\ Available at: https://ftp.cdc.gov/pub/Health_Statistics/NCHS/Publications/ICD10CM/2022/10cmguidelines-FY2022-April%201%20update%202-3-22.pdf.
---------------------------------------------------------------------------

    Reporting SDOH Z codes in inpatient claims data could enhance 
quality improvement activities, track factors that influence people's 
health, and provide further insight into existing health inequities. 
13 14 15 More routine collection of SDOH Z codes could also 
likely improve coordination within hospitals to utilize the data across 
their clinical care and discharge planning teams, including with post-
acute partners. CMS has heard from stakeholders about a number of 
reasons for why there may be less routine documentation and reporting 
of SDOH in the inpatient setting. First, Z codes are not required to be 
reported by inpatient hospitals and generally do not affect MS-DRG 
assignment. Rather, these codes are currently reported voluntarily by 
providers when and if supported in the medical record documentation. As 
such, consistent protocols may not be in place for documenting and 
reporting. Second, many of the circumstances captured through SDOH Z 
codes are dependent on the willingness of patients to discuss personal 
social, economic, or environmental conditions. Providers may or may not 
be able to reliably document certain circumstances,\16\ as a result, in 
the medical records. There are also questions of how bias can play into 
screening for SDOH and how systemic bias within the health care system 
can play a role in this process.\17\ CMS has also heard of the 
significant pressures on provider time, and whether providers have 
access to comprehensive care and coordination teams, including social 
workers, who may be more appropriately skilled to assess certain SDOH.
---------------------------------------------------------------------------

    \13\ Maksut JL, Hodge C, Van CD, Razmi, A, & Khau MT. 
Utilization of Z Codes for Social Determinants of Health among 
Medicare Fee-For-Service Beneficiaries, 2019. Office of Minority 
Health (OMH) Data Highlight No. 24. Centers for Medicare & Medicaid 
Services (CMS), Baltimore, MD, 2021.
    \14\ Truong HP, Luke AA, Hammond G, Wadhera RK, Reidhead M, 
Joynt Maddox KE. Utilization of Social Determinants of Health ICD-10 
Z-Codes Among Hospitalized Patients in the United States, 2016-2017. 
Med Care. 2020;58(12):1037-1043. doi:10.1097/MLR.0000000000001418.
    \15\ Wark K, Cheung K, Wolter E, Avey JP. Engaging stakeholders 
in integrating social determinants of health into electronic health 
records: A scoping review. International Journal of Circumpolar 
Health. 2021 Jan 1;80(1):1943983.
    \16\ Garg A, Boynton-Jarrett R, Dworkin PH. Avoiding the 
Unintended Consequences of Screening for Social Determinants of 
Health. JAMA. 2016;316(8):813-814. doi:10.1001/jama.2016.9282
    \17\ Egede LE, Walker RJ, Williams JS. Intersection of 
Structural Racism, Social Determinants of Health, and Implicit Bias 
With Emergency Physician Admission Tendencies. JAMA Netw Open. 
2021;4(9):e2126375. doi:10.1001/jamanetworkopen.2021.26375
---------------------------------------------------------------------------

    Given that SDOH diagnosis codes describe economic and environmental 
circumstances faced by patients and often correlate with substantial 
variance in health outcomes,\18\ more widely adopted consistent 
documentation and reporting in the inpatient setting could better 
identify non-medical factors affecting health and track progress toward 
addressing them. Doing so could also aid in work toward formulating 
more comprehensive and actionable policies to address health equity and 
promote the highest quality, best-value care for all beneficiaries.
---------------------------------------------------------------------------

    \18\ Commission on Social Determinants of Health. Closing the 
gap in a generation: Health equity through action on the social 
determinants of health: Final report of the commission on social 
determinants of health. World Health Organization, 2008.
---------------------------------------------------------------------------

    As we discuss more fully later in this section, we believe 
reporting of SDOH Z codes may also better determine the resource 
utilization for treating patients experiencing these circumstances to 
help inform whether a change to the severity designation of these codes 
would be clinically warranted as we 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.
    There are 96 diagnosis codes that describe the social determinants 
of health found in categories Z55-Z65. These 96 diagnosis codes for 
which we are soliciting comments as described in this proposed rule are 
shown in Table 6P.5a (which is available via the internet on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS). We note we are also making available the 
data describing the impact on resource use when reported as a secondary 
diagnosis for all 96 ICD-10-CM Z codes that describe the social 
determinants of health from categories Z55-Z65. 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 the comprehensive CC/MCC analysis.
    In Table 6P.5a associated with this proposed rule, column C 
displays the FY 2021 severity level designation for these diagnosis 
codes in MS-DRG GROUPER Version 38.1. Column D displays CMS's current 
FY 2022 severity level designation in MS-DRG GROUPER Version 39.1. 
Columns E--N show data on the impact on resource use generated using 
discharge claims from the September 2021 update of the FY 2021 MedPAR 
file and MS-DRG GROUPER Version 39.1. For further information on the 
data on the impact on resource use as displayed in Columns E--N, 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/Downloads/10082019ListingSessionTrasncriptandQandAsandAudioFile.zip for the 
transcript and audio file of the listening session. We also refer 
readers to https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for 
the supplementary file containing the data describing the impact on 
resource use of specific ICD-10-CM diagnosis codes when reported as a 
secondary diagnosis that was made available for the listening session. 
We note that the supplementary file that was made available for the 
listening session contains the mathematical data for the impact on 
resource use generated using claims from the FY 2018 MedPAR file. We 
have also made available on the CMS website updated impact on resource 
use files so that the public can review the mathematical data for the 
impact on resource use generated using claims from the FY 2019 MedPAR 
file, FY 2020 MedPAR file and the FY 2021 MedPAR files.
    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

[[Page 28179]]

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. In Version 39.1, the 96 diagnosis codes that describe the 
social determinants of health from categories Z55-Z65 have a severity 
designation of NonCC.
    If SDOH Z codes are not consistently reported in inpatient claims 
data, our methodology utilized to mathematically measure the impact on 
resource use, as described previously, may not adequately reflect what 
additional resources were expended by the hospital to address these 
SDOH circumstances in terms of requiring clinical evaluation, extended 
length of hospital stay, increased nursing care or monitoring or both, 
and comprehensive discharge planning. We seek public comment on whether 
CMS should consider requiring more robust documentation and claims data 
reporting to inform the impact on resource use these determinants have 
on caring for patients affected by these circumstances in an inpatient 
setting and inform our decision-making in a future year in determining 
the most appropriate CC subclass (NonCC, CC, or MCC) assignment for 
each SDOH Z code as a secondary diagnosis. We also seek public comment 
on developing protocols to standardize the screening for SDOH for all 
patients, and then consistently document and report such codes and on 
whether such protocols should vary based on certain factors, such as 
hospital size and type. For instance, we recognize that hospitals have 
different mixes of patients and volume of patients, and as such, may 
have different staffing resources to devote to proper documentation and 
coding of SDOH. In particular, we are interested in hearing the 
perspectives of different sized hospitals in both urban and rural 
settings, and hospitals disproportionately serving members of 
historically underserved and under-resourced communities in regard to 
their experience with reporting of SDOH. We are additionally interested 
in learning how reporting SDOH Z codes may be used to inform community 
health need assessment activities required by non-profit hospitals.
    We also recognize that there is a potential for different uses and 
complexity in appropriately determining and reporting the full range of 
Z codes. For instance, certain code categories like Z62 (Problems 
related to upbringing) and Z63 (Other problems related to principal 
support group, including family circumstances) may require specialized 
clinical training to diagnose and document, which may not be the 
primary purpose of the inpatient admission. Category Z57 describes 
occupational exposure to risk factors, which also may not be apparent 
in most inpatient admissions and would rely upon the patient providing 
this information voluntarily. Category Z60 (Problems related to social 
environment) also describes problems of adjustment to life-cycle 
transitions, which also may or may not be readily apparent or discussed 
by the patient in relation to the inpatient admission.
    Thus, we are seeking comment on which specific SDOH Z codes are 
most likely to influence (that is, increase) hospital resource 
utilization related to inpatient care, including any supporting 
information that correlates inpatient hospital resource use to specific 
SDOH Z codes. CMS believes a potential starting point for discussion is 
consideration of the SDOH Z diagnosis codes describing homelessness. 
Homelessness can be reasonably expected to have an impact on hospital 
utilization.\19\ Healthcare needs for patients experiencing 
homelessness may be associated with increased resource utilization 
compared to other patients due to difficulty finding discharge 
destinations to meet the patient's multifaceted needs which can result 
in longer inpatient stays and can have financial impacts for 
hospitals.\20\ Longer hospital stays for these patients \21\ can also 
be associated with increased costs because patients experiencing 
homelessness are less able to access care at early stages of illness, 
and also may be exposed to communicable disease and harsh climate 
conditions, resulting in more severe and complex symptoms by the time 
they are admitted to hospitals, potentially leading to worse health 
outcomes. Patients experiencing homelessness can also be 
disproportionately affected by mental health diagnoses and issues with 
substance use disorders. In addition, patients experiencing 
homelessness may have limited or no access to prescription medicines or 
over-the-counter medicines, including adequate locations to store 
medications away from the heat or cold,\22\ and studies have shown 
difficulties adhering to medication regimens among persons experiencing 
homeless.\23\ Patients experiencing homelessness may also face 
challenges in accessing transplants and clinicians may defer care 
because of the uncertain post-acute discharge.
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    \19\ Koh HK, O'Connell JJ. Improving Health Care for Homeless 
People. JAMA. 2016;316(24):2586-2587. doi:10.1001/jama.2016.18760.
    \20\ Canham SL, Custodio K, Mauboules C, Good C, Bosma H. Health 
and Psychosocial Needs of Older Adults Who Are Experiencing 
Homelessness Following Hospital Discharge. Gerontologist. 2020 May 
15;60(4):715-724. doi: 10.1093/geront/gnz078. PMID: 31228238. 
https://pubmed.ncbi.nlm.nih.gov/31228238/.
    \21\ Hwang SW, Weaver J, Aubry T. Hospital costs and length of 
stay among homeless patients admitted to medical, surgical, and 
psychiatric services. Med Care. 2011;49:350-354. https://journals.lww.com/lww-medicalcare/Fulltext/2019/01000/Trends,_Causes,_and_Outcomes_of_Hospitalizations.4.aspx.
    \22\ Sun R (AHRQ), Karaca Z (AHRQ), Wong HS (AHRQ). 
Characteristics of Homeless Individuals Using Emergency Department 
Services in 2014. HCUP Statistical Brief #229. October 2017. Agency 
for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb229-Homeless-ED-Visits-2014.pdf.
    \23\ Coe, Antoinette B. Coe et al. ``Medication Adherence 
Challenges Among Patients Experiencing Homelessness in a Behavioral 
Health Clinic. https://journals.lww.com/lww-medicalcare/Fulltext/2019/01000/Trends,_Causes,_and_Outcomes_of_Hospitalizations.4.aspx.
---------------------------------------------------------------------------

    To further examine the diagnosis codes that describe SDOH, we 
reviewed the data on the impact on resource use for diagnosis code 
Z59.0 (Homelessness) when reported as a secondary diagnosis to 
facilitate discussion for the purposes of this comment solicitation. We 
note that prior to FY 2022, homelessness was one of the more frequently 
reported codes that describe social determinants of health. We also 
note that effective FY 2022, this subcategory has been expanded and now 
includes codes Z59.00 (Homelessness, unspecified), Z59.01 (Sheltered 
homelessness), and code Z59.02 (Unsheltered homelessness).
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19243 through 
19244), as part of our proposal to change the severity level 
designations for 1,492 ICD-10-CM diagnosis codes, we proposed to change 
the severity level designation of code Z59.0 (Homelessness) from NonCC 
to CC. We stated that because the C1 value (C1 = 1.5964) in the table 
was generally close to 2, the data suggested that when reported as a 
secondary diagnosis, the resources involved in caring for a patient 
experiencing homelessness supported increasing the severity level from 
a NonCC to a CC. In the FY 2020 IPPS/LTCH PPS proposed rule, we also 
stated our clinical advisors reviewed these data and believed the 
resources involved in caring for these patients are more aligned with a 
CC. As noted in section II.D.13.b of this proposed rule, many 
commenters expressed concern with the proposed severity level 
designation changes overall and consequently we generally did not 
finalize our proposed changes to the severity designations for the 
1,492 ICD-10-CM diagnosis codes, at that time.

[[Page 28180]]

However, the proposal to change the severity designation of code Z59.0 
specifically did receive mostly supportive comments. Many commenters 
stated that a patient experiencing homelessness requires significant 
coordination of social services along with their health care. One 
commenter also recommended that CMS expand the change in designation to 
all the codes in category Z59, not just code Z59.0. Another commenter, 
while indicating their support of the proposal, noted that it is 
unclear that the status/condition would result in increased hospital 
resource use.
    Our proposal in FY 2020 was based on the data for the impact on 
resource use generated using claims from the FY 2018 MedPAR file. The 
following table reflects the impact on resource use data generated 
using claims from the FY 2019 MedPAR file, FY 2020 MedPAR file and the 
FY 2021 MedPAR file, respectively, for the diagnosis code that 
describes homelessness as a NonCC. We note there is currently no data 
for codes Z59.01 (Sheltered homelessness) and code Z59.02 (Unsheltered 
homelessness) as these codes became effective on October 1, 2021. 
Again, we refer readers to the FY 2008 IPPS/LTCH PPS final rule (72 FR 
47159) for a complete discussion of our historical approach to 
mathematically evaluate the extent to which the presence of an ICD-10-
CM code as a secondary diagnosis resulted in increased hospital 
resource use, and the explanation of the columns in the table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.059

    As shown in the table, we examined data for the diagnosis code(s) 
that describe homelessness as a NonCC in FY 2019 through FY 2021. When 
examining diagnosis code Z59.0 (Homelessness), the value in column C1 
is closer to 2.0 than to 1.0 in FY 2019 and FY 2020, though we note 
that we did not use FY 2020 data for rate setting purposes in light of 
impacts related to the PHE for COVID-19 as described in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 44778). The data suggests that when 
homelessness is reported as a secondary diagnosis, the resources 
involved in caring for these patients are more aligned with a CC than a 
NonCC or an MCC, as explained in the FY 2008 IPPS/LTCH PPS final rule 
(72 FR 47159). However, in FY 2021, the C1 value is generally closer to 
1, which suggest the resources involved in caring for patients 
experiencing homelessness are more aligned with a NonCC severity level 
than a CC or an MCC severity level. We also note fluctuations in the C1 
values year to year. We are uncertain if the data from FY 2021, in 
particular, reflect fluctuations that may be a result of the public 
health emergency or even reduced hospitalizations of certain 
conditions. We also are uncertain if homelessness may be underreported 
when there is not an available field on the claim when other diagnoses 
are reported instead. We seek public comment on these possibilities, 
particularly to inform our understanding of the trend of the C1 value.
    As we have stated in prior rulemaking, these mathematical 
constructs are used in conjunction with the judgment of our clinical 
advisors to classify each secondary diagnosis reviewed. We present 
these data to highlight that the resources expended in caring for 
patients reported to be affected by a SDOH such as homelessness during 
an inpatient hospitalization may not be consistently expressed in the 
inpatient claims data and to demonstrate how reporting the SDOH Z codes 
could more accurately reflect the health care encounter and improve the 
reliability and validity of the coded data.
    In summary, we appreciate public comment on these issues, including 
on the following questions:
     How the reporting of certain Z codes--and if so, which Z 
codes \24\--may improve our ability to recognize severity of illness, 
complexity of illness, and utilization of resources under the MS-DRGs?
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    \24\ https://www.cms.gov/files/document/zcodes-infographic.pdf.
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     Whether CMS should require the reporting of certain Z 
codes--and if so, which ones--to be reported on hospital inpatient 
claims to strengthen data analysis?
     The additional provider burden and potential benefits of 
documenting and reporting of certain Z codes, including potential 
benefits to beneficiaries.
     Whether codes in category Z59 (Homelessness) have been 
underreported and if so, why? In particular, we are interested in 
hearing the perspectives of large urban hospitals, rural hospitals, and 
other hospital types in regard to their experience. We also seek 
comments on how factors such as hospital size and type might impact a 
hospital's ability to develop standardized consistent protocols to 
better screen, document and report homelessness.
    The comments we receive on these issues may also be informative as 
we evaluate whether to develop a proposal in future rulemaking to 
change the severity level designation of the diagnosis codes describing 
homelessness from NonCC to CC and whether other SDOH, as described by Z 
codes, are also appropriate candidates to be proposed for designation 
as CCs.
    We note that examining the severity level designation of diagnosis 
codes is just one area to possibly support documentation and reporting 
of SDOH in the inpatient setting. We are also interested in ideas from 
the public on how the MS-DRG classification can be utilized in agency 
wide efforts to advance health equity, expand access, drive high-
quality, person-centered care, and promote affordability and 
sustainability in the Medicare program. Specifically, we invite public 
comment on ways the MS-DRG classification can be useful in addressing 
the challenges of defining and collecting accurate and standardized 
self-identified socioeconomic information for the purposes of 
reporting, measure stratification, and other data collection efforts. 
We are interested in learning more about the potential benefits and 
challenges associated with the collection of SDOH data in the inpatient 
setting. Feedback on the limitations and barriers providers could 
experience as they consider more robust documentation and reporting 
would also help inform our development of appropriately tailored 
efforts that address and mitigate barriers for all hospital types 
across communities and patient mixes. We will take

[[Page 28181]]

commenters' feedback into consideration in future policy development.
e. Proposed Additions and Deletions to the Diagnosis Code Severity 
Levels for FY 2023
    The following tables identify the proposed additions and deletions 
to the diagnosis code MCC severity levels list and the proposed 
additions and deletions to the diagnosis code CC severity levels list 
for FY 2023 and are available via the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    Table 6I.1--Proposed Additions to the MCC List--FY 2023;
    Table 6I.2--Proposed Deletions to the MCC List--FY 2023;
    Table 6J.1--Proposed Additions to the CC List--FY 2023; and
    Table 6J.2--Proposed Deletions to the CC List--FY 2023.
f. Proposed CC Exclusions List for FY 2023
    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.
     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 39.1 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.
    We are proposing additional changes to the ICD-10 MS-DRGs Version 
40 CC Exclusion List based on the diagnosis and procedure code updates 
as discussed in section II.D.14. of this FY 2023 IPPS/LTCH PPS proposed 
rule. Therefore, we have developed Table 6G.1.-Proposed Secondary 
Diagnosis Order Additions to the CC Exclusions List-FY 2023; Table 
6G.2.-Proposed Principal Diagnosis Order Additions to the CC Exclusions 
List-FY 2023; Table 6H.1.-Proposed Secondary Diagnosis Order Deletions 
to the CC Exclusions List-FY 2023; and Table 6H.2.-Proposed Principal 
Diagnosis Order Deletions to the CC Exclusions List-FY 2023. 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.
14. 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 2023, we have developed Table 6A.-New Diagnosis Codes, Table 
6B.-New Procedure Codes, Table 6C.-Invalid Diagnosis 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.17. 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

[[Page 28182]]

severity of illness, treatment difficulty, complexity of service and 
the resources utilized in the diagnosis 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 2023
 Table 6B.--New Procedure Codes-FY 2023
 Table 6C.--Invalid Diagnosis Codes-FY 2023
 Table 6E.--Revised Diagnosis Code Titles-FY 2023
 Table 6G.1.--Proposed Secondary Diagnosis Order Additions to 
the CC Exclusions List-FY 2023
 Table 6G.2.--Proposed Principal Diagnosis Order Additions to 
the CC Exclusions List-FY 2023
 Table 6H.1.--Proposed Secondary Diagnosis Order Deletions to 
the CC Exclusions List-FY 2023
 Table 6H.2.--Proposed Principal Diagnosis Order Deletions to 
the CC Exclusions List--FY 2023
 Table 6I.1.--Proposed Additions to the MCC List-FY 2023
 Table 6I.2.--Proposed Deletions to the MCC List-FY 2023
 Table 6J.1.--Proposed Additions to the CC List-FY 2023
 Table 6J.2.--Proposed Deletions to the CC List-FY 2023.
15. 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 2022 IPPS/LTCH PPS final rule (86 FR 44936), 
we made available the FY 2022 ICD-10 MCE Version 39 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 39 
(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 2023 IPPS/LTCH PPS proposed rule, we discuss the 
proposals we are making based on our internal review and analysis. We 
did not receive any specific MCE requests by the November 1, 2021 
deadline.
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.14. of the preamble of this proposed 
rule, Table 6C.--Invalid Diagnosis Codes, lists the diagnosis codes 
that are no longer effective October 1, 2022. Included in this table 
are codes currently subject to the External causes of morbidity codes 
as principal diagnosis edit. We are proposing to delete the ICD-10-CM 
diagnosis codes shown in Table 6P.6a 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 
that are currently subject to the External causes of morbidity codes as 
principal diagnosis edit since they will no longer be valid for 
reporting purposes.
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) Maternity Diagnoses
    Under the ICD-10 MCE, the Maternity diagnoses category for the Age 
conflict edit considers the age range of 9 to 64 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.14. 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, 2022. We are proposing to add new ICD-10-CM 
diagnosis codes to the edit code list for the Maternity diagnoses 
category as shown in Table 6P.6b 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 under the 
Age conflict edit.
    In addition, as discussed in section II.D.14. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective October 1, 2022. Included 
in this table are the following ICD-10-CM diagnosis codes that are 
currently listed on the edit code list for the Maternity diagnoses 
category under the Age conflict edit. We are proposing to delete these 
codes from the Maternity diagnoses edit code list.
BILLING CODE 4120-01-P

[[Page 28183]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.060

(2) Adult Diagnoses
    Under the ICD-10 MCE, the Adult diagnoses category for the Age 
conflict edit considers the age range of 15 to 124 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.14. 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, 2022. We are proposing to add the following new 
ICD-10-CM diagnosis codes to the edit code list for the Adult diagnoses 
category under the Age conflict edit.

[[Page 28184]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.061

    In addition, as discussed in section II.D.14. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective October 1, 2022. Included 
in this table are the following ICD-10-CM diagnosis codes that are 
currently listed on the edit code list for the Adult diagnoses category 
under the Age conflict edit. We are proposing to delete these codes 
from the Adult diagnoses edit code list.
[GRAPHIC] [TIFF OMITTED] TP10MY22.062


[[Page 28185]]


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.14. 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, 2022. We are proposing to add new ICD-10-CM 
diagnosis codes to the edit code list for the Diagnoses for females 
only category as shown in Table 6P.6c 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 
under the Sex conflict edit.
    In addition, as discussed in section II.D.14. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective October 1, 2022. Included 
in this table are the following ICD-10-CM diagnosis codes that are 
currently listed on the edit code list for the Diagnoses for females 
only category under the Sex conflict edit. We are proposing to delete 
these codes from the Diagnoses for females only edit code list.
[GRAPHIC] [TIFF OMITTED] TP10MY22.063

(2) Procedures for Males Only
    As discussed in section II.D.14. of the preamble of this proposed 
rule, Table 6B.--New Procedure Codes, lists the new procedure codes 
that have been approved to date which will be effective with discharges 
on and after October 1, 2022. Included in this table are the following 
procedure codes we are proposing to add to the edit code list for the 
Procedures for males only category under the Sex conflict edit.

[[Page 28186]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.064

d. Manifestation Code as Principal Diagnosis Edit
    In the ICD-10-CM classification system, manifestation codes 
describe the manifestation of an underlying disease, not the disease 
itself, and therefore should not be used as a principal diagnosis.
    As discussed in section II.D.14. 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, 2022. Included in this table are the following 
new ICD-10-CM diagnosis codes that we are proposing to add to the edit 
code list for the Manifestation code as principal diagnosis edit, 
because the disease itself would be required to be reported first.
[GRAPHIC] [TIFF OMITTED] TP10MY22.065


[[Page 28187]]


    In addition, as discussed in section II.D.14. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective October 1, 2022. Included 
in this table is ICD-10-CM diagnosis code F02.81 (Dementia in other 
diseases classified elsewhere with behavioral disturbance), that is 
currently listed on the edit code list for the Manifestation code as 
principal diagnosis edit. We are proposing to delete this code from the 
Manifestation code as principal diagnosis edit code list.
e. 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.14. 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, 2022. We are proposing to add the following new 
ICD-10-CM diagnosis codes to the Unacceptable Principal Diagnosis edit 
code list.
    As discussed in section II.D.1.b. of the preamble of this proposed 
rule, we are providing a test version of the ICD-10 MS-DRG GROUPER 
Software, Version 40, so that the public can better analyze and 
understand the impact of the proposals included in this proposed rule. 
We note that at the time of the development of the test software, a 
subset of the listed codes (F01.511 through F01.C4) proposed for this 
edit were unable to be included and therefore, the test software does 
not reflect these codes.
[GRAPHIC] [TIFF OMITTED] TP10MY22.066


[[Page 28188]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.067

    In addition, as discussed in section II.D.14. of the preamble of 
this proposed rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective October 1, 2022. Included 
in this table are the following

[[Page 28189]]

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] TP10MY22.068

f. Unspecified Code
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44940 through 
44943), we finalized the implementation of a new Unspecified code edit, 
effective with discharges on and after April 1, 2022. Unspecified codes 
exist in the ICD-10-CM classification for circumstances when 
documentation in the medical record does not provide the level of 
detail needed to support reporting a more specific code. However, in 
the inpatient setting, there should generally be very limited and rare 
circumstances for which the laterality (right, left, bilateral) of a 
condition is unable to be documented and reported.
    As discussed in section II.D.14. 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, 2022. We are proposing to add the following new 
ICD-10-CM diagnosis codes to the Unspecified code edit code list.
[GRAPHIC] [TIFF OMITTED] TP10MY22.069

g. 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.
[GRAPHIC] [TIFF OMITTED] TP10MY22.070

BILLING CODE 4120-01-C
    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 new electronic intake system, Medicare Electronic Application 
Request Information SystemTM (MEARISTM), 
discussed in section II.D.1.b. of the preamble of this

[[Page 28190]]

proposed rule at https://mearis.cms.gov/public/home by October 20, 
2022.
16. 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 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.
    Based on the changes that we are proposing to make for FY 2023, as 
discussed in section II.D. of the preamble of this proposed rule, we 
are proposing to maintain the existing surgical hierarchy for FY 2023.
17. Maintenance of the ICD-10-CM and ICD-10-PCS Coding Systems
    In September 1985, the ICD-9-CM Coordination and Maintenance 
Committee was formed. This is a Federal interdepartmental committee, 
co-chaired by the Centers for Disease Control and Prevention's (CDC) 
National Center for Health Statistics (NCHS) and CMS, charged with 
maintaining and updating the ICD-9-CM system. The final update to ICD-
9-CM codes was made on October 1, 2013. Thereafter, the name of the 
Committee was changed to the ICD-10 Coordination and Maintenance 
Committee, effective with the March 19-20, 2014 meeting. The ICD-10 
Coordination and Maintenance Committee addresses updates to the ICD-10-
CM and ICD-10-PCS coding systems. The Committee is jointly responsible 
for approving coding changes, and developing errata, addenda, and other 
modifications to the coding systems to reflect newly developed 
procedures and technologies and newly identified diseases. The 
Committee is also responsible for promoting the use of Federal and non-
Federal educational programs and other communication techniques with a 
view toward standardizing coding applications and upgrading the quality 
of the classification system.
    The official list of ICD-9-CM diagnosis and procedure codes by 
fiscal year can be found on the CMS website at https://cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/codes.html. The official 
list of ICD-10-CM and ICD-10-PCS codes can be found on the CMS website 
at https://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 ICD-10 Coordination and Maintenance Committee holds its 
meetings in the spring and fall 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.
    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.

[[Page 28191]]

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.
    The Committee presented proposals for coding changes for 
implementation in FY 2023 at a public meeting held on September 14-15, 
2021, and finalized the coding changes after consideration of comments 
received at the meetings and in writing by November 15, 2021.
    The Committee held its 2022 meeting on March 8-9, 2022. The 
deadline for submitting comments on the procedure code proposals that 
are being considered for an October 1, 2022 implementation was April 8, 
2022. The deadline for submitting comments on the diagnosis code 
proposals that are being considered for an October 1, 2023 
implementation is May 9, 2022. 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 2022 would be included in the October 1, 2022, 
update to the ICD-10-CM diagnosis and ICD-10-PCS procedure code sets. 
It was also announced at this meeting that we are changing the process 
for submitting requested updates to the ICD-10-PCS classification, 
beginning with the procedure code request submitted for consideration 
for the September 13-14, 2022 ICD-10 Coordination and Maintenance 
Committee Meeting. As stated in section II.D.1.b. of the preamble of 
this proposed rule, CMS is in the process of implementing a new 
electronic application intake system, MEARIS\TM\. Effective January 5, 
2022, MEARIS\TM\ became available as an initial release for users to 
begin gaining familiarity with a new approach and process to submit 
ICD-10-PCS procedure code requests. Information on this new approach 
for submitting an ICD-10-PCS code request can be accessed at https://mearis.cms.gov. Effective March 1, 2022, the full release of MEARIS\TM\ 
became active for ICD-10-PCS code request submissions. ICD-10-PCS code 
request submissions are due no later than June 10, 2022, to be 
considered for the September 13-14, 2022, ICD-10 Coordination and 
Maintenance Committee Meeting. Moving forward, CMS will only accept 
ICD-10-PCS code requests submitted via MEARIS\TM\. Requests submitted 
through the ICDProcedureCodeRequest mailbox will no longer be 
considered. Within MEARIS\TM\, we have built in several resources to 
support users, including a ``Resources'' section (available at https://mearis.cms.gov/public/resources) and technical support available under 
``Useful Links'' at the bottom of the MEARIS\TM\ site. Questions 
regarding MEARIS\TM\ can be submitted to CMS using the form available 
under ``Contact'' at https://mearis.cms.gov/public/resources.
    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, and Table 6E.--Revised Diagnosis Code Titles for 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. The code titles are adopted as part of the ICD-10 
Coordination and Maintenance Committee process. Therefore, although we 
make the code titles available through tables in association with 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 14-15, 2021, meeting and the March 
8-9, 2022, 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 14-15, 2021, meeting and March 8-9, 2022, meeting can be 
found at https://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 [email protected].
    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 three new diagnosis codes describing immunization 
status related to COVID-19 into the ICD-10-CM effective with discharges 
on and after April 1, 2022. The diagnosis codes are as follows:
[GRAPHIC] [TIFF OMITTED] TP10MY22.071

    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 three diagnosis codes 
effective with discharges on and after April 1, 2022, consistent with 
our established process for assigning new diagnosis codes. 
Specifically, we review the predecessor diagnosis code and MS-DRG 
assignment most closely associated with the new diagnosis code, and 
consider other factors that may be relevant to the MS-DRG assignment, 
including the severity of illness, treatment difficulty, and the 
resources utilized for the specific condition/diagnosis. We note that 
this process does not automatically result in the new diagnosis code 
being assigned to the same MS-DRG as the predecessor code. The 
assignments for the previously listed diagnosis codes are reflected in 
Table 6A.--New Diagnosis Codes (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

[[Page 28192]]

rule, we are soliciting public comments on the most appropriate MDC, 
MS-DRG, and severity level assignments for these codes for FY 2023, as 
well as any other options for the GROUPER logic.
    In addition, CMS implemented nine new procedure codes describing 
the introduction or infusion of therapeutics, including vaccines for 
COVID-19 treatment, into the ICD-10-PCS effective with discharges on 
and after April 1, 2022. The nine 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.
[GRAPHIC] [TIFF OMITTED] TP10MY22.072

    The ICD-10 MS-DRG assignment for cases reporting any one of the 
nine 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 nine 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 
these codes for FY 2023, as well as any other options for the GROUPER 
logic.
    We note that Change Request (CR) 12578, Transmittal 11174, titled 
``April 2022 Update to the Medicare Severity--Diagnosis Related Group 
(MS-DRG) Grouper and Medicare Code Editor (MCE) Version 39.1 for the 
International Classification of Diseases, Tenth Revision (ICD-10) 
Diagnosis Codes for 2019 Novel Coronavirus (COVID-19) Vaccination 
Status and ICD-10 Procedure Coding System (PCS) Codes for Introduction 
or Infusion of Therapeutics and Vaccines for COVID-19 Treatment'', was 
issued on January 14, 2022 (available via the internet on the CMS 
website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r11174cp) regarding the release of an updated 
version of the ICD-10 MS-DRG GROUPER and Medicare Code Editor software, 
Version 39.1, effective with discharges on and after April 1, 2022, 
reflecting the new diagnosis and procedure codes. The updated software, 
along with the updated ICD-10 MS-DRG V39.1 Definitions Manual and the 
Definitions of Medicare Code Edits V39.1 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

[[Page 28193]]

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.
    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 those determinations. Topics considered during the Fall ICD-10 
(previously ICD-9-CM) Coordination and Maintenance Committee meeting 
were considered for an April 1 update if a strong and convincing case 
was made by the requestor during the Committee's public meeting. The 
request needed to identify the reason why a new code was needed in 
April for purposes of the new technology process. Meeting participants 
and those reviewing the Committee meeting materials were provided the 
opportunity to comment on the expedited request. We refer the reader to 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 44950) for further 
discussion of the implementation of this prior April 1 update for 
purposes of the new technology add-on payment process.
    However, as discussed in the FY 2022 IPPS/LTCH PPS final rule (86 
FR 44950 through 44956), we adopted an April 1 implementation date, in 
addition to the annual October 1 update, beginning with April 1, 2022. 
We noted that the intent of this April 1 implementation date is to 
allow flexibility in the ICD-10 code update process. With this new 
April 1 update, CMS now uses the same process for consideration of all 
requests for an April 1 implementation date, including for purposes of 
the new technology add-on payment process (that is, the prior process 
for consideration of an April 1 implementation date only if a strong 
and convincing case was made by the requestor during the meeting no 
longer applies). We are continuing to use several aspects of our 
existing established process to implement new codes through the April 1 
code update, which includes presenting proposals for April 1 
consideration at the September ICD-10 Coordination and Maintenance 
Committee meeting, requesting public comments, reviewing the public 
comments, finalizing codes, and announcing the new codes with their 
assignments consistent with the new GROUPER release information. We 
note that under our established process, requestors indicate whether 
they are submitting their code request for consideration for an April 1 
implementation date or an October 1 implementation date. The ICD-10 
Coordination and Maintenance Committee makes efforts to accommodate the 
requested implementation date for each request submitted. However, the 
Committee determines which requests are to be presented for 
consideration for an April 1 implementation date or an October 1 
implementation date. As discussed earlier in this section of the 
preamble of this proposed rule, there were code proposals presented for 
an expedited April 1, 2022, implementation at the September 14-15, 
2021, Committee meetings that involved treatments related to the COVID-
19 PHE. One of these code proposals was also in connection with a 
request for a new technology add-on payment application. Following the 
receipt of public comments, the code proposals were approved and 
finalized, therefore, there were new codes implemented April 1, 2022.
    Consistent with the process we outlined for the April 1 
implementation date, we announced the new codes in November 2021 and 
provided the updated code files and ICD-10-CM Official Guidelines for 
Coding and Reporting in December 2021. In the January 24, 2022, Federal 
Register (87 FR 3549), notice for the March 8-9, 2022, ICD-10 
Coordination and Maintenance Committee Meeting was published that 
includes the tentative agenda and identifies which topics are related 
to a new technology add-on payment application. By February 1, 2022, we 
made available the updated V39.1 ICD-10 MS-DRG Grouper software and 
related materials via the internet on CMS web page at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    ICD-9-CM addendum and code title information is published on the 
CMS website at https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/addendum. ICD-10-CM and ICD-10-PCS addendum 
and code title information is published on the CMS website at https://www.cms.gov/medicare/coding/icd10. 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 2022, there are currently 72,750 diagnosis codes and 78,229 
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, there are 
1,176 new diagnosis codes and 45 new procedure codes that have been 
finalized for FY 2023 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.
18. 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

[[Page 28194]]

implantation of a device that subsequently failed or was recalled 
determined the base MS-DRG assignment. At that time, we specified that 
we will reduce a hospital's IPPS payment for those MS-DRGs where the 
hospital received a credit for a replaced device equal to 50 percent or 
more of the cost of the device.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51556 through 
51557), we clarified this policy to state that the policy applies if 
the hospital received a credit equal to 50 percent or more of the cost 
of the replacement device and issued instructions to hospitals 
accordingly.
b. Proposed Changes for FY 2023
    For FY 2023 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.
[GRAPHIC] [TIFF OMITTED] TP10MY22.073


[[Page 28195]]


    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 2023 IPPS/LTCH PPS final rule and also will be issued to providers 
in the form of a Change Request (CR).
19. Other Policy Issues
a. Comment Solicitation on Possible Mechanisms To Address Rare Diseases 
and Conditions Represented by Low Volumes Within the MS-DRG Structure
    As discussed in section II.D.13.d. of the preamble of this proposed 
rule, we are soliciting public comments involving how the reporting of 
certain diagnosis codes may improve our ability to recognize severity 
of illness, complexity of illness, and utilization of resources under 
the MS-DRGs, as well as feedback on mechanisms to improve the 
reliability and validity of the coded data as part of an ongoing effort 
across CMS to evaluate and develop policies to reduce health 
disparities. In concert with that effort, we are also soliciting 
comments to explore possible mechanisms through which we can address 
rare diseases and conditions that are represented by low volumes in our 
claims data.
    One subset of our beneficiary population for which we are seeking 
comment on potential issues related to patient access in the inpatient 
setting are patients diagnosed with rare diseases and conditions that 
are represented by low volumes in our claims data. The Orphan Drug Act 
(ODA) added section 526(a)(2)(B) to the Federal Food, Drug, and 
Cosmetic Act (21 U.S.C. 360bb(a)(2)(B)), defining a rare disease or 
condition as ``any disease or condition which (A) affects less than 
200,000 persons in the United States, or (B) affects more than 200,000 
in the United States and for which there is no reasonable expectation 
that the cost of developing and making available in the United States a 
drug for such disease or condition will be recovered from sales in the 
United States of such drug.'' Most rare diseases, however, affect far 
fewer people. The Genetic and Rare Diseases Information Center (GARD), 
which was created in 2002 by the National Institutes of Health (NIH) 
Office of Rare Diseases Research, estimates that there are as many as 
7,000 distinct rare diseases. Rare diseases, which can include genetic 
diseases, autoimmune conditions, some cancers, and uncommon infections, 
are highly diverse, may affect many organ systems and have wide 
variations in the rates and patterns of manifestations and progression.
    The ODA created a process for the U.S. Food and Drug Administration 
(FDA) to identify a drug as a drug developed for the treatment of a 
rare disease or condition called ``orphan-drug designation''. The 
sponsor of a drug that has orphan drug designation may be eligible for 
certain financial incentives, such as tax credits and potentially seven 
years of market exclusivity after approval, all of which are intended 
to incentivize developing drugs for small numbers of patients. We have 
heard from some stakeholders, however, that there may be a number of 
barriers to providers in treating these patients with these orphan 
designated drugs in the Medicare hospital inpatient setting.
    According to these stakeholders, one significant barrier that 
continues to present challenges to manufacturers is accessing formulary 
coverage for potentially high cost therapeutics for rare diseases. 
These stakeholders have stated that hospitals utilize formularies for 
inpatient drugs as a cost-management tool that strongly incentivizes 
physicians to use on-formulary drugs over off-formulary drugs, whenever 
clinically appropriate to do so. A drug formulary is defined as a list 
of medications and continually updated related information, that 
represents the clinical judgment of pharmacists, physicians, and other 
experts in the diagnosis and treatment of disease or promotion of 
health. It is often described as a list of medications routinely 
stocked by the health care system. These stakeholders stated that 
although certain therapeutics can be associated with better outcomes 
for patients with rare diseases, the lack of access to hospital 
formularies represents a hurdle under the IPPS MS-DRGs. According to 
these stakeholders, when Medicare reimbursement is insufficient to 
cover the costs of certain therapeutics that treat patients with rare 
diseases, a disincentive can be created in addressing these conditions.
    For the purposes of this comment solicitation we describe in this 
section three selected requests we have received relating to the MS-DRG 
classification of rare diseases and conditions that are represented by 
low volumes in our claims data.
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53311), the FY 2015 
IPPS/LTCH PPS final rule (79 FR 49901), and the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41200), we discussed requests we received to revise 
the MS-DRG classification for cases of patients diagnosed with 
porphyria to recognize the resource requirements in caring for these 
patients, to ensure appropriate payment for these cases, and to 
preserve patient access to necessary treatments. Porphyria is defined 
as a group of rare disorders (``porphyrias'') that interfere with the 
production of hemoglobin that is needed for red blood cells. While some 
of these disorders are genetic (inborn) and others are acquired, they 
all result in the abnormal accumulation of hemoglobin building blocks, 
called porphyrins, which can be deposited in the tissues where they 
particularly interfere with the functioning of the nervous system and 
the skin. Treatment for patients suffering from disorders of porphyrin 
metabolism consists of an intravenous injection of Panhematin[supreg] 
(hemin for injection).
    In the FY 2019 proposed rule, we stated our data analysis showed 
that cases reporting diagnosis code E80.21 (Acute intermittent 
(hepatic) porphyria) as the principal diagnosis in MS-DRG 642 (Inborn 
and Other Disorders of Metabolism) had higher average costs and longer 
average lengths of stay compared to the average costs and length of 
stay for all other cases in MS-DRG 642. However, after considering 
these findings in the context of the current MS-DRG structure, we 
stated that we were unable to identify an MS-DRG that would more 
closely parallel these cases with respect to average costs and length 
of stay that would also be clinically aligned. We further stated that 
our clinical advisors believed that, in the current MS-DRG structure, 
the clinical characteristics of patients in these cases are most 
closely aligned with the clinical characteristics of patients in all 
cases in MS-DRG 642. Moreover, given the small number of porphyria 
cases, we stated we did not believe there was justification for 
creating a new MS-DRG and did not propose to revise the MS-DRG 
classification for porphyria cases.
    In response, some commenters described significant difficulties 
encountered by patients with acute porphyria attacks in obtaining 
Panhematin[supreg] when presenting to an inpatient hospital, which they 
attributed to the strong financial disincentives faced by facilities to 
treat these cases on an inpatient basis. The commenters stated that, 
based on the lower than expected average cost per case and longer than 
expected length of stay for acute porphyria attacks, it appeared that 
facilities were frequently not providing Panhematin[supreg] to patients 
in this condition, and instead attempting to provide symptom relief and 
transferring patients to an outpatient setting to receive the drug 
where they can be adequately paid. The commenters stated that this is 
in contrast to the standard of

[[Page 28196]]

care for acute porphyria attacks and could result in devastating long-
term health consequences.
    In the FY 2019 final rule (83 FR 41200), as we have stated in prior 
rulemaking, we noted it is not appropriate for facilities to deny 
treatment to beneficiaries needing a specific type of therapy or 
treatment that involves increased costs. We further noted the MS-DRG 
system is a system of averages and it is expected that across the 
diagnostic related groups that within certain groups, some cases may 
demonstrate higher than average costs, while other cases may 
demonstrate lower than average costs. While we recognized the average 
costs of the small number of porphyria cases were greater than the 
average costs of the cases in MS-DRG 642 overall, we also noted that an 
averaged payment system depends on aggregation of similar cases with a 
range of costs, and that we 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 of 
diagnoses. We further stated that we were sensitive to the commenters' 
concerns about access to treatment for beneficiaries who have been 
diagnosed with this condition and we would continue to explore 
mechanisms through which to address rare diseases and low volume DRGs.
    Similarly, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44869), 
we discussed a request we received to review potential access issues in 
the inpatient setting for the administration of ANDEXXA[supreg]. 
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). We noted that while our data 
findings demonstrated the average costs for the cases reporting the 
intravenous administration of ANDEXXA[supreg] were higher when compared 
to all cases in their respective MS-DRG, these cases represented a very 
small percentage of the total number of cases reported in those MS-
DRGs. We stated 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. We also stated that while we were 
sensitive to the requestors' concerns about continued access to 
treatment for beneficiaries who require the reversal of anticoagulation 
due to life-threatening or uncontrolled bleeding, we indicated 
additional time was needed to explore options and other mechanisms 
through which to address low volume, high-cost drugs outside of the MS-
DRGs.
    Lastly, we received a request to reconsider how cases reporting the 
administration of Zulresso[supreg] (brexanolone) are recognized for 
payment under the ICD-10 MS-DRGs in an effort to improve access to 
treatment for maternal mental health. On March 19, 2019 
Zulresso[supreg] (brexanolone) became the first Food and Drug 
Administration (FDA) approved drug, specifically for postpartum 
depression (PPD) in adults. According to the requestor, PPD is one of 
the most common complications during and after pregnancy. The requestor 
stated PPD is a serious but manageable disorder and that with early 
treatment, the life of the mother, baby, and the entire family could be 
positively impacted. The requestor indicated it shares CMS's goals of 
addressing disparities in access to care, and urged CMS to take 
additional steps to address inequities in women's health by permitting 
separate payment for Zulresso[supreg] (brexanolone), in addition to the 
MS-DRG payment.
    Effective with discharges on and after October 1, 2020, cases 
reporting the administration of Zulresso[supreg] in the inpatient 
setting are identified by ICD-10-PCS procedure codes XW03306 
(Introduction of brexanolone into peripheral vein, percutaneous 
approach, new technology group 6) or XW04306 (Introduction of 
brexanolone into central vein, percutaneous approach, new technology 
group 6). These procedure codes are designated as non-O. R. procedures 
and do not affect the MS-DRG assignment when reported on an inpatient 
claim. We note that an application for new technology add-on payment 
for Zulresso[supreg] (brexanolone) was discussed in the FY 2021 IPPS/
LTCH PPS proposed rule (85 FR 32672 through 32676) and was not 
approved, as discussed in the final rule (85 FR 58709 through 58715).
    We analyzed claims from the September 2021 update of the FY 2021 
MedPAR file for cases reporting the administration of Zulresso[supreg] 
(brexanolone). Our analysis of the claims data identified only one case 
reporting the administration of Zulresso[supreg] (brexanolone) in MS-
DRG 870 (Septicemia or Severe Sepsis with MV >96 Hours) with an average 
length of stay of 22 days and average costs of $67,812. For all cases 
in MS-DRG 870, the average costs are $55,459 and the average length of 
stay is 15.9 days. While the average length of stay for the case 
reporting the administration of Zulresso[supreg] (brexanolone) is 
greater (22 days versus 15.9 days) and the average costs are higher 
($67,812 versus $55,459), than all cases in MS-DRG 870 it is unclear if 
treatment with Zulresso[supreg] (brexanolone) is the underlying reason 
for these factors, given that the MS-DRG assigned is for sepsis and it 
is not uncommon for sepsis patients to have multiple co-morbidities and 
intensive treatment strategies to address this severe, often life 
threatening condition.
    We appreciate the requestor's interest in sharing CMS's goal of 
advancing women's health, however, we note that the population in which 
Zulresso[supreg] (brexanolone) is indicated generally does not include 
our inpatient Medicare population. As we have stated in prior 
rulemaking, (83 FR 41210), we have not adopted the same approach to 
refine the maternity and newborn MS-DRGs because of the extremely low 
volume of Medicare patients there are in these MS-DRGs. When there is 
not a high volume of these cases (for example, maternity and newborn) 
represented in the Medicare data, we generally advise that other payers 
should develop DRGs to address the needs of their patients. We believe 
the same would apply with respect to administration of Zulresso[supreg] 
(brexanolone) for which, as noted, we identified only one case in the 
FY 2021 MedPAR file.
    As discussed in prior rulemaking, the MS-DRGs are a classification 
system intended to group together diagnoses and procedures with similar 
clinical characteristics and utilization of resources. Rare diseases 
and conditions that are represented by low volumes in our claims data 
however, pose a unique challenge to this methodology as these 
conditions by definition affect small subsets of the population. It has 
been difficult to identify other MS-DRGs that would be more appropriate 
MS-DRG assignments for these rare conditions based on the wide variance 
in the clinical characteristics and utilization of resources for each 
condition, depending on the diagnosis. Creating a new MS-DRG for these 
conditions as a distinct ``related'' group is also challenging for the 
same reasons.
    As previously noted, 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. We have been concerned that basing MS-DRG reclassification 
decisions on small numbers of cases could lead to complexities in 
establishing the relative payment weights for the MS-DRGs

[[Page 28197]]

because several expensive cases could impact the overall relative 
payment weight. Having larger clinical cohesive groups within an MS-DRG 
provides greater stability and thus predictability for hospitals for 
annual updates to the relative payment weights.
    As also previously noted, 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. However, as noted, cases 
involving treatment of rare diseases may involve more resource use than 
other cases in their respective MS-DRG. 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, however we are soliciting feedback on other 
mechanisms we can explore through which we could address concerns 
relating to payment for patients with rare diseases and conditions that 
are represented by low volumes in our claims data. We are also 
interested in receiving comments on other meaningful ways in which we 
may potentially improve access to treatment for postpartum depression 
in certain populations, including through activities pursuant to Vice 
President Harris's Call to Action to Reduce Maternal Mortality and 
Morbidity.\25\
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    \25\ Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    To inform decision making, we are also looking for feedback on how 
to mitigate any unintended negative payment impacts to providers 
serving patients with rare diseases or conditions that are represented 
by low volumes in our claims data. In particular, we are interested in 
hearing the perspectives of large urban hospitals, rural hospitals, and 
other hospital types in regard to their experience. We also seek 
comments on how factors such as hospital size and type might impact a 
hospital's ability to develop protocols to better address these 
conditions. We will take commenters' feedback into consideration in 
future policy development.

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

E. Recalibration of the FY 2023 MS-DRG Relative Weights

1. Data Sources for Developing the Relative Weights
    Consistent with our established policy, in developing the MS-DRG 
relative weights for FY 2023, 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 2021 MedPAR data used in this 
proposed rule include discharges occurring on October 1, 2020, through 
September 30, 2021, based on bills received by CMS through December 31, 
2021, 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 2021 MedPAR file used in calculating the proposed relative 
weights includes data for approximately 7,417,999 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 December 31, 2021 update 
of the FY 2021 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 2023 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 2023 relative weights are 
based on the ICD-10-CM diagnosis codes and ICD-10-PCS procedure codes 
from the FY 2021 MedPAR claims data, grouped through the ICD-10 version 
of the proposed FY 2023 GROUPER (Version 40).
    The second data source used in the cost-based relative weighting 
methodology is the Medicare cost report data files from the HCRIS. In 
general, we use the HCRIS dataset that is 3 years prior to the IPPS 
fiscal year. Specifically, for this proposed rule, we used the December 
31, 2021 update of the FY 2020 HCRIS for calculating the proposed FY 
2023 cost-based relative weights. Consistent with our historical 
practice, for this FY 2023 proposed rule, we are providing the version 
of the HCRIS from which we calculated these proposed 19 CCRs on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. Click on the link on the left side of the 
screen titled ``FY 2023 IPPS Proposed Rule Home Page'' or ``Acute 
Inpatient Files for Download.''
2. Methodology for Calculation of the Relative Weights
a. General
    We continued to calculate the proposed FY 2023 relative weights 
based on 19 CCRs. The methodology we are proposing to use to calculate 
the FY 2023 MS-DRG cost-based relative weights based on claims data in 
the FY 2021 MedPAR file and data from the FY 2020 Medicare cost reports 
is as follows:
     To the extent possible, all the claims were regrouped 
using the proposed FY 2023 MS-DRG classifications discussed in sections 
II.B. and II.D. 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 2021 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

[[Page 28198]]

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 through 58842). For FY 2022 and subsequent years, 
we 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 92.9 percent of the providers in the MedPAR file 
had charges for 14 of the 19 cost centers. All claims of providers that 
did not have charges greater than zero for at least 14 of the 19 cost 
centers were deleted. In other words, a provider must have no more than 
five blank cost centers. If a provider did not have charges greater 
than zero in more than five cost centers, the claims for the provider 
were deleted.
     Statistical outliers were eliminated by removing all cases 
that were beyond 3.0 standard deviations from the geometric mean of the 
log distribution of both the total charges per case and the total 
charges per day for each MS-DRG.
     Effective October 1, 2008, because hospital inpatient 
claims include a POA indicator field for each diagnosis present on the 
claim, only for purposes of relative weight-setting, the POA indicator 
field was reset to ``Y'' for ``Yes'' for all claims that otherwise have 
an ``N'' (No) or a ``U'' (documentation insufficient to determine if 
the condition was present at the time of inpatient admission) in the 
POA field.
    Under current payment policy, the presence of specific HAC codes, 
as indicated by the POA field values, can generate a lower payment for 
the claim. Specifically, if the particular condition is present on 
admission (that is, a ``Y'' indicator is associated with the diagnosis 
on the claim), it is not a HAC, and the hospital is paid for the higher 
severity (and, therefore, the higher weighted MS-DRG). If the 
particular condition is not present on admission (that is, an ``N'' 
indicator is associated with the diagnosis on the claim) and there are 
no other complicating conditions, the DRG GROUPER assigns the claim to 
a lower severity (and, therefore, the lower weighted MS-DRG) as a 
penalty for allowing a Medicare inpatient to contract a HAC. While the 
POA reporting meets policy goals of encouraging quality care and 
generates program savings, it presents an issue for the relative 
weight-setting process. Because cases identified as HACs are likely to 
be more complex than similar cases that are not identified as HACs, the 
charges associated with HAC cases are likely to be higher as well. 
Therefore, if the higher charges of these HAC claims are grouped into 
lower severity MS-DRGs prior to the relative weight-setting process, 
the relative weights of these particular MS-DRGs would become 
artificially inflated, potentially skewing the relative weights. In 
addition, we want to protect the integrity of the budget neutrality 
process by ensuring that, in estimating payments, no increase to the 
standardized amount occurs as a result of lower overall payments in a 
previous year that stem from using weights and case-mix that are based 
on lower severity MS-DRG assignments. If this would occur, the 
anticipated cost savings from the HAC policy would be lost.
    To avoid these problems, we reset the POA indicator field to ``Y'' 
only for relative weight-setting purposes for all 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 https://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 2022, and consistent with how we have treated hospitals 
that participated in the BPCI Initiative, for FY 2023, 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

[[Page 28199]]

hospitals are still receiving IPPS payments under section 1886(d) of 
the Act. Consistent with the FY 2022 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 2020 cost report data, consistent with our 
proposed FY 2023 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 https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. 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 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 2023 proposed rule, this 
calculation was applied to address non-monotonicity for cases that 
grouped to MS-DRG 504 and MS-DRG 505, as well as MS-DRG 793 and MS-DRG 
794. 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 2023 relative weights and the changes 
in relative weights from FY 2022.
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. Effective for FY 2022, we revised 
MS-DRG 018 to include cases that report the procedure codes for CAR T-
cell and non-CAR T-cell therapies and other immunotherapies (86 FR 
44798 through 448106). We refer the reader to section II.D.17. of this 
proposed rule for discussion of the agenda items for the March 8-9, 
2022 ICD-10 Coordination and Maintenance Committee meeting relating to 
new procedure codes to describe the administration of a CAR T-cell or 
another type of gene or cellular therapy product, as well as our 
established process for determining the MS-DRG assignment for codes 
approved at the March meeting.
    For MS-DRG 018, we include a modification to our existing relative 
weight methodology to ensure that the relative weight for MS-DRG 018 
appropriately reflects the relative resources required for providing 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies 
outside of a clinical trial, while still accounting for the clinical 
trial cases in the overall average cost for all MS-DRGs. For cases that 
group to MS-DRG 018, we do not include claims determined to be clinical 
trial claims that group to MS-DRG 018 when calculating the average cost 
for 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, 
non-CAR T-cell or other immunotherapy product is purchased in the usual 
manner, but the case involves a clinical trial of a different product, 
we include the claim when calculating the average cost for MS-DRG 018 
to the extent such claims can be identified in the historical data, and 
(b) when there is expanded access use of the CAR T-cell, non-CAR T-cell 
or other immunotherapy product, 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 
calculate an adjustment to account for the CAR T-cell, non-CAR T-cell 
and other immunotherapy cases determined to be clinical trial cases, as 
described later in this proposed rule and include revenue center 891 in 
our calculation of standardized drug charges for MS-DRG 018. We refer 
the reader to the FY 2021 IPPS/LTCH PPS final rule for further 
discussion of our modifications to the relative weight calculation for 
MS-DRG 018.
    We are proposing to continue to use the same process to identify 
clinical trial claims in the FY 2021 MedPAR for purposes of calculating 
the FY 2023 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 FY 2021 MedPAR data used for this proposed 
rule. (As previously noted, effective beginning FY 2022, we revised MS-
DRG 018 to include cases that report the procedure codes for CAR T-cell 
and non-CAR T-cell therapies and other immunotherapies (86 FR 44798 
through 448106).) 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 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 all other cases to be 
assigned to MS-DRG 018
     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)

[[Page 28200]]

When the CAR T-cell, non-CAR T-cell or other immunotherapy 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 2021 
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.
    Applying this previously finalized methodology, based on the 
December 2021 update of the FY 2021 MedPAR file used for this proposed 
rule, we estimated that the average costs of cases assigned to MS-DRG 
018 that are identified as clinical trial cases ($61,356) were 20 
percent of the average costs of the cases assigned to MS-DRG 018 that 
are identified as non-clinical trial cases ($299,460). Accordingly, as 
we did for FY 2022, we are proposing to adjust the transfer-adjusted 
case count for MS-DRG 018 by applying the proposed adjustor of .20 to 
the applicable clinical trial and expanded access use immunotherapy 
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 an applicable clinical trial or expanded access use 
immunotherapy case was adjusted by .20. As we did for FY 2022, we are 
applying this same adjustor for the applicable cases that group to MS-
DRG 018 for purposes of budget neutrality and outlier simulations. We 
are also proposing to update the value of the adjustor based on more 
recent data for the final rule.
c. Proposed Averaging of Relative Weights for FY 2023
    In section I.F. of this proposed rule, we discuss our proposal to 
use the FY 2021 MedPAR data for purposes of FY 2023 IPPS ratesetting, 
with certain proposed modifications to our usual methodologies, 
including a proposed averaging approach for calculating the FY 2023 
relative weights. As discussed, we observed that COVID-19 cases were 
impacting the relative weights as calculated using the FY 2021 claims 
data for a few COVID-19-related MS-DRGs. For example, for MS-DRG 870 
(Septicemia or Severe Sepsis with MV >96 hours), the relative weight 
calculated using the FY 2021 MedPAR data was approximately 9 percent 
higher than the relative weight calculated excluding the COVID-19 cases 
in the FY 2021 data. As also discussed in that section, we believe it 
is reasonable to assume that there will be fewer COVID-19 
hospitalizations among Medicare beneficiaries in FY 2023 than there 
were in FY 2021. However, we cannot know the precise number of COVID-19 
hospitalizations among Medicare beneficiaries in FY 2023. To account 
for the anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries as compared to FY 2021, we are proposing to determine the 
MS-DRG relative weights for FY 2023 by averaging the relative weights 
as calculated with and without COVID-19 cases in the FY 2021 data, as 
described in greater detail below. Given the uncertainty in the number 
of COVID-19 hospitalizations in FY 2023, we are proposing to use 50 
percent of the relative weights calculated using all applicable cases 
in the FY 2021 claims data and 50 percent of the relative weights 
calculated without the COVID-19 cases in the FY 2021 claims data. We 
believe this proposed approach would appropriately reduce, but not 
remove entirely, the effect of COVID-19 cases on the relative weight 
calculations, consistent with our expectation that Medicare inpatient 
hospitalizations for COVID-19 will continue in FY 2023 at a lower level 
as compared to FY 2021. By averaging the relative weights in this 
manner, we believe the result would reflect a reasonable estimation of 
the case mix for FY 2023 based on the information available at this 
time, as discussed in section I.F. of the preamble to this proposed 
rule, and more accurately estimate the relative resource use for the 
cases treated in FY 2023 than if we were to calculate the proposed 
relative weights based on 100% of the relative weights as calculated 
for all applicable cases in the FY 2021 data. For this proposed rule, 
our proposed calculation is as follows:
     Step 1: Calculate a set of relative weights using all 
applicable cases in the December 2021 update of the FY 2021 MedPAR 
data, using the methodology as described earlier in this section, and 
then applying a normalization adjustment factor as described later in 
this section.
     Step 2: Calculate a set of relative weights using the 
December 2021 update of the FY 2021 MedPAR data excluding cases with a 
principal or secondary diagnosis of COVID-19 (ICD-10-CM diagnosis code 
U07.1), and otherwise using the methodology as described earlier in 
this section, and then applying a normalization adjustment factor as 
described later in this section.
     Step 3: Average the results of step 1 and step 2 to 
calculate a set of averaged relative weights, geometric mean length of 
stays, and arithmetic mean length of stays.
     Step 4: Calculate the proposed FY 2023 relative weights by 
applying an additional normalization factor to these averaged relative 
weights. This additional normalization factor is necessary to ensure 
that the average case weight as calculated in step 3 of this proposed 
averaging methodology for recalibration of the FY 2023 relative weights 
is equal to the average case weight before recalibration. We note that 
this factor is very close to 1 and is described later in this section.
    We note that in Step 5 of this proposed calculation, we apply the 
proposed 10 percent cap to the relative weights for those MS-DRGs for 
which the relative weight as calculated in Step 4 would otherwise have 
declined by more than 10 percent from the FY 2022 relative weight, as 
discussed more fully later in this section. We also note that we intend 
to update this calculation for the final rule using the March 2022 
update of the FY 2021 MedPAR file.
    The proposed relative weights, geometric mean length of stay, and 
average length of stay as calculated using this proposed methodology 
are set forth in Table 5 associated with this proposed rule, which is 
available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. We are also making available 
the relative weights, geometric mean length of stay, and average length 
of stay as calculated in steps 1 and 2 of this proposed methodology on 
our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    As discussed in section I.O. of Appendix A of this proposed rule, 
as an alternative to our proposed approach, we also considered 
calculating the FY 2023 MS-DRG relative weights based on all applicable 
cases in the FY 2021 MedPAR data, without the averaging approach we are 
proposing to account for COVID-19 cases. We note, as an example, that 
the proposed relative weight for MS-DRG 871 (Septicemia Or Severe 
Sepsis Without MV >96 Hours with MCC) as calculated using our

[[Page 28201]]

proposed averaging of the relative weights as calculated with and 
without the COVID-19 cases in the FY 2021 data is 1.9549, while the 
relative weight as calculated without this proposed averaging would be 
1.9954. We are making available supplemental information, including the 
relative weights, average length of stay, and geometric mean length of 
stay, calculated both with and without COVID-19 cases as noted 
previously. 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.
d. Proposed Cap for Relative Weight Reductions
    In the FY 2018 IPPS/LTCH PPS final rule, we summarized comments we 
had received requesting a transition period for substantial reductions 
in relative weights in order to facilitate payment stability. 
Specifically, some commenters asked CMS to establish a cap on the 
decline in a relative weight from FY 2017 to FY 2018, or a phase-in or 
multi-year transition period in cases of substantial fluctuation of 
payment rates (82 FR 38103).
    After consideration of these comments, and for the reasons 
discussed in the FY 2018 final rule, we adopted a temporary one-time 
measure for FY 2018 for MS-DRGs where the relative weight would have 
declined by more than 20 percent from the FY 2017 relative weight, 
consistent with our general authority to assign and update appropriate 
weighting factors under sections 1886(d)(4)(B) and (C) of the Act (82 
FR 38103). Specifically, for these MS-DRGs, the relative weight for FY 
2018 was set at 80 percent of the FY 2017 relative weight. In the FY 
2019 IPPS/LTCH PPS final rule, in response to similar comments, we 
adopted a temporary one-time measure for FY 2019 for an MS-DRG where 
the FY 2018 relative weight declined by 20 percent from the FY 2017 
relative weight and the FY 2019 relative weight would have declined by 
20 percent or more from the FY 2018 relative weight (83 FR 41273). 
Specifically, for an MS-DRG meeting this criterion, we set the FY 2019 
relative weight equal to the FY 2018 relative weight. In the FY 2020 
IPPS/LTCH PPS final rule, in response to similar comments, we adopted a 
temporary one-time measure for FY 2020 for an MS-DRG where the FY 2018 
relative weight declined by 20 percent from the FY 2017 relative weight 
and the FY 2020 relative weight would have declined by 20 percent or 
more from the FY 2019 relative weight, which was maintained at the FY 
2018 relative weight (84 FR 42167). Specifically, for an MS-DRG meeting 
this criterion, we set the FY 2020 relative weight equal to the FY 2019 
relative weight, which was in turn set equal to the FY 2018 relative 
weight.
    In the FY 2021 IPPS/LTCH PPS proposed rule, we noted the one-time 
measure adopted for FY 2020 and sought comment on whether we should 
consider a similar policy for FY 2021, or an alternative approach such 
as averaging the FY 2020 relative weight and the otherwise applicable 
FY 2021 relative weight for MS-DRG 215, which was the only MS-DRG 
impacted by the FY 2020 policy setting the FY 2020 relative weight 
equal to the FY 2019 relative weight. Commenters generally supported 
either setting the FY 2021 weight for MS-DRG 215 equal to the FY 2020 
relative weight or an averaging approach. Some commenters requested 
that CMS consider such an approach when the relative weight for an MS-
DRG is drastically reduced in a given year, particularly when it 
follows a significant decline in prior years. After consideration of 
comments received, and for the reasons discussed in the FY 2021 final 
rule, we set the FY 2021 relative weight for MS-DRG 215 equal to the 
average of the FY 2020 relative weight and the otherwise applicable FY 
2021 weight. With regard to the concerns raised about other MS-DRGs 
with significant reductions relative to FY 2020, we noted that these 
other MS-DRGs were low volume in our claims data, and therefore 
typically experience a greater degree of year-to-year variation. We 
acknowledged the longstanding concerns related to low volume MS-DRGs 
and stated that we would take into consideration the unique issues 
relating to such MS-DRGs and the stability of their weights for future 
rulemaking.
    We have continued to consider the comments we received in response 
to prior rulemaking recommending that CMS limit significant declines in 
the relative weights for the MS-DRGs more broadly, including by 
establishing a cap on the degree to which the relative weight for an 
MS-DRG may decline from one fiscal year to the next. For prior fiscal 
years, as previously discussed, we have adopted limited, temporary 
measures to address potentially substantial declines in the relative 
weights in certain outlier circumstances to mitigate the impacts of 
such declines. However, we have also acknowledged commenters' concerns 
related to significant reductions in the weights for other MS-DRGs, in 
particular low volume MS-DRGs. For these low volume MS-DRGs, 
fluctuations in the volume or mix of cases and/or the presence of a few 
high cost or low cost cases can have a disproportionate impact on the 
calculated relative weight, thus resulting in greater year-to-year 
variation in the relative weights for these MS-DRGs. This variation may 
reduce the predictability and stability of an individual hospital's 
Medicare payments from year-to-year. We also recognize that significant 
declines in the relative weights may occur for higher-volume MS-DRGs, 
with such fluctuations likewise affecting the predictability and 
stability of hospital payments.
    In light of these concerns, we have further considered requests 
made by commenters that we address year-to-year fluctuations in 
relative weights, particularly for low volume MS-DRGs, and to mitigate 
the financial impacts of significant fluctuations. In consideration of 
the concerns that commenters have raised about year-to-year 
fluctuations in relative weights and the financial impacts of 
significant fluctuations, we believe it would be appropriate to limit 
such fluctuations by applying a cap on reductions in the relative 
weight for an MS-DRG for a given fiscal year. Therefore, consistent 
with our statutory authority under section 1886(d)(4)(B) and (C) of the 
Act to assign and update appropriate weighting factors, we are 
proposing a permanent 10-percent cap on the reduction in a MS-DRG's 
relative weight in a given fiscal year, beginning in FY 2023. This 
proposal is consistent with our general authority to assign and update 
appropriate weighting factors as part of our annual reclassification of 
the MS-DRGs and recalibration of the relative weights under sections 
1886(d)(4)(B) and (C)(i) of the Act, as well as the requirements of 
section 1886(d)(4)(C)(iii) of the Act, which specifies that the annual 
DRG reclassification and recalibration of the relative weights be made 
in a manner that ensures that aggregate payments to hospitals are not 
affected. In addition, we have authority to implement this proposed cap 
and the associated budget neutrality adjustment under our special 
exceptions and adjustments authority at section 1886(d)(5)(I)(i) of the 
Act, which similarly gives the Secretary broad authority to provide by 
regulation for such other exceptions and adjustments to the payment 
amounts under section 1886(d) of the Act as the Secretary deems 
appropriate. As discussed, we believe this cap on declines in the 
relative weights would be appropriate in order to promote 
predictability and

[[Page 28202]]

stability in hospital payments and to mitigate the financial impacts of 
significant fluctuations in the weights. That is, by smoothing year-to-
year changes in the MS-DRG relative weights, this proposed policy would 
provide greater predictability to hospitals, allowing time to adjust to 
significant changes to relative weights. Moreover, consistent with the 
budget neutrality requirement for annual updates to the relative 
weights, including our implementation of similar caps on significant 
declines in the relative weight for prior fiscal years, we believe that 
application of this proposed 10-percent cap on relative weight 
reductions should not increase estimated aggregate Medicare payments 
beyond the payments that would be made had we never applied this cap. 
Accordingly, we are proposing to apply a budget neutrality adjustment 
to the standardized amount for all hospitals to ensure that application 
of the proposed 10-percent cap does not result in an increase or 
decrease of estimated aggregate payments. For a further discussion of 
the proposed budget neutrality adjustment, we refer readers to the 
Addendum of this proposed rule.
    Under this proposal, in cases where the relative weight for a MS-
DRG would decrease by more than 10 percent in a given fiscal year, we 
propose to limit the reduction to 10 percent for that fiscal year. For 
example, if the relative weight for an MS-DRG in FY 2022 is 1.100 and 
the relative weight for FY 2023 would otherwise be 0.9350, which would 
represent a decrease of 15 percent from FY 2022, the reduction would be 
limited to 10 percent, such that the proposed relative weight for FY 
2023 for MS-DRG XYZ would be 0.9900 (that is, 0.90 x FY 2022 weight of 
1.100). The proposed relative weights for FY 2023 as set forth in Table 
5 associated with this proposed rule and available on the CMS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS reflect the application of this proposed cap.
    As previously summarized, in the past, we have adopted a temporary 
cap of 20 percent on the decline in an MS-DRG's relative weight to 
address certain outlier circumstances. However, as also previously 
discussed, we recognize that hospitals may benefit from the phase-in of 
smaller declines in the relative weight that may nonetheless contribute 
to less stability and predictability in hospital payment rates. 
Accordingly, for purposes of this proposed permanent cap, we considered 
that a higher cap, such as the twenty percent cap that we have applied 
previously (see, for example, 82 FR 38103), would limit declines in the 
relative weights for fewer MS-DRGs (5 MS-DRGs in our analysis of FY 
2021 claims), while a lower cap, such as a five percent cap, would 
limit declines in the relative weights for more MS-DRGs (89 MS-DRGs in 
our analysis of FY 2021 claims), but with a larger associated budget 
neutrality adjustment to the standardized amount. On balance, we 
believe that a 10-percent cap would mitigate financial impacts 
resulting from significant fluctuations in the relative weights, 
particularly for low volume MS-DRGs, without the larger budget 
neutrality adjustment associated with a smaller cap. We note that this 
proposed policy would limit declines in the relative weight for 27 MS-
DRGs, based on the FY 2021 claims data used for this proposed rule.
    We note that this proposed 10-percent cap on reductions to a MS-
DRG's relative weight would apply only to a given MS-DRG with its 
current MS-DRG number. In cases where CMS creates new MS-DRGs or 
modifies the MS-DRGs as part of its annual reclassifications resulting 
in renumbering of one or more MS-DRGs, we are proposing that this limit 
on the reduction in the relative weight would not apply to any MS-DRGs 
affected by the renumbering (that is, the proposed 10 percent cap would 
not apply to the relative weight for any new or renumbered MS-DRGs for 
the fiscal year). We propose to modify the regulations at Sec.  
412.60(b) to reflect this proposed permanent cap on relative weight 
reductions. We are seeking comments on our proposal to apply a 10-
percent cap on decreases in a MS-DRG relative weight from one fiscal 
year to the next.
3. Development of Proposed National Average CCRs
    We developed the proposed national average CCRs as follows:
    Using the FY 2020 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.
    As discussed earlier in this section, we are proposing to (a) use 
50 percent of the relative weights calculated using all cases in the FY 
2021 MedPAR data and 50 percent of the relative weights calculated 
without COVID-19 cases in the FY 2021 MedPAR data to calculate the 
relative weights for FY 2023 and (b) apply a permanent 10-percent cap 
on the reduction in a MS-DRG's relative weight in a given fiscal year, 
beginning in FY 2023.
    In developing the proposed relative weights consistent with these 
proposals, we first created a set of relative weights using all 
applicable cases in the December 2021 update of the FY 2021 MedPAR 
data, using the methodology as described earlier in this section (Step 
1). These relative weights were then normalized by an adjustment factor 
of 1.947540 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.
    Next, we created a set of relative weights using the December 2021 
update of the FY 2021 MedPAR data

[[Page 28203]]

excluding cases with a principal or secondary diagnosis of COVID-19 
(ICD-10-CM diagnosis code U07.1), and otherwise using the methodology 
as described earlier in this section (Step 2). These relative weights 
were then normalized by an adjustment factor of 1.915575.
    We then averaged the results of Step 1 and Step 2 (Step 3), and 
normalized these relative weights by applying an adjustment factor of 
1.000308 (Step 4). This normalization adjustment is intended to ensure 
that this proposed averaging methodology for recalibration of the FY 
2023 relative weights neither increases nor decreases total payments 
under the IPPS, as required by section 1886(d)(4)(C)(iii) of the Act.
    Finally, we applied the proposed 10 percent cap to the relative 
weights for those MS-DRGs for which the relative weight as calculated 
in Step 4 would otherwise have declined by more than 10 percent from 
the FY 2022 relative weight (Step 5). Specifically, for those MS-DRGs 
for which the relative weight as calculated in Step 4 declined by more 
than 10 percent from the FY 2022 relative weight, we set the proposed 
FY 2023 relative weight equal to 90 percent of the FY 2022 relative 
weight. The proposed relative weights for FY 2023 as set forth in Table 
5 associated with this proposed rule and available on the CMS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS reflect the application of this proposed cap. We are 
also making available a supplemental file setting forth the relative 
weights as calculated with all cases (Step 1), excluding cases with a 
principal or secondary diagnosis of COVID-19 (Step 2), following 
application of the normalization factor and prior to the application of 
this proposed cap (Step 4), and with the application of this proposed 
cap (Step 5) along with the other supplemental files for this proposed 
rule, on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. The proposed 19 national average 
CCRs for FY 2023 are as follows:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.074

    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 
2023. Using data from the FY 2021 MedPAR file, there were 7 MS-DRGs 
that contain fewer than 10 cases. For FY 2023, 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 2022 
relative weights by the percentage change in the average weight of the 
cases in other MS-DRGs from FY 2022 to FY 2023. The crosswalk table is 
as follows.

[[Page 28204]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.075

BILLING CODE 4120-01-C

F. Add-On Payments for New Services and Technologies for FY 2023

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. The regulations at 
42 CFR 412.87 implement these provisions and Sec.  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 further discussion on the 
new technology add-on payment criteria, we refer readers to the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51572 through 51574), the 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 whether: (1) A product uses the same or a similar 
mechanism of action to achieve a therapeutic outcome; (2) a product is 
assigned to the same or a different MS-DRG; and (3) 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

[[Page 28205]]

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 2023 
are presented in a data file that is available, along with the other 
data files associated with the FY 2022 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 2024 are 
presented in a data file that is available on the CMS website, along 
with the other data files associated with the FY 2023 proposed rule, by 
clicking on the FY 2023 IPPS proposed rule home page at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized our proposal 
to use the FY 2019 MedPAR claims data where we ordinarily would have 
used the FY 2020 MedPAR claims data for purposes of FY 2022 
ratesetting. Consistent with that final policy, we finalized our 
proposal to use the FY 2019 claims data to set the thresholds for 
applications for new technology add-on payments for FY 2023. We note 
that, for the reasons discussed in section I.F. of the preamble of this 
proposed rule, we are proposing to use the FY 2021 MedPAR claims data 
for FY 2023 ratesetting, with certain proposed modifications to our 
relative weight setting and outlier methodologies. Consistent with this 
proposal, for the FY 2024 proposed threshold values, we are proposing 
to use the FY 2021 claims data to set the proposed thresholds for 
applications for new technology add-on payments for FY 2024. In 
addition, as discussed in section III.E.1.c. of this proposed rule, we 
are proposing to use an averaging approach for calculating the FY 2023 
relative weights, to account for the anticipated decline in COVID-19 
hospitalizations of Medicare beneficiaries as compared to FY 2021. 
Specifically, we are proposing to average the relative weights as 
calculated with and without COVID-19 cases in the FY 2021 data to 
determine the MS-DRG relative weights for FY 2023. Certain steps of 
calculating the thresholds for applications for new technology add-on 
payments use the same charge data that is used to calculate the MS-DRG 
weights. As a result, different average charges per MS-DRG are 
calculated using the charge data for the relative weights as calculated 
with and without COVID-19 cases. Therefore, for purposes of calculating 
the FY 2024 thresholds, we are also proposing to average the data in 
the steps of the calculation that use charge data from the calculation 
of the MS-DRG weights. In addition, as discussed in section III.E.1.c. 
of this proposed rule, we are also considering, as an alternative to 
our proposal, calculating the FY 2023 MS-DRG relative weights without 
this proposed averaging approach to account for COVID-19 cases. In 
connection with this alternative approach, we are making available the 
threshold values as calculated without this averaged data on the ``FY 
2023 Proposed Rule Homepage'' at https://www.cms.gov/medicare/medicare-
fee-for-service-payment/acuteinpatientpps, as well as other 
supplemental files as discussed further in section I.O. of Appendix A 
of this proposed rule.
    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 further 
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,

[[Page 28206]]

relative to services or technologies previously available, the 
diagnosis or treatment of Medicare beneficiaries means--
    ++ The new medical service or technology offers a treatment option 
for a patient population unresponsive to, or ineligible for, currently 
available treatments;
    ++ The new medical service or technology offers the ability to 
diagnose a medical condition in a patient population where that medical 
condition is currently undetectable, or offers the ability to diagnose 
a medical condition earlier in a patient population than allowed by 
currently available methods, and there must also be evidence that use 
of the new medical service or technology to make a diagnosis affects 
the management of the patient;
    ++ The use of the new medical service or technology significantly 
improves clinical outcomes relative to services or technologies 
previously available as demonstrated by one or more of the following: A 
reduction in at least one clinically significant adverse event, 
including a reduction in mortality or a clinically significant 
complication; a decreased rate of at least one subsequent diagnostic or 
therapeutic intervention; a decreased number of future hospitalizations 
or physician visits; a more rapid beneficial resolution of the disease 
process treatment including, but not limited to, a reduced length of 
stay or recovery time; an improvement in one or more activities of 
daily living; an improved quality of life; or, a demonstrated greater 
medication adherence or compliance; or
    ++ The totality of the circumstances otherwise demonstrates that 
the new medical service or technology substantially improves, relative 
to technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
     Evidence from the following published or unpublished 
information sources from within the United States or elsewhere may be 
sufficient to establish that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries: Clinical trials, peer reviewed journal 
articles; study results; meta-analyses; consensus statements; white 
papers; patient surveys; case studies; reports; systematic literature 
reviews; letters from major healthcare associations; editorials and 
letters to the editor; and public comments. Other appropriate 
information sources may be considered.
     The medical condition diagnosed or treated by the new 
medical service or technology may have a low prevalence among Medicare 
beneficiaries.
     The new medical service or technology may represent an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of a 
subpopulation of patients with the medical condition diagnosed or 
treated by the new medical service or technology.
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule for 
additional discussion of the evaluation of substantial clinical 
improvement for purposes of new technology add-on payments under the 
IPPS.
    We note, consistent with the discussion in the FY 2003 IPPS final 
rule (67 FR 50015), that although we do not question FDA's regulatory 
responsibility for decisions related to marketing authorization (for 
example, approval, clearance, etc.), we do not rely upon FDA criteria 
in our evaluation of substantial clinical improvement for purposes of 
determining what drugs, devices, or technologies qualify for new 
technology add-on payments under Medicare. This criterion does not 
depend on the standard of safety and effectiveness on which FDA relies 
but on a demonstration of substantial clinical improvement in the 
Medicare population.
b. 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 FDA as a Qualified Infectious Disease Product (QIDP), 
and, beginning with FY 2022, a drug that is approved by 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 further 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 reviews the application based on the 
information provided by the applicant only under the alternative 
pathway specified by the applicant at the time of application 
submission. 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 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. 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 requirements of Sec.  412.87(c). We note 
that 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 further 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 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

[[Page 28207]]

treatment of Medicare beneficiaries. Under this alternative pathway for 
QIDPs and LPADs, a medical product that has received FDA marketing 
authorization and is designated by FDA as a QIDP or approved under the 
LPAD pathway will need to meet the requirements of Sec.  412.87(d).
    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 further 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.
c. 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 
further 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.
d. 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 regulation 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/LTCH PPS 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/LTCH PPS 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

[[Page 28208]]

eligible antimicrobial products would begin receiving the new 
technology add-on payment sooner, effective for discharges the quarter 
after the date of FDA marketing authorization provided that the 
technology receives FDA marketing authorization by July 1 of the 
particular fiscal year for which the applicant applied for new 
technology add-on payments.
e. New Technology Liaisons
    Many stakeholders (including device/biologic/drug developers or 
manufacturers, industry consultants, others) engage CMS for coverage, 
coding, and payment questions or concerns. In order to streamline 
stakeholder engagement by centralizing the different innovation 
pathways within CMS including new technology add-on payments, CMS has 
established a team of new technology liaisons that can serve as an 
initial resource for stakeholders. This team is available to assist 
with all of the following:
     Help to point stakeholders to or provide information and 
resources where possible regarding process, requirements, and 
timelines.
     Coordinate and facilitate opportunities for stakeholders 
to engage with various CMS components.
     Serve as a primary point of contact for stakeholders and 
provide updates on developments where possible or appropriate.
    We received many questions from stakeholders interested in pursuing 
new technology add-on payments who may not be entirely familiar with 
working with CMS. While we encourage stakeholders to first review our 
resources available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech, we know that there may be 
additional questions about the application process. Stakeholders with 
further questions about Medicare's coverage, coding, and payment 
processes, and about how they can navigate these processes, whether for 
new technology add-on payments or otherwise, can contact the new 
technology liaison team at [email protected].
f. Application Information for New Medical Services or Technologies
    Applicants for add-on payments for new medical services or 
technologies for FY 2024 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. CMS will review the application based on 
the information provided by the applicant under the pathway specified 
by the applicant at the time of application submission. 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 2024, 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 Paper 
Reduction Act (PRA) and approved under OMB control number 0938-1347, 
and has an expiration date of 11/30/2023.
    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, with an 
expiration date of November 30, 2023. 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. The process for evaluating new medical service 
and technology applications requires the Secretary to do all of the 
following:
     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.
     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 2023 prior 
to publication of the FY 2023 IPPS/LTCH PPS proposed rule, we published 
a notice in the Federal Register on September 24, 2021 (86 FR 53056), 
and held a virtual town hall meeting on December 14, 2021. In the 
announcement notice for the meeting, we stated that the opinions and 
presentations provided during the meeting would assist us in our 
evaluations of applications by allowing public discussion of the 
substantial clinical improvement criterion for the FY 2023 new medical 
service and technology add-on payment applications before the 
publication of the FY 2023 IPPS/LTCH IPPS proposed rule.
    Approximately 378 individuals registered to attend the virtual town 
hall meeting. We posted the recordings of the 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 27, 2021, 
deadline, in our evaluation of the new technology add-on payment 
applications for FY 2023 in the development of this FY 2023 IPPS/

[[Page 28209]]

LTCH PPS proposed rule. In response to the published notice and the 
December 14, 2021, New Technology Town Hall meeting, we received 
written comments regarding the applications for FY 2023 new technology 
add on payments. As explained earlier and in the Federal Register 
notice announcing the New Technology Town Hall meeting (86 FR 53056 
through 53059), 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 2023. Therefore, we 
are not summarizing those written comments in this proposed rule that 
are unrelated to the substantial clinical improvement criterion. In 
section II.F.6. 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.
    As discussed in more detail in section II.F.8. of the preamble of 
this proposed rule, we are proposing to use NDCs instead of ICD-10-PCS 
Section ``X'' codes to identify cases involving the use of therapeutic 
agents approved for new technology add-on payments beginning with a 
transitional period in FY 2023. We refer the reader to section II.F.8. 
of the preamble of this proposed rule for a full discussion of this 
proposal.
4. New COVID-19 Treatments Add-On Payment (NCTAP)
    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 71157 
through 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.
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized a change to 
our policy to extend NCTAP through the end of the FY in which the PHE 
ends for all eligible products 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 also finalized that, for a 
drug or biological product eligible for NCTAP that is also approved for 
new technology add-on payments, we will reduce the NCTAP for an 
eligible case by the amount of any new technology add-on payments so 
that we do not create a financial disincentive between technologies 
eligible for both the new technology add-on payment and NCTAP compared 
to technologies eligible for NCTAP only (85 FR 45162).
    Further information about NCTAP, including updates and a list of 
currently eligible drugs and biologicals, is available on the CMS 
website at https://www.cms.gov/medicare/covid-19/new-covid-19-treatments-add-payment-nctap.
5. Proposed FY 2023 Status of Technologies Receiving New Technology 
Add-On Payments for FY 2022
    In this section of the proposed rule, we discuss the proposed FY 
2023 status of 37 technologies approved for FY 2022 new technology add-
on payments, including 2 technologies approved for 2 separate add-on 
payments for different indications (RECARBRIOTM and 
FETROJA[supreg]), 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 note that, as 
discussed later in this section, we provided a 1-year extension of new 
technology add-on payments for FY 2022 for 13 technologies for which 
the new technology add-on payment would otherwise be discontinued 
beginning in FY 2022 using our authority under section 1886(d)(5)(I) of 
the Act.
    Additionally, we note that we conditionally approved CONTEPO for FY 
2022 new technology add-on payments under the alternative pathway for 
certain antimicrobial products (86 FR 45155), subject to the technology 
receiving FDA marketing authorization by July 1, 2022. As of the time 
of the development of this proposed rule, CONTEPO has not yet received 
FDA approval. If CONTEPO 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 
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 CONTEPO for FY 2022. If CONTEPO receives FDA marketing 
authorization prior to July 1, 2022, we are proposing to continue 
making new technology add-on payments for CONTEPO for FY 2023. If 
CONTEPO does not receive FDA marketing authorization by July 1, 2022, 
then it would not be eligible for new technology add-on payments for FY 
2022, and therefore would not be eligible for the continuation of new 
technology add-on payments for FY 2023. We further note that the 
applicant for CONTEPO did not submit an application for FY 2023 new 
technology add on payments and, therefore, the technology also would 
not be eligible for approval or conditional approval for

[[Page 28210]]

new technology add-on payments for FY 2023.
a. Proposed FY 2023 Status of Technologies Approved for FY 2022 New 
Technology Add-On Payments
    As noted previously, we used our authority under section 
1886(d)(5)(I) of the Act to allow a 1-year extension of new technology 
add-on payments for FY 2022 for 13 technologies for which the add-on 
payments would otherwise be discontinued beginning in FY 2022 because 
the technologies would no longer be considered ``new'' for FY 2022. In 
this section, we discuss the proposed FY 2023 status for the remaining 
24 technologies approved for FY 2022 new technology add-on payments. 
Specifically, we present our proposals to continue the new technology 
add-on payment for FY 2023 for those technologies that were approved 
for the new technology add-on payment for FY 2022 and which would still 
be considered ``new'' for purposes of new technology add-on payments 
for FY 2023. We also present our proposals to discontinue new 
technology add-on payment for FY 2023 for those technologies that were 
approved for the new technology add-on payment for FY 2022 and which 
would no longer be considered ``new'' for purposes of new technology 
add-on payments for FY 2023.
    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 following table lists the technologies for which we are 
proposing to discontinue making new technology add-on payments for FY 
2023 because they are no longer ``new'' for purposes of new technology 
add-on payments. This table also presents the newness start date, new 
technology add-on payment start date, the 3-year anniversary date of 
the product's entry onto the U.S. market, relevant final rule citations 
from prior fiscal years, and coding assignments for each technology. 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.
    We are inviting public comments on our proposals to discontinue new 
technology add-on payments for FY 2023 for the technologies listed in 
the Table BBBB-A1.
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    Table II.F.-02 lists the technologies for which we are proposing to 
continue making new technology add-on payments for FY 2023 because they 
are still 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, 3-year anniversary date of the 
product's entry onto the U.S. market, relevant final rule citations 
from prior

[[Page 28212]]

fiscal years, proposed maximum add-on payment amount, and coding 
assignments for each technology. 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.
    We note, as discussed in the FY 2022 IPPS/LTCH PPS final rule (86 
FR 45104 through 45107), on May 1, 2020, VEKLURY[supreg] (remdesivir) 
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. 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. 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. In the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45107), we determined that VEKLURY[supreg] meets the 
newness criterion with an indication for use in adults and pediatric 
patients (12 years of age and older and weighing at least 40 kg) for 
the treatment of COVID-19 requiring hospitalization. We stated that 
consistent with our longstanding policy, we considered the newness 
period for VEKLURY[supreg] to begin on October 22, 2020, when the NDA 
for VEKLURY[supreg] was approved by FDA 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. We also discussed 
comments solicited regarding the newness period for products available 
through an EUA for COVID-19 in section II.F.7. of the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45159 through 45160), including comments we 
received regarding the potential variability in cost estimates for 
technologies available under an EUA due to government price subsidies 
or variable treatment practices in the context of the global pandemic 
and comments suggesting that CMS monitor pricing changes for products 
available under an EUA once a product receives full marketing 
authorization, instead of basing the newness period on data that may 
have become available under an EUA, and indicated that we would 
consider these comments for future rulemaking.
    After further review of the information provided by the applicant, 
we believe that additional information related to VEKLURY[supreg]'s 
commercial availability is relevant to assessing the start of the 
newness period for VEKLURY[supreg]. The applicant stated that once 
VEKLURY[supreg] was issued an EUA, from May through June 2020, the 
entire existing supply of VEKLURY[supreg] was donated worldwide and 
distributed to hospitals free of charge.\26\ The applicant further 
stated that the commercial list price of the technology was announced 
when it entered into the agreement with the U.S. Government previously 
described, in anticipation of the post-donation phase. Under this 
agreement, the U.S. Government allocated VEKLURY[supreg] to each 
hospital, and the hospitals would then choose to purchase quantities of 
VEKLURY[supreg] directly from the applicant's subsidiary who was the 
sole distributor.27 28
---------------------------------------------------------------------------

    \26\ https://stories.gilead.com/articles/an-update-on-covid-19-from-our-chairman-and-ceo.
    \27\ Remdesivir for the Commercial Marketplace. https://www.phe.gov/emergency/events/COVID19/investigation-MCM/Pages/factsheet.aspx.
    \28\ Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response (ASPR). 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.
---------------------------------------------------------------------------

    We continue to believe this issue is complex, particularly as it 
relates to VEKLURY[supreg] as a technology that has been available 
under both an EUA and an NDA. As discussed in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45159 through 45160), while an EUA is not marketing 
authorization within the meaning of Sec.  412.87(e)(2) for purposes of 
eligibility for new technology add-on payments, 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. In the case of VEKLURY[supreg], we believe that 
there may be unique considerations in determining the start of the 
newness period in light of the donation period, during which the 
technology was distributed at no cost. Accordingly, while we continue 
to believe that data reflecting the costs of a product that has 
received an EUA could become available as soon as the date of EUA 
issuance for that product, we believe that with respect to 
VEKLURY[supreg], such data may not have become available until after 
the end of the donation period, when the technology became commercially 
available, on July 1, 2020. For these reasons, after further 
consideration, we believe the newness period for VEKLURY[supreg] may 
more appropriately begin on July 1, 2020, the date on which the 
technology became available for sale under the allocation agreement. We 
note that VEKLURY[supreg] would still be considered new for FY 2023 
regardless of whether the newness period began on May 1 (the date of 
the EUA), July 1 (the date the donation phase ended), October 22 (the 
date of the NDA), or some other date in between, as in all cases the 
three-year anniversary date would occur after April 1, 2023, and 
therefore the product would remain eligible for FY 2023 new technology 
add-on payments.
    Therefore, as reflected in the table that follows, we are proposing 
to continue new technology add-on payments for VEKLURY[supreg] for FY 
2023. We invite public comments on this proposal, including the newness 
start date for VEKLURY[supreg]. As discussed, while we continue to 
believe that data reflecting the costs of a product that has received 
an EUA could become available as soon as the date of EUA issuance for 
that product, we also recognize that there may be unique considerations 
in determining the start of the newness period for a product available 
under an EUA. We are continuing to consider the comments as discussed 
in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45159) regarding the 
newness period for products available through an EUA for COVID-19, and 
we welcome additional comments in this proposed rule.
    We further note that we are proposing to continue new technology 
add-on payments for Caption Guidance for FY 2023, 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.
    We are inviting public comments on our proposals to continue new 
technology add-on payments for FY 2023 for the technologies listed in 
the following table.
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b. Status of Technologies Provided a One-Year Extension of New 
Technology Add-On Payments in FY 2022
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44789), 
our goal is always to use the best available data overall for 
ratesetting. The best available MedPAR data would typically 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.
    In the FY 2022 IPPS/LTCH PPS final rule, for the reasons discussed, 
we finalized that we would use FY 2019 MedPAR data instead of FY 2020 
MedPAR data to develop the FY 2022 MS-DRG relative weights (86 FR 44789 
through 44793). Because we finalized that we would use FY 2019 MedPAR 
data instead of FY 2020 MedPAR data for the development of the FY 2022 
MS-DRG relative weights, we stated that 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 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 this final policy, we 
finalized our proposal to use our authority under section 1886(d)(5)(I) 
of the Act to allow for a 1-year extension of new technology add-on 
payments for FY 2022 for 13 technologies (see table below) for which 
the new technology add-on payment would have otherwise been 
discontinued beginning with FY 2022. We refer the reader to the FY 2022 
IPPS/LTCH PPS final rule (86 FR 44975 through 44979) for a complete 
discussion regarding this 1-year extension for FY 2022.
    For FY 2023 ratesetting, as we discuss in section I.F. of this 
proposed rule, we believe the best available data would be the FY 2021 
MedPAR file. As discussed in section I.F. of this proposed rule, for FY 
2023, we are proposing to use the FY 2021 MedPAR (the best available 
data at the time of this proposed rule) for FY 2023 ratesetting, 
including for purposes of developing the FY 2023 relative weights. We 
refer the reader to section I.F. of this proposed rule for a complete 
discussion regarding our proposal to use the FY 2021 MedPAR for the FY 
2023 ratesetting and recalibration of the FY 2023 MS-DRG relative 
weights.
    As noted previously, 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. For FY 2023, because we are 
proposing to use FY 2021 MedPAR data to recalibrate the FY 2023 MS-DRG 
relative weights, we believe the costs of the 13 technologies in the 
following table, for which the 3-year anniversary date of the product's 
entry onto the U.S. market occurs prior to FY 2023 (and therefore are 
no longer ``new''), may now be fully reflected in the MedPAR data used 
to recalibrate the MS-DRG relative weights for FY 2023. As a result, we 
are proposing to discontinue new technology add on payments for these 
13 technologies in FY 2023.
    We are inviting public comments on our proposals to discontinue new 
technology add-on payments for FY 2023 for these 13 technologies listed 
in Table BBBB-A3.
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6. FY 2023 Applications for New Technology Add-On Payments (Traditional 
Pathway)
    We received 18 applications for new technology add-on payments for 
FY 2023 under the traditional new technology add-on payment pathway. In 
accordance with the regulations under Sec.  412.87(e), applicants for 
new technology add-on payments must have received 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. Five applicants 
withdrew their applications prior to the issuance of this proposed 
rule. We are addressing the remaining 13 applications.
a. CARVYKTITM (ciltacabtagene autoleucel)
    Janssen Biotech, Inc., submitted an application for new technology 
add-on payments for CARVYKTITM (ciltacabtagene autoleucel) 
for FY 2023. CARVYKTITM 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. We 
note that Janssen Biotech, Inc. previously submitted an application for 
new technology add-on payments for CARVYKTITM for FY 2022 
under the name ciltacabtagene autoleucel, as summarized in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25233 through 25239), but withdrew 
that application prior to the issuance of the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44979).
    The applicant stated that 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 LCAR-B38M are representative of the same CAR 
T-cell therapy, ciltacabtagene autoleucel.
    Multiple myeloma is an incurable blood cancer that affects a type 
of white blood cell called plasma cells.\29\ Plasma cells, found in 
bone marrow, make the antibodies that help the body attack and kill 
various pathogens. According to the applicant, when damaged, malignant 
plasma cells rapidly spread and replace the normal cells in the bone 
marrow.\30\ The applicant asserted the median age of onset is 69 years 
old and only 3% of patients are less than 45 at the age of diagnosis; 
it was estimated that in 2021 nearly 35,000 people would be diagnosed 
and more than 12,000 will die from multiple myeloma in the US.\31\ 
According to the applicant, multiple myeloma is associated with 
substantial morbidity and mortality \32\ and median 5 year survival is 
56%.\33\
---------------------------------------------------------------------------

    \29\ Ho, M., Chen, T., Liu, J. et al. Targeting histone 
deacetylase 3 (HDAC3) in the bone marrow microenvironment inhibits 
multiple myeloma proliferation by modulating exosomes and IL-6 
trans-signaling. Leukemia 34, 196-209 (2020). https://doi.org/10.1038/s41375-019-0493-x.
    \30\ Utley A, Lipchick B, Lee KP, Nikiforov MA. Targeting 
Multiple Myeloma through the Biology of Long-Lived Plasma Cells. 
Cancers (Basel). 2020 Jul 30;12(8):2117.
    \31\ Surveillance, Epidemiology, and End Results (SEER) Program. 
SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
    \32\ 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.
    \33\ SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
---------------------------------------------------------------------------

    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) (for example, bortezomib, carfilzomib, and 
ixazomib), histone deacetylase inhibitors (for example, panobinostat, 
vorinostat), immunomodulatory agents (IMiD) (for example, 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 PI), lenalidomide (an IMiD) and 
dexamethasone.\34\ According to the applicant, 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.\35\ However, 
despite these treatments, according to the applicant, most patients 
will relapse after first-line treatment and require further treatment 
\36\ with only 50% survival of relapsed patients after 5 
years.37 38 The applicant stated that 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.\39\ 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.
---------------------------------------------------------------------------

    \34\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021--
September 9, 2020.
    \35\ Branagan A, Lei M, Lou U, Raje N. Current Treatment 
Strategies for Multiple Myeloma. JCO Oncol Pract. 2020 Jan;16(1):5-
14.
    \36\ Sonneveld P, Broij lA. Treatment of relapsed and refractory 
multiple myeloma. Haematologica. 2016;101(4):396-406.
    \37\ SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
    \38\ Global Cancer Observatory. GLOBOCAN database 2018; https://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf.
    \39\ 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 asserted that relapsed and refractory (r/r) 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.40 41 The applicant stated the introduction of 
a new class of agents, CD38-targeting monoclonal antibodies (CD38 
MoAbs), daratumumab and isatuximab, have improved options in r/r 
patients.\42\ The applicant asserted 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 include triplet and quadruplet regimens, 
creating a complex treatment landscape.\43\ According to the applicant, 
while triplet regimens should be used as the standard therapy for 
patients with

[[Page 28219]]

multiple myeloma, elderly or frail patients may be treated with double 
regimens.\44\ The applicant further states that for patients with RRMM 
who have received at least three 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.\45\
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    \40\ 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.
    \41\ Nooka AK, Kastritis E, Dimopoulos MA, Lonial S. Treatment 
options for relapsed and refractory multiple myeloma. Blood. 2015 
May 14;125(20):3085-99.
    \42\ 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.
    \43\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021--
September 9, 2020.
    \44\ Ibid.
    \45\ 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.\46\ The applicant further stated that novel, innovative 
therapies are needed to improve long-term survival and outcomes. The 
applicant asserted 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 asserted that 
CARVYKTITM is an autologous CAR T-cell therapy directed 
against B cell maturation antigen (BCMA) for the treatment of patients 
with multiple myeloma. The applicant stated that BCMA, a protein that 
is highly expressed on myeloma cells \47\ 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.48 49 The applicant stated 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.50 51 52 According to the applicant, these expression 
characteristics make BCMA an ideal therapeutic target for the treatment 
of multiple myeloma.53 54 CARVYKTITM, 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.
---------------------------------------------------------------------------

    \46\ Rajkumar SV, Kumar S. Multiple myeloma current treatment 
algorithms. Blood Cancer J. 2020 Sep 28;10(9):94.
    \47\ 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.
    \48\ 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.
    \49\ Tai YT, Anderson KC. Targeting B-cell maturation antigen in 
multiple myeloma. Immunotherapy. 2015;7(11):1187-99.
    \50\ 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.
    \51\ Tai YT, Anderson KC. Targeting B-cell maturation antigen in 
multiple myeloma. Immunotherapy. 2015;7(11):1187-99.
    \52\ Palaiologou M, Delladetsima I, Tiniakos D. CD138 (syndecan-
1) expression in health and disease. Histol Histopathol. 2014 
Feb;29(2):177-89.
    \53\ Ibid
    \54\ 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 asserted 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. According to the 
applicant, a sample of the patient's T cells are collected from the 
blood, then modified in a laboratory setting to express a CAR.\55\ The 
applicant stated 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.\56\ According to the 
applicant, the binding domain expressed on the surface of T cells gives 
them the new ability to target a specific protein. The applicant 
stated, when the target is recognized, the intracellular portions of 
the receptor send signals within the T cells to destroy the target 
cells. The applicant asserted 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.
---------------------------------------------------------------------------

    \55\ June CH, Sadelain M. Chimeric Antigen Receptor Therapy. N 
Engl J Med. 2018 Jul 5;379(1):64-73.
    \56\ Sadelain M. Chimeric antigen receptors: driving immunology 
towards synthetic biology. Curr Opin Immunol. 2016 Aug;41:68-76.
---------------------------------------------------------------------------

    According to the applicant, CARVYKTITM is a CAR T-cell 
immunotherapy designed to recognize myeloma cells and target their 
destruction. According to the applicant, CARVYKTITM'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 asserted that, unlike the chimeric antigen receptor design of 
currently approved CAR T-cell immunotherapies, which are composed of a 
single-domain antibody (sdAbs), CARVYKTITM is composed of 
two antibody binding domains that allow for high recognition of human 
BCMA (CD269) and elimination of BCMA expressing myeloma cells. 
According to the applicant, the two distinct BCMA-binding domains 
confer avidity and distinguish CARVYKTITM from other BCMA-
targeting products. The applicant stated the BCMA binding domains are 
linked to the receptor's interior costimulatory (4-1BB) and signaling 
(CD3[zeta]) domains through a transmembrane linker (CD8a). The 
applicant asserted these intracellular domains are critical components 
for T cell growth and anti-tumor activity \57\ in the body once CAR T-
cells are bound to a BCMA target on multiple myeloma cells.
---------------------------------------------------------------------------

    \57\ 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, 
CARVYKTITM was granted Breakthrough Therapy designation in 
December 2019 for the treatment of adult patients with relapsed or 
refractory multiple myeloma, who previously received a proteasome 
inhibitor, an immunomodulatory agent, and an anti-CD38 antibody. Per 
the applicant, FDA approved the Biologics License Application (BLA) for 
CARVYKTITM on February 28, 2022 for the treatment of adult 
patients with relapsed or refractory multiple myeloma after four or 
more prior lines of therapy, including a proteasome inhibitor, an 
immunomodulatory agent, and an anti-CD38 monoclonal antibody. The 
applicant stated that procedures involving the administration of 
CARVYKTITM can be uniquely identified using the following 
ICD-10-PCS procedure codes: XW033A7 (Introduction of ciltacabtagene 
autoleucel into peripheral vein, percutaneous approach, new technology 
group 7) and XW043A7 (Introduction of ciltacabtagene autoleucel into 
central vein, percutaneous approach, new technology group 7). The 
applicant also noted that they will submit a request for a Healthcare 
Common Procedure Coding

[[Page 28220]]

System (HCPCS) code specific to the administration of 
CARVYKTITM 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 asserted that 
CARVYKTITM 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. The applicant 
asserted that ABECMA[supreg] also targets BCMA, but does so by binding 
to a single BCMA domain. In addition to detail provided in the 
applicant's FY 2022 application (as discussed in 86 FR 25235 through 
25236), the applicant asserted that CARVYKTITM differs 
significantly from ABECMA[supreg] and other BCMA-targeting agents, 
including Blenrep, because it targets BCMA with two distinct binding 
domains. According to the applicant, the distinct BCMA-binding moieties 
confer avidity and distinguish CARVYKTITM from other BCMA 
CAR T-cell constructs providing a novel mechanism of action.\58\ The 
applicant added, the 4-1BB and CD3z domains on the CAR optimize T cell 
activation and proliferation.\59\ According to the applicant, non-
clinical pharmacology and toxicology have been used to characterize the 
biological activity and mechanism of action of CARVYKTITM 
and confirm the on-target specificity to BCMA through (1) in vitro 
binding characterization; (2) in vitro co-culture assays to assess CAR 
T-cell cytotoxicity and cytokine release; (3) in vivo efficacy studies 
in mice with human CAR T- cells; and (4) an in vivo safety study. 
According to the applicant, because CARVYKTITM has a novel 
mechanism of action with two distinct BCMA-binding domains that confer 
binding avidity and unprecedented clinical activity compared with other 
novel anti-myeloma treatments in comparable study populations, it is 
unlike any existing technology utilized to treat relapsed/refractory 
multiple myeloma.
---------------------------------------------------------------------------

    \58\ Xu J, Chen LJ, Yang SS, Sun Y, Wu W, Liu YF, Xu J, Zhuang 
Y, Zhang W, Weng XQ, Wu J, Wang Y, Wang J, Yan H, Xu WB, Jiang H, Du 
J, Ding XY, Li B, Li JM, Fu WJ, Zhu J, Zhu L, Chen Z, Fan XF, Hou J, 
Li JY, Mi JQ, Chen SJ. Exploratory trial of a biepitopic CAR T-
targeting B cell maturation antigen in relapsed/refractory multiple 
myeloma. Proc Natl Acad Sci U S A. 2019 May 7;116(19):9543-9551.
    \59\ Weinkove R, George P, Dasyam N, McLellan AD. Selecting 
costimulatory domains for chimeric antigen receptors: functional and 
clinical considerations. Clin Transl Immunology. 2019 May 
11;8(5):e1049.
---------------------------------------------------------------------------

    With regard to whether a product is assigned to the same DRG when 
compared to an existing technology, the applicant asserted that because 
CMS has suggested that all inpatient hospitalizations involving a CAR 
T-cell treatment will be assigned to DRG 018 (Chimeric Antigen Receptor 
(CAR) T-Cell and Other Immunotherapies), CARVYKTITM is 
expected to be assigned to the same DRG as other multiple myeloma cases 
treated with a CAR T-cell therapy. We note that the DRG assignment was 
finalized to Pre-MDC MS-DRG 018, effective October 1, 2022 and is 
reflected in the V39.1 ICD-10 MS-DRG Grouper effective April 1, 2022 
(86 FR 58021).\60\
---------------------------------------------------------------------------

    \60\ CMS Manual System, Pub 100-04 Medicare Claims Processing, 
Transmittal 11255. February 4, 2022; https://www.cms.gov/files/document/r11255cp.pdf.
---------------------------------------------------------------------------

    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 in its application that CARVYKTITM is 
indicated for a broader population than other available therapies, 
specifically multiple myeloma patients having received three prior 
therapies. The applicant asserted in its application that Blenrep and 
ABECMA[supreg] are indicated only for those with at least 4 prior 
therapies whereas CARVYKTITM had a proposed indication for 
the treatment of patients with 3 or more prior therapies. According to 
the applicant, CARVYKTITM could potentially be used in a 
broader multiple myeloma population, that includes patients after 3 
prior therapies as opposed to 4 for Blenrep and ABECMA[supreg].
    According to the applicant, FDA is currently reviewing the 
registrational trial CARTITUDE 1. The applicant stated that in this 
trial, 17% (a total of 17 patients) of patients had only three prior 
lines of therapy; results were presented at the American Society of 
Hematology (ASH) 2021 meeting on fourth line patients. The applicant 
stated that among those with three prior lines of therapy, the response 
rate was 100%, the median duration of response (DoR) was 21.8 months, 
minimal residual disease (MRD) negativity was found in 80%, the 18-
month progression free survival (PFS) was 75.6%, and the 18-month 
overall survival (OS) was 88.2 months. According to the applicant, 
because the sample size was small (17), median endpoints may not be as 
rigorous as in the larger population.
    According to the applicant, the distinction between three and four 
previous lines of therapy is important. The applicant asserted with 
each subsequent therapy patients generally become frailer and their 
prognosis worsens. The applicant stated that studies comparing fourth 
line to fifth line are not as common as trials studying earlier lines, 
but in a real-world study by Yong et al. the percent of myeloma 
patients who were able to move from third line therapy to fourth line 
was 15% of all diagnosed myeloma patients, and only 1% of patients 
moved to a fifth line.\61\ The applicant added that in the same study 
of those patients in first line therapy, approximately 90% of patients 
were able to discontinue treatment due to remission and/or planned end 
of treatment while only 13% of those in fifth line ended treatment due 
to stable disease/remission.
---------------------------------------------------------------------------

    \61\ Yong et al. 2016. Multiple Myeloma: Patient outcomes in 
real-world practice. British Journal of Haematology, 175; 252-264. 
doi: 10.1111/bjh.14213.
---------------------------------------------------------------------------

    The applicant asserted that for these reasons, 
CARVYKTITM does not meet the third criterion and is 
therefore a new technology with regards to the population having been 
studied and being targeted for use.
    In summary, the applicant asserted that CARVYKTITM meets 
the newness criterion because it is not substantially similar to other 
available therapies due to its 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. As we stated in the FY 2022 proposed 
rule (86 FR 25236), we note that CARVYKTITM may have a 
similar mechanism of action to that of ABECMA[supreg]. We note 
ABECMA[supreg] received approval for new technology add-on payments for 
FY 2022 for the treatment of adult patients with RRMM after four or 
more prior lines of therapy, including an immunomodulatory agent, a 
proteasome inhibitor, and an anti-CD38 monoclonal antibody (86 FR 45028 
through 45035). Although the number of BCMA binding domains of 
CARVYKTITM and ABECMA[supreg] differ, it appears that the 
mechanism of action for both therapies is the binding to BCMA by a CAR

[[Page 28221]]

construct, which results in T-cell activation and killing of malignant 
myeloma cells. We note that the applicant asserted that 
CARVYKTITM's mechanism of action is unique due to its dual 
binding domain which affects the therapy's clinical activity, as 
compared to existing technologies with a single binding domain. 
However, we are unclear how the additional BCMA binding domain 
represents a change in the mechanism of action of this therapy, or if 
it may instead relate to an assessment of whether the technology meets 
the substantial clinical improvement criterion. Because of the 
potential similarity with the BCMA antigen and other actions, we 
believe that the mechanism of action for CARVYKTITM may be 
the same or similar to that of ABECMA[supreg].
    We note that the applicant stated that CARVYKTITM may 
serve a new patient population if approved as a fourth line treatment, 
as existing treatments are approved for fifth line treatment. However, 
we note that CARVYKTITM's recent approval states that it is 
indicated for fifth line treatment and we therefore question whether 
CARVYKTITM treats a new patient population.\62\
---------------------------------------------------------------------------

    \62\ https://www.fda.gov/media/156572/download.
---------------------------------------------------------------------------

    Accordingly, as it appears that CARVYKTITM and 
ABECMA[supreg] are purposed to achieve the same therapeutic outcome 
using the same or similar mechanism of action, are assigned to the same 
MS-DRG, and treat the same or similar patient population and disease, 
we believe that these technologies may be substantially similar to each 
other. We note that if this technology is substantially similar to 
ABECMA[supreg], we believe the newness period for this technology would 
begin on March 26, 2021, the date ABECMA[supreg] received FDA approval. 
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. We are inviting public comment on 
whether CARVYKTITM meets the newness criterion, including 
whether CARVYKTITM is substantially similar to 
ABECMA[supreg] for purposes of new technology add-on payments.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR final rule to identify potential cases representing 
patients who may be eligible for treatment using CARVYKTITM. 
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] TP10MY22.081

    The applicant stated that it identified two cohorts for the cost 
analysis: Cohort A limited the 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; Cohort B limited the analysis to MS-DRG 018 (CAR T-Cell and 
Other Immunotherapies). The applicant stated that the claim search 
resulted in 1,215 claims in Cohort A and 268 claims in Cohort B using 
the FY 2019 MedPAR. The applicant stated that it used the New 
Technology Threshold for FY 2023 from the FY 2022 IPPS/LTCH PPS final 
rule for MS-DRG 018. The applicant stated that it 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. Per the applicant, this is likely an 
overestimate of the charges that would be replaced by the use of 
CARVYKTITM. The applicant added that it then standardized 
the charges using the FY 2022 IPPS/LTCH PPS final rule impact file. 
Next, the applicant applied a 4-year inflation factor of 1.281834 or 
28.1834%, based on the inflation factor used in the FY 2022 IPPS/LTCH 
PPS final rule to update the outlier threshold) (86 FR 45542). To 
calculate the charges for the new technology for both cohorts, the 
applicant stated that it first used the inverse of a simulated 
alternative cost-to-charge ratio (CCR) specifically for CAR T-cell 
therapies and second used the national average drug CCR. The applicant 
stated that a simulated alternative CCR was used 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 After Outliers Removed (AOR)/
Before Outliers Removed (BOR) file and calculated an alternative markup 
percentage by dividing the AOR drug charges within MS-DRG 018 by the 
number of cases to determine a per case drug charge. The applicant then 
divided the drug charges per case by $373,000, the acquisition cost of 
YESCARTA[supreg] and KYMRIAH[supreg], the CAR T-cell products used in 
those claims, to arrive at a CCR of 0.295. The applicant stated that it 
used the national average drug CCR of 0.187 from the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 44966). For Cohort A, with the CAR T-cell CCR, 
the applicant calculated a final inflated average case-weighted 
standardized charge per case of $1,695,406, which it stated exceeded 
the average case-weighted threshold amount of $1,256,379. For Cohort A, 
with the national average drug CCR, the applicant stated that it 
calculated a final inflated average case-weighted standardized charge 
per case of $2,595,169, which it stated exceeded the average case-
weighted threshold amount of $1,256,379. For Cohort B, with the CAR T-
cell CCR, the applicant stated that it calculated a final inflated 
average case-weighted standardized charge per case of $1,713,723, which 
it stated exceeded the average case-weighted threshold amount of 
$1,256,379. The applicant stated that if CARVYKTITM meets 
the cost criterion using the more conservative alternate CAR T-cell CCR 
to inflate the cost of the treatment to charges, then it will also meet 
the cost criterion using the national average drug CCR to inflate the 
cost to charges. The applicant stated that because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, CARVYKTITM meets the cost 
criterion.
    In regard to the cost criterion, we question whether the ICD-10 
codes used to identify potential cases are appropriately representative 
of those who would receive CARVYKTITM.

[[Page 28222]]

Specifically, we are uncertain if the applicant's identification of 
cases using the previously specified ICD-10 codes differentiated 
between those treated with one, two, three, and four prior lines of 
therapy. We are also seeking clarification on whether these cases are 
appropriately representative of the technology. We note that while the 
applicant provided a cost analysis for Cohort A, with a simulated 
alternative CCR specifically for CAR T-cell therapies, the applicant 
did not provide the cost analyses for Cohort B or Cohort A with the 
national average drug CCR. We request these cost analyses as we are 
unable to evaluate these analyses based on the information provided by 
the applicant. As we have noted in previous discussions (86 FR 25237, 
86 FR 25279), the submitted costs for CAR T-cell therapies vary widely 
due to differences in provider billing and charging practices for this 
therapy, and we are continuing to consider the use of this submitted 
cost data for purposes of calculating a CAR T-cell CCR for use in the 
applicant's cost analyses given this potential for variability. 
Therefore, we request submission of the cost analyses with the national 
average drug CCR, which the applicant referenced, but did not submit, 
for cost criterion consideration.
    We invite public comment on whether CARVYKTITM meets the 
cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that it believes that CARVYKTITM 
represents a substantial clinical improvement over existing 
technologies because it: (1) Treats a new and expanded patient 
population, (2) offers a treatment for a patient population with 
limited options and continued disease progression, despite having been 
treated with multiple prior therapies; and (3) 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 CARVYKTITM 
treats a new and expanded patient population, the applicant stated that 
other multiple myeloma therapies, such as Blenrep and ABECMA[supreg], 
are indicated for patients with at least four prior therapies including 
a PI, an IMiD, and a CD38 antibody. In its application, the applicant 
asserted that CARVYKTITM may receive an indication for 
patients with only three prior lines of therapy. The applicant cited 
the CARTITUDE-1 trial where 17% of patients had three prior lines of 
therapy.
    With regard to the applicant's assertion that CARVYKTITM 
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 (n=113) 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 asserted 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 Phase 1b/2 CARTITUDE-1 study. According to the applicant, 
of the 113 enrolled patients, 16 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 cytokine release 
syndrome (CRS) and one due to acute myeloid leukemia (not treatment-
related). According to the applicant, 24 patients were ongoing in the 
phase 1b dose confirmation period with an additional 59 patients 
ongoing in the phase 2 portion. The applicant stated 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 
applicant asserted the primary objective of the Phase 2 portion of the 
trial is to evaluate the efficacy of ciltacabtagene autoleucel.
    The applicant asserted that at median follow-up of 18 months, 
ciltacabtagene autoleucel led to a 98% overall response rate (ORR) in 
all 97 study patients who received ciltacabtagene 
autoleucel.63 64 The applicant asserted that this 
unprecedented overall response rate of (98%), 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 
60%, daratumumab ORR 31%, Selinexor ORR 26%, and Blenrep ORR 31%.\65\ 
According to the applicant, in addition to the CARTITUDE-1 trial ORR, 
the Legend-2 study demonstrated an ORR of 87.8% (95% CI: 78.2, 94.3) at 
a 2 year follow up time period. The applicant asserted that both of 
these studies are ongoing and the depth and duration of response 
continues to improve over time.\66\
---------------------------------------------------------------------------

    \63\ Usmani SZ, et al. Ciltacabtagene Autoleucel, a B B-Cell 
Maturation Antigen Antigen-Directed Chimeric Antigen Receptor T T-
Cell Therapy, in Relapsed/Refractory Multiple Myeloma: Updated 
Results From CARTITUDE CARTITUDE-1. Oral presented at: ASCO Annual 
Meeting; June 4 4-8, 2021. https://meetinglibrary.asco.org/.
    \64\ 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.
    \65\ Martin, T., et al. Comparison of outcomes with 
ciltacabtagene autoleucel (cilta-cel) in CARTITUDE-1 vs real-world 
standard of care (RW SOC) for patients (pts) with triple-class 
exposed relapsed/refractory multiple myeloma (RRMM). Presented at 
2021 American Society of Clinical Oncology (ASCO) Annual Meeting; 
June 4-8, 2021; Poster #8045.
    \66\ Berdeja, J. Ciltacabtagene autoleucel, a B-cell maturation 
antigen-directed chimeric antigen receptor T-cell therapy in 
patients with relapsed or refractory multiple myeloma (CARTITUDE-1): 
A phase 1b/2 open-label study. Lancet. 2021 Jul 24;398(10297):314-
324.
---------------------------------------------------------------------------

    The applicant further asserted 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 18 months. The applicant 
stated that results of CARTITUDE-1 showed 80% of patients attaining a 
stringent complete response (sCR) and 93% of patients attaining a very 
good partial response (VGPR) or better. According to the applicant, 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, 1-9).67 68
---------------------------------------------------------------------------

    \67\ Usmani SZ, et al. Ciltacabtagene Autoleucel, a B B-Cell 
Maturation Antigen Antigen-Directed Chimeric Antigen Receptor T T-
Cell Therapy, in Relapsed/Refractory Multiple Myeloma: Updated 
Results From CARTITUDE CARTITUDE-1. Oral presented at: ASCO Annual 
Meeting; June 4 4-8, 2021. https://meetinglibrary.asco.org/.
    \68\ 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 
(JCO). 2020 38:15_suppl, 8505-8505.
---------------------------------------------------------------------------

    The applicant also asserted that most patients attained a status of 
MRD-negativity by the time they were evaluable for a CR. According to 
the applicant, of evaluable patients, 93.0% achieved MRD 
10-5 negativity.\69\

[[Page 28223]]

According to the applicant, 58% of patients were both MRD negative and 
in sCR at MRD detection level of 10-5. According to the 
applicant, the median time to MRD 10-5 negativity was 1 
month (0.8-7.7).\70\ The applicant stated, 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.\71\
---------------------------------------------------------------------------

    \69\ Usmani SZ, et al. Ciltacabtagene Autoleucel, a B B-Cell 
Maturation Antigen Antigen-Directed Chimeric Antigen Receptor T T-
Cell Therapy, in Relapsed/Refractory Multiple Myeloma: Updated 
Results From CARTITUDE CARTITUDE-1. Oral presented at: ASCO Annual 
Meeting; June 4 4-8, 2021. https://meetinglibrary.asco.org/.
    \70\ Usmani SZ, et al. Ciltacabtagene Autoleucel, a B B-Cell 
Maturation Antigen Antigen-Directed Chimeric Antigen Receptor T T-
Cell Therapy, in Relapsed/Refractory Multiple Myeloma: Updated 
Results From CARTITUDE CARTITUDE-1. Oral presented at: ASCO Annual 
Meeting; June 4 4-8, 2021. https://meetinglibrary.asco.org/.
    \71\ Usmani SZ, et al. Ciltacabtagene Autoleucel, a B B-Cell 
Maturation Antigen Antigen-Directed Chimeric Antigen Receptor T T-
Cell Therapy, in Relapsed/Refractory Multiple Myeloma: Updated 
Results From CARTITUDE CARTITUDE-1. Oral presented at: ASCO Annual 
Meeting; June 4 4-8, 2021. https://meetinglibrary.asco.org/.
---------------------------------------------------------------------------

    The applicant added that PFS at 12 months was 77% (95% CI; 66.0-
84.37) with median PFS not having been reached.\72\ According to the 
applicant, at median follow-up of 12.4 months, there were 14 deaths 
during the Phase 1b/2 study: One due to CRS and hemophagocytic 
lymphohistiocytosis (HLH), one due to neurotoxicity, and 12 due to 
other causes.\73\ The applicant asserted that the CRS was manageable in 
most patients; CRS was the most common adverse event (AE) (94.8%) 
observed in the CARTITUDE-1 study. According to the applicant, the 
median time to onset of CRS was 7 days (range 1-12 days) post 
ciltacabtagene autoleucel infusion with a median duration of 4 days. 
The applicant asserted that 90% of patients experienced Grade 1-2 CRS 
and 5 patients (5%) experienced grade 3 or greater CRS.\74\ According 
to the applicant there were 3 Grade 3 CRS, 1 Grade 4, and 1 
aforementioned death due to CRS/HLH Grade 5 event.
---------------------------------------------------------------------------

    \72\ 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.
    \73\ 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.
    \74\ 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 noted that in the CARTITUDE-1 trial, 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.
    According to the applicant, the LEGEND-2 study \75\ 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. The applicant stated 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 applicant stated 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). The 
applicant stated in the LEGEND-2 study, at a median follow up of 25 
months, the median PFS for all patients was 19.9 months and 28.2 months 
for patients with CR. According to the applicant, 17 patients (17/57--
29%) died during the study and follow up period (19 months) mostly due 
to progressive disease. The applicant asserted that none were related 
to CRS 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.
---------------------------------------------------------------------------

    \75\ Zhao, WH., Liu, J., Wang, BY. et al. A phase 1, open-label 
study of LCAR-B38M, a chimeric antigen receptor T cell therapy 
directed against B cell maturation antigen, in patients with 
relapsed or refractory multiple myeloma. J Hematol Oncol 11, 141 
(2018). https://jhoonline.biomedcentral.com/articles/10.1186/s13045-018-0681-6.
---------------------------------------------------------------------------

    The applicant further asserted that outcomes from the LEGEND-2 
study show that ciltacabtagene autoleucel provides a significantly 
improved clinical outcome relative to other therapies, either approved 
or still under FDA review, used in the RRMM setting. According the 
applicant, at a median follow up of 19 months, the overall response 
rate for ciltacabtagene autoleucel was 88%.\76\ The applicant stated 
the overall survival (OS) rate at 18 months was 68% (54-79%) with a 
median duration of response (mDOR) of 22 months (13-29). The applicant 
stated that of MRD-negative patients with CR, 91% were still alive at 
data cut, with a 27-month (95% CI, 14.3-NE) mDOR. The applicant added 
that the median time to first response was 1.1 months. The applicant 
asserted there was no relationship between best response and baseline 
BCMA expression level or weight-adjusted CAR T-cells infused. We note 
some inconsistencies between the citation provided and what the 
applicant stated. Specifically, per the citation, the median time to 
follow-up was 25 months, with a median overall survival among all 
patients of 36.1 months (95% CI, 26.4-NE), and a MDOR of 29.1 months 
(95% CI, 19.9-NE).\77\
---------------------------------------------------------------------------

    \76\ Wang. Bai-Yan. 2019. Long-term follow-up of a phase 1, 
first-in-human open-label study of LCAR-B38M, a structurally 
differentiated chimeric antigen receptor T (CAR-T) cell therapy 
targeting B-cell maturation antigen (BCMA), in patients (pts) with 
relapsed/refractory multiple myeloma (RRMM). Abstract #579, 
Presented at ASH Annual Meeting.
    \77\ Ibid.
---------------------------------------------------------------------------

    The applicant asserted 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.\78\ According to the applicant, the 
median PFS rate for all treated patients was 20 months (10-28); median 
PFS for MRD-neg patients with CR was 28 months (20-31).\79\ The 
applicant stated that at 18 months, the PFS rate was 50 (36-63%) for 
all patients and 71% (52-84%) for MRD-neg patients with CR.\80\ The 
applicant stated that 17 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.
---------------------------------------------------------------------------

    \78\ Ibid.
    \79\ Ibid.
    \80\ Ibid.
---------------------------------------------------------------------------

    According to the applicant, 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.\81\ Tocilizumab 
(46%), oxygen (35%), vasopressor (11%), and intubation (1 patient) were 
used to treat CRS.\82\ Neurotoxicity with Grade 1 aphasia, agitation 
and seizure-like activity was

[[Page 28224]]

observed in 1 patient in the LEGEND-2 study.\83\ The applicant believes 
that since ciltacabtagene autoleucel displayed a manageable CRS safety 
profile that it represents a substantial clinical improvement over 
existing therapies.
---------------------------------------------------------------------------

    \81\ Ibid.
    \82\ Ibid.
    \83\ Ibid.
---------------------------------------------------------------------------

    The applicant lastly discussed multiple unpublished studies which 
used matching-adjusted indirect treatment comparison (MAIC) and other 
matching techniques to compare ciltacabtagene autoleucel to other 
existing therapies. The applicant stated that while there are no 
randomized head-to-head trials comparing ciltacabtagene autoleucel to 
ABECMA[supreg], there is a peer-reviewed, published MAIC where 
individual patient data from CARTITUDE-1 (ciltacabtagene autoleucel) 
and published summary-level data for ABECMA[supreg] from the KarMMA 
trial are compared.\84\ According to the applicant, the authors 
concluded that ciltacabtagene autoleucel demonstrated clinically 
superior results for all outcomes studied (ORR, CR rate, DoR, PFS, and 
OS), and these were robust across all sensitivity analyses. The 
applicant provided, as an example, results from one study by Martin et 
al. (2021) which, when comparing ciltacabtagene autoleucel to 
ABECMA[supreg], found that the former had a 34% higher chance of 
response, a 220% higher chance of a CR, a hazard ratio of 0.5 for the 
DoR, 0.37 for PFS, and 0.55 for OS.\85\ The applicant asserted that 
based on these findings, ciltacabtagene autoleucel offers substantial 
clinical benefits for patients with triple-class exposed RRMM compared 
to ABECMA[supreg].
---------------------------------------------------------------------------

    \84\ Martin et al, 2021. Matching-adjusted indirect comparison 
of efficacy outcomes for ciltacabtagene autoleucel in CARTITUDE-1 
versus idecabtagene vicleucel in KarMMa for the treatment of 
patients with relapsed or refractory multiple myeloma.
    \85\ Ibid.
---------------------------------------------------------------------------

    According to the applicant, there are several unpublished studies 
employing MAIC and other matching techniques comparing clinical 
outcomes for patients receiving ciltacabtagene autoleucel and the 
standard of care, or other conventional therapies, such as belantamab 
mafadotin or selinexor and dexamethasone.86 87 88 The 
applicant stated that in a comparison to patients receiving various 
conventional therapies, the authors conclude that treatment with 
ciltacabtagene autoleucel is associated with higher response rate and 
superior PFS and OS.\89\ The applicant stated that in a comparison with 
treatment with selinexor and dexamethasone, the study authors conclude 
that the analysis shows that ciltacabtagene autoleucel ``offers 
substantially more clinical benefit'' for patients with triple-class 
exposed RRMM.\90\ The applicant also asserted that in a study that 
assessed the comparative effectiveness of ciltacabtagene autoleucel to 
physician's choice of treatment (PCT) using an external real-world 
control arm from the Flatiron Health multiple myeloma cohort registry, 
authors found that ciltacabtagene autoleucel offers substantial 
clinical benefits for PFS, time to next treatment (TTNT), and OS over 
PCT for patients with triple class exposed RRMM.\91\ According to the 
applicant, patients receiving ciltacabtagene autoleucel were 3.2 times 
more likely to achieve overall response than patients receiving 
belantamab mafodotin after adjusting for refractory status, cytogenetic 
profile, International Staging System (ISS) stage, and extramedullary 
disease.
---------------------------------------------------------------------------

    \86\ Costa L, et al. Ciltacabtagene Autoleucel Versus 
Conventional Treatment in Patients With Relapsed/Refractory Multiple 
Myeloma. ASCO 2021. Poster #8030.
    \87\ Weisel et al. Matching-Adjusted Indirect Comparison of 
Ciltacabtagene Autoleucel Versus Belantamab Mafodotin in Patients 
With TripleClass Exposed Relapsed/Refractor y Multiple Myeloma. EHA 
2021. Poster #EP978.
    \88\ Martin 2021, eJHaem accepted manuscript.
    \89\ Costa L, et al. Ciltacabtagene Autoleucel Versus 
Conventional Treatment in Patients With Relapsed/Refractory Multiple 
Myeloma. ASCO 2021. Poster #8030.
    \90\ Weisel et al. Matching-Adjusted Indirect Comparison of 
Ciltacabtagene Autoleucel Versus Belantamab Mafodotin in Patients 
With TripleClass Exposed Relapsed/Refractor y Multiple Myeloma. EHA 
2021. Poster #EP978.
    \91\ Martin 2021, eJHaem accepted manuscript.
---------------------------------------------------------------------------

    Lastly, the applicant summarized data from 22 months follow-up for 
CARTITUDE-1, which was presented at ASH 2021.\92\ The applicant 
asserted that compared to the previous 12-month and 18-month data, 2-
year data showed responses deepening over time. The applicant stated 
the ORR continued at 98% (up from 96% at 12 months) and the sCR at 22 
months was 82.5%, compared to 67% at 12 months and 80.4% at 18 months. 
According to the applicant, at 22 months, 92% of the patients with MRD 
status noted were MRD negative, which is consistent with 18-month data 
(92%) and 12-month data (93%), illustrating persistent ability for the 
treatment to maintain MRD negativity over time. According to the 
applicant, the two-year PFS was 60.5% and 71% when a sCR was achieved 
and the two-year OS for all patients was 74%. The applicant stated that 
at the 2-year median follow up, no new treatment-related deaths had 
occurred since the median approximately 1-year follow-up, and there 
were no new safety signals reported. The applicant added that adverse 
events were generally low grade, well tolerated and managed with 
standard treatment algorithms employing drugs such as tocilizumab, 
corticosteroids, and anakinra.
---------------------------------------------------------------------------

    \92\ Martin et al. 2021. Updated Results From CARTITUDE-1: Phase 
1b/2 Study of Ciltacabtagene Autoleucel, a B-cell Maturation 
Antigen-Directed Chimeric Antigen Receptor T Cell Therapy, in 
Patients With Relapsed/Refractory Multiple Myeloma. Presented at the 
63rd American Society of Hematology (ASH) Annual Meeting & 
Exposition; December 11-14, 2021; Oral Presentation #549.
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant as part 
of its FY 2023 application for new technology add-on payments for 
CARVYKTITM, we have the following concerns regarding the 
substantial clinical improvement criterion. We note that in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25238 through 25239), we expressed 
concern regarding a lack of comparisons between CARVYKTITM 
and other existing therapies. We note that the applicant provided new 
references in its FY 2023 application to compare CARVYKTITM 
to other therapies.93 94 However, we further note that many 
of the references provided are in abstract or presentation format with 
limited data on the overall study design and methodology used to 
achieve the presented results. With respect to the LEGEND-2 study, the 
authors stated that for the initial patient sample (n=57), the median 
number of prior lines of therapy was 3, with a range of 1 to 9.\95\ 
Furthermore, we note that in the LEGEND-2 study only 11 (19%) of the 
respondents were 65 and older in the sample. As only 60% of this 
patient sample had received both a proteasome inhibitor and an 
immunomodulatory agent, and no patients had received a CD38 antibody, 
we question the true refractoriness of the test population in the 
LEGEND-2 study and whether the results are generalizable to the 
Medicare population for which this treatment is intended.
---------------------------------------------------------------------------

    \93\ Martin et al,. Matching-adjusted indirect comparison of 
efficacy outcomes for ciltacabtagene autoleucel in CARTITUDE-1 
versus idecabtagene vicleucel in KarMMa for the treatment of 
patients with relapsed or refractory multiple myeloma.
    \94\ Martin T, et al. Ciltacabtagene Autoleucel Versus 
Selinexor+ Dexamethasone in Triple-Class Exposed Patients With 
Relapsed/Refractory Multiple Myeloma: A Matching Adjusted Indirect 
Comparison.
    \95\ Zhao, WH., Liu, J., Wang, BY. et al. A phase 1, open-label 
study of LCAR-B38M, a chimeric antigen receptor T cell therapy 
directed against B cell maturation antigen, in patients with 
relapsed or refractory multiple myeloma. J Hematol Oncol 11, 141 
(2018). https://doi.org/10.1186/s13045-018-0681-6.
---------------------------------------------------------------------------

    In addition, we request clarification on any potential 
inconsistencies between the statements in the

[[Page 28225]]

applicant's new technology add-on payment application and the citation 
which explains the LEGEND-2 study, including inconsistencies in median 
time to follow-up, median OS, and mDOR, as previously noted.\96\
---------------------------------------------------------------------------

    \96\ Wang. Bai-Yan. 2019. Long-term follow-up of a phase 1, 
first-in-human open-label study of LCAR-B38M, a structurally 
differentiated chimeric antigen receptor T (CAR-T) cell therapy 
targeting B-cell maturation antigen (BCMA), in patients (pts) with 
relapsed/refractory multiple myeloma (RRMM). Abstract #579, 
Presented at ASH Annual Meeting.
---------------------------------------------------------------------------

    Finally, while the applicant has asserted that 
CARVYKTITM treats a new and expanded patient population 
since existing treatments are indicated for patients with at least four 
prior therapies, we note that CARVYKTITM was recently 
approved with an indication for patients with at least four prior lines 
of therapy as well. Therefore, we would appreciate additional 
clarification on any differences between CARVYKTITM and 
existing therapies with respect to the patient populations indicated 
for treatment.
    We are inviting public comment on whether CARVYKTITM 
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 
CARVYKTITM.
b. DARZALEX FASPRO[supreg] (daratumumab and hyaluronidase-fihj)
    Janssen Biotech, Inc., submitted an application for new technology 
add-on payments for DARZALEX FASPRO[supreg] for FY 2023. DARZALEX 
FASPRO[supreg] is a combination of daratumumab (a monoclonal CD38-
directed cytolytic antibody), and hyaluronidase (an endoglycosidase) 
indicated for the treatment of light chain (AL) amyloidosis in 
combination with bortezomib, cyclophosphamide and dexamethasone 
(CyBorD) in newly diagnosed patients and is administered through a 
subcutaneous injection.
    According to the applicant, AL amyloidosis is a life-threatening 
blood disorder caused by increased production of misfolded 
immunoglobulin light chains by an abnormal proliferation of malignant 
CD38+ plasma cells. Per the applicant, these deficient immunoglobulin 
light chains aggregate into highly ordered amyloid fibrils that deposit 
in tissues, eventually resulting in progressive organ dysfunction and 
damage due to the toxic effect of the misfolded proteins 
(proteotoxicity) and the distortion of the normal tissue architecture 
by the amyloid deposits.\97\ The applicant stated that the most 
frequently affected organs are the heart, kidney, liver, spleen, 
gastrointestinal tract and nervous system. Per the applicant, patients 
often have a poor prognosis, and as many as 30% of patients with AL 
amyloidosis die within the first year after diagnosis. The applicant 
stated that approximately 4,500 people in the US develop AL amyloidosis 
each year.\98\ The applicant stated that while there were no FDA 
approved therapies prior to daratumumab, a number of therapies were 
used clinically to treat AL amyloidosis including combination therapies 
like cyclophosphamide-bortezomib-dexamethasone (CyBorD), bortezomib-
lenalidomide-dexamethasone (VRd), bortezomib-melphalan-dexamethasone 
(VMd), melphalan-dexamethasone (Md), and bortezomib-dexamethasone (Vd). 
The applicant further noted that none of these combination regimens are 
approved for use by FDA in this specific indication.
---------------------------------------------------------------------------

    \97\ Merlini et al. Systemic immunoglobin light chain 
amyloidosis. Nat Rev Dis Primers. 2018; 4:38-19.
    \98\ Amyloidosis Foundation. AL amyloidosis facts. http://www.amyloidosis.org/facts/al/. Accessed September 2021
---------------------------------------------------------------------------

    According to the applicant, DARZALEX FASPRO[supreg] is the first 
and only FDA-approved treatment for patients with AL amyloidosis and is 
also approved for multiple indications for treatment of patients with 
multiple myeloma. The applicant stated that the indication for the 
technology for which it is submitting a new technology add-on payment 
application is for the treatment of adult patients with AL amyloidosis 
in combination with bortezomib, cyclophosphamide and dexamethasone in 
newly diagnosed patients. The applicant noted that DARZALEX 
FASPRO[supreg] is not indicated nor recommended to be used in patients 
with AL amyloidosis who have NYHA Class IIIB or Class IV cardiac 
disease or Mayo Stage IIIB, except in the context of controlled 
clinical trials.
    According to the applicant, DARZALEX FASPRO[supreg] is the 
subcutaneous formulation of daratumumab, which is a human IgG- kappa 
monoclonal antibody that targets CD38, an enzymatic protein that is 
uniformly expressed on human plasma cells. Per the applicant, in 
DARZALEX FASPRO[supreg], daratumumab is co-formulated with recombinant 
human hyaluronidase (rHuP20), which critically allows daratumumab to be 
administered in a volume of 15 mL by a 3-5 minute injection under the 
skin, compared to the 500-1000 mL volume and 3-7 hour administration 
time required for IV daratumumab. The applicant further noted that 
given the cardiac and renal dysfunction which afflicts many AL 
amyloidosis patients and makes them poor candidates for large volume IV 
administration, rHuP20 is a critical component of DARZALEX 
FASPRO[supreg]. Per the applicant, daratumamab binds to the CD38 
protein on the surface of the malignant plasma cells which are 
responsible for abnormal amyloid protein production in AL amyloidosis, 
directly killing the malignant CD38+ plasma cells and/or directing the 
immune system to destroy them. The immunomodulatory response consists 
of CD8+ clonal expansion, CD38 enzymatic inhibition, complement 
activation and cell recruitment to enable antibody dependent cellular 
phagocytosis (ADPC) and antibody dependent cellular cytotoxicity 
(ADCC). Per the applicant, the mechanism of actions of daratumumab in 
AL amyloidosis are the same as the mechanisms of action of daratumumab 
in multiple myeloma, since both disease entities are disorders of 
malignant CD38+ plasma cells.99 100 101
---------------------------------------------------------------------------

    \99\ de Weers et al. Daratumumab, a Novel Therapeutic Human CD38 
Monoclonal Antibody, Induces Killing of Multiple Myeloma and Other 
Hematogical Tumors. J Immunol 2011;186:1840-1848).
    \100\ Overdijk et al. Antibody-mediated phagocytosis contributes 
to the anti-tumor activity of the therapeutic antibody daratumumab 
in lymphoma and multiple myeloma. MAbs.2015;7:311-321).
    \101\ Krejcik J, Casneuf T, Nijhof IS, et al. Daratumumab 
depletes CD38+ immune regulatory cells, promotes T-cell expansion, 
and skews T-cell repertoire in multiple myeloma. Blood 2016; 128: 
384-94.
---------------------------------------------------------------------------

    The applicant stated that without hyaluronidase, it is not possible 
to inject more than 2-3 mL of drug directly into the subcutaneous 
tissue under the skin. Per the applicant rHuPH20 naturally mimics 
natural hyaluronidase and increases the permeability of subcutaneous 
tissue by degrading hyaluronan. By co-formulating daratumumab with 
rHuPH20, it becomes possible for 15 mL containing 1,800 mg of 
daratumamab to be administered subcutaneously in approximately 3 to 5 
minutes. The applicant stated that the ability to administer 
daratumumab subcutaneously reduces the reaction rate to daratumumab, 
may improve convenience and patient satisfaction, and greatly reduces 
the volume of administration, which is critical in light of the cardiac 
dysfunction and kidney dysfunction which afflict many patients with AL 
amyloidosis.

[[Page 28226]]

    With respect to the newness criterion, the applicant stated that 
DARZALEX FASPRO[supreg] was granted accelerated approval from FDA on 
January 15, 2021, indicated for the treatment of adult patients with 
light chain (AL) amyloidosis in combination with bortezomib, 
cyclophosphamide and dexamethasone in newly diagnosed patients. Per the 
applicant, DARZALEX FASPRO[supreg] is not indicated and recommended for 
the treatment of patients with AL amyloidosis who have NYHA Class IIIB 
or Class IV cardiac disease or Mayo Stage IIIB outside of controlled 
clinical trials.\102\ The applicant also stated that DARZALEX 
FASPRO[supreg] received FDA approval on September 26, 2019, for the 
treatment of adult patients with multiple myeloma as part of a 
combination therapy in newly diagnosed patients eligible for autologous 
stem cell transplant, and on May 1, 2020, for the treatment of patients 
with multiple myeloma. As stated previously, the indication for which 
the applicant submitted an application for new technology add-on 
payments is for the treatment of adult patients with AL amyloidosis in 
combination with bortezomib, cyclophosphamide and dexamethasone in 
newly diagnosed patients. The applicant stated that DARZALEX 
FASPRO[supreg] for newly diagnosed AL amyloidosis was commercially 
available immediately following the accelerated approval granted by 
FDA. The recommended dosage for DARZALEX FASPRO[supreg] for newly 
diagnosed AL amyloidosis is 1,800 mg of daratumumab and 30,000 units of 
hyaluronidase administered subcutaneously over approximately 3 to 5 
minutes in combination with bortezomib, cyclophosphamide and 
dexamethasone. According to the applicant, patients receiving DARZALEX 
FASPRO[supreg] for this indication receive a weekly dose for the first 
8 weeks (week 1 to week 8), one dose every 2 weeks from week 9 to week 
24, followed by one dose monthly from week 25 onward until disease 
progression for a maximum of 2 years.
---------------------------------------------------------------------------

    \102\ According to the applicant, continued approval for this 
indication may be contingent upon verification and description of 
clinical benefit in confirmatory trials.
---------------------------------------------------------------------------

    The applicant stated that ICD-10-PCS code 3E013GC (Introduction of 
other therapeutic substance into subcutaneous tissue, percutaneous 
approach) may currently be used to identify DARZALEX FASPRO[supreg] 
under the ICD-10-PCS coding system but that there are currently no ICD-
10-PCS procedure codes that uniquely identify the use of DARZALEX 
FASPRO[supreg]. The applicant submitted a request for a unique ICD-10-
PCS code to identify procedures involving the administration of 
DARZALEX FASPRO[supreg]. The applicant stated that E85.81 (Light chain 
(AL) amyloidosis) may be used to currently identify the indication for 
DARZALEX FASPRO[supreg] under the ICD-10-CM coding system but that 
there is no ICD-10-CM diagnosis code that is specific to DARZALEX 
FASPRO[supreg] for newly diagnosed AL amyloidosis.
    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 purposes of new technology add-on 
payments.
    With respect to the first criterion, whether a technology uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that it does not use the same or similar mechanism 
of action as existing technologies. The applicant stated that DARZALEX 
FASPRO[supreg] was the first drug approved by FDA for treatment of AL 
amyloidosis and its mechanism of action is different from that of any 
other drug previously used to treat AL amyloidosis. According to the 
applicant, the other therapies currently used to treat amyloidosis off-
label (for example, bortezomib, cyclophosphamide, melphalan, 
lenlidomide) all have different mechanisms of action; none of them are 
monoclonal antibodies that specifically bind to CD38 on malignant 
plasma cells. The applicant stated that bortezomib induces cell death 
of the malignant plasma cell by inhibition of the 26S proteasome which 
plays a key role in cell survival by regulating protein breakdown in a 
controlled fashion. The applicant further stated that when bortezomib 
inhibits proteasome function, the normal balance within a cell is 
disrupted, resulting in a buildup of cell cycle and regulatory proteins 
which eventually leads to cell death.103 104 Per the 
applicant, lenalidomide is an immunomodulator which modulates the E3 
ubiquitin ligase complex. Modulation of this E3 ubiquitin ligase 
complex by lenalidomide eventually leads to enhanced function of 
specific immune cells and induction of cell death and the exact 
mechanism of action of lenalidomide is still not fully 
understood.105 106 The applicant stated that both melphalan 
and cyclophosphamide are alkylating chemotherapy drugs that add an 
alkyl group to the guanine base of the DNA molecule, preventing the 
strands of the double helix from linking, which causes breakage of the 
DNA strands, affecting the ability of the cancer cell to multiply. Per 
the applicant, like bortezomib and lenalidomide, melphalan and 
cyclophosphamide are not approved by FDA for the use in patients with 
AL amyloidosis. The applicant also noted that while the National 
Comprehensive Cancer Network[supreg] (NCCN[supreg]) Guidelines for 
Systemic Light Chain Amyloidosis state that both IV and SQ daratumumab 
can be used to treat previously treated amyloidosis,\107\ IV 
daratumumab is not approved by FDA for the treatment of patients with 
amyloidosis (newly diagnosed and previously treated). The applicant 
also stated that DARZALEX FASPRO[supreg] is the more appropriate option 
in the AL amyloidosis patient population due to the fact that 
subcutaneous dosing has a negligible volume administration (15 ml for 
SC vs up to 1000ml for IV), which is particularly important in patients 
with AL amyloidosis who often have compromised cardiac and renal 
function due to the amyloid deposition in cardiac and kidney tissue.
---------------------------------------------------------------------------

    \103\ Adams et al. Proteasome Inhibitors: A Novel Class of 
Potent and Effective Antitumor Agents. Cancer Res 1999;55; 2615-
2622.
    \104\ Adams et al. The proteasome: A suitable antineoplastic 
target. Nat Rev Cancer 2004; 4:349-360.
    \105\ Kastritis et al. Primary treatment of light chain 
amyloidosis with Bortezomib, lenalidomide and dexamethasone. Blood 
Adv 2019;3:3002-3009.
    \106\ Revlimid Prescribing Info.
    \107\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines[supreg]): Systemic Light Chain amyloidosis (Version 
1.2022). National Comprehensive Cancer Network. www.nccn.org. 
Published August 29 June 2021. Accessed July 21, 2021.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that this 
product is not expected to change the DRG assignment of a case when 
used for the treatment of AL amyloidosis.
    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 DARZALEX FASPRO[supreg] 
does not meet this criterion because it was the first approved drug to 
treat patients with AL amyloidosis. The applicant also stated that the 
NCCN[supreg] Guidelines for Systemic Light Chain Amyloidosis reflect 
the limited treatment options for this specific disease. The applicant 
further stated that DARZALEX FASPRO[supreg] in combination with CyBorD 
is the only

[[Page 28227]]

treatment with a Category 1 recommendation \108\ in the NCCN[supreg] 
Guidelines for patients with newly diagnosed AL amyloidosis.\109\
---------------------------------------------------------------------------

    \108\ Per the NCCN[supreg], a Category 1 recommendation is 
``Based upon high-level evidence, there is uniform NCCN[supreg] 
consensus that the intervention is appropriate.''
    \109\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines[supreg]): Systemic Light Chain amyloidosis (Version 
1.2022). National Comprehensive Cancer Network. www.nccn.org. 
Published August 29 June 2021. Accessed July 21, 2021.
---------------------------------------------------------------------------

    In summary, the applicant believes that DARZALEX FASPRO[supreg] is 
not substantially similar to other currently available therapies and/or 
technologies because it has a unique mechanism of action and because it 
is the first FDA approved treatment for AL amyloidosis.
    We are inviting public comments on whether DARZALEX FASPRO[supreg] 
is substantially similar to existing technologies and whether DARZALEX 
FASPRO[supreg] meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis to demonstrate that DARZALEX FASPRO[supreg] meets 
the cost criterion. To identify cases representing patients who may be 
eligible for treatment with DARZALEX FASPRO[supreg], the applicant 
searched the FY 2019 MedPAR database released with the FY 2022 IPPS 
final rule and stated that it used fee-for-service IPPS discharges, 
plus Maryland hospital discharges. The applicant searched for claims 
reporting ICD-10-CM diagnosis code E85.81 (Light chain amyloidosis) in 
conjunction with at least one of the following additional ICD-10-CM 
diagnosis codes:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.082

    The applicant excluded cases with a length of stay greater than 7 
days from the analysis. According to the applicant, administration of 
DARZALEX FASPRO[supreg] would likely be delayed if a patient becomes 
seriously ill during the course of treatment, so it is unlikely a 
patient would receive DARZALEX FASPRO[supreg] during an inpatient stay 
lasting longer than 7 days. The applicant indicated that based on the 
advice of clinical experts, it also excluded cases mapped to the 
following MS-DRGs, as DARZALEX FASPRO[supreg] would not be an 
appropriate treatment for patients receiving treatment for such 
conditions:

[[Page 28228]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.083


[[Page 28229]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.084

    After applying the case selection and exclusion criteria, the 
applicant's search resulted in the identification of 114 MS-DRGs using 
the FY 2019 MedPAR file dataset. The applicant imputed a case count of 
11 for 104 MS-DRGs with fewer than 11 cases, resulting in a total of 
1,494 cases mapping to the 114 MS-DRGs.

[[Page 28230]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.085


[[Page 28231]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.086


[[Page 28232]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.087

BILLING CODE 4120-01-C
    The applicant determined an average unstandardized case weighted 
charge per case of $47,599.
    The applicant did not remove charges for related or prior 
technologies because, per the applicant, DARZALEX FASPRO[supreg] would 
not replace other therapies a patient may receive during an inpatient 
stay. Next, the applicant standardized the charges using the FY 2022 
IPPS/LTCH PPS final rule impact file and applied a 4-year inflation 
factor of 1.281834 or 28.1834% based on the inflation factor used in 
the FY 2022 IPPS/LTCH PPS final rule to update the outlier threshold 
(86 FR 45542). The applicant then added charges for the new technology 
by multiplying the per treatment cost of DARZALEX FASPRO[supreg] by the 
inverse of the national average drug CCR of 0.187 from the FY 2022 
IPPS/LTCH PPS final rule (86 FR 44966).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $92,916, which exceeded the average 
case-weighted threshold amount of $61,426. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that DARZALEX 
FASPRO[supreg] meets the cost criterion.
    We are inviting public comment on whether DARZALEX FASPRO[supreg] 
meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that DARZALEX FASPRO[supreg] represents a 
substantial clinical improvement over existing technologies because it 
offers a treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments. The applicant also 
asserted that DARZALEX FASPRO[supreg] demonstrates significant 
improvement in a number of clinical outcomes including hematologic 
complete response (hemCR), prolonged survival free from major organ 
deterioration, increased cardiac and renal response rates, with a 
demonstrated safety and tolerability profile and no negative impact to 
health-related quality of life based on patient-reported outcomes.
    With regard to the claim that DARZALEX FASPRO[supreg] offers a 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments, the applicant stated 
that the initial standard of therapy (CyBorD) is considered inadequate, 
as most patients do not respond adequately to the CyBorD regimen alone. 
Furthermore, according to the applicant, the ANDROMEDA data shows that 
>80% of patients do not achieve a hemCR, >75% of patients with cardiac 
disease do not have an organ response, and >75% of patients with renal 
disease do not have an organ response when treated with the initial 
standard of therapy CyBorD. Per the applicant, there is a high unmet 
need to improve treatment for AL amyloidosis patients. The applicant 
stated that rapid and deep response like hemCR are critical and are 
strongly associated with organ response and improved survival in AL 
amyloidosis.\110\ Per the applicant, adding DARZALEX FASPRO[supreg] to 
CyBorD increases the hemCR rate by three-fold and doubles the cardiac 
and renal response rates, thereby addressing this high unmet medical 
need.
---------------------------------------------------------------------------

    \110\ Comenzo RL, Reece D, Palladini G, et al. Consensus 
guidelines for the conduct and reporting of clinical trials in 
systemic light chain amyloidosis. Leukemia. 2012;26: 2317-2325.
---------------------------------------------------------------------------

    With regard to the claim that the use of DARZALEX FASPRO[supreg] 
significantly improves clinical outcomes for a patient population as 
compared to currently available treatments, as stated previously, the 
applicant asserted that DARZALEX FASPRO[supreg] represents a 
substantial clinical improvement over existing technologies because it: 
(1) Demonstrates a consistent safety profile; (2) significantly 
improves hematologic complete response (hemCR rates); (3) maintains the 
increased hemCR rates for pre-specified subgroups; (4) shortens the 
time to hemCR; (5) improves very good partial response (VGPR) or better 
rates; (6) substantially improves cardiac response at 6 and at 12 
months; (7) improves renal response at 6 and at 12 months; (8) improves 
major-organ deterioration or progression-free survival (MOD-PFS); (9) 
improves Global Health status and fatigue as of cycle 6 of treatment, 
and maintains health-related quality of life (HRQoL); and (10) provides 
important advantages for the population with AL.
    In support of these claims, the applicant submitted the ANDROMEDA 
phase 3 trial as well as presentations related to these trials. The 
applicant stated that data in the ANDROMEDA study demonstrated that 
DARZALEX FASPRO[supreg] led to significantly better outcomes both at 
the time of the primary analysis \111\ as well as at the time of 
updated analyses which were presented at the 2021 ASCO annual meeting 
and 2021 EHA annual meeting.\112\
---------------------------------------------------------------------------

    \111\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. New England Journal of 
Medicine (NEJM). 2021; 385:46-58.
    \112\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    ANDROMEDA was a randomized, open-label, phase 3 study of 388 
patients with newly diagnosed AL amyloidosis randomized 1:1 to receive 
6 cycles of CyBorD, either alone (control group, n=193) or in 
combination with daratumumab SC (that is, DARZALEX FASPRO[supreg]), 
followed by DARZALEX FASPRO[supreg] monotherapy every 4 weeks for up to 
24 additional cycles (daratumumab group, n=195). The study enrolled 
patients between May 3, 2018 and August 15, 2019. Median age was 64 
(range 34-87). The study reported a median 11.4 month follow-up for the 
published trial, and 20.3 months for the follow-up data. The primary 
endpoint was hemCR, defined as having negative serum and urine 
immunofixation and a free light chain ratio (FLCr) within the reference 
range or abnormal free light-chain ratio if the uninvolved free light 
chain (uFLC) is higher than the involved free light chain (iFLC). 
According to the applicant, this definition of hemCR is in line with a 
recent clarification of the Internal Society of Amyloidosis 
guidelines.\113\ Secondary endpoints were survival free from major 
organ deterioration or hematologic progression (composite end point 
that included end-stage cardiac or renal failure,

[[Page 28233]]

hematologic progression), or death, organ response, overall survival, 
hematologic complete response at 6 months, VGPR or better, time to and 
duration of hematologic complete response, time to next treatment, and 
reduction in fatigue. The applicant noted that the safety population in 
the ANDROMEDA study consisted of 193 patients in the daratumumab arm 
and 188 patients in the control arm.
---------------------------------------------------------------------------

    \113\ Palladini et al. Daratumumab plus CyBord for patients with 
newly diagnosed AL amyloidosis: safety run-in results of ANDROMEDA. 
Blood.2020;136:71-80.
---------------------------------------------------------------------------

    The applicant also cited an oral presentation, presented at the 
American Society of Clinical Oncology (ASCO) 2021 and European 
Hematology Association (EHA) 2021 annual meetings, with updated data 
from the ANDROMEDA study after 20.3 months of follow-up, which 
described sustained primary outcome of higher rates of hemCR across 
subgroups as well as improved secondary endpoints of cardiac and renal 
response rate at 12 months. In the intent to treat population, there 
were 11 deaths in the CyBorD group compared to 7 deaths in the control 
group.\114\
---------------------------------------------------------------------------

    \114\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] 
demonstrates a consistent safety profile, the applicant cited Kastritis 
et al., discussed previously, stating that the safety profiles of 
daratumumab and bortezomib, cyclophosphamide, and dexamethasone in the 
ANDROMEDA trial were consistent with their known profiles and the 
underlying disease from previous trials.\115\ To support its assertion 
that DARZALEX FASPRO[supreg] significantly improves hemCR rate, the 
applicant stated that the trial results showed that patients treated 
with DARZALEX FASPRO[supreg] demonstrated a statistically significant 
increase in hemCR compared to control (53.3% versus 18.1%; relative 
risk ratio, 2.9; 95% CI, 2.1 to 4.1; odds ratio, 5.1; 95% CI, 3.2 to 
8.2; p<0.001 for both comparisons) at the 11.4 month median follow-up. 
To support its assertion that DARZALEX FASPRO[supreg] results in a 
shorter time to hemCR, the applicant noted that in the trial, median 
time to hemCR was 60 days in the daratumumab group and 85 days in the 
control group. In support of its assertion that the increased hemCR 
rate was maintained for pre-specified subgroups, the applicant also 
stated that hemCR remained consistent in most prespecified subgroups 
(for example, sex, age, weight, race, cardiac stage, etc.) receiving 
daratumumab.\116\ The applicant also cited results from the oral 
presentation, discussed previously, stating that after a median follow 
up of 20.3 months, the percentage of patients who achieved hemCR 
increased to 59% in the daratumumab group vs 19% in the control group 
(odds ratio: 5.9; 95% CI, 3.7 to 9.4; P<0.001), and that this advantage 
was seen consistently across all prespecified subgroups.\117\ The 
applicant stated that rapid and deep hematologic responses are critical 
and are strongly associated with organ response and improved survival 
in AL amyloidosis.\118\
---------------------------------------------------------------------------

    \115\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \116\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \117\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
    \118\ Comenzo RL, Reece D, Palladini G, et al. Consensus 
guidelines for the conduct and reporting of clinical trials in 
systemic light chain amyloidosis. Leukemia. 2012;26: 2317-2325.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] improved 
VGPR or better rates, the applicant also stated that the trial 
demonstrated that the secondary endpoint of VGPR or better was 78.5% in 
the daratumumab group and 49.2% in the control group (relative risk 
ratio, 1.6; 95% CI, 1.4 to 1.9; odds ratio, 3.8; 95% CI, 2.4 to 
5.9).\119\ Per the applicant, the substantial improvements in 
hematologic response rates and other endpoints like cardiac and renal 
response and MOD-PFS indicate the clinical meaningfulness of these 
efficacy results.
---------------------------------------------------------------------------

    \119\ Kastritis et al., Daratumumab for immunoglobulin light-
chain amyloidosis. N Eng J Med 2021; 385:48-58.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] 
substantially improves cardiac response at 6 and at 12 months, 
according to the applicant, of the subgroup that was evaluated for 
cardiac response (118 in the daratumumab group and 117 in the control 
group), 41.5% in the daratumumab group and 22.2% in the control group 
(odds ratio, 2.44; 95% CI: 1.35 to 4.42) demonstrated a cardiac 
response at 6 months.\120\ The applicant noted that at a median follow 
up of 20.3 months, cardiac response rates were higher with in the 
daratumumab group compared to CyBorD alone at 6 months (42% versus 22%, 
odds ratio 2.4, 95% CI 1.4 to 4.4; P=0.0029) and at 12 months (57% 
versus 28%, odds ratio 3.5 95% CI 2.0 to 6.2; P<0.0001).\121\ In 
addition, in support of its assertion that DARZALEX FASPRO[supreg] 
improves renal response at 6 and at 12 months, the applicant noted that 
in the subgroup evaluated for renal response (117 in the daratumumab 
group and 113 in the control group), 53.0% of patients in the 
daratumumab group and 23.9% in the control group (odds ratio, 3.34; 95% 
CI:1.88 to 5.94) demonstrated a renal response at 6 months.\122\ The 
applicant noted that at a median follow up of 20.3 months, renal 
response rates were higher with in the daratumumab group compared to 
CyBorD alone at 6 months (54% vs 27%; odds ratio 3.3 95% CI 1.9 to 5.9; 
P<0.0001) and at 12 months (57% vs 27%; odds ratio 4.1 95% CI 2.3 to 
7.3; P<0.0001).\123\ The applicant noted that the percentages of 
patients who had a cardiac or renal response were substantially higher 
in the daratumumab group than in the control group, which it stated was 
an important finding given that organ responses are also a predictor of 
improved survival.
---------------------------------------------------------------------------

    \120\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \121\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
    \122\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \123\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] improves 
MOD-PFS, the applicant noted significant findings of secondary endpoint 
survival free from major organ deterioration or hematologic progression 
in the daratumumab group compared to control (hazard ratio for major 
organ deterioration, hematologic progression, or death, 0.58; 95% CI, 
0.36 to 0.93; P = 0.02).\124\
---------------------------------------------------------------------------

    \124\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. NEJM. 2021;385:46-58.
---------------------------------------------------------------------------

    With regard to the claim that DARZALEX FASPRO[supreg] improves 
Global

[[Page 28234]]

Health status (GHS) and fatigue as of cycle 6 of treatment, as well as 
maintains HRQoL, the applicant cited a poster presentation of a 
subgroup analysis on patient reported outcomes (PRO) for patients 
participating in the ANDROMEDA study.\125\ The applicant noted that the 
patients were provided with PRO questionnaires and assessed on day 1 of 
cycles -1-6 as well as every 8 weeks thereafter in the daratumumab 
group. The applicant stated that of the 388 patients randomized in the 
study, compliance rates for all PRO questionnaires were >90% at 
baseline and >83% through Cycle 6. The questionnaires included the 
European Organization for Research and Treatment of Cancer Quality of 
Life Questionnaire Core 30-item (EORTC QLQ-C30), the EuroQol 5-
dimensional descriptive system (EQ-5D-5L), and Short Form-36 (SF-36). 
Secondary endpoints centered around improvements in EORTC QLQ-C30 
global health status (GHS), fatigue scale scores, and SF-36 mental 
component summary (MCS) score. Exploratory outcomes included physical 
function assessment, symptom improvement, functional improvement, and 
health utility as measured by the SF-36, EORTC QLQC30 with supplemental 
symptom items, and the EQ-5D-5L.
---------------------------------------------------------------------------

    \125\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    The applicant stated that the results from this presentation show 
that following Cycle 6, improvements in GHS and fatigue were reported 
in patients in the treatment group, and that these findings further 
support the value of daratumumab SQ plus CyBorD (Dara-CyBorD) in 
patients with AL amyloidosis. The applicant also stated that patients 
with AL amyloidosis treated with Dara-CyBorD experienced clinical 
improvements without any decrement in HRQoL over 6 cycles. The 
applicant noted that the findings demonstrated that the median time to 
improvement was shorter in the treatment group than in the control 
group for EORTC QLQ-C30 GHS (CyBorD: 16.79 months, 95% CI:11.79 to NE, 
Dara-CyBorD: 7.82 months, 95% CI: 3.94 to 17.58, HR 1.53; 95% CI: 1.10 
to 2.13), fatigue scales (CyBorD: NE, 95% CI:8.44 to NE, Dara-CyBorD: 
9.30 months, 95% CI: 5.55 to 13.01, HR 1.39; 95% CI: 1.00 to 1.93) and 
EQ-5D-5L visual analog scale (CyBorD: NE, 95% CI:16.79 to NE, Dara-
CyBorD: 10.05 months, 95% CI: 8.41 to NE, HR 1.21; 95% CI: 0.86 to 
1.71). The applicant also noted that the findings demonstrated that 
median time to worsening was longer in the treatment group than in the 
control group for EORTC QLQ-C30 GHS (CyBorD: 2.89 months, 95% CI:2.23 
to 3.78, Dara-CyBorD: 4.70 months, 95% CI: 2.83 to 7.36, HR 0.87; 95% 
CI: 0.66 to 1.13) and fatigue scales (CyBorD: 3.75 months, 95% CI: 2.86 
to 4.76 Dara-CyBorD: 8.84 months, 95% CI: 3.75 to NE, HR 0.78; 95% CI: 
0.58 to 1.04) and EQ-5D-5L visual analog scale (CyBorD: 3.38 months, 
95% CI:2.79 to 4.67, Dara-CyBorD: 4.14 months, 95% CI: 2.86 to 7.66, HR 
0.89; 95% CI: 0.67 to 1.19).\126\
---------------------------------------------------------------------------

    \126\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    Finally, the applicant stated that DARZALEX FASPRO[supreg] provides 
important advantages to the population with AL amyloidosis because the 
subcutaneous administration allows for a negligible volume of 
administration and a reduced rate of systemic administration-related 
reactions.\127\
---------------------------------------------------------------------------

    \127\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. NEJM. 2021;385:46-58.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether DARZALEX FASPRO[supreg] meets 
the substantial clinical improvement criterion. First, with respect to 
the ANDROMEDA trial, we note that the study's open label and unblinded 
design adds a potential risk of bias which may affect the treatment 
effect reported by the applicant. Additionally, we note that the 
ANDROMEDA trial used stratified randomization which resulted in 
potentially substantive differences between the treatment and control 
group at baseline; for example, the control group was slightly older, 
with more males, and more people at higher cardiac stage (based on N-
terminal pro-B-type natriuretic peptide and high-sensitivity cardiac 
troponin T). The groups also differed by Eastern Cooperative Oncology 
Group (ECOG) performance-status scores and uninvolved free light chain 
(dFLC) levels, and renal function. Additionally, compared to control, 
the daratumumab group appeared to have higher rates of peripheral 
sensory neuropathy, upper respiratory infection, and neutropenia in the 
longer term data.\128\ We question whether these differences noted at 
baseline are in fact significant and would have the potential to impact 
the treatment effect seen in this study. In terms of study outcomes, 
the ANDROMEDA study relied on hematologic and organ-based laboratory-
based outcomes, but we question whether a primary endpoint of overall 
survival would have provided stronger evidence.
---------------------------------------------------------------------------

    \128\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    Second, we have concerns about the generalizability of the 
ANDROMEDA population and subgroups. As clarified by the applicant 
during the New Technology Town Hall meeting, all subjects in the 
ANDROMEDA trial received DARZALEX FASPRO[supreg] in the outpatient 
setting. As such, we question whether the outcomes for this outpatient 
population are generalizable to patients who are sufficiently ill to 
require hospitalization. In regard to subpopulations, we note that the 
prespecified groups and the studies of cardiac stage and Asian cohorts 
exhibit the same potential limitations of the main trial with small 
sample size, open-label, and limited follow-up. We note that small 
sample size resulted in wider confidence intervals in some subgroups, 
which may limit the generalizability of the treatment results. For 
example, in the ANDROMEDA prespecified groups, the subgroups `other' 
race, cardiac stage I at baseline, and renal stage III had wider 
confidence intervals than other subgroups. Finally, while the applicant 
provided a phase 2 poster presentation in support of DARZALEX 
FASPRO[supreg] we question the extent to which these results are 
generalizable to the indication for which the applicant has applied for 
the new technology add-on payment (that is, the treatment of adult 
patients with light chain (AL) amyloidosis in combination with 
bortezomib, cyclophosphamide and dexamethasone in newly diagnosed 
patients) given that the indication within this source (that is 
monotherapy in patients with Stage 3B AL amyloidosis), does not 
match.\129\
---------------------------------------------------------------------------

    \129\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    We note that the applicant provided the outcomes of secondary 
endpoints

[[Page 28235]]

which appear to be exploratory or novel for some of the data presented 
in posters in support of its claims, such as the quality of life 
assessments \130\ and hematologic response as measured by involved and 
uninvolved free light chain,\131\ and we note that some of the 
endpoints are still being studied and validated. Specifically, we 
question whether these surrogate endpoints may be used to appropriately 
evaluate the measure for which they are intended to assess. We request 
further information on whether these secondary endpoints have been 
appropriately validated in relevant clinical settings.
---------------------------------------------------------------------------

    \130\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
    \131\ Comenzo et al., Reduction in Absolute Involved Free Light 
Chain and Difference Between Involved and Uninvolved Free Light 
Chain is Associated with Prolonged Major Organ Deterioration 
Progression Free survival in Patient with Newly Diagnosed AL 
Amyloidosis Receiving Bortezomib, Cyclophosphamide and Dexamethasone 
with or without Daratumumab: Results from ANDROMEDA, Oral 
presentation at: American Society of Hematology (ASH) Annual Virtual 
Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    We are inviting public comments on whether DARZALEX FASPRO[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 DARZALEX FASPRO[supreg].
    Comment: The applicant provided a supplemental written response 
pertaining to data from the ANDROMEDA trial. The applicant clarified 
that the ITT population represented all patients that underwent 
randomization, while the safety population represented patients who 
received at least one dose of study treatment. Per the applicant, among 
the 388 patients who underwent randomization (ITT population--195 vs. 
193 in the treatment vs. control group, respectively), 381 received at 
least one dose of trial treatment (safety population--193 vs. 188 in 
the treatment vs. control group, respectively).
    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 DARZALEX FASPRO[supreg].
c. Hemolung Respiratory Assist System (Hemolung RAS)
    ALung Technologies, Inc. submitted an application for new 
technology add-on payments for the Hemolung Respiratory Assist System 
(Hemolung RAS) for FY 2023. The applicant stated that the Hemolung RAS 
is the first and only FDA authorized technology for the treatment of 
acute, hypercapnic respiratory failure using an extracorporeal circuit 
to remove CO2 directly from the blood. Per the applicant, 
patients experiencing acute, hypercapnic respiratory failure are unable 
to remove excess CO2 waste molecules from their blood via 
their lungs, resulting in accumulation of CO2 in their blood 
(hypercapnia), acid/base derangement (respiratory acidosis), and life-
threatening clinical sequelae.\132\ The applicant stated that the 
Hemolung RAS does not treat a specific disease but removes 
CO2 directly from the blood to treat a variety of underlying 
respiratory disease states, including, but not limited to, cystic 
fibrosis (CF), chronic obstructive pulmonary disease (COPD), and 
asthma, where CO2 retention (hypercapnia) is the primary 
cause of continued clinical deterioration.
---------------------------------------------------------------------------

    \132\ Nin, N. et al. Severe hypercapnia and outcome of 
mechanically ventilated patients with moderate or severe acute 
respiratory distress syndrome. Intensive Care Med 43, 200-208 
(2017).
---------------------------------------------------------------------------

    Per the applicant, the Hemolung RAS provides low-flow, veno-venous 
extracorporeal carbon dioxide removal (ECCO2R) using a 15.5 
French dual lumen catheter inserted percutaneously in the femoral or 
jugular vein, providing partial ventilatory lung support independent of 
the lungs as an alternative or supplement to invasive mechanical 
ventilation. The applicant stated that the Hemolung RAS removes up to 
50% of basal metabolic carbon dioxide (CO2) production at 
circuit blood flows of 350-550 mL/min. According to the applicant, the 
Hemolung RAS is not intended to provide therapeutic levels of 
oxygenation. The applicant stated that during the Hemolung RAS therapy, 
blood passing through the circuit is oxygenated; however, at low 
extracorporeal blood flows, the limited oxygen-carrying capacity of 
blood precludes meaningful oxygenation of mixed venous blood. 
Extracorporeal therapy with the Hemolung RAS requires continuous 
systemic anticoagulation with unfractionated heparin or a standard of 
care alternative to prevent clotting of blood in the circuit.
    With respect to the newness criterion, the applicant stated that 
the Hemolung RAS received Breakthrough Device Designation from FDA in 
2015 specific to COPD patients experiencing acute, refractory, 
hypercapnic respiratory failure. The applicant stated it is not 
applying under the Breakthrough Device Alternative Pathway in the 
current application for new technology add-on payments, as the 
Breakthrough Device indication is different from its FDA De Novo 
indication. The applicant explained that the Hemolung RAS was 
classified as a Class III device and received a Breakthrough Device 
designation for COPD only. According to the applicant, on April 22, 
2020, the Hemolung RAS received an Emergency Use Authorization (EUA) to 
treat lung failure due to COVID-19 when used as an adjunct to 
noninvasive or invasive mechanical ventilation in reducing hypercapnia 
and hypercapnic acidosis due to COVID-19 and/or maintaining normalized 
levels of partial pressure of carbon dioxide (PCO2) and pH 
in patients suffering from acute, reversible respiratory failure due to 
COVID-19 for whom ventilation of CO2 cannot be adequately, 
safely, or tolerably achieved. The applicant further explained Hemolung 
RAS was later classified as a Class II device under the De Novo 
pathway. The applicant indicated its De Novo classification request 
(DEN210006) was granted on November 13, 2021, for the indication of 
respiratory support providing extracorporeal carbon dioxide 
(CO2) removal from the patient's blood for up to five days 
in adults with acute, reversible respiratory failure for whom 
ventilation of CO2 cannot be adequately or safely achieved 
using other available treatment options and continued clinical 
deterioration is expected. According to the applicant, the De Novo 
classified Hemolung RAS became available on the market on November 15, 
2021, the first business day following the FDA authorization. The 
applicant indicated that it is seeking new technology add-on payments 
for FY 2023 for the FDA De Novo indication for the treatment of 
hypercapnic respiratory failure due to all causes in adults, which 
would include the EUA indication for the use of the Hemolung RAS in 
patients with respiratory failure caused by COVID-19. The applicant 
stated that the following ICD-10-PCS code may be used to uniquely 
describe procedures involving the use of the Hemolung RAS: 5A0920Z 
(Assistance with respiratory filtration, continuous, 
ECCO2R).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be

[[Page 28236]]

considered substantially similar to an existing technology and would 
not be considered ``new'' for the purposes of new technology add-on 
payments. According to the applicant, patients experiencing acute, 
hypercapnic respiratory failure are treated pharmacologically and with 
non-invasive ventilatory support as a first line treatment. The 
applicant stated that if these treatments are insufficient to support 
the failing lungs, escalation of ventilatory support via intubation and 
invasive mechanical ventilation (IMV) are the only available treatment 
options. According to the applicant, patients who are intubated and 
invasively mechanically ventilated are at significant risk for 
increased morbidity and mortality. The applicant stated that no 
additional treatments are available if IMV is insufficient to correct 
refractory hypercapnia and respiratory acidosis, which ultimately lead 
to cardiopulmonary collapse and death. Furthermore, the applicant 
stated that no treatment options are available for patients who have a 
Do Not Intubate (DNI) order.
    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 the Hemolung RAS has a different mechanism of 
action compared to existing technologies. According to the applicant, 
IMV, the only existing technology used to treat acute, refractory, 
hypercapnic respiratory failure, utilizes positive airway pressure to 
deliver oxygen and remove CO2 from the lungs, whereas the 
Hemolung RAS removes CO2 directly from the blood, 
independent of the lungs and allowing the lungs to rest and recover. 
Thus, the applicant asserted that the Hemolung RAS uses a different 
mechanism of action when compared to the existing therapeutic option 
(that is, IMV). The applicant also stated that extracorporeal membrane 
oxygenation (ECMO) is a rescue therapy for patients experiencing 
refractory hypoxemic respiratory failure, where insufficient 
oxygenation is the source of the respiratory failure. However, the 
applicant stated that ECMO is not suitable, nor FDA-approved, as a 
treatment for acute, hypercapnic respiratory failure. Therefore, the 
applicant asserted that ECMO and the Hemolung RAS are fundamentally 
different technologies used to treat different patient populations.
    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 Hemolung RAS is assigned to 
the same MS-DRGs when compared to an existing technology. Per the 
applicant, the Hemolung RAS is an escalation therapy to be used when 
current therapies are unable to support a patient's failing lungs and 
continued clinical deterioration is expected. The applicant noted that 
MS-DRGs 207 and 208 (Respiratory System Diagnosis with Ventilator 
Support > 96 Hours and Respiratory System Diagnosis with Ventilator 
Support <= 96 Hours, respectively) relate to the treatment of 
respiratory failure using mechanical ventilation, so the Hemolung RAS 
may be assigned to the same MS-DRGs if mechanical ventilation is unable 
to safely or adequately remove CO2 from the blood.
    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 Hemolung RAS and IMV 
are both used to treat patients experiencing acute, refractory, 
hypercapnic respiratory failure due to numerous disease etiologies and 
pathophysiologies. However, the applicant noted that the Hemolung RAS 
is indicated for use as an escalation therapy when IMV is unable to 
safely or adequately remove CO2 from the blood and continued 
clinical deterioration is expected.
    In summary, the applicant maintained that the Hemolung RAS is not 
substantially similar to currently available therapies and/or 
technologies because it uses a new mechanism of action and therefore 
the technology meets the ``newness'' criterion.
    As noted previously, the applicant received an FDA De Novo 
classification for the device on November 13, 2021 (with the product 
becoming commercially available on November 15, 2021), for the FDA De 
Novo indication that is the subject of this application, for the 
treatment of hypercapnic respiratory failure due to all causes in 
adults. This De Novo indication would include use of the product for 
the indication for which the applicant initially received an EUA from 
FDA, for the use of the Hemolung RAS in patients with respiratory 
failure caused by COVID-19. In the FY 2005 IPPS/LTCH PPS final rule, we 
stated that 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 two to three 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 MS-DRG weights (69 FR 49002). While 
our policy is, generally, 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 as discussed in prior rulemaking (77 FR 
53348), we have noted that 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 (86 FR 
45159). We refer readers to section II.F.7. of the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45159 through 45160), for discussion of our 
solicitation of comments regarding the newness period for products 
available through an EUA for COVID-19. As discussed in section II.F.4 
of the preamble of this proposed rule, we are continuing to consider 
the comments we received regarding the newness period for products 
available through an EUA for COVID-19 as discussed in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45159), and we welcome additional comments 
in this proposed rule.
    Therefore, because data reflecting the costs of the Hemolung RAS 
used for the indication of COVID-19 could be available beginning with 
the EUA on April 22, 2020, we question whether the newness period for 
the use of the Hemolung RAS for patients with COVID-19 should begin 
with the date of EUA issuance, April 22, 2020, while the newness period 
for the use of Hemolung RAS for patients with other causes of 
hypercapnic respiratory failure unrelated to COVID-19 should begin on 
the date of commercial availability of the De Novo classified device, 
November 15, 2021. As discussed in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45159 through 45160), 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, a product available only 
through an EUA would not be eligible for new technology add-on 
payments. Therefore, cases involving pediatric patients, or cases 
involving the use of the Hemolung RAS for greater than 5 days, would 
not be eligible for new technology add-on payment if the Hemolung RAS 
is approved for new technology add-on payment for the patient 
population indicated in its FDA De Novo marketing authorization.
    We invite public comments on whether the newness period for the 
Hemolung RAS when used for patients with COVID-19 should begin on April 
22, 2020 (the date of its EUA), when the product became available on 
the market for this indication. We are inviting

[[Page 28237]]

public comments on whether the Hemolung RAS is substantially similar to 
existing technologies and whether the Hemolung RAS meets the newness 
criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR Limited 
Data Set (LDS) for cases that received ventilator support to identify 
patients who may have been eligible for the Hemolung RAS. The applicant 
reviewed multiple ICD-10-CM and ICD-10-PCS codes related to respiratory 
failure and hypercapnic disease and determined that two ICD-10-PCS 
codes were most applicable: 5A1955Z (Respiratory ventilation, greater 
than 96 consecutive hours) and 5A1945Z (Respiratory ventilation, 24-96 
consecutive hours). We note that, in the applicant's analysis, it 
listed ICD-10-PCS code 5A1955Z as 5A1935Z (Respiratory ventilation, 
greater than 96 consecutive hours), but we believe the applicant 
intended to reference the correct ICD-10-PCS code 5A1955Z (Respiratory 
ventilation, greater than 96 consecutive hours) to correctly map to MS-
DRG 207 (Respiratory System Diagnosis with Ventilator Support > 96 
Hours).
    The applicant identified 68,317 cases mapping to MS-DRGs 207 
(Respiratory System Diagnosis with Ventilator Support > 96 Hours) and 
208 (Respiratory System Diagnosis with Ventilator Support <= 96 Hours). 
MS-DRG 207 contained 24.6% of the cases and MS-DRG 208 contained the 
remaining 75.4% of cases.
    Next, the applicant removed 100% of the inhalation charges and 
charges associated with a 1-day length of stay (LOS) in the intensive 
care unit (ICU). The applicant explained that it removed the 1 day of 
routine care plus ICU day charges based on an assumed LOS reduction 
associated with the use of the Hemolung RAS from relevant cases (as 
compared to cases without the Hemolung RAS) to estimate the potential 
decrease in costs as a result of the use of the Hemolung RAS.\133\ The 
applicant then standardized the charges and applied a 4-year inflation 
factor of 1.281834 or 28.1834%, based on the inflation factor used in 
the FY 2022 IPPS/LTCH PPS final rule and correction notice to calculate 
outlier threshold charges (86 FR 45542). The applicant then added 
charges for the new technology, which it calculated by dividing the 
cost of the Hemolung RAS by the national average CCR for inhalation 
therapy, which is 0.147 (86 FR 44966).
---------------------------------------------------------------------------

    \133\ Tiruvoipati, et al., ``Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients:'' Crit Care Med. Vol 456(7). e649-e656.
---------------------------------------------------------------------------

    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $178,436, which exceeded the average 
case-weighted threshold amount of $102,867. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that the 
Hemolung RAS meets the cost criterion.
    After review of the cost analysis provided by the applicant, we 
question whether the analysis should have included patients who would 
also require a tracheostomy, which could result in cases mapping to the 
Pre-Major Diagnostic Category (Pre-MDC) MS-DRGs 003 or 004 if used with 
mechanical ventilation, and whether the inclusion of those additional 
MS-DRGs would impact the cost analysis. We are seeking comments on 
whether the Hemolung RAS meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that the Hemolung RAS offers a treatment option for 
patients unresponsive to non-invasive mechanical ventilation (NIV), 
patients unresponsive to invasive mechanical ventilation (IMV), and 
patients ineligible for currently available treatments (that is, 
failure of NIV with DNI order). Further, the applicant asserted that 
the Hemolung RAS significantly improves clinical outcomes relative to 
available services or technologies.
    With regard to the claim that the Hemolung RAS offers a treatment 
option for patients unresponsive to NIV, the applicant noted that while 
acute respiratory failure can often be treated with NIV, which does not 
require intubation and is typically safe and well tolerated, 12-50% of 
patients are unresponsive to NIV as a result of several factors, 
including elevated respiratory rates, uncorrected respiratory acidosis, 
and reduced level of consciousness.134 135 136 Further, the 
applicant stated that if a patient fails NIV, the only currently 
indicated treatment is escalation to IMV; however, per the applicant, 
intubation and IMV following NIV failure is associated with a 200% 
increase in mortality compared to patients successfully treated with 
NIV; 27% vs 9% mortality rate, respectively.\137\
---------------------------------------------------------------------------

    \134\ Conti, V. et al. Predictors of outcome for patients with 
severe respiratory failure requiring noninvasive mechanical 
ventilation. Eur Rev Med Pharmacol Sci 19, 3855-3860 (2015).
    \135\ Bott, J. et al. Randomised controlled trial of nasal 
ventilation in acute ventilatory failure due to chronic obstructive 
airways disease. Lancet 341, 1555-1557 (1993).
    \136\ Phua, J., Kong, K., Lee, K.H., Shen, L. & Lim, T.K. 
Noninvasive ventilation in hypercapnic acute respiratory failure due 
to chronic obstructive pulmonary disease vs. other conditions: 
Effectiveness and predictors of failure. Intensive Care Med 31, 533-
539 (2005).
    \137\ Chandra, D. et al. Outcomes of noninvasive ventilation for 
acute exacerbations of chronic obstructive pulmonary disease in the 
United States, 1998-2008. Am. J. Respir. Crit. Care Med. 185, 152-
159 (2012).
---------------------------------------------------------------------------

    The applicant asserted that the Hemolung RAS can be an effective 
tool for patients unresponsive to NIV by rapidly correcting respiratory 
acidosis (pH and arterial partial pressure of carbon dioxide 
(PaCO2)), thereby reducing respiratory drive and improving 
NIV efficacy. In support of this claim, the applicant submitted a 
consensus paper by Combes et al.\138\ In this consensus paper, 14 
clinical experts in critical care and respiratory support using 
ECCO2R convened to determine how ECCO2R therapy 
is applied, identify how patients are selected, and discuss how 
treatment decisions are made. Per the applicant, the results of the 
paper showed that there were two groups of patients where 
ECCO2R therapy was indicated--patients with acute 
respiratory distress syndrome (ARDS) or patients with COPD. The 
treatment goal for ECCO2R therapy in patients with ARDS is 
to provide ultra-protective lung ventilation via managing 
CO2 levels. The criteria for initiating ECCO2R 
therapy in patients with ARDS and on NIV is when there was no decrease 
in PaCO2 and no decrease in respiratory rate. In patients 
with acute COPD exacerbation, treatment targets were patient comfort, 
pH between 7.30-7.35, respiratory rate less than 20-25 breaths per 
minute, decrease of PaCO2 by 10-20%, weaning from NIV, 
decrease in bicarbonate levels (HCO3), and maintaining 
hemodynamic stability. The clinical experts came to the consensus that 
ECCO2R therapy may be an effective support treatment for 
adults with ARDS or COPD exacerbation, but noted the need for further 
evidence from randomized clinical trials and/or high quality 
prospective studies to better guide decision-making.
---------------------------------------------------------------------------

    \138\ Combes, A. et al. ECCO2R therapy in the ICU: 
Consensus of a European round table meeting. Critical Care 24, 
(2020).
---------------------------------------------------------------------------

    The applicant also submitted three peer-reviewed publications in 
support of this claim. First the applicant cited Bonin et al.,\139\ a 
case study of a 50-year-

[[Page 28238]]

old male awaiting a bilateral lung transplant, admitted for COPD 
exacerbation caused by infection. The patient was initially treated 
with antibiotics and continuous NIV, which he tolerated for three days. 
After three days, the patient decompensated due to a spontaneous 
pneumothorax. The lung was emergently reinflated, but the patient's 
respiratory status continued to decline with a PaCO2 between 
72-85 mmHg, pH of less than 7.3, and a respiratory rate of 30-40. The 
patient showed signs of exhaustion but did not qualify for intubation 
due to the recent pneumothorax. The patient consented to the Hemolung 
RAS therapy and within the first hour of treatment, the patient's 
respiratory rate improved to around 10 breaths/minute. However, the 
patient was no longer able to tolerate the NIV minimum set breathing 
rate, so the minimum set breathing rate was turned off. The 
PaCO2 decreased to 55-60 mmHg for the duration of therapy (6 
days). The patient was able to be successfully weaned from continuous 
NIV. The patient was also able to take oral nutrition and participate 
in interventions against pressure sores. After day 6, the patient was 
able to wean from the Hemolung RAS support and continue with 
intermittent NIV support.
---------------------------------------------------------------------------

    \139\ Bonin, F., Sommerwerck, U., Lund, L. & Teschler, H. 
Avoidance of intubation during acute exacerbation of chronic 
obstructive pulmonary disease for a lung transplant candidate using 
extracorporeal carbon dioxide removal with the Hemolung. The Journal 
of Thoracic and Cardiovascular Surgery 145, e43-e44 (2013).
---------------------------------------------------------------------------

    Second, the applicant cited a multi-national pilot study done by 
Burki et al.\140\ in India and Germany. There were 20 COPD patients 
with hypercapnic respiratory failure treated with ECCO2R 
therapy and placed into 1 of 3 groups. Group 1 had seven patients on 
NIV with a high likelihood of requiring IMV; Group 2 had two patients 
who could not be weaned from NIV; and Group 3 had 11 patients on IMV 
who failed weaning attempts. The authors found that the device was 
well-tolerated with complications and rates similar to those seen with 
central venous catheterization. The patients in Group 1 successfully 
avoided IMV as a result of ECCO2R therapy, although three 
patients died within 30 days of ECCO2R therapy due to 
underlying disease states. The patients in Group 2 were successfully 
weaned from continuous NIV after receiving ECCO2R therapy 
and were alive 30 days after ECCO2R therapy, but remained on 
intermittent non-invasive, positive-pressure ventilation (NIPPV) 
support. Of the patients in Group 3, nine of the 11 patients had been 
on IMV for greater than 15 days prior to ECCO2R therapy. In 
Group 3, three patients were weaned from IMV, three patients had 
decreased IMV support, one patient expired from retroperitoneal bleed 
following catheterization, and one patient remained on the same level 
of ventilatory support despite receiving ECCO2R therapy. The 
authors concluded that the single catheter, low-flow ECCO2R 
system, provided clinically useful levels of CO2 removal in 
patients with COPD and could be a potentially valuable addition to the 
treatment of hypercapnic respiratory failure.
---------------------------------------------------------------------------

    \140\ Burki, N. et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest 143, 678-686 (2013).
---------------------------------------------------------------------------

    Third, the applicant cited a case series by Tiruvoipati et al. 
(2016),\141\ which retrospectively reviewed 15 patients among three 
Australian ICUs treated with the Hemolung RAS who had severe 
hypercapnic respiratory failure due to COPD, ARDS, asthma, or 
bronchiolitis obliterans syndrome (BOS), to show that ECCO2R 
was safe and effective in the removal of CO2. For five 
patients (four with COPD and one with BOS), the indication for the 
Hemolung RAS was to avoid intubation, whereas for the other 10 patients 
(five with acute lung injury/ARDS, three with asthma, and two with 
COPD), the indication was to institute lung-protective ventilation. The 
median age of the patients was 61.5 years; 12 patients were men, the 
median Acute Physiology and Chronic Health Evaluation III (APACHE III) 
score was 85, and the median duration of ECCO2R was 5 days. 
The primary outcome measures of the study were clearance of 
CO2 and change in pH with the use of ECCO2R. 
Secondary outcome measures included complications associated with 
Hemolung RAS use, survival to weaning from the Hemolung RAS, and 
survival to ICU and hospital discharge. There was no specified protocol 
for managing mechanical ventilation across the three centers; however, 
all centers used low-pressure ventilation for ARDS. For asthma, the 
mechanical ventilation was characterized by low tidal volume, low 
respiratory rate, and short inspiratory time associated with prolonged 
expiratory time to avoid dynamic hyperinflation. Four of the five 
patients treated for this indication, as well as all 10 patients who 
were treated to institute lung-protective ventilation, avoided 
intubation; successful lung-protective ventilation was achieved by a 
reduction in peak inspiratory pressure, tidal volume, and minute 
ventilation. The clearance of CO2 and return of 
PaCO2 to near-normal levels was achieved within 6 hours, and 
there was significant reduction in minute ventilation and peak airway 
pressures. Complications reported during the study included hemorrhage, 
thrombocytopenia, and compartment syndrome, none of which required 
cessation of the Hemolung RAS therapy. Overall, 93.3% of the patients 
survived to discontinuation of ECCO2R, 73.3% of patients 
survived to ICU discharge, and 66.66% of patients survived to hospital 
discharge. In conclusion, the study authors stated that the Hemolung 
RAS appears to be safe and effective for managing hypercapnic 
respiratory failure of various etiologies, but noted that more research 
is needed to clarify which patients may benefit most from this therapy.
---------------------------------------------------------------------------

    \141\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
---------------------------------------------------------------------------

    In addition to the previous peer-reviewed studies, the applicant 
also cited the Hemolung RAS Registry Program Analysis in support of its 
claim.\142\ Per the applicant, the voluntary Hemolung RAS Registry 
Program collected data from commercial use of the Hemolung RAS outside 
of the US as well as US EUA therapies. 176 patients from the Hemolung 
RAS Registry were analyzed to evaluate the benefits and safety of the 
Hemolung RAS therapy. The applicant stated that the Hemolung RAS 
Registry Program Analysis demonstrated that 86% (19/22) of patients 
failing NIV avoided intubation due to the Hemolung RAS therapy.
---------------------------------------------------------------------------

    \142\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that the Hemolung RAS 
offers a treatment option for patients unresponsive to IMV and are 
retaining CO2, the applicant stated that the Hemolung RAS 
de-couples CO2 removal from the mechanical ventilator 
thereby allowing correction of hypercapnia and hypercapnic acidosis 
without a dangerous escalation of ventilator settings. The applicant 
provided 10 publications that document the use of the Hemolung RAS in 
patients unresponsive to IMV to significantly reduce ventilator 
settings to lung safe levels or to significantly correct and control 
hypercapnic acidosis, including

[[Page 28239]]

Tiruvoipati et al. (2016) \143\ and Combes et al.,\144\ discussed 
previously.
---------------------------------------------------------------------------

    \143\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
    \144\ Combes, A. et al. ECCO2R therapy in the ICU: 
Consensus of a European round table meeting. Critical Care 24, 
(2020).
---------------------------------------------------------------------------

    In the first case study, a 44-year-old male with acute asthma 
exacerbation went into respiratory arrest and was intubated in the 
emergency department (ED).\145\ The patient was found to have a left 
tension pneumothorax, which was decompressed, and then developed a 
second tension pneumothorax on the right side, which was also 
decompressed. The patient was transferred to the ICU for further 
management. The patient continued to deteriorate over the subsequent 48 
hours due to subcutaneous emphysema and ongoing air leaks, and after 72 
hours had uncontrollable hypercapnia (PaCO2 73, pH 7.22) 
despite optimal medical management with corticosteroids, nebulized and 
intravenous bronchodilators, magnesium, ketamine, and muscle relaxants. 
ECCO2R was indicated for hypercapnia and to facilitate de-
escalation of IMV. After initiating ECCO2R, it was possible 
to decrease the support on the IMV while maintaining satisfactory gas 
exchange and allowing the withdrawal of muscle relaxants. Within 1 hour 
of initiation of ECCO2R, the pH improved from 7.22 to 7.28, 
and the PaCO2 went from 68.1 to 60.6. The patient remained 
on ECCO2R for a total of 7 days mainly due to ongoing air 
leaks from three chest drains and a bleeding complication that was 
managed with transfusion. After discontinuing ECCO2R 
therapy, the patient received a tracheostomy to assist in weaning from 
IMV. The patient was successfully weaned from IMV after 23 days in the 
ICU and was ultimately discharged home. The authors discussed that 
while this patient could have been treated with ECMO, the use of ECMO 
is limited to specialized centers and requires a multidisciplinary 
approach for a successful outcome.
---------------------------------------------------------------------------

    \145\ Tiruvoipati R, et al. Low-flow veno-venous extracorporeal 
carbon dioxide removal in the management of severe status 
asthmatics: A case report. Clin Respir J. 2014;10(5):653-656.
---------------------------------------------------------------------------

    In the second case study, the Hemolung RAS system was used to treat 
hypercapnia in a 58-year-old male patient with an out-of-hospital 
cardiac arrest where mechanical ventilation failed to achieve 
normocapnia.\146\ The patient was intubated in the ED and treated with 
nebulized bronchodilators, corticosteroids, and therapeutic 
hypothermia. Initially, the PaCO2 was 82 mmHg (baseline 50 
mmHg) with a pH of 7.20, but as the next few hours progressed, the 
patient became more difficult to ventilate and the PaCO2 
increased to 94 mmHg. ECCO2R therapy was indicated to 
prevent lung injury and secondary brain injury. After initiating the 
Hemolung RAS, the minute ventilation and the respiratory rate could be 
decreased and the team was able to optimize the inspiratory and 
expiratory time ration to minimize the risk of barotrauma. The patient 
was on the Hemolung RAS therapy for 3 days and was able to de-escalate 
the ventilator settings, but still required mechanical ventilation. 
After cessation of the Hemolung RAS therapy, the patient started to 
show signs of significant hypoxic brain injury. Despite maximal medical 
treatment, the neurological prognosis was considered to be very poor, 
and all life-sustaining therapies were withdrawn. The authors stated 
that ECCO2R therapy is safe to use in a metropolitan 
hospital where the staff have a limited period of education, and that 
the extracorporeal therapy was delivered without complications. The 
authors also stated that ECMO is not an option in every health care 
center since it requires a specialized team including cardiac surgeons 
and perfusionists and is costly. The authors stated that 
ECCO2R is less invasive and able to provide partial 
respiratory support. Thus, the authors concluded that ECCO2R 
may have a role in patients with severe respiratory failure when IMV 
alone is inadequate and in centers that are not capable of initiating 
ECMO in the management of severe hypercapnic respiratory failure.
---------------------------------------------------------------------------

    \146\ Tiruvoipati R, et al. Management of severe hypercapnia 
post cardiac arrest with extracorporeal carbon dioxide removal. 
Anaesth Intensive Care. 2014;42(2):248-252.
---------------------------------------------------------------------------

    Next, the applicant cited a United Kingdom case study about a 48-
year-old male presenting to the ED with 7 days of cough, fever, and 
shortness of breath.\147\ He tested positive for COVID-19 via 
respiratory viral swab and had a chest x-ray demonstrating bilateral 
infiltrates. He initially required supplemental oxygen via facemask and 
oral doxycycline to treat possible bacterial co-infection. He continued 
to deteriorate, was trialed on NIV and failed, and was then 
transitioned to IMV on day four of the hospitalization and transferred 
to the ICU for further management. The patient continued to deteriorate 
and within a week and was found to be in ARDS due to COVID-19 
pneumonitis. The patient was treated with several strategies for lung 
recruitment, and was referred to ECMO but was declined on the basis of 
futility. The treatment team felt that continuing to treat the patient 
with high airway pressure was contributing to the progression of the 
ARDS, so the Hemolung RAS was initiated as a rescue therapy. After 
initiation, the PaCO2 and pH improved, which allowed the 
treatment team to reduce the tidal volume and respiratory rate. The 
patient spent 6 days on the Hemolung RAS without bleeding events or 
vasopressors and could continue to receive prone position ventilation 
without complication. The patient was successfully weaned from the 
Hemolung RAS and then completed a slow respiratory wean followed by a 
percutaneous tracheostomy. The patient was ultimately discharged from 
the ICU to home with mobility and cognition intact. The authors 
concluded that ECCO2R can be used as a rescue therapy for 
patients with hypercapnic respiratory failure resulting from ARDS in 
COVID-19 pneumonitis and to facilitate lung protective ventilation in 
patients on IMV. According to the authors, refractory hypercapnia is an 
acceptable indication for ECMO in ARDS and that ECCO2R can 
be considered as rescue therapy if ECMO is deemed inappropriate or 
cannot be delivered due to resource constraints. Per the authors, 
potential advantages of using ECCO2R over ECMO include lack 
of requirement for transfer to an ECMO center, smaller catheter size, 
and lower blood flow rate which may reduce the likelihood of 
complications.
---------------------------------------------------------------------------

    \147\ Tully RP, et al. The successful use of extracorporeal 
carbon dioxide removal as a rescue therapy in a patient with severe 
COVID-19 pneumonitis. Anaesthesia Reports 2020; 8:113-115.
---------------------------------------------------------------------------

    The applicant also cited a case study of an 18-year-old male with 
solitary mediastinal metastasis and ARDS, in which the Hemolung RAS was 
used to facilitate de-escalation of mechanical ventilation.\148\ Post-
treatment with chemotherapy, a residual mediastinal mass was found with 
extension to the left lung hilum. The patient underwent lung resection 
and was extubated postoperatively without issue. The patient became 
febrile and developed a progressively extensive right lung infiltrate. 
On postoperative day five, the patient developed severe hypercapnia, 
hypoxemia, and hypotension, necessitating re-intubation and invasive 
mechanical ventilation. The Hemolung RAS was initiated to provide 
ECCO2R. Arterial PCO2 decreased from 73 to 53

[[Page 28240]]

mmHg within 4 hours (with a concomitant pH increase from 7.28 to 7.44), 
permitting tidal volume reduction to 3.5 mL/kg, and plateau airway 
pressure to 25 cm H2O, with simultaneous hemodynamic improvement. 
ECCO2R was titrated to maintain an arterial PCO2 
between 45 and 50 mmHg, and the patient was weaned and decannulated 
after 71 hours of support. The patient was removed from mechanical 
ventilation within 24 hours and then transferred to an intermediate 
care unit. No ECCO2R-related complications were observed. 
The authors stated the Hemolung RAS has a conceptual advantage over 
ECMO as the Hemolung RAS uses one small dual-lumen venous catheter, 
without additional arterial access and its attendant risks. The authors 
concluded that in appropriately selected patients, a minimally invasive 
ECCO2R approach may be useful.
---------------------------------------------------------------------------

    \148\ Akkanti B, et al. Low-flow extracorporeal carbon dioxide 
removal using the Hemolung Respiratory Dialysis System[supreg] to 
facilitate lung-protective mechanical ventilation in acute 
respiratory distress syndrome. J Extra Corpor Technol. 
2017;49(2):112-114.
---------------------------------------------------------------------------

    Next, the applicant cited a case study by Saavedra-Romero et 
al.,\149\ which describes the use of ECCO2R immediately 
administered with lung-protective mechanical ventilation on a patient 
with COVID-19 ARDS in her mid-60s. The authors stated that, upon 
arrival to the ICU, on inpatient day 5, the patient's oxygen saturation 
by pulse oximeter (SpO2) was 77%, blood pressure (BP) 90/40 
on norepinephrine at 10 mcg/min, and the patient's initial arterial 
blood gas (ABG) results were pH = 7.14, PaCO2 = 90 mmHg, 
PaO2 = 52 mmHg, and HCO3 = 30mEq/L. The patient 
had significant whole-body subcutaneous crepitus, and the chest x-ray 
(CXR) showed an inflated right lung, subcutaneous emphysema, and an 
appropriately positioned endotracheal tube (ETT). The patient became 
increasingly tachycardic and tachypneic due to further worsening of 
hypercapnia and respiratory acidosis. ECCO2R was initiated 
using the Hemolung RAS and was administered for 17 days without 
complications. Ventilator settings were maintained at PEEP of 14, rate 
of 26, and minute ventilation at 7.8 liters during the first 24 hours. 
Respiratory rate and tidal volumes were subsequently titrated downward, 
maintaining adequate oxygen levels and permissive hypercapnia. The 
patient's chest tubes were removed 4 days after the Hemolung RAS 
decannulation, and the patient was weaned from mechanical ventilation 
28 days from ICU admission, and discharged 47 days after admission. The 
authors stated that this case report highlights the use of 
ECCO2R to facilitate effective treatment of a patient with 
severe hypercapnic respiratory failure secondary to COVID-19 ARDS and 
multiple risk factors for death. The authors stated that treatment with 
ECCO2R allowed a lung-protective ventilator management 
strategy with ultralow tidal volumes, minimizing the risk of 
ventilator-induced lung injury, attenuating severe hypercapnia and 
acidosis, and limiting the expansion of an existing pneumothorax. The 
authors concluded that ECCO2R facilitates early lung-
protective ventilation and control of refractory hypercapnia and can be 
safely utilized to increase the likelihood of survival among patients 
with severe COVID-19 ARDS.
---------------------------------------------------------------------------

    \149\ Saavedra-Romero R, et al. Treatment of Severe Hypercapnic 
Respiratory Failure Caused by SARS-CoV-2 Lung Injury with 
ECCO2R Using the Hemolung Respiratory Assist System. Case 
Reports in Critical Care 2021; 1-5.
---------------------------------------------------------------------------

    Finally, the applicant cited a case study by Bermudez et al.,\150\ 
in which a 33-year-old male with cystic fibrosis (CF), post double lung 
transplantation who developed severe hypercarbic respiratory failure 
due to adenovirus pneumonia requiring hospitalization, tracheostomy, 
and prolonged IMV for greater than 30 days. The patient was transferred 
to a tertiary care center and was treated with the Hemolung RAS because 
of persistent hypoxemia and hypercarbia. The patient was not a 
candidate for ECMO because of frail clinical condition, volume 
overload, and need for a redo lung transplantation. After 4 days of the 
Hemolung RAS support, the patient was weaned from vasopressors, and 
after 9 days, the patient was accepted as a candidate for redo lung 
transplantation because of considerable clinical improvement.
---------------------------------------------------------------------------

    \150\ Bermudez, et al. ``Prolonged Use of the Hemolung 
Respiratory Assist System as a Bridge to Redo Lung Transplantation'' 
Annals of Thorac Surg. 2015 Vol 100 (6). P. 2330-2333.
---------------------------------------------------------------------------

    Lastly, the applicant provided a retrospective, multicenter study 
of 31 patients placed on the Hemolung RAS at 8 sites across the 
U.S.\151\ The cohort was comprised of patients with COVID-19 who were 
mechanically ventilated with severe hypercapnia and respiratory 
acidosis and treated with low-flow extracorporeal CO2 
removal treated between March 4 and September 30, 2020. Two patients 
underwent cannulation but were never started on therapy due to a 
vascular access failure in one patient and immediate circuit clotting 
in the other. For the 29 patients who received the Hemolung RAS 
treatment, analysis of covariance revealed a significant improvement 
trend in both pH and PaCO2 (p<0.0001). Comparison of time 
intervals yielded a statistically significant improvement in pH (7.24 
 0.12 to 7.35  0.07; p<0.0001) and decrease in 
PCO2 (79  23 to 58  14; p<0.0001) 
from baseline to 24 hours after start of therapy. There were numerical, 
but not significant, decreases from baseline to 24 hours in respiratory 
rate (26.6  5.4 to 23.4  4.9), tidal volume 
(407  100 to 386  75 mL), and minute 
ventilation (10.2  3.2 to 8.7  2.2 L/min). The 
authors indicated that this is the first reported use of 
ECCO2R in the U.S. for this patient population. The authors 
reported that limitations of the study are its small size and single-
cohort retrospective nature. The applicant stated that the study 
results demonstrated the efficacy of ECCO2R using the 
Hemolung RAS to improve respiratory acidosis in patients with severe 
hypercapnic respiratory failure due to COVID-19.
---------------------------------------------------------------------------

    \151\ Akkanti B, et al. Physiologic Improvement in Respiratory 
Acidosis Using Extracorporeal CO2 Removal With Hemolung 
Respiratory Assist System in the Management of Severe Respiratory 
Failure From Coronavirus Disease 2019. Critical Care Explorations. 
2021;3:e0372.
---------------------------------------------------------------------------

    In addition to the case reports and retrospective study, the 
applicant also cited to the Hemolung RAS Registry Program Analysis, 
discussed previously, in support of its claim.\152\ The applicant 
stated that the Hemolung RAS Registry Program Analysis demonstrated 
clinically and statistically significant correction of pH and 
PaCO2 within the first day of the Hemolung RAS therapy 
(p<0.05).\153\ Additionally, the applicant noted that the statistical 
analysis showed this correction in pH and PaCO2 was 
independent of the patient's primary diagnosis.
---------------------------------------------------------------------------

    \152\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
    \153\ Ibid. ClinicalTrials.gov. Retrieved December 21, 2021, 
from Hemolung RAS Registry Program--Full Text View--
ClinicalTrials.gov.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that the Hemolung RAS 
offers a treatment option for patients ineligible for currently 
available treatments (for example, patients with a DNI order), the 
applicant reiterated that intubation with IMV is the only currently 
available treatment option for patients failing NIV; however, the 
applicant indicated that these patients have no other therapeutic 
options if they were to fail NIV because of their preference to not be 
intubated. According to the applicant, the CO2 removal by 
the Hemolung RAS would rapidly correct the pH and PaCO2 
which would reduce the respiratory drive and improve NIV

[[Page 28241]]

efficacy and prevent continued clinical 
deterioration.154 155
---------------------------------------------------------------------------

    \154\ Burki, N. et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest 143, 678-686 (2013).
    \155\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
---------------------------------------------------------------------------

    The applicant submitted three peer-reviewed case reports that have 
documented the use of the Hemolung RAS in patients failing NIV with a 
DNI order. In the first case study done in Germany,\156\ a 72-year-old 
female with a past medical history of severe COPD (GOLD 4, nocturnal 
home ventilation therapy) with a DNI order presented to an ED in a 
hypercapnic coma. The patient had a Glasgow Coma Score of 3, pH of 
6.97, and PaCO2 greater than 150 mm Hg. The patient was 
hemodynamically stable on NIV with a respiratory rate of 28, oxygen 
saturation of 88% on supplemental oxygen with an inspired fraction 
(FiO2) of 30%. After 30 minutes of NIV treatment, the 
patient's PaCO2 improved, but the patient was nearly 
unconscious and was transferred to the ICU. Because of the high 
predictive mortality for patients with severe COPD who fail NIV and 
require intubation and invasive mechanical ventilation, combined with 
the patient's DNI order, the Hemolung RAS was initiated to supplement 
treatment. Within the first hour of treatment with both NIV and 
Hemolung RAS, the PaCO2 levels continued to decrease from 
109 mmHg to 89 mmHg and the patient's level of consciousness improved 
after about 25 minutes. Ultimately, the patient was able to start oral 
nutrition, communicate, and start mobilizing early because of her 
improved mental state within four hours of starting the Hemolung RAS 
and was discharged to rehabilitation.
---------------------------------------------------------------------------

    \156\ Engel, M., Albrecht, H. & Volz, S. Use of Extracorporeal 
CO2 Removal to Avoid Invasive Mechanical Ventilation in 
Hypercapnic Coma and Failure of Noninvasive Ventilation. J Pulm 
Respir Med 6, 1-3 (2016).
---------------------------------------------------------------------------

    The second case study by Mani et al. described two patients with 
severe COPD admitted to the ICU with an acute COPD exacerbation 
requiring NIV, but failed NIV treatments.\157\ A 69-year-old female in 
India was admitted with acute COPD exacerbation, waning consciousness 
and a pH of 7.20 and PaCO2 of 101 mmHg. After starting NIV 
for 2 hours, the PaCO2 had risen to 105 mmHg and pH had 
dropped to 7.193. After 1 hour of the Hemolung RAS treatment and NIV, 
the PaCO2 declined to 93 mmHg with a pH 7.25. After 6 hours 
of treatment with the Hemolung RAS and NIV, the patient was awake with 
a PaCO2 of 68 mmHg and a pH of 7.35. Ultimately, she was 
discharged to home on home oxygen and nocturnal NIV. There was also a 
report of a 78-year-old male with COPD and other comorbidities who had 
a DNI order in Germany. He was admitted with an acute COPD exacerbation 
and treated with NIV after his initial arterial blood gas (ABG) showed 
PaCO2 92 mmHg and pH of 7.24. After treatment with both the 
Hemolung RAS and NIV for 1 hour, the patient's PaCO2 dropped 
to 68 mmHg and pH 7.33. Ultimately, the patient was discharged to home 
on nocturnal NIV. Both patients were both diagnosed with 
thrombocytopenia as a known complication of extracorporeal therapy, but 
neither required transfusion.
---------------------------------------------------------------------------

    \157\ Mani, R.K., Schmidt, W., Lund, L.W. & Herth, F.J.F. 
Respiratory dialysis for avoidance of intubation in acute 
exacerbation of COPD. ASAIO J 59, 675-678 (2013).
---------------------------------------------------------------------------

    The applicant submitted a third case study in which Cole et al. 
describe a 62-year-old female with past medical history of COPD (GOLD 
class 3) and 2 recent hospitalizations for COPD exacerbations in the 
past 60 days.\158\ The patient had hypercapnic respiratory failure for 
which she did not want to be intubated, so she was started on NIV. She 
initially improved, but by day four of NIV treatment, she deteriorated, 
as evidenced by tachypnea and fatigue due to increased work of 
breathing. She was started on the Hemolung RAS and within two hours 
therapy with the Hemolung RAS alone (patient requested to stop NIV with 
the initiation of the Hemolung RAS), the patient's respiratory rate 
improved. Within 6 hours, the patient was able to converse and fully 
engage with her treatment. Ultimately the patient was discharged to 
home at her baseline activity level and did not require home oxygen 
therapy, and was not readmitted to hospital within 30 days of 
discharge.
---------------------------------------------------------------------------

    \158\ Cole, S. et al. Extracorporeal carbon dioxide removal as 
an alternative to endotracheal intubation for noninvasive 
ventilation failure in acute exacerbation of COPD. J Int Care Soc 
15, 344-346 (2014).
---------------------------------------------------------------------------

    Furthermore, the applicant claimed that the Hemolung RAS 
significantly improves clinical outcomes relative to services or 
technologies previously available by mitigating the harmful clinical 
sequelae from hypercapnic acidosis and facilitates de-escalation of 
high pressure and high volume ventilatory support or prevent 
intubation, both of which are known predictors for poor clinical 
outcomes. Thus, per the applicant, the correction of hypercapnia and 
hypercapnic acidosis (that is, pH and PaCO2) are appropriate 
surrogate markers for improved clinical outcomes in critically ill, 
mechanically ventilated patients. Per the applicant, the use of 
correction of hypercapnia and hypercapnic acidosis as surrogate markers 
for improved clinical outcomes was accepted by FDA as evidence of the 
clinical benefit of the Hemolung RAS as part of FDA's clearance of its 
De Novo request.
    The applicant asserted that the pH and PaCO2 correction 
due to the Hemolung RAS therapy provide the following six improved 
outcomes: (1) Reduced mortality in intubated and IMV patients; (2) 
reduced length of stay in IMV patients; (3) de-escalation of mechanical 
ventilation settings (decreased rate of subsequent diagnostic or 
therapeutic interventions); (4) avoidance of intubation following NIV 
failure; (5) reduced mortality in NIV patients; and (6) improvement in 
activities of daily living/quality of life.
    In support of its assertion that the Hemolung RAS reduces mortality 
in intubated and IMV patients, the applicant cited two background 
studies.159 160 In the study by Nin et al., the authors 
completed a secondary analysis of 3 prospective, non-interventional 
cohort studies in 1,899 patients with ARDS among 40 ICUs. The goal of 
the study was to determine the relationship between severe hypercapnia 
(PaO2 >=50 mmHg) in the first 48 hours following onset of 
ARDS and mortality. The applicant stated that the study results 
demonstrate that severe hypercapnia in IMV patients was independently 
associated with increased risk of ICU mortality (odds ratio: 1.93, 95% 
CI: 1.32-2.81, p=0.001). The second study by Tiruvoipati et al (2017), 
was a multicenter, binational, retrospective study that included 
252,812 patients of 3 cohorts: Normocapnia and normal pH (n=110,104), 
compensated hypercapnia (n=20,463), and hypercapnic acidosis 
(n=122,245), that aimed to determine the relationship between these 
states and Acute Physiology and Chronic Health Evaluation (APACHE) III 
score and mortality. The study found that those with compensated 
hypercapnia and hypercapnic acidosis had higher APACHE III scores (49.2 
vs. 53.2 vs. 68.6, p<0.01); mortality was highest in the hypercapnic 
acidosis patients (OR: 1.18, 95% CI: 1.1-1.25) and lowest in the 
normocapnia and normal pH,

[[Page 28242]]

p<0.001. The applicant stated that the adjusted odds ratio for hospital 
mortality remained significantly higher in compensated hypercapnia and 
hypercapnic acidosis when compared with patients with normocapnia and 
normal pH irrespective of their P/F ratios.
---------------------------------------------------------------------------

    \159\ Nin, et al., ``Severe hypercapnia and outcome of 
mechanically ventilated patients with moderate or severe acute 
respiratory distress syndrome'' Intensive Care Med. 2017. p. 200-
208.
    \160\ Tiruvoipati, et al., ``Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients'' Crit Care Med. 2017. Vol 456 (7). e649-e656.
---------------------------------------------------------------------------

    In support of the applicant's second assertion that use of the 
Hemolung RAS contributes to reduced LOS in IMV patients, the applicant 
cited Tiruvoipati et al (2017), previously discussed.\161\ The median 
hospital LOS was 10.5 days in the normocapnia and normal pH group, 12 
days in the compensated hypercapnia group and 11 days in the 
hypercapnic acidosis group (p<0.001). The median ICU LOS was 1.9 days 
vs 2.2 days vs. 2.9 days in the normocapnia/normal pH group vs. 
compensated hypercapnia group vs. the hypercapnic acidosis group, 
respectively (p<0.001). The authors noted that that there was increased 
mortality in patients with hypercapnic acidosis and compensated 
hypercapnia with unclear cause.
---------------------------------------------------------------------------

    \161\ Ibid.
---------------------------------------------------------------------------

    In support of the applicant's assertion that use of the Hemolung 
RAS results in de-escalation of mechanical ventilation settings and 
decreased rate of subsequent diagnostic or therapeutic interventions, 
the applicant cited the Tully et al. case report,\162\ discussed 
previously, in which intubated patients had a 20% decrease in peak 
airways pressure and 30% decrease in driving pressure during the 
Hemolung RAS therapy. The applicant also cited the Tiruvoipati et al. 
(2016) study, discussed previously, in which 10 patients showed a 19% 
decrease in peak respiratory pressure and a 26% decrease in minute 
ventilation within 1 day of the Hemolung RAS therapy.\163\ The 
applicant also cited the Hemolung RAS Registry Program Analysis,\164\ 
which demonstrated statistically significant correction of pH and 
PaCO2 within the first day of the Hemolung RAS therapy 
(p<0.05).
---------------------------------------------------------------------------

    \162\ Tully RP, et al. The successful use of extracorporeal 
carbon dioxide removal as a rescue therapy in a patient with severe 
COVID-19 pneumonitis. Anaesthesia Reports 2020; 8:113-115.
    \163\ Tiruvoipati, R, et al. Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients*: Critical Care Medicine. 2017;45(7):e649-e656.
    \164\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    In support of its assertion that use of the Hemolung RAS 
contributes to avoidance of intubation following NIV failure, the 
applicant noted that respiratory acidosis is the primary determinant of 
NIV failure citing risk charts using a background study from 
Confalonieri et al.,\165\ in which data from 1,033 patients admitted to 
experienced hospital units was used to predict the likelihood of 
failure of noninvasive positive pressure ventilation (NPPV). The 
prediction charts were calculated using the APACHE II, GCS, pH, and 
respiratory rate data of 1,033 patients admitted with acute respiratory 
failure due to exacerbation of COPD treated with NIV. The applicant 
stated that the study results show that pH < 7.25 (acidosis) after 2 
hours of NIV is the primary determinant of NIV failure [odds ratio: 
21.02; 95% CI: 10.07-43.87], and that additionally, a pH between 7.25 
and 7.29 (acidosis) after 2 hours of NIV is also significant predictor 
of NIV failure [odds ratio: 2.92; 95% CI: 1.62-5.28]. The applicant 
stated that accuracy and generalizability of the model's ability to 
predict NIV failure was validated on an independent group of 145 COPD 
patients treated with NIV.
---------------------------------------------------------------------------

    \165\ Confalonieri M, et al. A chart of failure risk for 
noninvasive ventilation in patients with COPD exacerbation. European 
Respiratory Journal. 2005;25(2):348-355.
---------------------------------------------------------------------------

    In a prospective, single-arm feasibility study, Burki et al., 
previously discussed, stated that 100% (\7/7\) patients failing NIV and 
treated with the Hemolung RAS therapy avoided intubation and 100% (\2/
2\) patients failing NIV with a DNI and treated with the Hemolung RAS 
therapy were successfully weaned from NIV.\166\ The applicant cited a 
retrospective review by Tiruvoipati et al. (2016), also previously 
discussed, in which 80% (\4/5\) of patients failing NIV and treated 
with Hemolung RAS therapy avoided intubation.\167\ Furthermore, the 
applicant cited an unpublished study of the Hemolung RAS Registry 
Program Analysis,\168\ in which 86% of patients (19 of the 22 patients 
in the analysis) who failed NIV and were treated with the Hemolung RAS 
therapy avoided intubation.
---------------------------------------------------------------------------

    \166\ Burki N, et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest. 2013;143(3):678-686.
    \167\ Tiruvoipati R, et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc. 2016;18(4):261-269.
    \168\ The applicant cited an unpublished study using data 
collected from physicians as part of the Hemolung Registry Program. 
We believe information regarding the Hemolung Registry Program is 
available here: Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    In support of the assertion that the Hemolung RAS reduced mortality 
in NIV patients, the applicant submitted two retrospective studies as 
background studies, in addition to two case studies that utilized the 
technology. The first background study \169\ was a retrospective 
analysis of data from the Healthcare Cost and Utilization Project's 
Nationwide Inpatient Sample between 1998 and 2008 to assess the pattern 
and NIPPV use for acute exacerbations of COPD. The patient cohort was 
defined as people greater than 35-years-old admitted with a primary 
diagnosis of COPD or a primary diagnosis of respiratory failure with a 
secondary diagnosis of COPD. The study demonstrated a decline over time 
in overall in-hospital mortality for those patients treated with NIPPV 
without a subsequent need for IMV. Mortality was high and increased 
over time in patients who transitioned from NIPPV to IMV (27%) compared 
to those patients who did not transition (9%). Charges for 
hospitalization increased from 1998 to 2008, especially for patients 
who transitioned from NIPPV to IMV. LOS decreased in all patients 
except those who transitioned from NIPPV to IMV. The authors noted a 
few limitations that would have allowed for a more detailed examination 
of predictors of NIPPV failure and death, including the lack of 
information on the severity of the exacerbation, response to NIPPV 
treatment, end-of-life decision-making, or location of the patient in 
the hospital (ICU vs. medical ward vs. ED, etc.).
---------------------------------------------------------------------------

    \169\ Chandra, et al, ``Outcomes of noninvasive ventilation for 
acute exacerbations of chronic obstructive pulmonary disease in the 
United States, 1998-2008'' Am J Respir Crit Care Med. 2012. Vol 185 
(2). p. 152-159.
---------------------------------------------------------------------------

    The applicant also cited a retrospective study by Sprooten et 
al.\170\ as background, that looked at patients admitted to the 
Respicare Unit located in Maastricht University Medical Center (MUMC) 
in the Netherlands between 2009 and 2011 who met the criteria of 
admitted for exacerbation of COPD requiring NIV therapy and a 
definitive COPD diagnosis. In-hospital mortality was 14% with a median 
LOS of 16.5 days. Overall, this single-center study showed that 
patients who are admitted to the hospital for a first hospitalization 
requiring NIV for acute respiratory due to COPD exacerbation have a 
high short-

[[Page 28243]]

and long-term mortality rate. According to the article, older age, NIV 
use greater than eight days and lack of successful NIV response were 
independent prognostic factors to two-year mortality rather than 
response of levels of PaCO2 or pH.
---------------------------------------------------------------------------

    \170\ Sprooten, et al. ``Predictors for long-term mortality in 
COPD patients requiring non-invasive positive pressure ventilation 
for the treatment of acute respiratory failure'' Clinical Resp J. 
2020. Vol 14 (12). p. 1144-1152.
---------------------------------------------------------------------------

    The applicant also cited two case studies where the Hemolung RAS 
was used to successfully treat patients in hypercapnic respiratory 
failure caused by COPD. The applicant stated that in these case 
reports, the Hemolung RAS therapy prevented imminent death in COPD 
patients with a DNI order who were failing NIV. In a case study by 
Engel et al., previously described,\171\ a 72-year-old female with 
hypercapnic coma due to COPD exacerbation was administered the Hemolung 
RAS; after 4 hours, PaCO2, pH, and clinical parameters 
improved, and the patient was weaned off therapy after 7 days.
---------------------------------------------------------------------------

    \171\ Engel, et al. ``Use of Extracorporeal CO2 
Removal to Avoid Invasive Mechanical Ventilation in Hypercapnic Coma 
and Failure of Noninvasive Ventilation'' J. Pulm & Resp Med. 2016 
Vol 6 (3) p.1-3.
---------------------------------------------------------------------------

    In a second study by Mani et al., previously described,\172\ the 
Hemolung RAS was used to treat two patients. The first patient, a 69-
year-old female with COPD, was placed on the Hemolung RAS after failing 
NIV treatment. After 66 hours of treatment, the patient was weaned off 
the Hemolung RAS, and was discharged home 4 days later. The second 
patient, a 78-year-old male with COPD, was placed on the Hemolung RAS 
after failing NIV treatment. After 48 hours of treatment, the patient 
was weaned off the Hemolung RAS, and was discharged home 10 days later.
---------------------------------------------------------------------------

    \172\ Mani, R.K., Schmidt, W., Lund, L.W. & Herth, F.J.F. 
Respiratory dialysis for avoidance of intubation in acute 
exacerbation of COPD. ASAIO J 59, 675-678 (2013).
---------------------------------------------------------------------------

    In support of the assertion that the Hemolung RAS improves 
activities of daily living/quality of life, the applicant submitted one 
randomized controlled trial (RCT) abstract and three case studies. In 
the RCT abstract by Barrett at al.,\173\ 18 patients (median age: 67.5 
years) with acute hypercapnic respiratory failure due to exacerbations 
of COPD were randomized to receive NIV alone or ECCO2R and 
NIV. The applicant stated that the study included patients who were at 
high risk of failing NIV (pH<7.30 after >=1 hour of NIV). The applicant 
stated that the control arm continued to be treated with NIV only (n=9) 
and the test arm was treated with ECCO2R (n=9). The primary 
endpoint was the time to cessation of NIV. Secondary outcomes included 
device tolerance and complications, changes in arterial blood gases 
(ABGs) and hospital survival. The time to NIV discontinuation was 
shorter in the ECCO2R arm (7 hours) vs in the NIV alone arm 
(24.5 hours), p = 0.004. The study claimed that dyspnea rapidly 
improved with ECCO2R, but that ICU and hospital LOS were 
longer with the ECCO2R group and there was no difference in 
mortality or functional outcomes at follow-up. The authors concluded 
that ECCO2R can be an alternative to NIV for patients who 
are at risk of failing or cannot tolerate NIV, or for patients in whom 
a more rapid correction of hypercapnia is desirable.
---------------------------------------------------------------------------

    \173\ Barrett, N, et al. A randomized controlled trial of Non-
Invasive Ventilation compared with ECCO2R for Acute 
Hypercapnic Exacerbations of COPD. ASAIO J. 2021; 67 (Supp 3) 
Presented at the 32nd Annual ELSO Conference.
---------------------------------------------------------------------------

    The applicant referred to three case studies using the Hemolung RAS 
to treat hypercapnic respiratory failure, to demonstrate improvement in 
activities of daily living/quality of life. In the case study by Engel 
et al., previously described,\174\ the applicant stated that early 
mobilization, communication, and nutrition were facilitated with 
Hemolung therapy. In the Bermudez et al. case study, previously 
discussed,\175\ the Hemolung RAS was successfully used to bridge a 
patient with COPD to a lung transplantation. The applicant stated that 
considerable clinical improvement attributed to Hemolung therapy 
permitted the patient to be awake and mobilized to sit on the edge of 
the bed. In the Bonin et al. case study, previously discussed,\176\ the 
applicant stated that drinking and recovery from pressure sores were 
possible by day three of the Hemolung RAS.
---------------------------------------------------------------------------

    \174\ Engel, et al. ``Use of Extracorporeal CO2 
Removal to Avoid Invasive Mechanical Ventilation in Hypercapnic Coma 
and Failure of Noninvasive Ventilation'' J. Pulm & Resp Med. 2016 
Vol 6 (3) p.1-3.
    \175\ Bermudez, et al. ``Prolonged Use of the Hemolung 
Respiratory Assist System as a Bridge to Redo Lung Transplantation'' 
Annals of Thorac Surg. 2015 Vol 100 (6). p. 2330-2333.
    \176\ Bonin, et al. ``Avoidance of intubation during acute 
exacerbation of chronic obstructive pulmonary disease for a lung 
transplant candidate using extracorporeal carbon dioxide removal 
with the Hemolung''. J Thorac Cardiovac Surg. 2013. Vol 145 (5). 
e43-e44.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether the Hemolung RAS meets the 
substantial clinical improvement criterion. We note that the evidence 
provided for several of the claims of substantial clinical improvement 
include small, non-randomized studies without the use of comparators or 
controls, including case studies, which may affect the ability to draw 
meaningful conclusions about treatment outcomes from the results of the 
studies. The benefits of avoiding intubation or de-escalating IMV 
settings are described in case studies, but the absence of comparative 
data may make it more difficult to determine whether there are 
clinically meaningful changes in these outcomes. We also note that in 
the one abstract of an RCT using the Hemolung RAS,\177\ although the 
time to NIV discontinuation was shorter in the ECCO2R arm 
than in the NIV alone arm, the ICU and hospital length of stay were 
longer with the ECCO2R group and there were no differences 
in mortality or functional outcomes at follow-up. Additionally, while 
the applicant states that the Hemolung RAS results in improved clinical 
outcomes, such as reducing mortality in NIV patients compared to 
continuing the patient's previous treatment, given that many of the 
case studies provided as evidence to support improved clinical outcomes 
included only one or two patients, it is not clear whether or not the 
results of these studies are generalizable to the Medicare population. 
We also note that several of the case studies, for example, Bonin et 
al., Mani et al., Tully et al., etc., mentioned by the applicant 
included patients and cases from outside the U.S., and we question if 
there may be differences in treatment guidelines between these 
countries that may have affected clinical outcomes. Lastly, we note 
that for several of the claims of substantial clinical improvement, the 
applicant provided evidence from background studies that did not 
utilize the Hemolung RAS to support the use of the technology to 
improve clinical outcomes. For example, in support of its assertion 
that the Hemolung RAS reduces mortality in NIPPV patients, the study 
cited by the applicant only addressed NIPPV as a treatment option to 
treat exacerbations in patients with COPD, but did not directly address 
the use of the Hemolung RAS as an intervention.
---------------------------------------------------------------------------

    \177\ Barrett, N, et al. A randomized controlled trial of Non-
Invasive Ventilation compared with ECCO2R for Acute 
Hypercapnic Exacerbations of COPD. ASAIO J. 2021; 67 (Supp 3) 
Presented at the 32nd Annual ELSO Conference.
---------------------------------------------------------------------------

    We are inviting public comments on whether the Hemolung RAS 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 the Hemolung RAS.

[[Page 28244]]

    Comment: The applicant submitted a public comment from a commenter 
who supported the use of the Hemolung RAS. The commenter explained that 
they have treated five patients with the Hemolung RAS (two in the 
Investigational Device Exemption (IDE) clinical trial for the Hemolung 
RAS in patients with COPD and three via the EUA for COVID-19 pneumonia) 
and found the Hemolung RAS to be reliable and safe. They noted that 
they found that it consistently removed roughly 80 ml of CO2 
per minute with a blood flow rate of 300-400 mL/min and it allowed the 
reduction of ventilator settings including tidal volume and rate while 
maintaining or lowering the PaCO2. They further commented 
that the nurses and staff found it easy to use and comparable to 
continuous veno-venous hemofiltration (CVVHD). The commenter also 
offered that they anticipate using the Hemolung RAS in a number of 
clinical scenarios, such as to avoid intubation or facilitate 
extubation in patients with hypercapnic respiratory failure due to COPD 
or other forms of acute chronic hypercapnic respiratory failure. 
Lastly, the commenter explained that the randomized controlled trial 
(RCT) was very difficult to enroll due to a number of factors including 
the challenges of getting rapid consent when trying to enroll patients 
failing NIV, consent concerns by proxies, difficulties enrolling at 
night and on weekends, and many others. However, the commenter believed 
that when it is available outside of the context of a clinical trial, 
the Hemolung RAS will be used more often to reduce the need for IMV in 
hypercapnic patients, enhance comfort, and permit more efficient use of 
ICU resources.
    The applicant also submitted a second public comment from a 
commenter who supported the Hemolung RAS for release for clinical use, 
especially during the COVID-19 pandemic during which the commenter had 
seen an increase in the admission rate for COPD patients infected with 
COVID-19. The commenter stated they believe that the Hemolung RAS can 
reduce LOS and ICU ventilation days. In support, the commenter stated 
that its site has been involved in the Hemolung RAS trial in the US and 
has a large population of COPD patients who are admitted with 
exacerbation of COPD, with the majority requiring mechanical 
ventilation. The commenter stated that the Hemolung RAS had allowed 
them to avoid mechanical ventilation or successfully extubate patients 
enrolled in the study. They further stated that they have not had any 
serious adverse side effects with the use of the device and that the 
nursing and respiratory therapy staff acquired the needed skill to use 
the device with minimal training.
    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 Hemolung RAS.
d. Lifileucel
    Iovance Biotherapeutics submitted an application for new technology 
add-on payments for lifileucel for FY 2023. According to the applicant, 
lifileucel is a proprietary, one-time autologous Tumor Infiltrating 
Lymphocytes (TIL) cell-based therapy for the treatment of unresectable 
or metastatic melanoma. 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. We note 
that Iovance Biotherapeutics previously submitted an application for 
new technology add-on payments for lifileucel for FY 2022, as 
summarized in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25272 
through 25282), but withdrew the application prior to the issuance of 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 44979).
    As noted in our prior review, the applicant stated relapsed and 
refractory metastatic melanoma presents a high unmet medical need with 
low survival rates and limited durable treatment options.\178\ 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%) 179 180 or displaying primary or 
acquired resistance (>70%) and the disease 
progresses.181 182 183 184 185 The applicant 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 186 187 188 or 
experimental combined ICIs \189\ offers a poor Objective Response Rate 
(ORR) \190\ of 4%-10%,191 192 193 a median

[[Page 28245]]

PFS of 2.7-3.7 months 194 195 196 and a median OS of ~7-8 
months.197 198
---------------------------------------------------------------------------

    \178\ 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.
    \179\ 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.
    \180\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
    \181\ 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.
    \182\ 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.
    \183\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
    \184\ 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.
    \185\ 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.
    \186\ 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.
    \187\ 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.
    \188\ 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.
    \189\ 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.
    \190\ As used by the applicant and the studies provided, 
Objective Response Rate (ORR) is the combination of Complete and 
Partial Responses.
    \191\ Weichenthal M, et al. Salvage therapy after failure from 
anti-PD-1 single agent treatment: A study by the German ADOReg 
melanoma registry. J Clin Oncol 37, 2018 (suppl; abstr 9505).
    \192\ 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.
    \193\ 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.
    \194\ 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.
    \195\ 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.
    \196\ 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.
    \197\ 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.
    \198\ 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.
---------------------------------------------------------------------------

    According to the applicant, lifileucel is being studied for 
effectiveness in solid tumors. The applicant stated that in addition to 
the pivotal programs researching metastatic melanoma (C-144-01) and 
advanced cervical cancer (C-145-04) patients, TIL cell therapy is being 
investigated in the treatment of patients with locally advanced, 
recurrent, or metastatic non-small-cell lung cancer (IOV-COM-202 and 
IOV-LUN-202) as well as in peripheral blood lymphocyte (PBL) blood 
cancers. The applicant asserted lifileucel is expected to be 
administered primarily in the hospital inpatient setting to assure 
appropriate patient monitoring and to ensure the supervision of a 
qualified physician experienced with the use and administration of IL-2 
(for example, aldesleukin). However, the applicant added, some 
treatment centers may make the clinical decision to infuse lifileucel 
as an outpatient procedure.
    With respect to the newness criterion, the applicant indicated that 
they are pursuing a Biologics License Application (BLA) for lifileucel 
from FDA. The applicant added that the proposed prescribing information 
for lifileucel is currently in development and will be submitted upon 
BLA submission to FDA. The applicant stated the proposed indication for 
lifileucel is as a one-time autologous TIL immunotherapy 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 
lifileucel has received Regenerative Medicine Advanced Therapy (RMAT), 
Orphan Drug, and Fast Track designations from FDA for the treatment of 
advanced melanoma. The applicant stated that currently, the following 
ICD-10-PCS procedure codes, effective October 1, 2021, uniquely 
identify procedures involving the administration of lifileucel in the 
inpatient setting: XW033L7 (Introduction of lifileucel immunotherapy 
into peripheral vein, percutaneous approach, new technology group 7) 
and XW043L7 (Introduction of lifileucel immunotherapy into central 
vein, percutaneous approach, new technology group 7). Based on their 
clinical trial protocol and proposed label, the applicant stated a 
single dose of lifileucel contains between 1 x 109 and 150 x 109 
autologous TIL suspended in up to four patient-specific infusion bags 
for intravenous infusion. The applicant stated patients receive pre-
treatment in the form of a nonmyeloablative lymphodepleting 
chemotherapy regimen of cyclophosphamide 60 mg/kg intravenously daily 
for 2 days followed by fludarabine 25 mg/m\2\ intravenously daily for 5 
days before infusion of lifileucel administration within 24 hours of 
the last dose. The applicant stated that 3 to 24 hours following the 
administration of lifileucel, patients should receive a post-treatment 
of a short course of high dose IL-2 (600,000 IU/kg every 8-12 hours for 
up to a maximum of six doses).
    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 does not use the same or similar 
mechanism of action as compared to currently available products used in 
the treatment of advanced melanoma. The applicant stated that clinical 
studies suggest that TIL therapy lyses tumor cells via the following 
mechanism: \199\
---------------------------------------------------------------------------

    \199\ Ch[aacute]vez-Gal[aacute]n L, et al. Cell death mechanisms 
induced by cytotoxic lymphocytes. Cell Mol Immunol. 2009; 6(1): 15-
25.
---------------------------------------------------------------------------

     Reinfused TIL circulate in the blood until they recognize 
tumor-specific antigens (TSAs) on the surface of the tumor cells via 
chemokines produced by the tumor. The TIL depart the capillaries, 
migrate to the tumor, and recognize tumor antigen peptides presented by 
MHC molecules on the surface of the tumor cells via their T cell 
receptors.
     Upon tumor antigen recognition, the TIL are activated and 
release perforin, a pore-forming protein.
     TIL then release granzyme, a pro-apoptotic protease, which 
enters the tumor via the pores, causing lysis of the tumor cells.
     TIL also release IFN-[gamma], which promotes macrophage 
activation to phagocytize (that is, engulf and internalize) the lysed 
tumor cell debris and present tumor antigens.
     TIL therapy mediates regression of tumors both by direct 
cell lysis and by inducing cytokine- (IFN-[gamma]) mediated tumor cell 
killing.
    According to the applicant, the currently available first and 
second line treatments for advanced melanoma include kinase inhibitors 
(BRAF and MEK inhibitors) and immune checkpoint inhibitors (anti-CTLA-4 
antibody and anti-PD-1 antibody).200 201 The applicant 
explained that kinase inhibitors selectively inhibit the mutated BRAF 
V600E- or V600K kinase and MEK inhibitors are used in combination with 
BRAF inhibitors to interfere with the signaling of the MEK-1 and MEK-2 
protein within the cancer cell.202 203 204 205 The applicant 
next explained that immune checkpoint inhibitors include CTLA-4 
blocking antibodies and PD-1 blocking antibodies that are humanized 
monoclonal or recombinant IgG4 kappa immunoglobulin produced in 
recombinant Chinese hamster ovary cell lines.206 207 208 The 
applicant asserted that there are no approved treatment options for 
patients with metastatic melanoma that have progressed after two lines 
of therapy but stated that some patients may receive high-dose IL-2 or

[[Page 28246]]

cytotoxic agents per NCCN clinical practice guidelines.\209\
---------------------------------------------------------------------------

    \200\ 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.
    \201\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines. Melanoma: Cutaneous. V2.2021--February 19, 2021. https://www.nccn.org.
    \202\ Zelboraf (vemurafenib) prescribing information. Genentech, 
2011.
    \203\ Tafinlar (dabrafenib) prescribing information. Novartis, 
2013.
    \204\ Mekinst (trametinib) prescribing information. Novartis, 
2013.
    \205\ Cotellic (cobinmetnib) prescribing information. Novartis, 
2015.
    \206\ Keytruda (pembrolizumab) presecribing information. Merck & 
Co., Inc.; 2019.
    \207\ Yervoy (ipilmumab) prescribing information. Bristol Myers 
Squibb, 2011.
    \208\ Opdivo (nivolumab) prescribing information. Bristol Myers 
Squibb, 2014.
    \209\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines. Melanoma: Cutaneous. V2.2021--February 19, 2021. https://www.nccn.org.
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    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. According to the applicant, lifileucel TIL cell 
therapy involves the Adoptive Cell Therapy (ACT) of autologous T-cells 
directly isolated from the patient's tumor tissue and expanded ex vivo. 
The applicant added that 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 stated that as well as having tumor recognition, 
discussed previously, TIL therapy is personalized, polyclonal, and 
neoantigen-specific. According to the applicant, TIL is inherently 
personalized because it is derived from the patient's tumor tissue. 
According to the applicant, theoretically, tumor tissue TIL recognize a 
multitude of an individual's tumor specific antigens (TSAs) as opposed 
to CAR T-cell therapies which recognize only one TSA.\210\ The 
applicant asserted that TIL therapy is polyclonal because it can 
recognize an array of different tumor antigens which best addresses the 
high mutational diversity of solid tumors.211 212 According 
to the applicant, TIL is neoantigen-specific because the TIL therapy 
process ensures the inclusion of neoantigen-specific T cell clones 
without prior knowledge of the number or identity of those 
neoantigens.\213\
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    \210\ Raskov H, et al. British Journal of Cancer (2021) 124:359-
367; https://doi.org/10.1038/s41416-020-01048-4.
    \211\ 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.
    \212\ Schumacher TN and Schreiber RD. Neoantigens in cancer 
immunotherapy. Science 2015; (6230): 69-74.
    \213\ 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.
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    The applicant asserted TIL cell therapy with lifileucel is also 
highly differentiated from currently approved 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) and 
ABECMA[supreg] (idecabtagene vicleucel) indicated for the treatment of 
relapsed/refractory multiple myeloma. The applicant stated that while 
other ACT, including CAR T-cell therapies, utilize circulating T-cells 
from the blood, TIL therapy harvests neoantigen-directed T-cells that 
are isolated from a tumor biopsy. The applicant stated that whereas T-
cells are genetically altered to have special receptors called chimeric 
antigen receptors in CAR T-cell therapy, TIL from tumor tissue 
fragments are cultured with IL-2 to allow outgrowth of TIL cell 
population during pre-rapid expansion (pre-REP). The applicant asserted 
that TIL cells obtained at the end of the pre-REP are subsequently 
cultured with IL-2, anti-CD-2 and feeder cells to start REP which is 
lastly cryopreserved.
    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 added that CAR T-cells return to 
the bloodstream and lymphatic system and have more contact with blood 
tumor cells which may reduce their ability to penetrate tumor tissue 
through the vascular endothelium. The applicant stated another obstacle 
with the use of CAR T-cell therapy in the treatment of solid tumors is 
a phenomenon known as ``tumor antigen escape'' where a tumor expresses 
alternative forms of the target antigen that lack the extracellular 
epitopes recognized by CAR T-cells.\214\ 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.\215\ Per the 
applicant, 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.
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    \214\ Qu J, et al.: Chimeric antigen receptor (CAR)-T-cell 
therapy in non-small-cell lung cancer (NSCLC): Current status and 
future perspectives. Cancer Immunol Immunother 70:619-631, 2021.
    \215\ 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 in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 44798 through 44806), CMS 
finalized its proposal to assign existing procedure codes describing 
CAR T-cell, non-CAR T-cell and other immunotherapies to Pre-MDC 018 and 
to modify the title to ``Chimeric Antigen Receptor (CAR) T-cell and 
Other Immunotherapies'' to better reflect the cases reporting the 
administration of non-CAR T-cell therapies and other immunotherapies. 
The applicant stated their appreciation and support for CMS' final 
decision to assign lifileucel ICD-10-PCS codes to Pre-MDC MS-DRG 018. 
The applicant agreed that while the clinical and resource intensity of 
lifileucel is comparable to that of CAR T-cell therapy inpatient 
episodes of care, the TIL cell therapy mechanism of action and patient 
population differ from autologous CAR T-cell therapy.
    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 if FDA grants 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, including a PD-1 blocking antibody and, if BRAF V600 
mutation positive, a BRAF inhibitor or BRAF inhibitor with MEK 
inhibitor. The applicant asserted lifileucel will be the first and only 
FDA-approved cellular treatment for this challenging to treat patient 
population.
    After review of the information provided by the applicant, we note 
that in regard to the MS-DRG assignment, while the applicant stated 
that lifileucel is assigned to the same MS-DRG as CAR T-cell therapies, 
it seems that lifileucel maps to a different MS-DRG than existing 
treatments for metastatic melanoma. We also note that there are 
currently other therapies for the treatment of metastatic melanoma and 
we are not certain that the distinction of being the first cellular 
treatment is relevant to the third criterion. We are seeking public 
comment on whether lifileucel would indeed be the only FDA approved 
treatment for the patient population identified here.
    We are inviting public comments on whether lifileucel is 
substantially

[[Page 28247]]

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 analyses to demonstrate the technology meets the cost 
criterion: (1) A primary cohort, (2) a cohort with a principle or 
admitting diagnosis of melanoma and metastasis, and (3) a cohort with 
any diagnosis of melanoma and metastasis. The ICD-10 codes used to 
identify melanoma and metastasis and MS-DRGs identified by the 
applicant (for the primary cohort) are listed in the following tables.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.088


[[Page 28248]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.089


[[Page 28249]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.090


[[Page 28250]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.091


[[Page 28251]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.092

[GRAPHIC] [TIFF OMITTED] TP10MY22.093

BILLING CODE 4120-01-C
    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 ICD-10-CM codes C43.XXX 
and D03.XXX (where XXX represents all codes in the broader category) 
also noted in the prior tables, and any ICD-10 diagnosis of metastasis 
from ICD-10-CM codes C77.X, C78.XX, and C79.XX (where the X and XX 
represent all codes in the

[[Page 28252]]

broader categories respectively) and in the prior tables, and any ICD-
10 procedure code indicating administration of IL-2 or other 
chemotherapy via central or peripheral vein from the previous tables.
    The applicant used the FY 2019 MedPAR file dataset with the FY 2019 
final rule with Correction Notice IPPS Impact File and the FY 2023 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 IPPS/LTCH PPS final rule IPPS Impact 
File. The previously discussed criteria resulted in 39 claims from 20 
MS-DRGs in the primary cohort, 387 claims from 80 MS-DRGs in the 
sensitivity cohort 1, and 4,985 claims from 372 MS-DRGs in sensitivity 
cohort 2. The applicant imputed a case count of 11 for those MS-DRGs 
with fewer than 11 cases. For each cohort, the applicant provided two 
analyses, first using the national pharmacy CCR of 0.187 from the FY 
2022 IPPS/LTCH PPS final rule (86 FR 44966) to calculate charges, and 
second using the applicant-calculated CAR T-cell CCR (0.2936) to 
calculate charges. The applicant first calculated a case weighted 
threshold of $1,256,379 for the primary, sensitivity one, and 
sensitivity two cohorts where the MS-DRG 018 threshold was applied for 
all MS-DRGs identified. We note, in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 44806) we finalized our proposal to assign other 
immunotherapies to 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 $1,256,379.
    For these analyses, 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 
national average pharmacy CCR of 0.187 from the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44966), and in secondary analyses, by a CAR T-cell 
CCR of 0.2936 calculated by the applicant. To estimate the CAR T-cell 
CCR, the applicant obtained the total drug charges for cases in MS-DRG 
018 from the FY 2022 IPPS final rule AOR/BOR file. Next the applicant 
divided the total drug charges ($184,237,653.25) by the number of cases 
(145) to get an average drug charge per case of $1,270,605. Using the 
acquisition cost of YESCARTA[supreg] and KYMRIAH[supreg] ($373,000) as 
the cost per case, the applicant divided by the charge per case 
($1,270,605) to get a CCR of 0.2936.
    The applicant stated no charges were removed for the prior 
technology because previous treatments will continue to be reflected in 
cases where lifileucel is administered. Next the applicant calculated 
the average standardized charge per case using the FY 2019 IPPS/LTCH 
PPS final rule impact file. A 3-year inflation factor of 20.4686% was 
obtained from the FY 2022 IPPS/LTCH PPS final rule (86 FR 45542) 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 $2,196,319 and $1,448,803 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 $1,256,379.
    The applicant determined a final inflated average case-weighted 
standardized charge per case of $2,139,220 and $1,391,704 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 $1,256,379.
    The applicant determined a final inflated average case-weighted 
standardized charge per case of $2,136,701 and $1,389,185 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 $1,256,379.
    Because the final inflated average case-weighted standardized 
charge per case for all the analyses exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    As we have noted in previous discussions (86 FR 25237, 86 FR 
25279), the submitted costs for CAR T-cell therapies vary widely due to 
differences in provider billing and charging practices for this 
therapy, and we are continuing to consider the use of this submitted 
cost data for purposes of calculating a CAR T-cell CCR for use in the 
applicant's cost analyses given this potential for variability. 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. The applicant asserted that the 
one-time administration of lifileucel, an autologous TIL immunotherapy, 
has demonstrated substantial clinical improvement compared to current 
therapies used to treat patients with unresectable or metastatic 
melanoma who have been previously treated with at least one systemic 
therapy; that patients with unresectable or metastatic melanoma who 
have failed at least one prior systemic therapy will have substantially 
improved ORRs compared with patients treated with currently available 
therapies; that responses continue to deepen over time after a single 
infusion of lifileucel; and that efficacy and safety data have shown 
lifileucel is an effective therapy for advanced melanoma patients.
    The applicant asserted that when approved by FDA, lifileucel will 
provide a treatment option for patients with advanced melanoma who 
relapse on or do not tolerate treatment with immune checkpoint 
inhibitors and BRAF-targeted therapies and who respond poorly to a 
subsequent round of therapy with these agents or chemotherapy. The 
applicant stated metastatic melanoma is capable of rapidly 
metastasizing to distant organs and accounts for the majority of skin 
cancer-related deaths.216 217 According to the applicant, 
despite the advances in available treatments, there are currently no 
treatment options based on data from patients with advanced melanoma 
who have progressive disease after one line of immune checkpoint 
inhibitor therapy (for BRAF wild-type tumors), or two

[[Page 28253]]

lines of therapy (for BRAF V600 mutation-positive tumors).\218\ The 
applicant added, patients recurring with advanced melanoma after 
adjuvant anti-PD-1 therapy for high-risk disease represent an emerging 
unmet need.\219\ As the applicant stated previously, patient outcomes 
are consistently poor for this population. Based on the C-144-01 study, 
the applicant concluded that treatment with lifileucel represents 
substantial clinical improvement over published, poor outcomes for 
retreatment with chemotherapy.
---------------------------------------------------------------------------

    \216\ 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.
    \217\ American Cancer Society. Cancer Facts and Figures 2020. 
https://www.cancer.org/content/dam/cancerorg/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2020/cancer-facts-and-figures-2020.pdf. Accessed April 6, 2020.
    \218\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10.1200/
JCO.21.00612, Published online May 12, 2021.
    \219\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10.1200/
JCO.21.00612, Published online May 12, 2021.
---------------------------------------------------------------------------

    The applicant next stated that lifileucel significantly improves 
clinical outcomes compared to current therapies. In support of this 
assertion, the applicant provided data from two of four cohorts of the 
C-144-01 study, an ongoing phase 2 multicenter study (NCT02360579) to 
assess the efficacy and safety of autologous TIL in patients with stage 
IIIc-IV metastatic melanoma. Those 4 cohorts are:
     Cohort 1 (n=30 generation 1 non-cryopreserved TIL 
product), not included for review as part of the applicant's 
application for new technology add-on payments.
     Cohort 2 (n=66 generation 2 cryopreserved TIL product), 
included for review as part of the applicant's application for new 
technology add-on payments.
     Cohort 3 (a sub-sample of n=10 from cohorts 1, 2, and 4), 
not included for review as part of the applicant's application for new 
technology add-on payments.
     Cohort 4 (n=75 generation 2 cryopreserved TIL product), 
will be provided to FDA as part of the applicant's BLA and will be 
provided to CMS upon FDA approval.
    The applicant stated that patients were enrolled between April 2017 
and January 2019 at 26 sites.
    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 ORR, as assessed by the independent 
review committee (IRC) per Response Evaluation Criteria in Solid Tumors 
(RECIST) version 1.1.\220\ 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 metastatic melanoma by assessing 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 greater 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 had at least one measurable target lesion, 
as defined by RECIST v1.1 (which was not used for tumor resection), and 
at least one resectable lesion (or aggregate of lesions resected). 
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. 
According to the applicant, all patients were to receive the pre-
treatment, pre-medication, and post-treatment as described in the 
discussion of the newness criterion, in combination with the infusion 
of lifileucel. The applicant explained that prior to the infusion of 
lifileucel, the patients received NMA-LD with cyclophosphamide (60 mg/
kg) intravenously daily for 2 days followed by fludarabine (25 mg/m2) 
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.\221\
---------------------------------------------------------------------------

    \220\ 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.
    \221\ 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 concomitant therapy given to the patient even if more than one 
target for each treatment was involved.\222\ 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 88% had 
received BRAF/MEK inhibitors. All patients had received PD on their 
prior therapy before study entry.
---------------------------------------------------------------------------

    \222\ 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.
---------------------------------------------------------------------------

    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 years), 
patients responded to lifileucel therapy. According to the applicant, 
at the data cutoff of April 2020 patients in cohort 2 (n=66) had 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 (SD), 9 patients (14%) had 
progressive disease (PD), 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%.223 224 
The applicant added that the primary-refractory subset (n=42), defined 
as patients who had a best overall response of progressive disease to 
first immune checkpoint inhibitor, had an ORR of 41% (95% CI, 26, 57) 
with 2 CRs (5%), 15 PRs (36%), 17 (41%) SD, and 5 (12%) having PD. The 
applicant asserted that this subset is important because 40%-65% of all 
patients with metastatic melanoma and >70% of those treated with anti-
CTLA-4 therapy have disease that is primary

[[Page 28254]]

refractory to initial immune checkpoint inhibitor 
therapy.225 226 227 228 229
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    \223\ 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.
    \224\ 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.
    \225\ 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.
    \226\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
    \227\ Larkin J, et al. Combined nivolumab and ipilimumab or 
monotherapy in untreated melanoma. N Engl J Med 2015;373:23-34.
    \228\ Wolchok JD, et al. Overall survival with combined 
nivolumab and ipilimumab in advanced melanoma. N Engl J Med 
377:1345-1356, 2017.
    \229\ Gide TN, et al. Primary and acquired resistance to immune 
checkpoint inhibitors in metastatic melanoma. Clin Cancer Res 
2018;24:1260-70.
---------------------------------------------------------------------------

    Next, the applicant asserted that, because the median duration of 
response (DOR) had not been reached at a median follow-up of 33 months, 
the treatment effect will be durable and provide long-term benefit to 
those treated with lifileucel. The applicant added that the median time 
from infusion to best response was 1.4 months (1.3-8.7 months). At 18.7 
months the median OS was 17.4 months (95% CI, 11.0 to not reached), 
with 1-year OS of 58% (95% CI, 45 to 69).\230\ The applicant stated 
that a univariable Cox proportional hazards regression model was used 
to estimate hazard ratios with 95% confidence intervals between 
subgroups on DOR which found that for every 6-month decrease in 
cumulative duration of prior anti-PD-1/anti-PD-L1 therapy, the median 
DOR to lifileucel was nearly doubled.\231\ The applicant concluded from 
these results that shorter duration of prior anti-PD-1 therapy 
maximizes DOR to lifileucel treatment and that all newly diagnosed 
patients should be closely monitored for progression on anti-PD-1 
therapy.\232\
---------------------------------------------------------------------------

    \230\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10. 1200/
JCO.21.00612, Published online May 12, 2021.
    \231\ Larkin JMG, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced melanoma: Evaluation of impact of prior anti-PD-1 
therapy. Abstract 9505, oral session; 2021 American Society of 
Clinical Oncology's (ASCO) Annual Meeting. Abstract 9505, oral 
session. JCO, DOI: 10.1200/JCO/2021.39.15_suppl.9505, JCO 39, no. 
15_suppl (May 20, 2021) 9505-9505. Published online May 28, 2021.
    \232\ Larkin JMG, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced melanoma: Evaluation of impact of prior anti-PD-1 
therapy. Abstract 9505, oral session; 2021 American Society of 
Clinical Oncology's (ASCO) Annual Meeting. Abstract 9505, oral 
session. JCO, DOI: 10.1200/JCO/2021.39.15_suppl.9505, JCO 39, no. 
15_suppl (May 20, 2021) 9505-9505. Published online May 28, 2021.
---------------------------------------------------------------------------

    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 
(TEAE) 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.\233\ The applicant added that 
the most common grade \3/4\ TEAEs included thrombocytopenia (89%), 
chills (80%), anemia (68%), pyrexia (59%), neutropenia (56%), febrile 
neutropenia (55%), hypophosphatemia (46%), leukopenia (42%), 
lymphopenia (35%), and tachycardia (35%) \234\ which were consistent 
with the lymphodepletion regimen and known profile of IL-
2.235 236 237 One patient died due to intra-abdominal 
hemorrhage reported as possibly related to TIL and one due to acute 
respiratory failure assessed as not related to TIL.\238\ 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. The applicant 
asserted that this profile of the incidence of TEAEs over time, 
including grade \3/4\ TEAEs that decreased rapidly over time reaching 
background rate by approximately day 10 post lifileucel administration, 
is reflective of the potential benefit of the one-time treatment with 
lifileucel.
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    \233\ 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.
    \234\ 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.
    \235\ 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
    \236\ 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.
    \237\ 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.
    \238\ 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 addition to the evidence summarized previously and in the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25281), the applicant submitted 
one article \239\ and two presentations with abstracts 
240 241 in support of its claims regarding substantial 
clinical improvement. The published article discussed the C-144-01 
trial previously summarized and provided greater detail on Cohort 2; 
\242\ the authors described the study design, patient sample, and study 
endpoints for Cohort 2. In addition to previously discussed 
information, the authors stated that 78 patients underwent tumor 
resection in preparation for participation in this trial, however only 
66 patients received lifileucel. The article stated that three of the 
patients either received a low dosage or did not receive TIL and nine 
patients could not be treated because of other causes; while it is not 
directly stated in the article it is likely that these patients were 
not included in the analysis. The authors added that only 25% of 
patients had progressed after achieving a response from lifileucel. The 
authors stated that the median DOR had not been reached with a 1-year 
DOR of 69% (95% CI, 46-84). The authors stated that 34 (52%) of 
patients received anti-PD-1 plus anti-CTLA-4 combination therapy, 
either as frontline (n=5, 23%) or after failing frontline therapy (n=9, 
29%); the ORRs for these subsets were 33% and 32%, respectively. 
According to the authors, the ORRs for patients with primary resistance 
(n=17) or acquired resistance (n=11) to anti-PD-1 plus anti-CTLA-4 
combination therapy were 35% and 27%, respectively. The article lastly 
discussed similar safety outcomes as previously discussed by the 
applicant.
---------------------------------------------------------------------------

    \239\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10. 1200/
JCO.21.00612, Published online May 12, 2021.
    \240\ Larkin JMG, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced melanoma: Evaluation of impact of prior anti-PD-1 
therapy. Abstract 9505, oral session; 2021 American Society of 
Clinical Oncology's (ASCO) Annual Meeting. Abstract 9505, oral 
session. JCO, DOI: 10.1200/JCO/2021.39.15_suppl.9505, JCO 39, no. 
15_suppl (May 20, 2021) 9505-9505. Published online May 28, 2021.
    \241\ Chesney JA, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced (unresectable or metastatic melanoma: Sustained 
duration of response at 28 month follow up. Oral presentation CT008; 
American Association for Cancer Research (AACR) Annual Meeting 2021. 
Oral presentation. Cancer Research, DOI: 10.1158/1538-7445.AM2021-
CT008 Published July 2021.
    \242\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10. 1200/
JCO.21.00612, Published online May 12, 2021.

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[[Page 28255]]

    Finally, the applicant discussed presentations from the American 
Association for Cancer Research (AACR) 2021 annual meeting (28-month 
follow-up data) \243\ and the 2021 American Society of Clinical 
Oncology (ASCO) annual meeting (33-month follow-up data).\244\ The 
first presentation provided 28-month follow up data from the C-144-01 
study of the efficacy and safety of lifileucel cohort 2.\245\ Data 
presented is similar to the preceding presentation and article 
discussed previously. According to the second presentation, 81% (50/62) 
of patients had a reduction in tumor burden while 11 patients (17.7%) 
had further sum of diameters (SOD) reduction since April 2020.\246\ The 
presentation stated that 79% of responders to lifileucel received prior 
ipilimumab. The presentation provides a brief case study of a patient 
who achieved PR at day 42 and CR at day 84. The presentation concluded 
that: Lifileucel resulted in a 36.4% ORR with a median DOR not reached 
at 33.1 months; patient responses deepened over time with continued 
decrease in tumor size for 11 patients (17.7%); and that early 
intervention with lifileucel at the time of initial progression on 
anti-PD-1 agents may maximize the benefit seen.
---------------------------------------------------------------------------

    \243\ Chesney JA, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced (unresectable or metastatic melanoma: Sustained 
duration of response at 28 month follow up. Oral presentation CT008; 
American Association for Cancer Research (AACR) Annual Meeting 2021. 
Oral presentation. Cancer Research, DOI: 10.1158/1538-7445.AM2021-
CT008 Published July 2021.
    \244\ Larkin JMG, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced melanoma: Evaluation of impact of prior anti-PD-1 
therapy. Abstract 9505, oral session; 2021 American Society of 
Clinical Oncology's (ASCO) Annual Meeting. Abstract 9505, oral 
session. JCO, DOI: 10.1200/JCO/2021.39.15_suppl.9505, JCO 39, no. 
15_suppl (May 20, 2021) 9505-9505. Published online May 28, 2021.
    \245\ Chesney JA, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced (unresectable or metastatic melanoma: Sustained 
duration of response at 28 month follow up. Oral presentation CT008; 
American Association for Cancer Research (AACR) Annual Meeting 2021. 
Oral presentation. Cancer Research, DOI: 10.1158/1538-7445.AM2021-
CT008 Published July 2021.
    \246\ Larkin JMG, et al. Lifileucel (LN-144), a cryopreserved 
autologous tumor infiltrating lymphocyte (TIL) therapy in patients 
with advanced melanoma: Evaluation of impact of prior anti-PD-1 
therapy. Abstract 9505, oral session; 2021 American Society of 
Clinical Oncology's (ASCO) Annual Meeting. Abstract 9505, oral 
session. JCO, DOI: 10.1200/JCO/2021.39.15_suppl.9505, JCO 39, no. 
15_suppl (May 20, 2021) 9505-9505. Published online May 28, 2021.
---------------------------------------------------------------------------

    In response to concerns expressed by CMS in the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25281 and 25282) about the appropriateness of 
the ORR as the primary outcome, the applicant stated the ORR was 
determined to be the appropriate primary endpoint for C-144-01 
following a review of studies in patients with advanced cancers where 
FDA approval has been granted and in consultation with key opinion 
leaders in oncology. The applicant next summarized their June 17, 2021, 
public comment letter to CMS.\247\ In their comment the applicant 
stated that FDA has described the significance of ORR as assessed by 
its magnitude and duration of effect. The comment added that ORR can 
represent direct clinical benefit based on the specific disease, 
context of use, magnitude of the effect, the number of CRs, the 
durability of response, the disease setting, the location of the 
tumors, available therapy, and the risk-benefit relationship. According 
to the comment, the surrogate endpoint of ORR has allowed for earlier 
measurement of lifileucel results and has demonstrated direct, ongoing 
clinical benefit for patients with metastatic melanoma with limited 
treatment options. Furthermore, the comment stated further evidence of 
ORR as an accepted and important efficacy measure for metastatic or 
unresectable melanoma is that it has been recognized by the National 
Comprehensive Cancer Network (NCCN) in the NCCN Clinical Practice 
Guidelines in Oncology, Melanoma: Cutaneous, Version 2.2021.\248\ The 
comment concluded that given the limited treatment options and poor 
response rates for patients, lifileucel has demonstrated a favorable 
risk-benefit profile and represents a substantial clinical improvement 
for patients with metastatic melanoma who otherwise have limited 
treatment options.
---------------------------------------------------------------------------

    \247\ Sarnaik A. Public comment letter, CMS 1752-P. June 20, 
2020. www.regulations.gov.
    \248\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines. Melanoma: Cutaneous. V2.2021--February 19, 2021. https://www.nccn.org.
---------------------------------------------------------------------------

    The applicant next addressed the second concern raised by CMS in 
the FY 2022 PPS/LTCH PPS proposed rule in response to the FY 2022 
application for new technology add-on payments, that CMS was unable to 
verify the appropriateness of a historical control because the evidence 
describing it was not provided. According to the applicant, only 
dacarbazine (DTIC) is an appropriate comparator for Cohort 4 as it is 
the only chemotherapy agent approved for the treatment of metastatic 
melanoma. The applicant added that other published studies provide 
evidence on other treatment options without prior anti-PD-1 and are not 
pertinent comparators for the C-144-01 study population (weighted 
average ORR of DTIC alone was 15.3% across 24 studies).\249\ The 
applicant stated that a more recent study in the post-immune checkpoint 
inhibitor era reported ORR of 4% from the investigator's choice 
arm.\250\ While not appropriate for direct comparison to Cohort 4, the 
applicant asserted that these studies do provide historical ORR 
information in metastatic melanoma in general and demonstrate that the 
ORR in these historical studies approximates the 10% ORR from the DTIC 
arm of the Goldinger 2018 study.\251\ According to the applicant, at 
the End-of-Phase 2 (EOP2) meeting held in September 2018, FDA concluded 
that a controlled trial likely could not be concluded in the patient 
population of interest. The applicant stated the precedence for a 10% 
historical control rate in the metastatic melanoma population was 
established in FDA's approval of BLA 125514 for KEYTRUDA, a PD-1 
indicated for the treatment of patients with unresectable or metastatic 
melanoma, among other oncologic indications. According to the 
applicant, FDA's Medical Review Summary dated August 2, 2014 stated, 
``There are no historical data of the response rate of chemotherapies 
in patients who are refractory to ipilimumab; however, response rate of 
chemotherapies ranged from 5% to 10% in three recently completed Phase 
3 studies (ipilimumab in 1st line melanoma patients, and trametinib and 
vemurafenib in patients with BRAF V600E mutation). Therefore, the 
applicant stated that it is reasonable to use 10% as the null 
hypothesis for testing the anti-tumor activity of MK-3475 against 
putative chemotherapies in this population.'' \252\ The applicant 
concluded that the chemotherapy control arms of the original 
registration study of pembrolizumab (KEYTRUDA) and nivolumab (OPDIVO) 
provide further support for the 10% historical control rate for Study 
C-144-01. According to the applicant, these two studies provide a 
substantial and

[[Page 28256]]

coherent data set for response to chemotherapy following treatment with 
ipilimumab, an immune checkpoint inhibitor, as well as a BRAF 
inhibitor, where indicated. The applicant reported that these studies 
had ORRs of 4% (95% CI 2,9) (n=179) \253\ and 10.6% (95% CI 3.5, 23.1) 
(n=47).\254\
---------------------------------------------------------------------------

    \249\ Lui P, et al. Treatments for metastatic melanoma: 
Synthesis of evidence from randomized trials. Cancer treatment 
reviews. 2007;33(8):665-680.
    \250\ Ribas A, et al. Pembrolizumab versus investigator-choice 
chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A 
randomised, controlled, phase 2 trial. Lancet Oncol 16:908-918, 
2015.
    \251\ Goldinger SM, et al. The utility of chemotherapy after 
immunotherapy failure in metastatic melanoma: A multicenter case 
series. J Clin Oncol 36, 2018 (suppl; abstr e21588).
    \252\ Center for Drug Evaluation and Research (CDER), 
Application #125514Orig1s000 Medical Review. (Keytruda) https://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/125514Orig1s000MedR.pdf.
    \253\ Hamid O, et al. Final Analysis of a randomized trial 
comparing pembrolizumab versus investigator-choice chemotherapy for 
ipilimumab-refractory advanced melanoma. Eur J Cancer. 2017 
Nov;86:37-45. Doi: 10.1016/j.ejca.2017.07.022.
    \254\ Weber JS, et al. Nivolumab versus chemotherapy in patients 
with advanced melanoma who progressed after anti-CTLA-4 treatment 
(Checkmate 037); a randomized, controlled, open-label, phase 3 
trial. Lancet Oncol 2015: 16:375-384.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding the substantial clinical improvement 
criterion. We note that while multiple references were provided in 
support of substantial clinical improvement, those that evaluate 
lifileucel are based solely on the C-144-01 trial. We question whether 
there are methods by which lifileucel might be compared to existing 
treatments which were used to construct the historical controls in the 
studies provided. Similar to the discussion in the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25279 through 25282) we also 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. We also question whether the patient sample or 
samples used to construct the historical control are representative of 
the C-144-01 cohort.
    We note a low sample size in the primary reference which is used to 
explain the findings of C-144-01.\255\ First, we note that the study 
enrolled 66 of 78 patients who underwent tumor resection. Given the 
small sample size, the 12 patients who withdrew represent a substantial 
proportion of the total patients evaluated and may make it even more 
difficult to determine whether the results of the patients remaining in 
the study are generalizable, especially to the Medicare patient 
population. We are concerned that those patients who were not included 
in the study may have had poorer clinical outcomes as compared to those 
evaluated in the study which would potentially bias the results seen in 
the study. Second, in regard to the sample studied, we note a median 
age of 55 with males represented at 59%; data on race, ethnicity, and 
other demographics are not presented. We question whether the sample 
evaluated is appropriately representative of the Medicare population 
and whether this sample has a disease burden similar to that seen in 
Medicare beneficiaries.
---------------------------------------------------------------------------

    \255\ Sarnaik A, et al. Lifileucel, a tumor-infiltrating 
lymphocyte therapy, in metastatic melanoma. JCO, DOI: 10. 1200/
JCO.21.00612, Published online May 12, 2021.
---------------------------------------------------------------------------

    Next, we note that according to the applicant, high-dose IL-2 has 
been used to treat MM in the past and is given as a post-treatment to 
lifileucel. The applicant asserted that the occurrence of grade 3 and 4 
TEAEs was early and consistent with the lymphodepletion regimen (NMA-
LD) and known profile of IL-2. If lifileucel is always given in 
conjunction with the pre- and post-treatments, we question how it is 
possible to determine the cause of the TEAEs which are categorized as 
severe based on the Common Terminology Criteria for Adverse Events 
v4.03. We further note that we have not received any analyses which 
controlled for the amount of IL-2 used per patient. There did not 
appear to be a discussion of how the number of doses of IL-2 
administered to a patient interacted with lifileucel and impacted the 
treatment effects (for example, CR, PR, SD), and TEAEs. We believe it 
is important to understand the effect of IL-2 on the response rate and 
these values as it may be possible for higher doses of IL-2 leading to 
better patient outcomes or worse TEAEs as compared to those with fewer 
doses of IL-2. Specifically, we question whether the effect seen in C-
144-01 is due to lifileucel itself or due to other factors such as the 
use of IL-2, general changes in medical practice over time, and the 
specific sample identified for the trial at hand.
    Separate from our concern about the use of a historical comparator, 
we note that according to the applicant, based on data from 1985 
through 1993 analyzing 270 patients across 8 clinical trials, high dose 
IL-2 resulted in an ORR of 16% and CR of 6%, as compared to an ORR of 
36% for the C-144-01 trial. However, we question whether the 
differences in the studies, the samples, and the time period in which 
the studies were conducted may account for this difference in the ORR 
values as opposed to the use of lifileucel itself.
    We are inviting public comments on whether lifileucel meets the 
substantial clinical improvement criterion.
    We received a comment from the applicant in response to the New 
Technology Town Hall meeting notice published in the Federal Register 
regarding the substantial clinical improvement criterion for 
lifileucel.
    Comment: In response to CMS' question related to the level of 
therapeutic effect of IL-2 which is administered following the one-
time, single administration of lifileucel TIL therapy, the applicant 
described IL-1 and discussed its approved therapeutic use. The 
applicant asserted that IL-2 is a naturally occurring cytokine that has 
been shown to drive T cell activation and effector function. The 
applicant added that IL-2 plays a role in the maintenance of CD4 
regulatory T cells and differentiation of CD8+ T cells into mature 
cytotoxic cells. According to the applicant, to support T-cell activity 
after the lifileucel infusion, a short course of high-dose IL-2 (for 
example, aldesleukin) is administered in vivo at 600,000 IU/kg every 8 
to 12 hours for up to 6 doses beginning 3 to 24 hours after lifileucel 
is infused. The applicant stated this short course of high-dose IL-2 
differs substantially from the typical high-dose IL-2 antineoplastic 
regimens discussed previously: 79% lower dose IL-2 is instead 
administered to support the migration, antitumor cytotoxicity and 
persistence of the infused TIL, not for antineoplastic effect.
    According to the applicant, the methodology of adoptive cell 
transfer (ACT), giving autologous ex vivo expanded TIL to 
nonmyeloablated lymphodepleted cancer patients followed by a short 
course of high-dose IL-2 was developed in 1988.256 257 The 
applicant stated that in a phase I trial which evaluated the anti-tumor 
effect of TIL therapy with varying IL-2 doses in 15 patients with 
metastatic melanoma, tumor response was not seen in patients that did 
not receive any IL-2 (n=6).\258\ The applicant next stated that in a 
second study, patients who experienced an objective response received 
fewer doses of high-dose IL-2 as compared to non-responders.\259\ 
According to the applicant, this might be explained by the fact that 
IL-2 administration

[[Page 28257]]

significantly increased the number of CD4+FoxP3+regulatory T-cells 
(Tregs) with a direct correlation between the number of IL-2 doses 
given and reconstitution of Treg numbers in the blood and an inverse 
correlation between reconstitution of the Tregs and the probability of 
achieving an anti-tumor response. The applicant summarized that the use 
of IL-2 in TIL therapy is not for antineoplastic effect, but instead 
for the sole purpose of creating the right cytokine environment and 
supporting T-cell activity after the lifileucel infusion.
---------------------------------------------------------------------------

    \256\ Rosenberg SA, Packard BS, Aebersold PM, et al. Use of 
Tumor-Infiltrating Lymphocytes and Interleukin-2 in the 
Immunotherapy of Patients with Metastatic Melanoma. A Preliminary 
Report. N Engl J Med. 1988; 319(25):1676-80.
    \257\ Topalian SL, Solomon D, Avis FP, et al. Immunotherapy of 
Patients with Advanced Cancer Using Tumor-Infiltrating Lymphocytes 
and Recombinant Interleukin-2: A Pilot Study. J Clin Oncol. 
1988;6(5):839-53.
    \258\ Dudley ME, Wunderlich JR, Robbins PF, et al. Cancer 
Regression and Autoimmunity in Patients after Clonal Repopulation 
with Antitumor Lymphocytes. Science. 2002;298(5594):850-4.
    \259\ Yao, X., Ahmadzadeh, M., Lu, Y.C., Liewehr, D.J., Dudley, 
M.E., Liu, F., Schrump, D.S., Steinberg, S.M., Rosenberg, S.A., 
Robbins, P.F., 2012. Levels of peripheral CD4([thorn])FoxP3([thorn]) 
regulatory T cells are negatively associated with clinical response 
to adoptive immunotherapy of human cancer. Blood 119, 5688e5696.
---------------------------------------------------------------------------

    Next the applicant stated that the purpose of the comment letter 
was to respond to CMS' question on whether a multivariate analysis had 
been conducted to determine the impact of independent predictors on the 
efficacy results of lifileucel and, specifically, if the impact of IL-2 
had been analyzed in such a univariable analysis. The applicant noted 
that the updated analyses are proprietary until further notice. We note 
that we are therefore unable to discuss them in this proposed rule or 
consider them in support of this application.
    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 lifileucel.
e. LIVTENCITYTM (maribavir)
    Takeda Pharmaceuticals U.S.A., Inc. submitted an application for 
new technology add-on payments for LIVTENCITYTM (maribavir) 
for FY 2023. LIVTENCITYTM is a cytomegalovirus (CMV) pUL97 
kinase inhibitor indicated for the treatment of adults and pediatrics 
(12 years of age and older and weighing at least 35 kg) with post-
transplant CMV infection/disease that is refractory to treatment (with 
or without genotypic resistance) to ganciclovir, valganciclovir, 
cidofovir, or foscarnet.
    According to the applicant, LIVTENCITYTM is the only 
antiviral therapy indicated to treat post-transplant patients with CMV 
in solid organ transplant (SOT) and hematopoietic stem cell transplant 
(HCT). Per the applicant, LIVTENCITYTM provides multi-
targeted anti-CMV activity by inhibiting protein kinase UL97 and its 
natural substrates, which subsequently inhibits CMV DNA replication, 
encapsidation, and nuclear egress of viral capsids.
    The applicant stated that CMV is one of the most common viral 
infections experienced by transplant recipients, with an estimated 
incidence rate between 16%-56% in SOT recipients and 30%-70% in HCT 
recipients.\260\ CMV is a beta herpesvirus that commonly infects 
humans; serologic evidence of prior infection can be found in 40%-100% 
of various populations.\261\ CMV typically resides latent and 
asymptomatic in the body but may reactivate during periods of 
immunosuppression. The applicant estimated that there are approximately 
200,000 adult transplants per year globally and an estimated 1,435 
cases of CMV post-transplant in the Medicare population per year. The 
applicant stated that in transplant patients, reactivation of CMV can 
potentially lead to serious consequences including loss of the 
transplanted organ and, in extreme cases, death.
---------------------------------------------------------------------------

    \260\ Azevedo L, Pierrotti L, Abdala E, et al. Cytomegalovirus 
infection in transplant recipients. Clinics.2015;70(7):515-523. 
doi:10.6061/clinics/2015(07)09; World Health Organization (WHO). 
International Report on Organ Donation and Transplantation 
Activities-Executive Summary 2018.
    \261\ Krech U. Complement-fixing antibodies against 
cytomegalovirus in different parts of the world. Bull WHO. 
1973(49):103-106.
---------------------------------------------------------------------------

    Per the applicant, there are four FDA-approved therapies for the 
treatment and/or prevention (that is, prophylaxis) of CMV disease: 
Valganciclovir, ganciclovir, foscarnet, and cidofovir. The applicant 
stated that ganciclovir and valganciclovir are approved for prevention 
of CMV disease in transplant recipients and for treatment of CMV 
retinitis in immunocompromised hosts, including those with Acquired 
Immune Deficiency Syndrome (AIDS); and foscarnet and cidofovir are 
approved for treatment of CMV retinitis in AIDS patients. Per the 
applicant, none of these four therapies are FDA-approved for the 
treatment of resistant or refractory CMV infection and disease. The 
applicant provided a table that included the therapy, transplant type, 
mechanism of action, approved indications that were CMV-related, and 
the formulation(s).
BILLING CODE 4120-01-P

[[Page 28258]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.094

BILLING CODE 4120-01-C
    With respect to the newness criterion, the applicant stated that 
LIVTENCITYTM was granted Breakthrough Therapy, Priority 
Review, and Orphan Drug designations from FDA, and subsequently 
received FDA approval for its New Drug Application on November 23, 
2021. LIVTENCITYTM is indicated for the treatment of adults 
and pediatric patients (12 years of age or older and weighing at least 
35 kg) with post-transplant CMV infection/disease that is refractory to 
treatment (with or without genotypic resistance) with ganciclovir, 
valganciclovir, cidofovir, or foscarnet. Per the applicant, 
LIVTENCITYTM became commercially available on December 2, 
2021. The applicant did not explain the reason for the delay between 
market authorization and commercial availability. The recommended 
dosing is 400 mg (two 200 mg tablets) orally twice daily with or 
without food. The applicant stated that if LIVTENCITYTM is 
co-administered with carbamazepine, then the dosage is increased to 800 
mg twice daily; if co-administered with phenytoin or phenobarbital, the 
dosage is increased to 1,200 mg twice daily.
---------------------------------------------------------------------------

    \262\ VALCYTE[supreg] (valganciclovir) United States Prescribing 
Information (2018).
    \263\ CYTOVENE-IV[supreg] (ganciclovir) United States 
Prescribing Information (2018).
    \264\ FOSCAVIR[supreg] (foscarnet) United States Prescribing 
Information (2017).
    \265\ VISTIDE[supreg] (cidofovir) United States Prescribing 
Information (2010).
---------------------------------------------------------------------------

    According to the applicant, ICD-10-PCS code 3E0DX29 (Introduction 
of other anti-infective into mouth and pharynx, external approach) may 
be used to identify administration of LIVTENCITYTM but does 
not uniquely identify it. The applicant submitted a request for 
approval for a unique ICD-10-PCS procedure code for 
LIVTENCITYTM beginning in FY 2023.
    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 purposes of new technology add-on 
payments.
    With respect to the first criterion, whether a technology uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that LIVTENCITYTM targets a different 
gene locus (pUL97 vs. pUL54) than the existing therapies to treat CMV 
infection, including those resistant or refractory to conventional 
therapy. Specifically, LIVTENCITYTM inhibits CMV DNA 
replication, encapsidation, and nuclear egress of viral capsids

[[Page 28259]]

through inhibition of pUL97 and its natural substrates. The applicant 
provided the mechanisms of action for the other existing anti-CMV 
drugs, namely valganciclovir ganciclovir, foscarnet, and cidofovir in 
the table previously listed and concluded that the 
LIVTENCITYTM uses a different mechanism of action compared 
to existing anti-CMV drugs.
    With respect to the second criterion, whether a technology is 
assigned to the same or a different MS-DRG when compared to an existing 
technology, the applicant stated that LIVTENCITYTM is 
expected to be assigned to the same MS-DRGs as therapies that are 
currently used off-label for the treatment of CMV infection or disease.
    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 noted that there are no other 
existing therapies indicated to treat the same or similar type of 
disease or patient population as LIVTENCITYTM. The applicant 
noted that currently available therapies are used off-label to treat 
patients with refractory or resistant CMV infection or disease. Thus, 
the applicant maintained that LIVTENCITYTM is indicated to 
treat a different patient population compared to existing technologies.
    In summary, the applicant asserted that LIVTENCITYTM is 
not substantially similar to other currently available therapies 
because it uses a new mechanism of action and is indicated to treat a 
unique patient population and/or disease and, therefore, the technology 
meets the newness criterion. We are inviting public comments on whether 
LIVTENCITYTM is substantially similar to existing 
technologies and whether LIVTENCITYTM meets the newness 
criterion. As noted previously, the applicant did not explain the 
reason for the delay between market authorization and commercial 
availability, and we therefore also request additional information 
regarding this point.
    With respect to the cost criterion, the applicant presented the 
following analysis. To identify patients who may be eligible to receive 
LIVTENCITYTM as a treatment, the applicant searched the 2019 
MedPAR dataset for cases with the following ICD-10-CM codes for CMV and 
post-transplant SOT and HCT infection. The applicant included inpatient 
discharges under Medicare fee-for-service (FFS) and excluded Medicare 
Advantage discharges.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.095

BILLING CODE 4120-01-C
    The applicant identified 1,435 claims mapping to 108 MS-DRGs. For 
MS-DRGs where the case volume was below 11, the applicant imputed a 
count of 11 cases. The table lists the nine MS-DRGs with the highest 
volume of cases.

[[Page 28260]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.096

    The applicant did not remove charges for a prior technology, as the 
applicant claimed that any current treatment that is used off-label to 
treat CMV patients post-transplant SOT and HCT may not be reflected in 
claims data. The applicant further explained that in cases where an 
off-label treatment is reflected on the claim, LIVTENCITYTM 
might be used as a second-line treatment rather than to replace the 
off-label treatment. The applicant then standardized the charges and 
applied a 4-year inflation factor of 1.281834 or 28.1834%, based on the 
inflation factor used in the FY 2022 IPPS/LTCH PPS final rule and 
correction notice to update the outlier threshold (86 FR 45542). The 
applicant added charges for the new technology by dividing the cost of 
LIVTENCITYTM by the national average CCR for drugs which is 
0.187 (86 FR 44966). The applicant estimated the costs of 
LIVTENCITYTM based on 8-week dosing regimens to complete the 
full treatment.
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $508,855 which exceeded the average 
case-weighted threshold amount of $76,739.
    We invite public comments on whether LIVTENCITYTM meets 
the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that LIVTENCITYTM represents a new 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments. To support this claim, 
the applicant reiterated that there are no existing therapies that are 
approved by FDA to treat post-transplant patients with refractory or 
resistant CMV infection or disease. The applicant also asserted that 
the use of LIVTENCITYTM may significantly improve clinical 
outcomes by improving efficacy and reducing adverse effects compared to 
available therapies.
    To support the claim of improved efficacy, the applicant cited 
results from SOLSTICE, a phase III, open-label, randomized controlled 
trial in which 352 transplant recipients [HCT (n=211) and SOT (n=141)] 
with refractory \266\ or resistant \267\ CMV were assigned 2:1 to 
receive 400 mg of LIVTENCITYTM twice daily (n=235) or 
investigator-assigned therapy (IAT) with drug-specific dosing (n=117) 
for 8 weeks, with 12 weeks of follow-up.\268\ The choice of specific 
IAT was at the investigators' discretion and included mono- or 
combination therapy (<=2 drugs) with intravenous (IV) ganciclovir, oral 
valganciclovir, IV foscarnet or IV cidofovir, where switching between 
ganciclovir and valganciclovir was permitted. The median (range) 
duration of exposure was 57 (2-64) days in the LIVTENCITYTM 
arm and 34 (4-64) days with IAT. The primary endpoint was the 
proportion of patients achieving CMV clearance at 8 weeks, and the key 
secondary endpoint was achievement of CMV clearance \269\ and symptom 
control \270\ at the end of week 8, maintained through week 16. With 
respect to the primary endpoint, the applicant indicated that CMV 
clearance at 8 weeks was achieved in 55.7% (n=131/235) of the 
LIVTENCITYTM group and 23.9% (n=28/117) of the IAT group 
with an adjusted difference of 32.8%, where the results achieved 
statistical significance [95% CI, 22.8-42.7%, p<0.001]. With respect to 
the secondary endpoint, the applicant indicated that 18.7% (n=44/235) 
of the LIVTENCITYTM-treated group and 10.3% (n=12/117) of 
IAT-treated group maintained CMV viremia clearance and symptom control 
through week 16 (p=0.013).\271\ The applicant stated that, based on 
these results, LIVTENCITYTM is superior to conventional 
antiviral therapies in achieving and maintaining CMV viremia clearance 
and symptom control.
---------------------------------------------------------------------------

    \266\ Failure to achieve >1 log10 decrease in CMV DNA 
after at least 14 days of anti-CMV treatment.
    \267\ At least 1 genetic mutation associated with resistance to 
ganciclovir/valganciclovir, foscarnet, and/or cidofovir.
    \268\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: Results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
    \269\ Measured as CMV DNA level less than lower limit of 
quantification.
    \270\ Resolution or improvement in tissue-invasive CMV disease 
or syndrome for participants symptomatic at baseline or no new 
symptoms of tissue-invasive CMV disease or syndrome for participants 
asymptomatic at baseline.
    \271\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: Results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    The applicant also claimed that the efficacy of 
LIVTENCITYTM is consistent across SOT types, as evidenced by 
an unpublished subgroup analysis by Avery et al.\272\ which evaluated 
211 SOT patients from the SOLSTICE trial for CMV clearance 
(LIVTENCITYTM vs. conventional) by transplant type, with the 
following results: Heart: 42.9% (n=6/14) vs. 11.1% (n=1/9) (adjusted 
difference: 30.7% [95% CI, -1.72-63.15%]); lung: 47.5% (n=19/40) vs. 
13.6% (n=3/22), adjusted difference: 38.2% [95% CI, 16.89-59.53%]; 
kidney: 59.5% (n=44/74) vs. 34.4% (n=11/32); adjusted difference: 26.7% 
[95% CI, 7.48-45.85%].
---------------------------------------------------------------------------

    \272\ Avery RK, Blumberg EA, Florescu D, et al. A randomized 
phase 3 open-label study of maribavir vs. investigator-assigned 
therapy for refractory/resistant cytomegalovirus infection in 
transplant recipients: Subgroup analyses of efficacy by organ. in: 
The 2021 American Transplant Congress; 2021. Abstract LB 9.
---------------------------------------------------------------------------

    Finally, with regard to efficacy, the applicant stated that 
LIVTENCITYTM is active against refractory or resistant CMV 
infections and tolerable across doses. To support this claim, the 
applicant pointed to a randomized, dose-ranging, open-label, phase II 
study by Papanicolaou et al.,\273\ in which HCT

[[Page 28261]]

and SOT recipients with refractory or resistant CMV infections (n=120) 
were randomized 1:1:1 to twice-daily LIVTENCITYTM doses of 
400 mg (n=40), 800 mg (n=40), or 1,200 mg (n=40) for up to 24 weeks. 
The primary efficacy endpoint was the proportion of patients with 
confirmed undetectable plasma CMV DNA within 6 weeks of treatment. 
About two-thirds (n=80/120) of the patients achieved undetectable 
plasma CMV DNA within 6 weeks of treatment among all doses [95% CI, 57-
75%], and 70% of patients receiving 400 mg of LIVTENCITYTM 
twice daily [95% CI, 53-83]; 62% of patients receiving 800 mg twice 
daily [95% CI, 46-77%], and 68% of patients receiving 1,200 mg twice 
daily [95% CI, 51-81%] achieved the primary endpoint. About a third of 
patients experienced recurrent CMV infection while on 
LIVTENCITYTM (n=25) and 13 patients developed mutations 
conferring LIVTENCITYTM resistance.
---------------------------------------------------------------------------

    \273\ Papanicolaou GA, Silveira FP, Langston AA, et al. MBV for 
r/r CMV infections in HCT or SOT recipients: A randomized, dose-
ranging, double-blind, phase 2 study. Clin Infect Dis. 
2019;68(8):1255-1264. doi:10.1093/cid/ciy706.
---------------------------------------------------------------------------

    To support the claim of decreased adverse effects, the applicant 
cited the results of two secondary endpoints from the SOLSTICE trial. 
Per the applicant, neutropenia and acute kidney injury are known, 
common adverse effects associated with valganciclovir/ganciclovir and 
foscarnet, respectively. The applicant noted that the rates of 
treatment-related neutropenia and acute kidney injury were both 1.7% 
(n=4/234), separately, in the LIVTENCITYTM treatment group. 
The applicant also noted that the rate of neutropenia was 25% (n=14/56) 
in the valganciclovir/ganciclovir group, and the rate of acute kidney 
injury was 19.1% (n=9/47) in the foscarnet group.\274\ The applicant 
maintained that the rate of treatment-related neutropenia and acute 
kidney injury was lower in the LIVTENCITYTM group vs. 
conventional therapy group. The applicant asserted that, based on these 
results, LIVTENCITYTM has a lower incidence of treatment-
related toxicities than existing therapies.
---------------------------------------------------------------------------

    \274\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: Results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    The applicant more specifically claimed that transplant patients 
treated with LIVTENCITYTM for CMV infection experienced a 
lower incidence of treatment-related neutropenia compared with 
valganciclovir. To support this claim, the applicant cited the primary 
safety endpoint from Maertens et al.,\275\ a parallel-group, phase II 
study. In this open-label, LIVTENCITYTM-blinded trial, 120 
HCT or SOT recipients with CMV reactivation were randomly assigned to 
receive LIVTENCITYTM at a dose of 400 mg (n=40), 800 mg 
(n=40), or 1,200 mg (n=40) twice daily or the standard dose of 
valganciclovir for 12 weeks for preemptive treatment. The primary 
efficacy endpoint was the percentage of patients with a response to 
treatment, defined as confirmed undetectable CMV DNA in plasma, within 
3 weeks and 6 weeks after the start of treatment. The primary safety 
endpoint was the incidence of adverse events that occurred or worsened 
during treatment. Specifically, the applicant cited the rate of 
treatment-emergent neutropenia in this study which was identified in 4% 
(n=5/118) of patients administered LIVTENCITYTM versus 15% 
(n=6/39) of patients administered valganciclovir through week 6. 
Similar results were found through week 12: 5% (n=6/118) vs. 18% (n=7/
39). The statistical significance of the difference in treatment-
emergent neutropenia between the two groups was not reported in the 
study.
---------------------------------------------------------------------------

    \275\ Maertens J, Cordonnier C, Jaksch P, et al. Maribavir for 
preemptive treatment of cytomegalovirus reactivation. N Engl J Med. 
2019;381(12):1136-1147. doi:10.1056/NEJMoa1714656.
---------------------------------------------------------------------------

    Finally, the applicant stated that LIVTENCITYTM had a 
lower incidence of adverse events leading to discontinuation. To 
support this assertion, the applicant cited the rate of treatment-
emergent adverse effects (TEAEs) leading to discontinuation from 
SOLSTICE, which was lower in the LIVTENCITYTM group (13.2% 
(n=31/324)) vs. the conventional group (31.9% (n=37/116)).\276\
---------------------------------------------------------------------------

    \276\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: Results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    After reviewing the information provided by the applicant, we have 
the following concerns regarding whether LIVTENCITYTM meets 
the substantial clinical improvement criterion. First, while the 
applicant provided data to demonstrate that the proportion of patients 
achieving CMV clearance at 8 weeks was higher among patients using 
LIVTENCITYTM, we note similar rates of mortality and new-
onset CMV between the 2 treatment groups in this trial: 
LIVTENCITYTM vs. comparator: 11% (n=27/235) vs. 6% (n=13/
117) and 6% (n=14/235) vs. 6% (n=7/113), respectively.\277\ We also 
note that it is unclear whether the SOLSTICE study was sufficiently 
powered to detect a difference in CMV viremia clearance at week 16, one 
of the study's secondary endpoints.\278\ We further note that while the 
rate of TEAEs leading to discontinuation was lower in the 
LIVTENCITYTM group, the rate of overall TEAEs and serious 
TEAEs in the SOLSTICE trial was similar between the two treatment 
groups [LIVTENCITYTM vs. comparator: Any TEAE: 97.4% (n=229/
234) vs. 91.4% (n=106/116), serious TEAE: 38.5% vs. 37.1%].\279\ 
Furthermore, we would appreciate additional information from the 
applicant regarding safeguards taken to minimize or prevent bias from 
the treating physician in choosing the conventional therapy for 
patients in the investigator-assigned therapy group of the phase III 
trial.
---------------------------------------------------------------------------

    \277\ Ibid.
    \278\ Ibid.
    \279\ Ibid.
---------------------------------------------------------------------------

    We are inviting public comments on whether LIVTENCITYTM 
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 
LIVTENCITYTM.
f. Mosunetuzumab
    Genentech, Inc. submitted an application for new technology add-on 
payments for mosunetuzumab for FY 2023. According to the applicant, 
mosunetuzumab is an investigational drug that is anticipated to be a 
novel first-in class therapy for the treatment of any non-Hodgkin 
lymphoma (NHL). The applicant stated that it intends to seek FDA 
approval for the use of mosunetuzumab in adults with relapsed or 
refractory (r/r) follicular lymphoma (FL) who have received at least 
two prior systemic therapies.
    According to the applicant, mosunetuzumab is a humanized bispecific 
monoclonal antibody (BsAb) that exhibits potential antineoplastic 
activity. The applicant stated that mosunetuzumab contains two antigen-
recognition sites: One for human CD3 (a T cell surface antigen) and one 
for human CD20 (a tumor-associated antigen expressed on B cells, and 
often overexpressed in B cell malignancies). Per the applicant, 
mosunetuzumab binds to both patients' existing T cells and CD20-
expressing tumor cells, linking them, which can cause a cytotoxic T-
lymphocyte response against CD20-expressing tumor B cells. According to 
the applicant, mosunetuzumab's dual targeting design,

[[Page 28262]]

due to two fragment antigen-binding or `Fab' binding regions, activates 
and redirects engagement of a lymphoma patient's T cells to eliminate 
malignant B cells by releasing cytotoxic proteins into the B cells. The 
applicant further stated that target B cell killing occurs only upon 
simultaneous binding to both targets, as it is a conditional agonist. 
According to the applicant, clinical trials of mosunetuzumab are 
ongoing with different dosing regimens including subcutaneous and 
intravenous administration.
    FL is the second most prevalent form of non-Hodgkins lymphoma 
(NHL), affecting approximately 16,000 individuals annually in the 
US.\280\ According to the National Institute of Health (NIH), the rate 
of new cases of FL was 2.7 per 100,000 men and women per year based on 
2014-2018 cases, age-adjusted.\281\ According to the applicant, the 
vast majority of patients treated for FL will have an initial response 
to therapy with 40 to 80 percent demonstrating a complete response, 
depending on the initial regimen used. In addition, less than 10 
percent of patients treated with initial chemoimmunotherapy will not 
respond to treatment (that is, have refractory disease).\282\
---------------------------------------------------------------------------

    \280\ Shi Q, Flowers CR, Hiddemann W, Marcus R, Herold M, 
Hagenbeek A, Kimby E, Hochster H, Vitolo U, Peterson BA, Gyan E, 
Ghielmini M, Nielsen T, De Bedout S, Fu T, Valente N, Fowler NH, 
Hoster E, Ladetto M, Morschhauser F, Zucca E, Salles G, Sargent DJ. 
Thirty-Month Complete Response as a Surrogate End Point in First-
Line Follicular Lymphoma Therapy: An Individual Patient-Level 
Analysis of Multiple Randomized Trials. J Clin Oncol. 2017 Feb 
10;35(5):552-560. doi: 10.1200/JCO.2016.70.8651.
    \281\ https://seer.cancer.gov/statfacts/html/nhl.html.
    \282\ Freedman, A.S., Friedberg, Jonathan, et.al. (2022). 
Treatment of relapsed or refractory follicular lymphoma. UpToDate. 
Retrieved February 7, 2022, from https://www.uptodate.com/contents/
treatment-of-relapsed-or-refractory-follicular-
lymphoma?search=relapsed%20refractory%20follicular%20lymphoma&source=
search_result&selectedTitle=1~150&usage_type=default&display_rank=1.
---------------------------------------------------------------------------

    According to the applicant, FL is an indolent, incurable disease 
and patients are expected to have relapses. Based on a 10-year 
retrospective study of follicular NHL patients treated with first line 
(1L) therapy between 1998-2009, 50% progressed to second line (2L) 
therapy. Of those who completed 2L treatment, 65% progressed to third 
line (3L) therapy, and 65% of those patients then progressed to fourth 
line (4L).\283\ An observational National LymphoCare Study also noted 
that of patients undergoing 1L, 37% progressed to 2L, 18% received 3L, 
and 9% and 5% went on to 4L and 5L, respectively.\284\ The applicant 
stated that multiply relapsed FL has a high unmet medical need 
especially in patients who are relapsed or refractory to different 
classes of agents and have limited treatment options with challenging 
safety profiles. Therefore, per the applicant, novel treatments with 
improved efficacy and tolerability are needed.
---------------------------------------------------------------------------

    \283\ Hubel K, Ghielmini M, Ladetto M, Gopal A. Controversies in 
the Treatment of Follicular Lymphoma. HemaSphere. 2020;4(1): e317. 
doi:10.1097/HS9.0000000000000317.
    \284\ Link et al. Br. J. Haematol. 2019;184:634-696 https://doi.org/10.1111/bjh.15149.
---------------------------------------------------------------------------

    The applicant stated that the NCCN provides suggested treatment 
regimens for existing agents in FL. According to the applicant, choice 
of therapy requires consideration of several factors, including age and 
comorbidities, as well as refractory status to prior therapies. 
However, per the applicant, there is no established standard of care 
for FL in third-line or later (3L+) settings. The applicant stated that 
the currently FDA approved treatments for r/r FL include anti-CD20-
based treatment regimens (including the combination of lenalidomide + 
rituximab known as the R2 regimen), phosphatidylinositol 3-kinase 
(PI3K) inhibitors, enhancer of zeste homolog 2 (EZH2) inhibitors, and 
CAR T-cell therapy.
    According to the applicant, chemoimmunotherapy with anti-CD20 
monoclonal antibodies (mAb) approved for FL includes rituximab, a Type 
I antibody, and obinutuzumab, a Type II antibody.\285\ The applicant 
stated that while the anti-CD20 antibodies are NCCN Guidelines 
Preferred treatments for 2L and subsequent therapy, they are not 
considered the most beneficial treatment for 3L+ FL; most patients are 
treated with rituximab-based therapies in the early lines (1L and 2L) 
of treatment, which the applicant stated leads to decreasing duration 
of response (DOR) and increasing refractoriness to therapies in the 
later lines of treatment. The applicant further asserted that the 
predominantly elderly FL population, together with the fact that many 
patients have typically been through multiple rounds of therapy, limits 
their ability to tolerate anti-CD20 mAb plus chemotherapy-based 
regimens.
---------------------------------------------------------------------------

    \285\ Salles GA, Morschhauser F, Solal-Ce[acute]ligny P, et al. 
obinutuzumab (GA101) in patients with relapsed/refractory indolent 
non-Hodgkin lymphoma: Results from the phase II GAUGUIN study. J. 
Clin. Oncol. 2013;31(23):2920-2926. doi:10.1200/JCO.2012.46.9718.
---------------------------------------------------------------------------

    According to the applicant, since anti-CD20 mAbs alone or with 
chemotherapy are not curative, show decreasing efficacy with repeated 
administrations, and because chemotherapy-based regimens are associated 
with long-term toxic effects, leading to limited tolerability 
especially for the elderly population, different targets were sought in 
the treatment of r/r FL.\286\ Per the applicant, the FDA has granted 
accelerated approval for idelalisib \287\ \288\ copanlisib,\289\ and 
duvelisib \290\ as single agent inhibitors of PI3K delta, alpha/delta, 
and delta/gamma isoforms, respectively, for the treatment of patients 
with r/r FL who have received >=2 prior therapies. More recently, the 
dual PI3K delta and casein kinase 1 epsilon inhibitor umbralisib \291\ 
gained accelerated approval for treatment of patients with r/r FL who 
have received at least three prior lines of systemic therapy. The 
applicant asserted that balancing tumor target inhibition with dose-
limiting toxicities has presented a challenge for PI3K inhibitors, and 
that although these PI3K inhibitors have shown efficacy, they have also 
been associated with significant toxicities. The applicant further 
stated that these treatments provide important options to physicians 
and patients, but their side-by-side evaluation for FL in cross-trial 
comparisons is challenging due to variability in patient selection and 
treatments. The applicant noted that both duvelisib and idelalisib have 
recently been voluntarily withdrawn from the US market for the 
treatment of FL.\292\ \293\
---------------------------------------------------------------------------

    \286\ Bachy E, Houot R, Morschhauser F, et al. Long-term follow 
up of the FL2000 study comparing CHVP-interferon to CHVP-interferon 
plus rituximab in follicular lymphoma. Haematologica. 
2013;98(7):1107-1114. doi:10.3324/haematol.2012.082412.
    \287\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N. Engl. 
J. Med. 2014;370:1008-1018. doi:10.1056/NEJMoa1314583.
    \288\ Salles G, Schuster SJ, de Vos S, et al. Efficacy and 
safety of idelalisib in patients with relapsed, rituximab-and 
alkylating agent-refractory follicular lymphoma: A subgroup analysis 
of a phase 2 study. Haematologica. 2017;102:156-159. doi:10.3324/
haematol.2016.151738.
    \289\ Dreyling M, Santoro A, Mollica L, et al. 
Phosphatidylinositol 3-kinase inhibition by copanlisib in relapsed 
or refractory indolent lymphoma. J. Clin. Oncol. 2017;35:3898-3905. 
doi:10.1200/JCO.2017.75.4648.
    \290\ Flinn IW, Miller CB, Ardeshna KM, et al. DYNAMO: A phase 
II study of duvelisib (IPI-145) in patients with refractory indolent 
non-Hodgkin lymphoma. J. Clin. Oncol. 2019;37(11):912-922. 
doi:10.1200/JCO.18.00915. Erratum in: J. Clin. Oncol. 
2019;37(16):1448. doi:10.1200/JCO.19.00976.
    \291\ Fowler NH, Samaniego F, Jurczak W, et al. umbralisib, a 
dual PI3K[delta]/CK1[egr] inhibitor in patients with relapsed or 
refractory indolent lymphoma. J. Clin. Oncol. 2021;39:1609-1618. 
doi:10.1200/JCO.20.03433,
    \292\ Gilead statement on zydelig[supreg] U.S. indication for 
follicular lymphoma and small lymphocytic leukemia. https://www.gilead.com/news-and-press/company-statements/gilead-statement-on-zydelig-us-indication-for-follicular-lymphoma-and-small-lymphocytic-leukemia. Accessed January 25, 2022.
    \293\ Inc SB. Secura bio announces copiktra[supreg] (Duvelisib) 
strategic focus on t-cell lymphoma and voluntary U.S. withdrawal of 
the relapsed or refractory follicular lymphoma indication. https://www.prnewswire.com/news-releases/secura-bio-announces-copiktra-duvelisib-strategic-focus-on-t-cell-lymphoma-and-voluntary-us-withdrawal-of-the-relapsed-or-refractory-follicular-lymphoma-indication-301436834.html. Accessed January 25, 2022.

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

[[Page 28263]]

    According to the applicant, a newer therapeutic approach to treat 
FL includes EZH2 inhibitor therapy, a catalytic subunit of the 
chromatin remodeling Polycomb Repressive Complex 2 (PRC2).\294\ 
According to the applicant, the FDA granted accelerated approval to 
tazemetostat,\295\ a first-in-class EZH2 inhibitor for patients with r/
r FL who received >=2 prior therapies whose tumors are positive for an 
EZH2 mutation, and for patients with r/r FL who have no satisfactory 
alternative treatment options. The applicant stated that EZH2 exhibits 
somatic, gain-of-function activating mutations in 7-29% of FL 
patients.\296\ \297\ \298\ EZH2 mutations represent an early event in 
FL, and in the majority of cases are maintained throughout disease 
transformation. The applicant further stated that considering the high 
overall incidence of EZH2 mutations in FL, their stability during 
disease progression, and that EZH2 selective inhibitors can be made, it 
follows that efforts would be placed on developing FL therapies 
targeting the inhibition of EZH2.
---------------------------------------------------------------------------

    \294\ Morin RD, Johnson NA, Severson TM, et al. Somatic 
mutations altering EZH2 (Tyr641) in follicular and diffuse large B-
cell lymphomas of germinal-center origin. Nat. Genet. 2010;42:181-
185. doi: 10.1038/ng.518
    \295\ Morschhauser F, Tilly H, Chaidos A, et al. tazemetostat 
for patients with relapsed or refractory follicular lymphoma: An 
open-label, single-arm, multicentre, phase 2 trial. Lancet Oncol. 
2020;21:1433-1442. doi:10.1016/S1470-2045(20)30441-1.
    \296\ Morin RD, Johnson NA, Severson TM, et al. Somatic 
mutations altering EZH2 (Tyr641) in follicular and diffuse large B-
cell lymphomas of germinal-center origin. Nat. Genet. 2010;42:181-
185. doi: 10.1038/ng.518.
    \297\ B[ouml]d[ouml]r C, Grossmann V, Popov N, et al. EZH2 
mutations are frequent and represent an early event in follicular 
lymphoma. Blood. 2013;122:3165-3168. doi:10.1182/blood-2013-04-
496893.
    \298\ Huet S, Xerri L, Tesson B, et al. EZH2 alterations in 
follicular lymphoma: Biological and clinical correlations. Blood 
Cancer J. 2017;7:e555. doi:10.1038/bcj.2017.32.
---------------------------------------------------------------------------

    The applicant stated that recent developments have supported the 
effectiveness of therapies that utilize T cells in the treatment of B-
cell malignancies, such as the ex vivo manipulation of T lymphocytes to 
express chimeric antigen receptors (CARs) that target lineage-specific 
surface molecules such as CD19.\299\ According to the applicant, 
axicabtagene ciloleucel (YESCARTA[supreg]) was the second approved 
gene-altering cancer treatment, first-in-class for aggressive lymphoma, 
and was approved by FDA based on clinical study results \300\ for the 
treatment of patients with r/r FL who have received >=2 prior 
therapies. The applicant asserted that while offering strong efficacy, 
CAR T-cell therapy has significant limitations as it adds complexities 
in manufacturing and treatment which the applicant states negatively 
impact patient access significantly. The applicant stated that CAR T-
cell therapy requires mandatory hospitalization and is only available 
at one of only approximately 100 authorized treatment centers (ATCs) 
across the United States,\301\ adding cost and travel burdens on 
patients, particularly older patients who may be on limited incomes and 
have difficulty traveling long distances. Per the applicant, CAR T-cell 
therapy also raises risks for serious toxicities and prominent side 
effects like neurotoxicity and cytokine release syndrome (CRS).\302\
---------------------------------------------------------------------------

    \299\ Viardot A, Wais V, Sala E, et al. Chimeric antigen 
receptor (CAR) T-cell therapy as a treatment option for patients 
with B-cell lymphomas: Perspectives on the therapeutic potential of 
axicabtagene ciloleucel. Cancer Manag. Res. 2019;11:2393-2404. 
doi:10.2147/CMAR.S163225.
    \300\ Jacobson C, Chavez JC, Sehgal AR, et al. Primary analysis 
of zuma-5: A phase 2 study of axicabtagene ciloleucel (axi-cel) in 
patients with relapsed/refractory (r/r) indolent non-hodgkin 
lymphoma (iNHL). Blood. 2020;136 (Supplement 1):40-41. doi:10.1182/
blood-2020-136834.
    \301\ Yescarta[supreg] (axicabtagene ciloleucel) Authorized 
Treatment Centers. YESCARTA HCP website, 10 Sept. 2021, https://www.yescartahcp.com/large-b-cell-lymphoma/authorized-treatment-centers.
    \302\ Jacobson C, Chavez JC, Sehgal AR, et al. Primary analysis 
of zuma-5: A phase 2 study of axicabtagene ciloleucel (axi-cel) in 
patients with relapsed/refractory (r/r) indolent non-hodgkin 
lymphoma (iNHL). Blood. 2020;136(Supplement 1):40-41. doi:10.1182/
blood-2020-136834.
---------------------------------------------------------------------------

    The applicant stated that for these reasons, there is a high unmet 
need for patients with r/r FL who have received >=2 prior therapies, 
particularly for patients who are refractory to different classes of 
agents and are left with limited treatment options that may have 
challenging safety profiles. Per the applicant, new treatment options 
are needed that will significantly extend the duration of remission and 
can overcome resistance to existing therapies, while providing 
acceptable safety and tolerability.
    With respect to the newness criterion, the applicant stated that 
mosunetuzumab was granted Breakthrough Therapy designation by FDA. The 
applicant indicated that it expects to receive FDA approval by June 30, 
2022 and stated that the final review pathway has yet to be determined. 
Additionally, the applicant stated they may be limited in their ability 
to make mosunetuzumab available immediately following FDA approval and 
pointed to printing and labeling requirements as the reason. Per the 
applicant, while the drug has not yet been FDA-approved, the 
recommended dosage is presented in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.097

    The applicant described a dose escalation for mosunetuzumab to be 
administered intravenously for eight cycles unless there is 
unacceptable toxicity or disease progression. For patients who achieve 
a complete response (CR), no further treatment beyond eight cycles is 
required. For patients who achieve a partial response

[[Page 28264]]

(PR) or have stable disease control in response to treatment with 
mosunetuzumab after eight cycles, an additional nine cycles of 
treatment (17 cycles total) should be administered. Additionally, if 
there is any dose delay >7 days in cycle 1, the previous tolerated dose 
should be repeated prior to resuming the planned treatment schedule. If 
a dose interruption occurs between cycles 1 and 2 that results in a 
treatment-free interval of >=6 weeks, mosunetuzumab is recommended to 
be administered as 1 mg on day 1 and 2 mg on day 8, and then the 
planned cycle 2 treatment of 60 mg is resumed on day 15. If a dose 
interruption occurs that results in a treatment-free interval of >=6 
weeks between any cycles in cycle 3 onwards, mosunetuzumab is to be 
administered at 1 mg on day 1 and 2 mg on day 8, and then the planned 
treatment schedule of 30 mg is resumed on day 15.
    According to the applicant, there are currently no ICD-10-PCS 
procedure codes to distinctly identify procedures involving 
administration of mosunetuzumab. The applicant submitted a request for 
approval for a unique ICD-10-PCS code to identify procedures involving 
the administration of mosunetuzumab for FY 2023. The applicant also 
listed the following diagnosis codes that could be used to identify the 
indications associated with the technology:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.098


[[Page 28265]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.099


[[Page 28266]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.100

BILLING CODE 4120-01-C
    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 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 mosunetuzumab does not use the same or a 
similar mechanism of action when compared to other therapies approved 
in the treatment of 3L+ r/r FL. The applicant stated that mosunetuzumab 
is a bispecific CD20xCD3 monoclonal antibody. The applicant asserted 
that mosunetuzumab has a mechanism of action that is unique and 
different from that of existing technologies used to treat FL. The 
applicant asserted that mosunetuzumab is a novel, full-length, 
humanized, IgG1 bispecific antibody that concomitantly binds CD3 on T-
cells and CD20 on malignant B-cells. Importantly, according to the 
applicant, 98-100% of FL cases are positive for CD20.303 304 
Per the applicant, crosslinking leads to T-cell activation, which 
redirects T-cells to engage and eliminate malignant B-cells. The 
applicant stated that an amino acid substitution in the Fc region of 
mosunetuzumab results in a non-glycosylated heavy chain with minimal 
binding to Fc-[gamma] receptors, significantly reducing Fc effector 
functions.
---------------------------------------------------------------------------

    \303\ Ray S, Craig FE, Swerdlow SH. Abnormal patterns of 
antigenic expression in follicular lymphoma: A flow cytometric 
study. Am. J. Clin. Pathol. 2005;124(4):576-583. doi:10.1309/
2GFKU23XA1DH38L7.
    \304\ Liu Q, Weaver LS, Liewehr D, Venzon D, Stetler-Stevenson 
M, Yuan CM. Increased expression of CD20 and CD45 and diminished 
expression of CD19 are features of follicular lymphoma. PLMI. 
2013;5:21-30. doi:10.2147/PLMI.S43597.
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    The applicant provided a summary of the currently available 
treatments, their respective mechanisms of action and FDA approval 
dates in the following table:
BILLING CODE 4120-01-P

[[Page 28267]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.101


[[Page 28268]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.102

BILLING CODE 4120-01-C
    The applicant stated that regimens using monospecific, anti-CD20 
antibodies, including lenalidomide + rituximab (R2), are approved for 
r/r FL, but data for R2 was derived from less pre-treated and 
refractory patients. According to the applicant, rituximab alone, or 
anti-CD20 mAbs combined with chemotherapy, are critical mainstay 
therapies used in earlier lines of FL, but patients become refractory 
or have short DOR to them as they go through relapses. According to the 
applicant, PI3K inhibitors, EZH2 inhibitors, and CAR T-cell therapies 
all have different mechanisms of action when compared to mosunetuzumab.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that with the 
exception of CAR T-cell therapies, which are assigned to a separate MS-
DRG (MS-DRG 018 Chimeric Antigen Receptor (CAR) T-cell Immunotherapy 
and Other Immunotherapies), mosunetuzumab may be assigned to the same 
MS-DRG as existing technologies. The applicant stated that with respect 
to PI3K inhibitors, however, they are often provided in outpatient care 
and it is unlikely that they would be used in inpatient care such that 
they would be wrapped into an existing MS-DRG. The applicant stated 
that although mosunetuzumab might be assigned to the same MS-DRG as 
existing technologies, this does not mean that mosunetuzumab is not 
new. The applicant stated that the MS-DRG payment system cannot 
differentiate between patients with r/r FL who could be grouped to MS-
DRGs included in the MDC 17 (Myeloproliferative Diseases and Disorders, 
Poorly Differentiated Neoplasms). The applicant stated they have not 
requested new or different MS-DRGs for mosunetuzumab for FY 2023. 
According to the applicant, procedures involving the use of 
mosunetuzumab are expected to map to the following MS-DRGs:
[GRAPHIC] [TIFF OMITTED] TP10MY22.103

    The applicant further noted that MDC 17 includes ICD-10 CM 
diagnosis codes that are not specific to FL and that for patients 
diagnosed with FL, according to the applicant, the current MS-DRG 
payment system does not factor in whether the patient has received 
previous treatment.\305\ As a result, according to the applicant, 
mosunetuzumab and an existing technology used to treat r/r FL could be 
assigned to any of the aforementioned MS-DRGs. The applicant asserted 
that the assignment of mosunetuzumab to the same MS-DRGs mentioned 
previously is a result of the lack of specificity in the current MS-DRG 
system with respect to its classification of lymphomas rather than 
because mosunetuzumab is not new.
---------------------------------------------------------------------------

    \305\ MDC 17 Myeloproliferative Diseases & Disorders, Poorly 
Differentiated Neoplasm. In: ICD-10-CM/PCS MS-DRGv37.2 Definitions 
Manual. Centers for Medicare & Medicaid Services. https://www.cms.gov/icd10m/version372-fullcode-cms/fullcode_cms/P0309.html. 
Accessed September 09, 2021.
---------------------------------------------------------------------------

    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 mosunetuzumab will not 
involve the treatment of the same type of disease and the same or 
similar patient population when compared to existing technologies. The 
applicant asserted that mosunetuzumab would treat FL 3+ line patients 
for whom there is no current standard of care. The applicant asserted 
that in the U.S., there are no therapies with full FDA approval for the 
specific indication of r/r FL patients who have received 2 or more 
prior systemic therapies.306 307 308 309 310 The applicant 
further stated that available options used in practice are primarily 
composed of approved therapies in earlier lines,

[[Page 28269]]

including anti-CD20 monoclonal antibody plus chemotherapy or 
lenalidomide, or therapies under accelerated approval including pathway 
inhibitors and cellular therapies.\311\ According to the applicant, 
each of these options presents several limitations for the treatment of 
multiple relapsed FL, particularly for patients who are relapsed or 
refractory to different classes of 
agents.312 313 314 315 316
---------------------------------------------------------------------------

    \306\ Freedman, A, Jacobsen, E. Follicular lymphoma: 2020 update 
on diagnosis and management. Am. J. Hematol. 2020; 95:316-
327.doi:10.1002/ajh.25696.
    \307\ Luminari S, Trotman J, Federico M. Advances in Treatment 
of Follicular Lymphoma. Cancer J. 2020; 26(3):231-240 doi:10.1097/
PPO.0000000000000444.
    \308\ Carbone A, Roulland S, Gloghini A, et al. Follicular 
lymphoma. Nat. Rev. Dis. Primers. 2019;(5):83. doi:10.1038/s41572-
019-0132-x.
    \309\ Batlevi CL, Sha F, Alperovich A, et al. Follicular 
lymphoma in the modern era: survival, treatment outcomes, and 
identification of high-risk subgroups. Blood Cancer J. 2020;10:74. 
doi:10.1038/s41408-020-00340-z.
    \310\ Matasar MJ, Luminari S, Barr PM, et al. Follicular 
Lymphoma: Recent and Emerging Therapies, Treatment Strategies, and 
Remaining Unmet Needs. The Oncol. 2019;24:e1236-e1250. doi:10.1634/
theoncologist.2019-0138.
    \311\ National Comprehensive Cancer Network B-cell Lymphomas 
(version 5 2021) https://www.nccn.org/professionals/physician_gls/pdf/b-cell.pdf. Accessed Oct 27, 2021 [i] National Comprehensive 
Cancer Network. B-Cell Lymphomas (Version 5.2021). https://www.nccn.org/professionals/physician_gls/pdf/b-cell.pdf. Accessed 
Oct 27, 2021.
    \312\ Freedman, A, Jacobsen, E. Follicular lymphoma: 2020 update 
on diagnosis and management. Am. J. Hematol. 2020; 95:316-
327.doi:10.1002/ajh.25696.
    \313\ Luminari S, Trotman J, Federico M. Advances in Treatment 
of Follicular Lymphoma. Cancer J. 2020; 26(3):231-240. doi:10.1097/
PPO.0000000000000444.
    \314\ Carbone A, Roulland S, Gloghini A, et al. Follicular 
lymphoma. Nat. Rev. Dis. Primers. 2019;(5):83. doi:10.1038/s41572-
019-0132-x.
    \315\ Batlevi CL, Sha F, Alperovich A, et al. Follicular 
lymphoma in the modern era: Survival, treatment outcomes, and 
identification of high-risk subgroups. Blood Cancer J. 2020;10:74. 
doi:10.1038/s41408-020-00340-z.
    \316\ Matasar MJ, Luminari S, Barr PM, et al. Follicular 
Lymphoma: Recent and Emerging Therapies, Treatment Strategies, and 
Remaining Unmet Needs. The Oncol. 2019;24:e1236-e1250. doi:10.1634/
theoncologist.2019-0138.
---------------------------------------------------------------------------

    In summary, the applicant asserted that mosunetuzumab is new 
because it does not use the same or a similar mechanism of action 
compared to other technologies currently available to Medicare 
beneficiaries to treat FL, and that upon FDA approval, mosunetuzumab 
would treat FL in 3L+ settings, for which there is no established 
standard of care. According to the applicant, all existing options have 
limitations that emphasize the need for a better solution.
    We note that the applicant asserted that use of mosunetuzumab will 
not involve the treatment of the same or similar type of disease and 
the same or similar patient population when compared to existing 
technologies. The applicant asserted that mosunetuzumab would treat FL 
in 3L+ settings, for which there is no established standard of care and 
that there are no therapies with full FDA approval for the specific 
indication of r/r FL patients who have received 2 or more prior 
systemic therapies. We note that FL in 3L+ settings is not a new 
population because there are FDA approved therapies indicated in the 
treatment of patients with r/r FL after two or more lines of systemic 
therapy. We also note that CAR T-cell therapies, such as 
Yescarta[supreg], are FDA approved therapies. We believe that 
mosunetuzumab would be used for the same disease and patient population 
when compared to other therapies approved to treat FL in 3L+ settings. 
We are inviting public comments on whether mosunetuzumab is 
substantially similar to existing technologies and whether 
mosunetuzumab meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analyses to demonstrate that mosunetuzumab meets the cost 
criterion across four different cohorts. For each cohort, the applicant 
searched the FY 2019 MedPAR database for cases representing patients 
who may be eligible for mosunetuzumab. To identify cases for patients 
with a diagnosis of FL, the applicant searched for claims with ICD-10-
CM diagnosis codes C82.00-C82.99. Per the applicant, because a 
potential patient would need to fail an established prior therapy and 
not be engaged in active treatment, the applicant then removed cases 
with the following ICD-10-CM diagnosis codes to exclude cases for 
patients still actively in the bone marrow transplant process for all 
four cohorts:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.104

    Per the applicant, as mosunetuzumab would not be administered 
concomitant to an allogenic bone marrow transplant or CAR T-cell 
therapy, the applicant also excluded cases with the following ICD-10-
PCS procedure codes related to allogenic bone marrow transplants or CAR 
T-cell therapy for all four cohorts.

[[Page 28270]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.105

    Per the applicant, as mosunetuzumab is being evaluated as a 
monotherapy for 3L+ r/r FL, cases with at least one ICD-10-PCS 
procedure code related to chemotherapy administration were removed in 
Cohort 1 and Cohort 2. Cases with these ICD-10-PCS procedure codes 
related to chemotherapy administration were maintained in Cohort 3 and 
Cohort 4. Per the applicant, as the exclusion criteria for one portion 
of one clinical trial excluded grade IIIb FL patients, cases with at 
least one ICD-10-CM diagnosis code associated with grade IIIb FL were 
removed in Cohort 2 and Cohort 4. Cases with these ICD-10-CM diagnosis 
codes associated with grade IIIb FL were maintained in Cohort 1 and 
Cohort 3.
[GRAPHIC] [TIFF OMITTED] TP10MY22.106

BILLING CODE 4120-01-C

[[Page 28271]]

    Per the applicant, the top five MS-DRGs covering the greatest case 
volume in each of the four cohorts were 840 (Lymphoma and Non-Acute 
Leukemia with MCC), 841 (Lymphoma and Non-Acute Leukemia with CC), 824 
(Lymphoma and Non-Acute Leukemia with Other Procedure with CC), 823 
(Lymphoma and Non-Acute Leukemia with Other Procedure with MCC), and 
825 (Lymphoma and Non-Acute Leukemia with Other Procedure without CC/
MCC).
    The applicant did not remove charges for prior technology. The 
applicant stated that the predominate prior technologies identified 
were associated with pain and inflammation relief or contrast agents 
for radiology, and patients receiving mosunetuzumab may also benefit 
from the use of these technologies. The applicant standardized the 
charges across all four cohorts using the FY 2019 IPPS/LTCH PPS final 
rule and Correction Notice Impact File, and conducted separate analyses 
on each cohort using both the three-year inflation factor (rounded to 
20.5%) and four-year inflation factor (rounded to 28.2%) based on the 
inflation factor from the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542) to calculate outlier threshold charges. The applicant stated 
that it did not add any charges for the new technology.
    In the first analysis (Cohort 1), the applicant computed a final 
inflated average case-weighted standardized charge per case of $85,452 
using the three-year inflation factor, and $90,912 using the four-year 
inflation factor, both of which exceeded the average case-weighted 
threshold amount of $80,433.
    In the second analysis (Cohort 2), the applicant computed a final 
inflated average case-weighted standardized charge per case of $84,849 
using the three-year inflation factor, and $90,271 using the four-year 
inflation factor, both of which exceeded the average case-weighted 
threshold amount of $80,008.
    In the third analysis (Cohort 3), the applicant computed a final 
inflated average case-weighted standardized charge per case of $103,236 
using the three-year inflation factor, and $109,833 using the four-year 
inflation factor, both of which exceeded the average case-weighted 
threshold amount of $82,688.
    In the fourth analysis (Cohort 4), the applicant computed a final 
inflated average case-weighted standardized charge per case of $102,520 
using the three-year inflation factor, and $109,071 using the four-year 
inflation factor, both of which exceeded the average case-weighted 
threshold amount of $82,325.
    Because the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount 
under all analyses without the addition of any costs related to the new 
technology, the applicant asserted that the technology meets the cost 
criterion.
    Based on the information provided by the applicant, we have the 
following concerns regarding the cost criterion. We note that the 
applicant did not specify the list of ICD-10-PCS procedure codes noted 
in its analysis related to chemotherapy administration used for 
exclusion of cases. Separately, while the applicant provided ICD-10-CM 
diagnosis codes listed previously, the applicant did not specifically 
list out which diagnoses were used to exclude grade IIIb FL from Cohort 
2 and Cohort 4. We invite public comments on whether mosunetuzumab 
meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that mosunetuzumab represents a substantial clinical 
improvement over existing technologies because--(1) mosunetuzumab 
offers a treatment option for patients with r/r FL who are relapsed or 
refractory to different classes of agents and are left with limited 
treatment options; and (2) mosunetuzumab significantly improves 
clinical outcomes relative to previously available therapies, 
demonstrating high overall and CR rates, high DOR, deep durable 
responses, and safety.
    According to the applicant, mosunetuzumab demonstrates robust 
efficacy and complete response rates in the context of the r/r FL after 
two or more prior lines of therapy, a disease setting with high unmet 
medical need for which novel treatments are needed. According to the 
applicant, mosunetuzumab also demonstrates complete response (CR) and 
overall response rates (ORR) approaching those observed with CAR T-cell 
therapy. The applicant asserted that mosunetuzumab demonstrates 
efficacy for those who have had prior systemic therapies, including an 
anti-CD20 (aCD20) antibody, alkylator, PI3K inhibitor, immunomodulatory 
drug (IMiD), and/or CAR T-cell therapy, as well >=2 prior therapies, 
and that the therapy also shows antitumor response for those having 
prior autologous stem cell transplant (ASCT). According to the 
applicant, mosunetuzumab demonstrates efficacy for those who are 
refractory to their last prior therapy, refractory to any prior aCD20, 
or double refractory to any prior aCD20 therapy + alkylator therapy. 
The applicant further stated that mosunetuzumab shows responses for FL 
patients who experience progression of disease within 2 years of 
initial chemoimmunotherapy.
    To support the assertion that mosunetuzumab offers a treatment 
option for patients who are relapsed or refractory to different classes 
of agents and are left with limited treatment options, the applicant 
described an abstract and presentation from Budde, et al. of an open-
label, uncontrolled pivotal Phase II trial of 90 patients with r/r FL 
(Grade 1 to 3a) and >2 prior therapies that were treated with 
mosunetuzumab.317 318 The median age of enrolled patients 
was 60 years (range 29 to 90), and these patients had a median of 3 
prior therapies (range 2-10). Mosunetuzumab doses started with 1 mg on 
days 1 and 8, stepping up dosing to mitigate CRS. On day 15 of the 
first 21-day cycle, 60 mg was administered. In the second cycle, 60 mg 
was administered, but on subsequent cycles, the day 1 dose was 30 mg. 
This could be repeated up to 17 cycles, depending upon whether a 
patient had a CR, a PR, or stable disease. The response was assessed 
both by the investigators and by an independent reviewer. The 
investigators noted that there was no mandatory hospitalization for 
administration of mosunetuzumab.\319\ The authors noted that the CR 
rate assessed by PET/CT was 60% (n=54; CI 49%, 70%) as compared to a 
historical control of 14% CR rate
---------------------------------------------------------------------------

    \317\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (r/r) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. 
Oral Presentation at the 63rd ASH Annual Meeting and Exposition. 
2021.
    \318\ Budde E, et al. ASH Abstract 2021. Mosunetuzumab 
Monotherapy Is an Effective and Well-Tolerated Treatment Option for 
Patients with Relapsed/Refractory (R/R) Follicular Lymphoma (FL) Who 
Have Received >=2 Prior Lines of Therapy: Pivotal Results from a 
Phase I/II Study. https://ash.confex.com/ash/2021/webprogram/Paper145872.html.
    \319\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.

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[[Page 28272]]

(from a 2017 article on copanlisib \320\). The ORR was 80% (n=72). The 
median DOR in complete responders was 22.8 months (CI 18.7, NE) and the 
same for all responders (CI 9.7, NE). The median progression free 
survival (PFS) was 17.9 months (CI 10.1, NE).
---------------------------------------------------------------------------

    \320\ Dreyling M, et al. Phosphatidylinositol 3-kinase 
inhibition by copanlisib in relapsed or refractory indolent 
lymphoma. J. Clin. Oncol. 2017; 35:3898-3905.
---------------------------------------------------------------------------

    To support the assertion that monsunetuzumab is efficacious in 
high-risk subgroups and in patients with prior systemic therapies, the 
applicant pointed to a CR of 74% and ORR of 85% among patients who have 
had 2 prior therapies (n=34), and a CR of 52% and ORR of 77% among 
patients who have had >3 prior therapies (n=56).\321\ According to the 
applicant, mosunetuzumab demonstrated responses for FL patients who 
experience progression of disease within 2 years of initial 
chemoimmunotherapy (POD24) (N=47, CR =57% and ORR = 85%) and those who 
were not POD24 (N=43, CR = 63%,ORR=74%). The applicant also asserted 
that mosunetuzumab demonstrated efficacy for patients who are 
refractory to their last prior therapy (N=62, CR =52% and ORR = 77%) 
and those who were not refractory (N=28, CR =79% and ORR= 86%). The 
applicant asserted that mosunetuzumab demonstrated efficacy for 
patients who are double refractory to any prior aCD20 therapy + 
alkylator therapy (N=48, CR =50% and ORR =71%) and those who were not 
double refractory to any prior aCD20 therapy + alkylator therapy (N=42, 
CR = 71% and ORR =71%). Lastly, the applicant asserted that 
mosunetuzumab demonstrated efficacy for elderly patients (> 65 years) 
(N=30, CR of 70% and ORR = 87%).
---------------------------------------------------------------------------

    \321\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
---------------------------------------------------------------------------

    To support the assertion that mosunetuzumab offers a manageable 
safety profile with fewer discontinuations or treatment-ending 
toxicities when compared to PI3K inhibitors, as well as a low rate of 
CRS and neurotoxicity when compared to CAR T-cell therapies, the 
applicant again cited data from the Budde et al. pivotal Phase II 
trial, in which 83 patients had mosunetuzumab-related adverse events. 
The most common were CRS, fatigue, pyrexia, pruritus, neutropenia, 
hypophosphatemia, and headache. None of the mosunetuzumab-related 
adverse events were fatal; however, 30 were described as serious and 2 
led to the discontinuation of mosunetuzumab. The applicant also cited 
the Budde et al. article to support features of access to treatment, 
wide availability, off-the-shelf therapy, potential for administration 
without mandatory hospitalization, fixed treatment duration, and no 
requirement of lymphodepleting chemotherapy. The applicant asserted 
that mosunetuzumab will be immediately available for patients and 
avoids the ex-vivo T-cell manipulation and the resulting delay in 
treatment that may be prohibitive in patients with rapidly progressing 
disease.
    According to the applicant, while the therapies used in the 
treatment of r/r FL have not been tested in a head-to-head trial, when 
looking at the independent results in the treatment of patients with r/
r FL after >=2 prior systemic therapies, the CR rate and ORR achieved 
by mosunetuzumab (N=90, CR=60% and ORR=80%) are greater than those for 
the PI3K and EZH2 inhibitors (N=72, CR=6% and ORR=54%) and are 
approaching the response rates observed with CAR T-cell therapy (N=84, 
CR= 80% and ORR =94%).\322\ The applicant states, compared to the CAR 
T-cell therapy axicabtagene ciloleucel, CRS events reported for 
mosunetuzumab were less frequent and less severe, and that the 
management of CRS in patients treated with mosunetuzumab enabled more 
than 95% of affected patients to continue therapy and potentially 
benefit from its efficacy.\323\
---------------------------------------------------------------------------

    \322\ Jacobson C, Chavez JC, Sehgal AR, et al. Primary analysis 
of zuma-5: A phase 2 study of axicabtagene ciloleucel (axi-cel) in 
patients with relapsed/refractory (R/R) indolent non-hodgkin 
lymphoma (iNHL). Blood. 2020; 136(Supplement 1):40-41. doi:10.1182/
blood-2020-136834.
    \323\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
---------------------------------------------------------------------------

    According to the applicant, compared to axicabtagene ciloleucel, 
which the applicant asserts is only available at authorized treatment 
centers, mosunetuzumab may potentially be available in community 
clinics and hospital-based outpatient departments (HOPDs) with the 
potential for AEs that can be treated at local hospitals. Therefore, 
according to the applicant, mosunetuzumab is not expected to present 
significant barriers for widespread implementation of emerging cellular 
therapies such as CAR T-cell. In addition, the applicant stated that 
since mosunetuzumab may potentially be administered in a local 
community setting with no mandatory hospitalization, those unable to 
travel may still obtain treatment. The applicant states mosunetuzumab 
is an immediately available, off-the-shelf therapy, enabling critically 
ill patients with urgent need of treatment access to the drug without 
delay administered as a fixed treatment duration regimen.
    To support the claim that mosunetuzumab improves clinical outcomes, 
the applicant cited data from the Budde et al. pivotal Phase II trial 
of mosunetuzumab. The applicant stated that mosunetuzumab showed a 
complete response (CR) of 60% \324\ as compared to 14% for historical 
control,\325\ 1.2% for duvelisib,\326\ 6% for P13k,\327\ 20.2% for 
copanlisib,\328\ 5.1% for umbralisib,\329\ and 6% for idelalisib.\330\
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    \324\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
    \325\ Dreyling M, et al. Phosphatidylinositol 3-kinase 
inhibition by copanlisib in relapsed or refractory indolent 
lymphoma. J. Clin. Oncol. 2017; 35:3898-3905.
    \326\ Flinn IW, Miller CB, Ardeshna KM, et al. DYNAMO: A Phase 
II Study of Duvelisib (IPI-145) in Patients With Refractory Indolent 
Non-Hodgkin Lymphoma [published correction appears in J Clin Oncol. 
2019 Jun 1;37(16):1448]. J Clin Oncol. 2019; 37(11):912-922. 
doi:10.1200/JCO.18.00915.
    \327\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
    \328\ Dreyling M, Santoro A, Mollica L, et al. Long-term safety 
and efficacy of the PI3K inhibitor copanlisib in patients with 
relapsed or refractory indolent lymphoma: 2-year follow-up of the 
CHRONOS-1 study. Am J Hematol. 2020; 95(4):362-371. doi:10.1002/
ajh.25711.
    \329\ Fowler NH, Samaniego F, Jurczak W, et al. Umbralisib, a 
Dual PI3K[delta]/CK1[egr] Inhibitor in Patients With Relapsed or 
Refractory Indolent Lymphoma. J Clin Oncol. 2021; 39(15):1609-1618. 
doi:10.1200/JCO.20.03433.
    \330\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.

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

[[Page 28273]]

The applicant stated that mosunetuzumab showed an ORR of 80% \331\ as 
compared to 42.2% for duvelisib,\332\ 54% for P13k,\333\ 58.7% for 
copanlisib,\334\ 45.3% for umbralisib,\335\ and 54.0% for 
idelalisib.\336\ The applicant stated that mosunetuzumab showed an mDOR 
of 22.8 months \337\ as compared to 10.0 months for duvelisib,\338\ 
12.5 months for P13k,\339\ 14.1 months for copanlisib,\340\ 11.1 months 
for umbralisib,\341\ and 12.5 months for idelalisib.\342\ According to 
the applicant, while the mDOR for mosunetuzumab is still maturing, the 
estimate of patients who remain in remission at 12 months compares 
favorably with mDORs ranging from 10-13 months for therapies under 
accelerated approval to treat patients with r/r FL after >=2 prior 
systemic therapies.
---------------------------------------------------------------------------

    \331\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
    \332\ Flinn IW, Miller CB, Ardeshna KM, et al. DYNAMO: A Phase 
II Study of Duvelisib (IPI-145) in Patients With Refractory Indolent 
Non-Hodgkin Lymphoma [published correction appears in J Clin Oncol. 
2019 Jun 1;37(16):1448]. J Clin Oncol. 2019; 37(11):912-922. 
doi:10.1200/JCO.18.00915.
    \333\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
    \334\ Dreyling M, Santoro A, Mollica L, et al. Long-term safety 
and efficacy of the PI3K inhibitor copanlisib in patients with 
relapsed or refractory indolent lymphoma: 2-year follow-up of the 
CHRONOS-1 study. Am J Hematol. 2020; 95(4):362-371. doi:10.1002/
ajh.25711.
    \335\ Fowler NH, Samaniego F, Jurczak W, et al. Umbralisib, a 
Dual PI3K[delta]/CK1[egr] Inhibitor in Patients With Relapsed or 
Refractory Indolent Lymphoma. J Clin Oncol. 2021; 39(15):1609-1618. 
doi:10.1200/JCO.20.03433.
    \336\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
    \337\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
    \338\ Flinn IW, Miller CB, Ardeshna KM, et al. DYNAMO: A Phase 
II Study of Duvelisib (IPI-145) in Patients with Refractory Indolent 
Non-Hodgkin Lymphoma [published correction appears in J Clin Oncol. 
2019 Jun 1;37(16):1448]. J Clin Oncol. 2019; 37(11):912-922. 
doi:10.1200/JCO.18.00915.
    \339\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
    \340\ Dreyling M, Santoro A, Mollica L, et al. Long-term safety 
and efficacy of the PI3K inhibitor copanlisib in patients with 
relapsed or refractory indolent lymphoma: 2-year follow-up of the 
CHRONOS-1 study. Am J Hematol. 2020; 95(4):362-371. doi:10.1002/
ajh.25711.
    \341\ Fowler NH, Samaniego F, Jurczak W, et al. Umbralisib, a 
Dual PI3K[delta]/CK1[egr] Inhibitor in Patients With Relapsed or 
Refractory Indolent Lymphoma. J Clin Oncol. 2021; 39(15):1609-1618. 
doi:10.1200/JCO.20.03433.
    \342\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
---------------------------------------------------------------------------

    According to the applicant, the overall safety profile of 
mosunetuzumab appears manageable with no unexpected safety signals, 
considering the advanced nature of the disease and the heavily 
pretreated patient population under study. The applicant asserted that 
the tolerability of mosunetuzumab is evident by the lack of mandatory 
hospitalization, the low proportion of patients who discontinue 
mosunetuzumab due to AEs, and the ability to adequately manage and 
resolve AEs. As an example, the applicant states, CRS events, as the 
most common AE, were generally low-grade (Gr 1 or 2), mostly confined 
to cycle 1, manageable, and resolved after a median duration of three 
days.\343\ According to the applicant, dose interruptions generally do 
not prevent patients continuing to receive their planned mosunetuzumab 
dose for most of the duration of treatment.
---------------------------------------------------------------------------

    \343\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
---------------------------------------------------------------------------

    To support the claim that mosunetuzumab improves clinical outcomes 
related to safety, the applicant asserted that mosunetuzumab has a 
manageable safety profile with grade 3/4 AEs at 51.1%, SAEs at 33.3% 
and no grade 5 (fatal) AEs.\344\ According to the applicant, 
mosunetuzumab had fewer discontinuations of treatment at 4.4% as 
compared to idelalisib at 20.0%,\345\ copanlisib at 21.1%,\346\ 
duvelisib at 31.0%,\347\ umbralisib at 14.9% \348\ and EZH2 inhibitors 
at 8.0%.\349\ According to the applicant, mosunetuzumab has a lower 
rate of CRS and severe neurotoxicity in comparison to CAR T-cell 
therapy as evidenced by a CRS adverse event rate of any grade at 44.0% 
compared to 99% for axicabtagene ciloleucel.350 351
---------------------------------------------------------------------------

    \344\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
    \345\ Gopal AK, Kahl BS, de Vos S, et al. PI3K[delta] inhibition 
by idelalisib in patients with relapsed indolent lymphoma. N Engl J 
Med. 2014; 370(11):1008-1018. doi:10.1056/NEJMoa1314583.
    \346\ Dreyling M, Santoro A, Mollica L, et al. Long-Term 
Efficacy and Safety from the Copanlisib CHRONOS-1 Study in Patients 
with Relapsed or Refractory Indolent B-Cell Lymphoma. Blood. 2018; 
132:1595. doi:10.1182/blood-2018-99-114842.
    \347\ Flinn IW, Miller CB, Ardeshna KM, et al. DYNAMO: A Phase 
II Study of Duvelisib (IPI-145) in Patients with Refractory Indolent 
Non-Hodgkin Lymphoma [published correction appears in J Clin Oncol. 
2019 Jun 1;37(16):1448]. J Clin Oncol. 2019; 37(11):912-922. 
doi:10.1200/JCO.18.00915.
    \348\ Fowler NH, Samaniego F, Jurczak W, et al. Umbralisib, a 
Dual PI3K[delta]/CK1[egr] Inhibitor in Patients with Relapsed or 
Refractory Indolent Lymphoma. J Clin Oncol. 2021; 39(15):1609-1618. 
doi:10.1200/JCO.20.03433.
    \349\ Morschhauser F, Tilly H, Chaidos A, et al. Tazemetostat 
for patients with relapsed or refractory follicular lymphoma: An 
open-label, single-arm, multicentre, phase 2 trial. Lancet Oncol. 
2020; 21(11):1433-1442. doi:10.1016/S1470-2045(20)30441-1.
    \350\ Budde LE, et al. Mosunetuzumab Monotherapy is an Effective 
and Well-Tolerated Treatment Option for Patients with Relapsed/
Refractory (R/R) Follicular Lymphoma (FL) who have Received >=2 
Prior Lines of Therapy: Pivotal Results from a Phase I/II Study. ASH 
Presentation. 2021.
    \351\ Jacobson C, Chavez JC, Sehgal AR, et al. Primary analysis 
of zuma-5: A phase 2 study of axicabtagene ciloleucel (axi-cel) in 
patients with relapsed/refractory (R/R) indolent non-hodgkin 
lymphoma (iNHL). Blood. 2020; 136(Supplement 1):40-41. doi:10.1182/
blood-2020-136834.
---------------------------------------------------------------------------

    The applicant summarized that fixed-duration mosunetuzumab 
monotherapy results in high response rates and durable disease control 
with a tolerable safety profile in heavily pretreated, multiply 
relapsed patients with FL, including known high-risk subgroups. 
According to the applicant, mosunetuzumab offers a new treatment option 
with a novel mechanism of action and demonstrates clinically meaningful 
advantages over available therapies for the treatment of patients with 
r/r FL who have received >=2 prior therapies, a patient population with 
a high unmet medical need for which novel treatments are needed. The 
applicant asserted that the benefit-risk assessment of mosunetuzumab is 
considered to be positive based on the high unmet need in this disease 
setting and the compelling results from the Budde et.al. study compared 
to available therapies, in particular the complete response rates and 
durable remissions observed with current study follow-up. The applicant 
asserted that mosunetuzumab demonstrates high clinical efficacy and 
tolerability in 3L+ r/r FL and is a substantial clinical improvement. 
According to the applicant it is the first T-cell-engaging bispecific 
antibody to demonstrate clinically meaningful outcomes for patients 
with r/r FL who have received >=2 prior lines of therapy in the pivotal 
Phase II setting, and offers potentially promising off-the-shelf, 
outpatient therapy.
    After review of the information provided by the applicant, we have 
the following concerns regarding whether

[[Page 28274]]

mosunetuzumab meets the substantial clinical improvement criterion. We 
note that the applicant provided the abstract for one single-arm, phase 
II trial of 90 patients to support all of its claims of substantial 
clinical improvement. The applicant compared outcomes of the phase II 
trial with mosunetuzumab to outcomes, including CR and ORR, from 
background studies of other technologies. However, we note limitations 
in comparing to rates found in other clinical trials that were 
conducted in earlier time periods and under different circumstances of 
patient enrollment and treatment options. Additionally, the historical 
rates were compared directly to those from mosunetuzumab, without more 
detailed adjustment for patient characteristics. As an example, the 
applicant compared rates of AEs to NHL patients in trials for 
idelalisib, copanlisib, and duvelisib. In those studies, FL subtype 
data was not available for direct comparison and we are concerned that 
there may be potential for selection bias. Without a direct comparison 
of outcomes between these therapies, we are concerned as to whether the 
differences in outcomes such as CR, ORR, mDOR, AEs and treatment 
discontinuation identified by the applicant translate to clinically 
meaningful differences or improvements for patients treated with 
mosunetuzumab as compared to historical rates for other treatments. In 
addition, durability of response is still maturing per the applicant, 
and we would appreciate additional information regarding treatment 
durability when available. We note that the applicant stated that 
mosunetuzumab has a lower rate of CRS and severe neurotoxicity in 
comparison to CAR T-cell therapy as evidenced by a CRS adverse event 
rate of any grade at 44.0% compared to 99% for axicabtagene ciloleucel. 
However, the study provided by the applicant to support this claim, 
Jacobson et.al., referenced an any-grade AE rate of 99% for 
axicabtagene ciloleucel and did not include a value for any-grade CRS 
for axicabtagene ciloleucel. We would appreciate further clarification 
of this claim. Lastly, while we understand that there may be potential 
benefits related to mosunetuzumab potentially being available in 
community clinics and HOPDs, 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 mosunetuzumab 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 
mosunetuzumab.
g. Narsoplimab
    The Omeros Corporation submitted an application for new technology 
add-on payments for narsoplimab for FY 2023. Narsoplimab is a fully 
human monoclonal antibody for the treatment of hematopoietic stem cell 
transplantation-associated thrombotic microangiopathy (HSCT-TMA), also 
known as transplant-associated thrombotic microangiopathy (TA-TMA).
    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 HSCT-TMA. We note that the Omeros Corporation 
previously submitted an application for new technology add-on payments 
for narsoplimab for FY 2022, as summarized in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25282 through 25286), that it withdrew prior to 
the issuance of the FY 2022 IPPS/LTCH PPS final rule (86 FR 44979).
    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.\352\ 
\353\ \354\ 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.\355\ However, according to the applicant, the withdrawal of 
immunosuppressive therapies and ongoing monitoring for resolution of 
TMA symptoms has been determined to be ineffective.\356\ The applicant 
stated that there are multiple off-label treatments for HSCT-TMA which 
have either not been reviewed by 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.\357\ 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; \358\ (2) eculizumab is a C5 inhibitor that blocks activation of 
the terminal cascade of complement,\359\ the use of which is 
constrained by lack of efficacy and

[[Page 28275]]

safety evaluations by FDA \360\ and associated increased susceptibility 
to infections; 361 362 (3) defibrotide (Defitelio[supreg]), 
an oligonucleotide mixture with profibrinolytic properties whose 
mechanism of action has not been fully elucidated \363\ is not approved 
by 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,\364\ is not approved by 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 FDA for the treatment 
of HSCT-TMA.\365\
---------------------------------------------------------------------------

    \352\ Gavriilaki, E et al. Transplant-associated thrombotic 
microangiopathy: Opening Pandora's box. Bone Marrow Transplantation 
(2017) 52, 1355-1360.
    \353\ 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.
    \354\ Rosenthal, J Hematopoietic cell transplantation-associated 
thrombotic microangiopathy: A review of pathophysiology, diagnosis, 
and treatment. Journal of Blood Medicine 2016:7 181-186.
    \355\ Khosla J et al. Hematopoietic stem cell transplant-
associated thrombotic microangiopathy: Current paradigm and novel 
therapies. Bone Marrow Transplant. 2018; 53(2):129-137.
    \356\ 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.
    \357\ 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.
    \358\ 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).
    \359\ FDA. (2019, June). Soliris Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/125166s431lbl.pdf.
    \360\ 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.
    \361\ 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.
    \362\ Khosla J et al. Hematopoietic stem cell transplant-
associated thrombotic microangiopathy: Current paradigm and novel 
therapies. Bone Marrow Transplant. 2018; 53(2):129-137.
    \363\ FDA. (2016, March). Defitelio Prescribing Information. 
Retrieved from Highlights of Prescribing Information: https://www.accessdata.fda.gov/drugsatfdadocs/label/2016/208114lbl.pdf 
Defitelio PI. 3/2016.
    \364\ 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.
    \365\ 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 FDA has accepted the Biologics License Application 
(BLA) for narsoplimab for the treatment of HSCT-TMA with a PDUFA date 
of October 17, 2021. The applicant stated that as of November 2021 they 
have received a Complete Response Letter (CRL) from FDA regarding the 
BLA for narsoplimab. The applicant stated they intend to resubmit the 
pending application soon. According to the applicant, narsoplimab has 
received Orphan Drug designation, Breakthrough Therapy Designation, and 
Priority Review. The applicant stated that the recommended dosage of 
narsoplimab is 4 mg/kg given as a 30-minute intravenous infusion (up to 
a maximum of 370 mg per infusion) once weekly. The applicant stated 
that effective October 1, 2021, the following ICD-10-PCS codes may be 
used to uniquely describe procedures involving the use of narsoplimab: 
XW03357 (Introduction of narsoplimab monoclonal antibody into 
peripheral vein, percutaneous approach, new technology group 7) and 
XW04357 (Introduction of narsoplimab monoclonal antibody into central 
vein, percutaneous approach, new technology group 7). The applicant 
stated that effective October 1, 2021, the following ICD-10-CM code is 
used to identify the indication of narsoplimab: M31.11 (Hematopoietic 
stem cell transplant-associated thrombotic microangiopathy (HSCT-TMA)).
    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 
which inhibits the key effector enzyme of the lectin pathway of 
complement, MASP-2, provides an upstream (relative to other complement 
inhibitors) and targeted effect inhibiting complement-mediated 
inflammation and coagulation while leaving fully intact the alternative 
and classical pathways to fight infection. The applicant stated that 
narsoplimab binds with high affinity and specificity to, and blocks, 
MASP-2, the key effector enzyme of the lectin pathway of complement, 
inhibiting the inflammatory and pro-thrombotic responses to endothelial 
injury found in HSCT-TMA.366 367 The applicant stated that 
although all pathways of complement (lectin, alternative, and 
classical) result in production of pro-inflammatory anaphylatoxins and 
activation of membrane attack complex on targeted cells, each pathway 
is triggered in a unique manner.\368\
---------------------------------------------------------------------------

    \366\ 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.
    \367\ Kozarcanin, et al. 2016. ``The lectin complement pathway 
serine proteases (MASPs) represent a possible crossroad between the 
coagulation and complement systems in thromboinflammation''. Journal 
of Thrmobosis and Haemostasis. 14;531-545. DOI: 10.1111/jth.13208.
    \368\ Gavriilaki E, Brodsky RA. Complementopathies and precision 
medicine. J Clin Invest. 2020 May 1;130(5):2152-2163. doi: 10.1172/
JCI136094. PMID: 32310222; PMCID: PMC719
---------------------------------------------------------------------------

    According to the applicant, the lectin pathway of complement has a 
role that is different from the classical and alternative pathways in 
that it serves as a ``surveillance system'' responsible for the 
identification and removal of damaged host cells or microbes. The 
applicant asserted that upon host tissue injury or microbe exposure, 
lectins (MBLs and other pattern recognition molecules including 
ficolins and collections) recognize damage-associated molecular 
patterns (DAMPs) on the surface of injured cells or pathogen-associated 
molecular patterns on microbes, initiating the lectin 
cascade.369 370 371 372 According to the applicant, the 
alternative pathway is a signal amplification system that is 
consistently engaged at low levels through the presence of a small 
amount of autoactivated C3 in the blood, so-called ``C3 
tickover''.\373\ Lastly, the applicant stated the classical pathway is 
mainly responsible for the antigen-antibody innate immune response 
necessary to protect against infection and is activated by antibody-
antigen complexes recognized by complement component C1q.\374\
---------------------------------------------------------------------------

    \369\ Anders HJ, Schaefer L. Beyond tissue injury-damage-
associated molecular patterns, toll-like receptors, and 
inflammasomes also drive regeneration and fibrosis. J Am Soc 
Nephrol. 2014 Jul;25(7):1387-400. doi: 10.1681/ASN.2014010117. Epub 
2014 Apr 24. PMID: 24762401; PMCID: PMC407.
    \370\ Bohlson SS, O'Conner SD, Hulsebus HJ, et al. Complement, 
c1q, and c1q-related molecules regulate macrophage polarization. 
Front Immunol. 2014 Aug 21;5:402. doi: 10.3389/fimmu.2014.00402. 
PMID: 25191325; PMCID: PMC413.
    \371\ Eriksson O, Chiu J, Hogg PJ, et al. Thiol isomerase ERp57 
targets and modulates the lectin pathway of complement activation. J 
Biol Chem. 2019 Mar 29;294(13):4878-4888. doi: 10.1074/
jbc.RA118.006792. Epub 2019 Jan 22. PMID: 30670593; PMCID: PMC644.
    \372\ Farrar CA, Zhou W, Sacks SH. Role of the lectin complement 
pathway in kidney transplantation. Immunobiology. 2016 
Oct;221(10):1068-72. doi: 10.1016/j.imbio.2016.05.004. Epub 2016 May 
24. PMID: 27286.
    \373\ Barnum SR. Complement: A primer for the coming therapeutic 
revolution. Pharmacol Ther. 2017 Apr;172:63-72. doi: 10.1016/
j.pharmthera.2016.11.014. Epub 2016 Dec 1. PMID: 27914.
    \374\ Reid KB, Porter RR. Subunit composition and structure of 
subcomponent C1q of the first component of human complement. Biochem 
J. (1976) 155:19-23. doi: 10.1042/bj1550019.
---------------------------------------------------------------------------

    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.375 376 According to the

[[Page 28276]]

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.377 378 379 In addition, MASP-2 is activated by fibrin 
and activated platelets, further augmenting a procoagulant state.\380\ 
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 asserted that the mechanism of 
action of narsoplimab differs from that of the products occasionally 
used off label: Eculizumab, defibrotide sodium, rituximab, and 
vincristine.
---------------------------------------------------------------------------

    \375\ 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.
    \376\ 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.
    \377\ 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.
    \378\ Krarup, A et al. Simultaneous Activation of Complement and 
Coagulation by MBLAssociated Serine Protease 2. 2007. PLoS ONE 2(7): 
e623.
    \379\ Gulla, KC et al. Activation of mannan-binding lectin-
associated serine proteases leads to generation of a fibrin clot. 
Immunology, 2009. 129, 482-495.
    \380\ 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/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 HSCT-TMA, a serious multi-factorial 
syndrome for which no current FDA-approved technology exists. The 
applicant asserted that HSCT-TMA is a distinctly different TMA 
characterized by endothelial injury and microvascular thrombosis caused 
by pre-HSCT conditioning regimens and exposure to immunosuppressants 
and is further aggravated by potential complications of HSCT including 
GVHD and infections.
    The applicant next differentiated between thrombotic 
microangiopathies (TMAs) and HSCT-TMA. According to the applicant, TMAs 
are a group of disorders with hallmark features of thrombocytopenia, 
microangiopathic hemolytic anemia (MAHA), and end organ damage. The 
applicant asserted that two specific TMAs, atypical hemolytic uremic 
syndrome (aHUS) and thrombotic thrombocytopenic purpura (TTP), exhibit 
clinical presentations similar to HSCT-TMA; however, their underlying 
mechanism set their diagnosis and treatment apart from that of HSCT-
TMA. The applicant stated that HSCT-TMA is a distinct TMA arising from 
treatment and complications of HSCT, diagnosis of which requires a 
constellation of findings. According to the applicant HSCT-TMA is a 
distinctive endothelial injury syndrome (EIS) commonly associated with 
transplant conditioning (chemotherapy and total body irradiation), 
transplant complications such as infection and GVHD, and 
immunosuppressive agents (CNI and mTOR inhibitors). The applicant 
asserted that there is no approved treatment for HSCT-TMA.\381\
---------------------------------------------------------------------------

    \381\ 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.
---------------------------------------------------------------------------

    In summary, the applicant believes that narsoplimab is not 
substantially similar to other currently available therapies and/or 
technologies and meets the ``newness'' criterion. Similar to our 
discussion in the FY 2022 IPPS/LTCH PPS final rule (86 FR 25283-25284), 
we note that the applicant asserted 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 used the FY 2019 MedPAR inpatient claims data 
file released with the FY 2022 IPPS proposed rule 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. The applicant stated that given the 
nature of HSCT-TMA, patient claims map to many MS-DRGs. The applicant 
identified a total of 27 MS-DRGs with fewer than 11 patients in any one 
MS-DRG; the applicant stated the top four MS-DRGs by volume are 871 
(Septicemia or Severe Sepsis without MV >96 Hours with MCC), 919 
(Complications of Treatment with MCC), 546 (Connective Tissue Disorders 
with CC), and 545 (Connective Tissue Disorders with MCC). In the cost 
analysis, a total of 54 cases across 27 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 54 to 297 because 
all MS-DRGs had fewer than 11 claims.
    The applicant first calculated a case weighted threshold of $89,095 
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. Next the 
applicant calculated the average standardized charge per case using the 
FY 2022 IPPS/LTCH PPS final rule Impact file. The 4-year inflation 
factor of 1.281834 or 28.1834% was obtained from the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45542) and applied to the average standardized 
charge per case.
    According to the applicant, because narsoplimab has not yet 
received FDA approval, the price has not yet been established. 
Therefore, the applicant did not include the charges for the new 
technology in the cost analysis. Next, the applicant calculated the 
final inflated average case-weighted standardized charge per case of 
$508,855, which exceeded the average

[[Page 28277]]

case-weighted threshold amount of $76,739.
    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 because it offers a treatment 
option for a patient population unresponsive to currently available 
treatments due to filling an unmet need for patients with HSCT-TMA 
where supportive care and/or off-label therapies have been ineffective. 
The applicant also asserted that narsoplimab has demonstrated a 
substantial clinical improvement in the treatment of HSCT-TMA in the 
clinical trial setting and has demonstrated substantial improvement in 
TMA complete response.
    With respect to the assertion that narsoplimab fills an unmet need, 
the applicant stated that FDA awarded narsoplimab Breakthrough Therapy 
designation for the treatment of patients with HSCT-TMA who have 
persistent TMA despite modification of immunosuppressive therapy and if 
approved by 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 as 
demonstrated in the clinical trial setting, the applicant described the 
pivotal single-arm, open label trial OMS721-TMA-001 which included a 
high-risk sample (n=28) including patients with persistent TMA 
following calcineurin inhibitors (CNI) modification and other 
transplant features or complications such as GVHD, mismatched 
transplants, female-to-male transplants, and multiple organ 
involvement. According to the applicant, the study design allowed 
evaluation of patients at high risk for poor outcomes, including 
mortality.382 383 384 385 386 387 According to the 
applicant, 28 patients with HSCT-TMA received narsoplimab intravenously 
once weekly for four to eight weeks with an eight-week follow-up 
period. The applicant stated the primary end point of the study was a 
response defined by improvements in both TMA laboratory markers (LDH 
and platelet count) and clinical status (improvement in organ function 
[renal, pulmonary, gastrointestinal, or neurological] or freedom from 
transfusion). According to the applicant, patients had multiple risk 
factors for poor outcomes at baseline, including significant infection 
(85.7%), renal dysfunction (75%), GVHD (67.9%), neurological 
dysfunction (57.1%), multiple organ involvement (50%), and pulmonary 
dysfunction (17.9%). Because the primary response endpoint is novel, 
the applicant asserted that historical response data using the endpoint 
are not available.
---------------------------------------------------------------------------

    \382\ 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.
    \383\ Rambaldi, A et al. ``Narsoplimab (OMS721) for the 
Treatment of Adult Hematopoietic Stem Cell TransplantAssociated 
Thrombotic Microangiopat hy.'' European Hematology Association., 
June 12, 2020; Abstract S2626.
    \384\ Rambaldi A, Claes K, Goh YT, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplantassociated thrombotic 
microangiopathy (HSCT-TMA): Subgroup analyses.'' Abstracts from the 
47th Annual Meeting of the;
    \385\ Khaled SK, Boelens JJ, Cairo MS, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplantassociated thrombotic 
microangiopathy (HSCT-TMA).'' Transplantation and Cellular Therapy. 
2021;27(3):S24-S26. h
    \386\ Perales M, Cairo M, Duarte R, et al. ``Narsoplimab 
(OMS721) treatment contributes to improvements in organ function in 
adult patients with high-risk transplant associated thrombotic 
microangiopathy.'' Presented at: 26th European Hematology 
Association Congress; June 9-17, 2021. Oral presentation S241. 
https://library.ehaweb.org/eha/2021/eha2021-virtualcongress/324649/.
    \387\ Whitaker, Steve. OMS721-TMA-001. ``A Phase 2, 
Uncontrolled, Three-Stage, Dose-Escalation Cohort Study to Evaluate 
the Safety, Pharmacokinetics, Pharmacodynamics, Immunogenicity, and 
Clinical Activity of OMS721 in Adults with Thrombotic 
Microangiopathies''. October 12, 2018.
---------------------------------------------------------------------------

    According to the applicant, patients receiving narsoplimab in the 
full analysis set (FAS) (patients receiving at least 1 dose of 
narsoplimab) demonstrated a 61% complete response rate (17/28; 95% CI 
40.6% to 78.5%), and patients receiving per protocol dosing (>= 4 
doses) demonstrated a 74% complete response rate (17/23; 95% CI 51.6% 
to 89.8%).388 389 390 391 392 393 The applicant stated that 
the 100-day survival was demonstrated in 68% (19/28) of narsoplimab-
treated patients in the FAS, 83% (19/23) for patients receiving per 
protocol dosing, and 94% for patients determined to be complete 
responders (16/17). The applicant added that median overall survival 
for the full analysis population was demonstrated at 274 days (95% CI 
103, NE), 361 days (95% CI 176, NE) for the per protocol analysis, and 
median survival for the responder population was not reached (95% CI 
273, NE) because more than half of the patients were still alive. 
According to the applicant, similar populations described in the 
literature have demonstrated much shorter overall survival and much 
lower 100-day survival rates.
---------------------------------------------------------------------------

    \388\ 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.
    \389\ Rambaldi, A et al. ``Narsoplimab (OMS721)for the Treatment 
of Adult Hematopoietic Stem Cell TransplantAssociated Thrombotic 
Microangiopat hy.'' European Hematology Association., June 12, 2020; 
Abstract S2626.
    \390\ Rambaldi A, Claes K, Goh YT, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplantassociated thrombotic 
microangiopathy (HSCT-TMA): Subgroup analyses.'' Abstracts from the 
47th Annual Meeting of the European Society for Blood and Marrow 
Transplantation (EBMT). Bone Marrow Transplant. 2021;56:147-149. 
https://doi.org/10.1038/s41409-021-01342-6;
    \391\ Khaled SK, Boelens JJ, Cairo MS, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplantassociated thrombotic 
microangiopathy (HSCT-TMA).'' Transplantation and Cellular Therapy. 
2021;27(3):S24-S26.
    \392\ Perales M, Cairo M, Duarte R, et al. ``Narsoplimab 
(OMS721) treatment contributes to improvements in organ function in 
adult patients with high-risk transplant associated thrombotic 
microangiopathy.'' Presented at: 26th European Hematology 
Association Congress; June 9-17, 2021. Oral presentation S241. 
https://library.ehaweb.org/eha/2021/eha2021-virtualcongress/324649/.
    \393\ Whitaker, Steve. OMS721-TMA-001. ``A Phase 2, 
Uncontrolled, Three-Stage, Dose-Escalation Cohort Study to Evaluate 
the Safety, Pharmacokinetics, Pharmacodynamics, Immunogenicity, and 
Clinical Activity of OMS721 in Adults with Thrombotic 
Microangiopathies''. October 12, 2018.
---------------------------------------------------------------------------

    Next the applicant addressed clinical laboratory markers, 
improvement in clinical status, and key secondary objectives. According 
to the applicant, statistically significant (p < 0.01) and clinically 
relevant improvements from baseline were observed in platelet count, 
LDH, and haptoglobin.394 395 396 397 398 399 The

[[Page 28278]]

applicant stated that platelet count increased from baseline over time. 
The applicant stated that LDH, an adverse predictor for HSCT outcomes, 
decreased from baseline with narsoplimab treatment, consistent with 
clinical improvement. The applicant stated that haptoglobin, a marker 
for hemolysis which is often decreased in HSCT-TMA, steadily increased 
from baseline with narsoplimab treatment. The applicant stated that 
hemoglobin also increased with narsoplimab treatment. According to the 
applicant, the response across all key laboratory parameters was rapid 
and progressive over time. The applicant noted that overall freedom 
from transfusion was 48% in the FAS and 55% in the Per-Protocol 
Analysis Set (PAS).
---------------------------------------------------------------------------

    \394\ 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;
    \395\ Rambaldi, A et al. ``Narsoplimab (OMS721) for the 
Treatment of Adult Hematopoietic Stem Cell TransplantAssociated 
Thrombotic Microangiopat hy.'' European Hematology Association., 
June 12, 2020; Abstract S2626.;
    \396\ Rambaldi A, Claes K, Goh YT, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplantassociated thrombotic 
microangiopathy (HSCT-TMA): Subgroup analyses.'' Abstracts from the 
47th Annual Meeting of the European Society for Blood and Marrow 
Transplantation (EBMT). Bone Marrow Transplant. 2021;56:147-149. 
https://doi.org/10.1038/s41409-021-01342-6;
    \397\ Khaled SK, Boelens JJ, Cairo MS, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplant-associated thrombotic 
microangiopathy (HSCT-TMA).'' Transplantation and Cellular Therapy. 
2021;27(3):S24-S26.
    \398\ Perales M, Cairo M, Duarte R, et al. ``Narsoplimab 
(OMS721) treatment contributes to improvements in organ function in 
adult patients with high-risk transplant associated thrombotic 
microangiopathy.'' Presented at: 26th European Hematology 
Association Congress; June 9-17, 2021. Oral presentation S241. 
https://library.ehaweb.org/eha/2021/eha2021-virtualcongress/324649/.
    \399\ Whitaker, Steve. OMS721-TMA-001. ``A Phase 2, 
Uncontrolled, Three-Stage, Dose-Escalation Cohort Study to Evaluate 
the Safety, Pharmacokinetics, Pharmacodynamics, Immunogenicity, and 
Clinical Activity of OMS721 in Adults with Thrombotic 
Microangiopathies''. October 12, 2018.
---------------------------------------------------------------------------

    The applicant also asserted that narsoplimab was well-tolerated in 
this very sick population with multiple comorbidities. 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 GVHD, which according to the applicant are causes of 
death common in patients with HSCT. The applicant asserted that across 
all clinical trials, including trials in aHUS and IgA nephropathy 
(IgAN), with narsoplimab, no safety signal of concern has been 
observed.
    With respect to the claim that use of narsoplimab significantly 
improves clinical outcomes relative to existing treatments, the 
applicant stated that there is a lack of effective treatment options 
for TMA following HSCT. Per the applicant, in order to provide a 
comparison group for the HSCT-TMA patients treated in the narsoplimab 
study, a protocol-driven systematic (retrospective) literature review 
was conducted evaluating clinical outcomes in adult patients with HSCT-
TMA following allogeneic transplant. The applicant stated that 
publications dating from 2000-2020 which described the clinical course 
and outcomes of HSCT-TMA patients were identified by electronic 
database search (PubMed) using pre-specified search terms. The 
applicant stated the literature search identified 459 papers of which 
25 manuscripts describing 149 patient outcomes in HSCT-TMA were 
identified. The applicant stated that to facilitate data comparisons 
with the narsoplimab clinical trial, random effects logistic regression 
and propensity score analyses were performed. The applicant stated that 
they examined various imputation methods to ensure the robustness of 
findings and then evaluated the following: Age and days from HSCT to 
TMA diagnosis as continuous variables, and GVHD, infection, renal 
dysfunction, and neurologic dysfunction as categorical variables.
    According to the applicant, where only a minority of patients 
responded to treatment in the literature review, a majority of patients 
responded to narsoplimab. The applicant asserted that the comparison 
was conservative and biased toward the literature group, since the 
endpoint used in the narsoplimab pivotal trial is novel and rigorous, 
requiring a composite of laboratory and clinical measures, and none of 
the literature studies used this response endpoint. According to the 
applicant, many of the studies identified in the literature review used 
only one or two components of the narsoplimab primary endpoint or 
simply reported ``response''. According to the applicant, narsoplimab-
treated patients had an overall response rate of 61% (95% CI 40.6% to 
78.5%) for the full analysis set as compared to the literature-reported 
results with 23.3% (95% CI, 15.1% to 34.2%) response. According to the 
applicant, 62.5% of narsoplimab-treated patients had significant 
infection and responded to treatment as compared to 23.9% of the 
literature review dataset. The applicant asserted that propensity score 
analyses and sensitivity analyses, including all 4 imputation methods, 
comparing response rates of the narsoplimab-treated patients to those 
in the literature-based group, yielded odds ratios (ORs) that are all 
greater than 1 (2- to 8-fold and, with few exceptions, p-values < 
0.05), supporting superiority of narsoplimab. The applicant concluded 
that the results demonstrate that the response observed with 
narsoplimab is a marked deviation from the natural history of HSCT-TMA, 
and is especially notable given that the patients in the narsoplimab 
pivotal trial were at high risk for poor outcomes, yet the majority 
achieved a complete response with significant improvement in laboratory 
markers and in clinical status.
    In support of the application, the applicant submitted three new 
references in the form of abstracts.400 401 402 The first 
abstract discusses results from the single-arm open-label pivotal trial 
(NCT02222545) (n=28) involving adult TA-TMA patients.\403\ The authors 
stated that patients were at high risk for poor outcomes and had 
multiple comorbidities. Patients received 6.3 doses on average (2 to 8 
range) of narsoplimab for a median duration of treatment of 8 weeks. 
The authors discussed many of the outcomes discussed by the applicant 
previously adding that six patients died during the core study period: 
1 of septic shock, 2 of progressive AML, 2 of neutropenic sepsis, and 1 
of GVHD and TMA. The authors stated that these deaths occurred 3-42 
days following the last narsoplimab dose. The second and third 
abstracts also discuss the single-arm open-label pivotal trial 
(NCT02222545) (n=28) involving adult TA-TMA patients, as previously 
described.404 405
---------------------------------------------------------------------------

    \400\ Perales M, Cairo M, Duarte R, et al. ``Narsoplimab 
(OMS721) treatment contributes to improvements in organ function in 
adult patients with high-risk transplant-associated thrombotic 
microangiopathy.'' Presented at: 26th European Hematology 
Association Congress; June 9-17, 2021. Oral presentation S241. 
https://library.ehaweb.org/eha/2021/eha2021-virtual-congress/324649/.
    \401\ Rambaldi A, Claes K, Goh YT, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplant-associated thrombotic 
microangiopathy (HSCT-TMA): Subgroup analyses.'' Abstracts from the 
47th Annual Meeting of the European Society for Blood and Marrow 
Transplantation (EBMT). Bone Marrow Transplant. 2021;56:147-149. 
https://doi.org/10.1038/s41409-021-01342-6.
    \402\ Khaled SK, Boelens JJ, Cairo MS, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplant-associated thrombotic 
microangiopathy (HSCT-TMA).'' Transplantation and Cellular Therapy. 
2021;27(3):S24-S26.
    \403\ Perales M, Cairo M, Duarte R, et al. ``Narsoplimab 
(OMS721) treatment contributes to improvements in organ function in 
adult patients with high-risk transplant-associated thrombotic 
microangiopathy.'' Presented at: 26th European Hematology 
Association Congress; June 9-17, 2021. Oral presentation S241. 
https://library.ehaweb.org/eha/2021/eha2021-virtual-congress/324649/.
    \404\ Rambaldi A, Claes K, Goh YT, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplant-associated thrombotic 
microangiopathy (HSCT-TMA): Subgroup analyses.'' Abstracts from the 
47th Annual Meeting of the European Society for Blood and Marrow 
Transplantation (EBMT). Bone Marrow Transplant. 2021;56:147-149. 
https://doi.org/10.1038/s41409-021-01342-6.
    \405\ Khaled SK, Boelens JJ, Cairo MS, et al. ``Narsoplimab 
(OMS721), a MASP-2 inhibitor, for the treatment of adult 
hematopoietic stem cell transplant-associated thrombotic 
microangiopathy (HSCT-TMA).'' Transplantation and Cellular Therapy. 
2021;27(3):S24-S26.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have

[[Page 28279]]

concerns with regard to the substantial clinical improvement criterion. 
As we noted in the FY 2022 IPPS/LTCH PPS proposed rule, first, the 
sample from which the applicant draws conclusions is small (sample size 
of pivotal trial 28, plus five case studies previously discussed in the 
FY 2022 proposed rule (86 FR 25285 through 25286)). We question whether 
the sample and these results are generalizable to the greater Medicare 
population.
    As we discussed in the FY 2022 IPPS/LTCH PPS proposed rule, with 
regard to methodological concerns, 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 note the applicant has in their current application provided 
some insight into how the historical control was evaluated in 
comparison to narsoplimab outcomes, as previously discussed. We 
appreciate the greater detail provided by the applicant but without 
information regarding how the systematic review was designed and 
performed, we question the appropriateness of the sample used to 
identify a historical comparator. We question whether this systematic 
review and analysis sufficiently establish differences between various 
studies and whether they are sufficient to show that the difference 
between outcomes is due to differences in treatments as opposed to 
study design, samples, and so forth.
    As we also noted in the FY 2022 IPPS/LTCH PPS proposed rule, the 
study 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; a historical control was only assessed in post hoc 
analyses and was not incorporated in the initial study design. 
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 note that the 
applicant stated that the trial's composite endpoint of laboratory and 
clinical measures is novel and rigorous, and has not been previously 
used in the literature. We would appreciate additional information on 
the clinical significance of this endpoint as compared to others in the 
literature referenced by the applicant, and whether the composite 
endpoint has been clinically validated and is demonstrative of durable 
clinical benefit. Specifically, we note that in some cases, measures 
used as indicators for patient improvement such as haptoglobin 
initially showed increases at early time points (for example, 1-10 
weeks) but began to decrease at later time points (for example, 13-15 
weeks).
    We are inviting public comments on whether narsoplimab 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 
narsoplimab.
h. Spesolimab
    Boehringer Ingelheim Pharmaceuticals, Inc. (BIPI), submitted an 
application for new technology add-on payments for spesolimab for FY 
2023. According to the applicant, spesolimab is a humanized 
antagonistic monoclonal immunoglobulin G1 antibody blocking human IL36R 
signaling currently under investigation for the treatment of flares in 
adult patients with generalized pustular psoriasis (GPP). The applicant 
stated that binding of spesolimab to IL36R prevents the subsequent 
activation of IL36R by cognate ligands (IL36 [alpha], [beta] and 
[gamma]) and downstream activation of pro-inflammatory and pro-fibrotic 
pathways. Per the applicant, genetic human studies have established a 
strong link between IL36R signaling and skin inflammation.
    According to the applicant, GPP is a rare, heterogeneous, and 
potentially life-threatening neutrophilic skin disease, with an 
estimated prevalence of 1/10,000 in the United States.\406\ The 
applicant noted that a flare entails widespread formation of pustules 
that may occur with or without systemic inflammation. Per the 
applicant, GPP causes significant morbidity and, in some cases, 
mortality; infectious, metabolic, cardiac, liver, respiratory, and 
neurological comorbidities have been reported.\407\ The applicant also 
stated that various factors have been reported to trigger a GPP flare, 
including pregnancy, severe injury, or viral and bacterial infections. 
Per the applicant, the use and subsequent withdrawal of systemic 
corticosteroids is a key contributing factor.408 409 410
---------------------------------------------------------------------------

    \406\ Strober B., Kotowsky N, Medeiros R., et al., Unmet Medical 
Needs in the Treatment and Management of Generalized Pustular 
Psoriasis Flares: Evidence from a Survey of Corrona Registry. 
Dermatologists Dermatol Ther (Heidelb) (2021) 11:529-541.
    \407\ Ibid.
    \408\ Zelickson BD, et al. Generalized Pustular Psoriasis. Arch 
Dermatol 1991;127:1339-1345.
    \409\ Choon SE, et al. Clinical profile, morbidity, and outcome 
of adult-onset generalized pustular psoriasis: Analysis of 102 cases 
seen in a tertiary hospital in Johor, Malaysia. Int J Dermatol 
2014;53:676-684.
    \410\ The applicant referred to a third citation here, as 
``Goiriz 2007,'' but we are unable to identify the citation based 
upon the information provided by the applicant.
---------------------------------------------------------------------------

    According to the applicant, GPP can be distinguished from plaque 
psoriasis based on clinical, pathologic, and genetic features in GPP. 
The applicant asserted that although there are shared pathways between 
GPP and plaque psoriasis, the IL-36 pathway is predominantly involved 
in the pathogenesis of GPP, while the IL-23 axis drives plaque 
psoriasis. Per the applicant, binding of spesolimab to IL36R prevents 
the subsequent activation of IL36R by cognate ligands (IL36 [alpha], 
[beta] and [gamma]) and downstream activation of pro-inflammatory and 
pro-fibrotic pathways. The applicant also stated that IL-36R signaling 
is differentiated from TNF-[alpha], integrin and IL-23 inhibitory 
pathways by directly and simultaneously blocking both inflammatory and 
pro-fibrotic pathways.
    The applicant stated that in the absence of an FDA-approved therapy 
specifically indicated for GPP, immunomodulatory therapies, including 
biologics, are used in the treatment of GPP based on clinical 
experience in patients with plaque psoriasis. The applicant further 
noted that there is limited evidence on the efficacy and safety of 
these therapies in the treatment of GPP. Per the applicant, due to the 
rarity of the disease, there are no high-quality clinical trials 
providing evidence for treatment options in GPP.411 412 The 
applicant also stated that the National Psoriasis Foundation treatment 
recommendations include cyclosporine, retinoids, infliximab and 
methotrexate as first-line therapies \413\ but that current treatments 
are associated with slow resolution of GPP flares, and complete 
clearance of

[[Page 28280]]

pustules and skin is not always achieved.\414\
---------------------------------------------------------------------------

    \411\ Robinson A, et al. Treatment of pustular psoriasis: From 
the Medical Board of the National Psoriasis Foundation. J Am Acad 
Dermatol 2012; 67:279-288.
    \412\ Choon et al. Study protocol of the global Effisayil 1 
Phase II, multicentre, randomised, double-blind, placebo-controlled 
trial of spesolimab in patients with generalized pustular psoriasis 
presenting with an acute flare. BMJ Open 2021; 11:e043666.
    \413\ Robinson A, et al. Treatment of pustular psoriasis: From 
the Medical Board of the National Psoriasis Foundation. J Am Acad 
Dermatol 2012; 67:279-288.
    \414\ Strober B, et al. Unmet medical needs in the treatment and 
management of generalized pustular psoriasis flares: Evidence from a 
survey of corrona registry dermatologists. Dermatol Ther (Heidelb) 
2021.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant is pursuing 
FDA approval of a Biologics License Application (BLA). We note that a 
December 15, 2021, press release indicates that FDA has accepted a BLA 
and granted Priority Review for spesolimab for the treatment of flares 
in patients with GPP.\415\ The applicant indicated that it expects to 
receive FDA approval prior to the July 1 deadline. According to the 
applicant, the product will be available on the market 1 week post FDA 
approval. According to the applicant, spesolimab is administered as a 
single 900 mg (2 x 450 mg/7.5 mL vials) intravenous infusion over 90 
minutes, and an additional intravenous 900 mg dose may be administered 
1 week after the initial dose if flare symptoms persist. According to 
the applicant, there are currently no ICD-10-PCS procedure codes to 
distinctly identify spesolimab. The applicant submitted a request for 
approval of a unique ICD-10-PCS code to identify cases involving the 
administration of spesolimab beginning in FY 2023.
---------------------------------------------------------------------------

    \415\ Boehringer Ingelheim, https://www.boehringer-ingelheim.us/press-release/us-fda-grants-priority-review-spesolimab-treatment-flares-patients-generalized. Accessed 1/18/2022.
---------------------------------------------------------------------------

    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 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 spesolimab does not use the same or similar 
mechanism of action when compared to an existing technology. The 
applicant stated that spesolimab inhibits IL-36R signaling which is 
differentiated from TNF-[alpha], integrin and IL-23 inhibitory pathways 
by directly and simultaneously blocking both inflammatory and pro-
fibrotic pathways. The applicant described first line therapies that 
include acitretin, cyclosporine, methotrexate, infliximab, oral 
prednisone, topical corticosteroids, topical calcipotriene, and 
etanercept. As second line, the applicant cited adalimumab, etanercept, 
psoralen and long-wave ultraviolet light A (PUVA), ultraviolet light B 
(UVB) phototherapy, topical corticosteroids, topical calcipotriene, 
topical tacrolimus, and infliximab. The applicant stated there is 
limited evidence on the efficacy and safety of these therapies in the 
treatment of GPP. The applicant reported that due to the rarity of the 
disease, there are no high-quality clinical trials providing evidence 
for treatment options in GPP.416 417
---------------------------------------------------------------------------

    \416\ Robinson A, et al. Treatment of pustular psoriasis: From 
the Medical Board of the National Psoriasis Foundation. J Am Acad 
Dermatol 2012; 67:279-288.
    \417\ Choon et al. Study protocol of the global Effisayil 1 
Phase II, multicentre, randomised, double-blind, placebo-controlled 
trial of spesolimab in patients with generalized pustular psoriasis 
presenting with an acute flare. BMJ Open 2021; 11:e043666.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that there is 
no MS-DRG for spesolimab. We note that the applicant also stated that 
spesolimab currently maps to the following MS-DRGs: 603 (Cellulitis 
without MCC), 607 (Minor Skin Disorders without MCC), 871 (Septicemia 
or Severe Sepsis without MV >96 Hours with MCC), and 872 (Septicemia or 
Severe Sepsis without MV >96 Hours without MCC) under the MS-DRG 
grouper for FY 2022.
    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 the clinical, pathological, 
and genetic features associated with GPP establish it as a distinct 
disease entity from plaque psoriasis, which is managed with existing 
therapies.
    In summary, the applicant asserted that spesolimab is not 
substantially similar to other currently available therapies and/or 
technologies because it does not use the same or similar mechanism of 
action, there is no MS-DRG, and the features of GPP establish it as a 
distinct disease entity from plaque psoriasis and that therefore, the 
technology meets the ``newness'' criterion. However, we have the 
following concerns with regard to the newness criterion. First, we note 
that the applicant stated that there are no FDA-approved therapies 
specifically indicated for GPP. However, we question whether there are 
any treatments that may be indicated for psoriasis generally that may 
therefore be considered an on-label use for subtypes of psoriasis such 
as GPP, and request additional information on any such treatments. We 
also note that while the applicant stated that spesolimab has no DRG to 
which it maps, the applicant also provided a list of four MS-DRGs that 
cases eligible for the use of the technology would map to, and we 
believe these are the same MS-DRGs to which other treatments for GPP 
would map.
    We are inviting public comments on whether spesolimab is 
substantially similar to existing technologies and whether spesolimab 
meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant first searched the FY 2019 MedPAR for 
cases representing patients who may be eligible for spesolimab. The 
applicant selected claims with a diagnosis code of L40.1 (Generalized 
pustular psoriasis) and limited the data to PPS hospitals. The 
applicant removed HMO cases, cases with total charges or covered 
charges less than zero, and cases with a length of stay of zero. After 
imputing a value of 11 cases for MS-DRGs with a case volume less than 
11, the applicant identified 101 claims mapping to 4 MS-DRGs under the 
MS-DRG grouper for FY 2022: MS-DRG 603 (Cellulitis without MCC), MS-DRG 
607 (Minor Skin Disorders without MCC), MS-DRG 871 (Septicemia or 
Severe Sepsis without MV >96 Hours with MCC), and MS-DRG 872 
(Septicemia or Severe Sepsis without MV >96 Hours without MCC).
    The applicant did not remove charges for prior technology as the 
applicant stated it did not believe that it was applicable for this 
product. The applicant standardized the charges and applied a 4-year 
inflation factor of 1.281834 based on the inflation factor used in the 
FY 2022 IPPS/LTCH PPS final rule and correction notice to calculate 
outlier threshold charges. The applicant then added charges for the new 
technology by dividing the cost of spesolimab by the national average 
CCR for drugs which is 0.187 from the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 44966). The applicant stated that the final inflated average 
case-weighted standardized charge per case of $359,404 exceeded the 
average case-weighted threshold amount of $41,595. Because the final 
inflated average case-weighted standardized charge per case exceeded 
the average case-weighted threshold amount, the applicant asserted that 
spesolimab meets the cost criterion.
    We note the applicant's statement that removing charges for prior 
technology was not applicable to spesolimab; however, the applicant did 
not provide

[[Page 28281]]

an explanation as to why. We would be interested in additional detail 
regarding the applicant's decision not to remove charges for prior 
technology. We invite public comment on whether spesolimab meets the 
cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that spesolimab represents a substantial clinical 
improvement over existing technologies because it offers a treatment 
option for a patient population unresponsive to, or ineligible for, 
currently available treatments and significantly improves clinical 
outcomes relative to services or technologies previously available.
    With respect to the claim that spesolimab offers a treatment option 
for a patient population unresponsive to, or ineligible for, currently 
available treatments, the applicant stated that there are no FDA-
approved therapies specifically indicated for GPP. The applicant 
further stated that current treatments are associated with slow 
resolution of GPP flares, and complete clearance of pustules and skin 
is not always achieved.\418\ In support of this claim, the applicant 
submitted a study describing a structured survey which was purposed to 
gauge unmet needs for GPP. The study results of the survey of 29 
dermatologists were published regarding the range and adequacy of GPP 
treatment options.\419\ Dermatologists were identified by the Corrona 
Psoriasis Registry as likely to be currently treating patients with 
GPP, with a history of having treated at least one patient in the 
Corrona Registry. The survey was made up of 28 multiple choice 
questions regarding GPP flares, diagnosis, and treatment options. The 
authors found that all surveyed dermatologists believed that pustules 
were necessary to diagnose a GPP flare. Most surveyed dermatologists 
responded that treatment options for all flare frequencies were 
adequate ``most'' (79%) or ``all'' (14%) of the time, and 83% reported 
that treatments for residual disease for all flare frequencies are 
adequate ``most of the time.'' According to the applicant, this survey 
established the need for new therapies. The applicant stated that while 
the study results suggest that moderately effective therapies may 
exist, the need for GPP-specific treatments remains.
---------------------------------------------------------------------------

    \418\ Strober B, et al. Unmet medical needs in the treatment and 
management of generalized pustular psoriasis flares: Evidence from a 
survey of corrona registry dermatologists. Dermatol Ther (Heidelb) 
2021.
    \419\ Ibid.
---------------------------------------------------------------------------

    With respect to the claim that spesolimab improves outcomes, the 
applicant restated that there are no FDA-approved therapies 
specifically indicated for GPP, current treatments are associated with 
slow resolution of GPP flares, and complete clearance of pustules and 
skin is not always achieved.\420\ The applicant also stated that 
spesolimab, as compared to placebo, leads to rapid pustular clearance 
and rapid skin clearance; clinically significant improvements in 
patient-reported pain, psoriasis symptoms, and fatigue; and significant 
decreases in markers of systemic inflammation. The applicant provided 
three data submissions in support of their claims of improved outcomes.
---------------------------------------------------------------------------

    \420\ Ibid.
---------------------------------------------------------------------------

    The applicant submitted a published letter to the editor describing 
a phase I, proof-of-concept trial in 7 patients who were given a single 
intravenous dose of spesolimab 10mg/kg and followed for 20 weeks, to 
establish the results of spesolimab in a study. The authors noted that 
most adverse events were mild or moderate in nature and that a 
Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) 
score of 0 or 1 (clear or almost clear skin) was achieved in five 
patients by week 1 and in all patients by week 4. Complete pustular 
clearance was achieved in three patients within 48 hours after 
treatment (n=3; 42.9%), in five patients by week 1 (n=5; 71.4%) and in 
six patients by week 2 (n=6; 85.7%).\421\ According to the applicant, 
this proof-of-concept study demonstrated that spesolimab could achieve 
clear or almost clear skin with no serious adverse effects.
---------------------------------------------------------------------------

    \421\ Bachelez H, et al. Inhibition of the Interleukin-36 
Pathway for the Treatment of Generalized Pustular Psoriasis. N Engl 
J Med 2019; 380:981-983.
---------------------------------------------------------------------------

    The applicant also submitted a published study protocol describing 
Effisayil-1, a phase 2 multicenter, randomized, placebo-controlled 
trial designed to support the use of spesolimab for GPP in a double-
blind study. The protocol aimed to randomize at least 51 patients with 
an acute GPP flare in 2:1 fashion for a single 900 mg intravenous dose 
of spesolimab or placebo. Inclusion criteria included patients with a 
GPPGA score 0 or 1 and documented history of GPP; or acute GPP with 
moderate to severe intensity flare; or first episode acute GPP with 
moderate to severe intensity with diagnosis to be confirmed 
retrospectively. According to the protocol, patients would be followed 
for up to 28 weeks and the primary endpoint would be achievement of 
GPPGA pustulation subscore of 0 (pustule clearance) at Week 1. A 
secondary endpoint of GPPGA score of 0 or 1 (clear or almost clear) at 
Week 1 would also be assessed. Patients not qualifying to enter the 
open label extension study would be followed for an additional 16 
weeks. In addition to photographs, exam, vitals, safety laboratory 
testing, the IL36RN mutation status would be determined for all 
patients. Finally, safety would be assessed along with data collection 
of blood and skin biopsies.\422\
---------------------------------------------------------------------------

    \422\ Choon et al. Study protocol of the global Effisayil 1 
Phase II, multicentre, randomised, double-blind, placebo-controlled 
trial of spesolimab in patients with generalized pustular psoriasis 
presenting with an acute flare. BMJ Open 2021; 11:e043666.
---------------------------------------------------------------------------

    Finally, the applicant summarized unpublished data from Effisayil-
1, described previously to demonstrate that spesolimab improves 
outcomes as compared to placebo.\423\ According to the applicant, 54.3% 
of the treatment arm (19/35) achieved pustule clearance, as assessed by 
GPPGA pustulation subscore one week after treatment, compared to 
approximately 5.6% (1/18) of patients in the placebo arm (p<0.001), 
demonstrating rapid pustular clearance. The applicant also noted a 
secondary endpoint of clear or almost clear skin one week after 
treatment. The applicant stated that spesolimab also demonstrated rapid 
skin clearance, with 42.9% (15/35) of the treatment arm, compared to 
11.1% (12/18) of patients treated with placebo (p=0.012) achieving 
clear or almost clear skin as indicated by a total GPPGA score of 0 or 
1 at week 1.
---------------------------------------------------------------------------

    \423\ Bachelez et al., in print.
---------------------------------------------------------------------------

    With respect to the claim that spesolimab improved patient-reported 
outcomes, the applicant stated that patients in the Effisayil-1 trial 
discussed previously used a visual analog scale to measure their pain. 
According to the applicant, a significantly greater reduction in pain 
was measured in patients receiving spesolimab at Week 4 as compared to 
those receiving placebo (p=0.001). In addition, the applicant stated 
that patients receiving spesolimab reported significantly greater 
reductions in psoriasis symptoms (including pain, redness, itching, and 
burning) as indicated by the psoriasis symptom scale (PSS) by Week 4 
(p=0.004). The applicant also noted significantly greater reductions in 
fatigue by the Functional Assessment of Chronic Illness Therapy (FACIT) 
scores in the spesolimab group as compared to placebo (p=0.001) at Week 
4.
    Lastly, the applicant stated that the Effisayil-1 study also 
demonstrated significant decreases in markers of systemic inflammation. 
According to the applicant, serum biomarker data

[[Page 28282]]

showed that treatment with spesolimab led to normalization of C-
reactive protein (CRP) and neutrophil values that had been above the 
upper limit of normal at baseline within 2 weeks for CRP and within 1 
week for neutrophils. The applicant further stated that this effect was 
sustained through to Week 12.
    After review of the information provided by the applicant, we have 
the following concerns regarding whether spesolimab meets the 
substantial clinical improvement criterion. We note that the results of 
the Effisayil-1 trial are not included in the application. As the 
applicant references the Effisayil-1 trial in support of its assertions 
regarding improved outcomes we are concerned that our analysis of the 
clinical benefit of spesolimab relies entirely on the applicant's 
summary of the unpublished trial. To the extent that Bachelez et al., 
matched to the previously published protocol, it does not appear that 
the unpublished study met the goal of recruiting 51 patients and 
therefore we question if the study was adequately powered. In addition, 
the patient demographics, excluded cases, and details of adverse events 
are unable to be determined. We therefore question the generalizability 
of the Effisayil-1 trial outcomes to the Medicare population.
    With regard to the Effisayil-1 protocol and the unpublished 
data,424 425 we note that the protocol is not designed to 
compare spesolimab to current treatment options. While the applicant 
states that spesolimab will be the first GPP treatment targeting the 
IL-36 pathway, we note that the applicant previously described other 
treatments that are available, which include TNF-[alpha] inhibitors, 
etanercept, and others. We also question whether there are any 
treatments that may be indicated for psoriasis generally that may 
therefore be considered an on-label use for subtypes of psoriasis such 
as GPP, as discussed previously. In addition, we note that the 
dermatology survey results supplied by the applicant seem to indicate 
that there is perceived efficacy in current treatments.\426\ Most of 
the surveyed dermatologists indicated that treatment options for all 
flare frequencies were adequate ``most'' (79%) or ``all'' (14%) of the 
time, and 83% reported that treatments for residual disease for all 
flare frequencies are adequate ``most of the time.'' Given this, we 
question whether placebo is the most appropriate comparator for 
spesolimab.
---------------------------------------------------------------------------

    \424\ Choon SE, et al. Clinical profile, morbidity, and outcome 
of adult-onset generalized pustular psoriasis: Analysis of 102 cases 
seen in a tertiary hospital in Johor, Malaysia. Int J Dermatol 
2014;53:676-684.
    \425\ Bachelez et al., in print.
    \426\ Strober B, et al. Unmet medical needs in the treatment and 
management of generalized pustular psoriasis flares: Evidence from a 
survey of corrona registry dermatologists. Dermatol Ther (Heidelb) 
2021.
---------------------------------------------------------------------------

    We also note that there does not appear to be a standard way to 
assess GPP severity and response to treatment. Though the studies 
described in the application used GPPGA to assess these outcomes, 
because there are multiple assessment tools such as the Psoriasis Area 
and Severity Index (PASI), the GPPGA adapted from the Psoriasis 
Physician Global Assessment (PGA), the Clinical Global Impression (CGI) 
scale, the Japanese Dermatological Association Severity Index (JDA-SI), 
patient reported outcomes, and others, we question the extent of 
response and comparability to other therapies. We also question if skin 
manifestations correlate with systemic symptoms and laboratory values 
as those outcomes would also be of interest.
    We are inviting public comments on whether spesolimab 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 spesolimab.
    Comment: The applicant provided supplemental written responses to 
questions by CMS during the FY 2022 Town Hall meeting regarding the 
Effisayil-1 study. First, in response to a question regarding how the 
results of the Effisayil-1 trial align to labs and other findings, the 
applicant clarified that among patients with elevated baseline 
neutrophils in the Effisayil-1 trial, counts were normalized within one 
week of receiving spesolimab while median C-reactive protein (CRP) 
normalized within two weeks in patients with elevated baseline CRP (>= 
10mg/L).
    Second, in response to a question regarding whether safety data is 
available based on impact to the immune system, the applicant also 
stated that a comparison of safety data among patients with or without 
measurable changes to immune response cannot be answered since 
treatment with spesolimab consistently resulted in normalization of 
inflammatory markers among patients with elevated baseline values. Per 
the applicant, during the 1-week placebo-controlled period in 
Effisayil-1, infections were reported in 17.1% of patients treated with 
spesolimab compared with 5.6% of patients treated with placebo. Serious 
infection (urinary tract infection) was reported in one patient (2.9%) 
in the spesolimab group and no patients in the placebo group. The 
applicant also stated that infections observed were mild to moderate 
with no distinct pattern regarding pathogen or type of infection.
    Third, in response to a question regarding whether older adults 
were studied in the trial, the applicant stated that among patients 
enrolled in the Effisayil-1 study, the mean age was 43 years and the 
median age was 41 years, thirteen patients (24.5%) were 50 to <65 years 
of age and two patients (3.8%) were >=65 years of age. Per the 
applicant, the age distribution observed in the Effisayil-1 study is 
similar to what is known for the US population with GPP \427\ but 
market research has suggested a larger impact on the Medicare 
population. In utilizing IQVIA claims data, the applicant estimated 
that approximately 40% of GPP claims are adjudicated as Medicare.\428\
---------------------------------------------------------------------------

    \427\ Noe MH et al. JAMA Dermatol. doi:10.1001/
jamadermatol.2021.4640.
    \428\ IQVIA Longitudinal Access and Adjudicated Data 2016-2019.
---------------------------------------------------------------------------

    Fourth, in response to a request for the inclusion and exclusion 
criteria, the applicant clarified that patients aged 18-75 years were 
eligible for enrollment if they had a history of GPP consistent with 
criteria for diagnosis according to European Rare and Severe Psoriasis 
Expert Network (ERASPEN) criteria. The applicant further stated that 
patients had to have a GPP flare of moderate-to-severe intensity 
(defined as total GPPGA score >=3, new or worsening pustules, a GPPGA 
pustulation subscore >=2, and >=5% body surface area with erythema and 
the presence of pustules). Per the applicant, key exclusion criteria 
included patients with plaque psoriasis without pustules or with 
pustules restricted to psoriatic plaques, drug-triggered acute 
generalized exanthematous pustulosis, immediate life-threatening flare 
of GPP requiring intensive care treatment, and requirement for current 
treatment with methotrexate, cyclosporine, or retinoids, or any 
restricted medication.
    Fifth, in response to a question regarding whether the primary 
endpoint reached statistical significance, the applicant asserted that 
the Effisayil-1 study met its primary endpoint and achieved statistical 
significance with the following results: At week one, 19 patients 
(54.3%) receiving spesolimab versus one patient (5.6%) receiving 
placebo, achieved a GPPGA pustulation subscore of 0; (risk difference: 
48.7%

[[Page 28283]]

with a 95% confidence interval [CI] 21.5-67.2; one-sided p<0.001).
    Sixth, in response to a question regarding how IL-36R signaling 
could be utilized for other indications, the applicant stated that 
spesolimab is also under investigation for the prevention of GPP flares 
and for the treatment of other neutrophilic skin diseases, such as 
palmoplantar pustulosis (PPP) and hidradenitis suppurativa (HS).
    Seventh, in response to a question regarding when the published 
results of Effisayil-1 and Effisayil-2 are expected, the applicant 
stated that the primary results of Effisayil-1 were previously 
presented at the World Psoriasis and Psoriatic Arthritis Conference in 
June 2021, and the full manuscript has been accepted in a peer-reviewed 
journal for publication by the end of December 2021. The applicant 
further noted that the Effisayil-2 study is currently ongoing and 
publication of the results is to be determined.
    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 spesolimab. We note that as of the 
time of the development of this proposed rule, we have not received the 
published Effisayil-1 trial results.
i. Teclistamab
    Johnson & Johnson submitted an application for new technology add-
on payments for teclistamab for FY 2023. Teclistamab is a bispecific 
antibody (bsAb) that is intended to bind CD3 on T cells and B cell 
maturation antigen (BCMA) on myeloma cells in the treatment of relapsed 
or refractory multiple myeloma. The applicant stated that this dual 
binding brings T cells into proximity with target myeloma cells and 
triggers T cell activation, leading to a cascade of ``effector'' 
events, such as cytotoxicity, cytokine production and immune 
activation, and an overall anti-tumor response.
    Multiple myeloma is an incurable blood cancer that affects a type 
of white blood cell called plasma cells.\429\ Normal plasma cells are 
found in the bone marrow as part of the immune system and make 
antibodies that help the body fight infections. According to the 
applicant, when they become malignant, these plasma cells rapidly 
spread and replace normal cells in the bone marrow.\430\ As indicated 
by its name, multiple myeloma is characterized by dissemination of 
multiple tumor cells throughout the bone marrow.\431\ The applicant 
asserted that the median age of onset is 66 years old, and only 2% of 
patients are less than 40 at the age of diagnosis.\432\ In 2020, it is 
estimated that more than 32,000 people will be diagnosed and nearly 
13,000 will die from multiple myeloma in the US.\433\ It is associated 
with substantial morbidity and mortality, and approximately 25% of 
patients have a median survival of two years or less.434 435
---------------------------------------------------------------------------

    \429\ Raab MS, Podar K, Breitkreutz I, Richardson PG, Anderson 
KC. Multiple myeloma. Lancet. 2009 Jul 25;374(9686):324-39. doi: 
10.1016/S0140-6736(09)60221-X. Epub 2009 Jun 21. PMID: 19541364.
    \430\ Utley A, Lipchick B, Lee KP, Nikiforov MA. Targeting 
Multiple Myeloma through the Biology of Long-Lived Plasma Cells. 
Cancers (Basel). 2020 Jul 30;12(8):2117. doi: 10.3390/
cancers12082117. PMID: 32751699; PMCID: PMC7466116.
    \431\ Fairfield H, Falank C, Avery L, Reagan MR. Multiple 
myeloma in the marrow: Pathogenesis and treatments. Ann N Y Acad 
Sci. 2016 Jan;1364(1):32-51. doi: 10.1111/nyas.13038. PMID: 
27002787; PMCID: PMC4806534.
    \432\ Kyle RA, Gertz MA, Witzig TE, Lust JA, Lacy MQ, 
Dispenzieri A, Fonseca R, Rajkumar SV, Offord JR, Larson DR, Plevak 
ME, Therneau TM, Greipp PR. Review of 1027 patients with newly 
diagnosed multiple myeloma. Mayo Clin Proc. 2003 Jan;78(1):21-33. 
doi: 10.4065/78.1.21. PMID: 12528874.
    \433\ SEER Cancer Stat Facts: Myeloma. National Cancer 
Institute. Bethesda, MD, https://seer.cancer.gov/statfacts/html/mulmy.html.
    \434\ 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. 
doi: 10.1001/jamaoncol.2018.2128. PMID: 29800065; PMCID: PMC6143021.
    \435\ 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. PMID: 24518420.
---------------------------------------------------------------------------

    According to the applicant, multiple myeloma is incurable, with 
most patients relapsing despite current treatments.\436\ The applicant 
stated that immunotherapies, including CAR T-cell therapy and antibody-
based therapies, engage the patient's immune system to fight cancer. 
According to the applicant, new treatment options available in the last 
two decades have extended the median survival of multiple myeloma 
patients. The introduction of proteasome inhibitors (PI), histone 
deacetylase inhibitors, immunomodulatory agents (IMiD), monoclonal 
antibodies, antibody-drug conjugates, corticosteroids, conventional 
chemotherapy and cellular therapies like autologous stem cell 
transplantation (ASCT) have allowed numerous therapeutic options for 
patients with multiple myeloma. The applicant stated that other 
currently available treatment options include selective inhibitor of 
nuclear export (SINES) and melphalan flufenamide. However, the 
applicant stated that barriers to access and a complex, time-consuming 
manufacturing process limit access on some therapies. The applicant 
stated that bsAbs facilitate T cell redirection without the need for 
patient cell collection and external manipulation as is seen in CAR T-
cell therapy.
---------------------------------------------------------------------------

    \436\ Rajkumar SV. Multiple myeloma: Every year a new standard? 
Hematol Oncol. 2019 Jun;37 Suppl 1(Suppl 1):62-65. doi: 10.1002/
hon.2586. PMID: 31187526; PMCID: PMC6570407.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that 
teclistamab has not yet received FDA marketing authorization but was 
granted Breakthrough Therapy designation on May 26, 2021. The applicant 
stated that it is seeking accelerated approval for a Biologics License 
Application (BLA) for the proposed indication for adult patients with 
relapsed or refractory multiple myeloma, who have received at least 3 
prior therapies including a proteasome inhibitor, an immunomodulatory 
agent and an anti-CD38 monoclonal antibody, and that it expects FDA 
approval by June 2022. According to the applicant, teclistamab is 
designed to be given subcutaneously in two priming doses of 60 ug/kg 
and 300 ug/kg, then a maintenance dose of 1500 ug/kg. According to the 
applicant, ICD-10-PCS code 3E01305 (Introduction of other 
antineoplastic into subcutaneous tissue, percutaneous approach) can be 
used to identify the technology, but it does not distinctly identify 
procedures involving the administration of teclistamab. The applicant 
has submitted a request for approval for a unique ICD-10-PCS code to 
identify procedures involving the administration of teclistamab. The 
applicant also stated that the following ICD-10 CM diagnosis codes can 
be used to identify the proposed indication for teclistamab: C90.00 
(Multiple myeloma not having achieved remission), C90.01 (Multiple 
myeloma in remission), and C90.02 (Multiple myeloma in relapse).
    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 purposes of new technology add-on 
payments.
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant

[[Page 28284]]

asserts that teclistamab uses a different mechanism of action when 
compared to existing technologies used to treat myeloma. The applicant 
stated that teclistamab has a unique mechanism of action with a full-
sized antibody containing two distinct binding domains that 
simultaneously bind the BCMA target on tumor cells and the CD3 T-cell 
receptor. The applicant stated that teclistamab's mechanism of action 
is different from CAR T-cell therapies used to treat multiple myeloma 
such as idecabtagene vicleucel because it does not require cell 
extraction and engineering. The applicant submitted the following table 
that compares the mechanism of action for teclistamab to the mechanism 
of action for existing technologies used to treat multiple myeloma.
[GRAPHIC] [TIFF OMITTED] TP10MY22.107

    According to the applicant, there is currently no commercially 
available bispecific antibody for multiple myeloma: Blinatumomab is a 
bispecific T cell engager (BiTE) targeting CD3 and CD19 made up of two 
fragment antigen-binding (Fab) portions held together by a chemical 
linker that is only approved for pre-B-cell acute lymphoblastic 
lymphoma, and amivantamab targets two antigens specific to lung cancer 
cells and does not contain a CD3-binding domain. The applicant stated 
that teclistamab is not substantially similar to other existing 
bispecific antibodies like blinatumomab due to teclistamab's duobody 
structure of BCMA versus CD19, or amivantamab due to targeting of CD3 
and BCMA versus the lung cancer antigens, cMET and EGFR. Therefore, the 
applicant asserted that teclistamab has a novel structure and unique 
mechanism of action, and is unlike any existing technology utilized to 
treat multiple myeloma.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that the DRG 
assignment for treating multiple myeloma is not expected to change with 
this technology.
    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 its proposed indication 
is for treatment of adult patients with relapsed or refractory multiple 
myeloma, who have received at least three prior therapies including a 
proteasome inhibitor, an immunomodulatory agent and an anti-CD38 
monoclonal antibody. According to the applicant, this indication is 
similar to belantamab and idecabtagene vicleucel, which are approved 
for multiple myeloma patients who have failed four prior therapies or 
lines of therapy, respectively. The applicant asserts that it is likely 
that teclistamab will be approved for an indication identical or 
similar to these two other therapies.
    In summary, the applicant believes that teclistamab 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.
    We are inviting public comments on whether teclistamab is 
substantially similar to existing technologies and whether teclistamab 
meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR for cases 
representing patients who may be eligible for teclistamab based on the 
presence of the ICD-10-CM diagnosis codes listed.

[[Page 28285]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.108

    The applicant limited its case selection to cases mapping to MS-
DRGs 846 (Chemotherapy without Acute Leukemia as Secondary Diagnosis 
with MCC) and 847 (Chemotherapy without Acute Leukemia as Secondary 
Diagnosis with CC). The applicant identified 766 claims that mapped to 
these two MS-DRGs.
    Next, the applicant removed all charges in the drug cost center 
because it stated that it was not possible to differentiate between 
different drugs on inpatient claims. The applicant noted that the three 
doses of the drug administered during inpatient hospitalization would 
replace other therapies, but that removing all charges is likely an 
overestimation of the charges that would be replaced by use of 
teclistamab.
    The applicant then standardized the charges using the FY 2022 IPPS/
LTCH PPS final rule impact file and applied a 4-year inflation factor 
(1.281834) based on the inflation factor used in the FY 2022 IPPS/LTCH 
PPS final rule and correction notice (86 FR 45542) to calculate outlier 
threshold charges. Since the technology is not FDA approved, the cost 
of teclistamab has not yet been determined. However, the applicant 
added charges for the new technology by dividing an estimated cost of 
teclistamab by the national average CCR for drugs (0.187) published in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 44966).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $101,270, which exceeded the average 
case-weighted threshold amount of $58,800. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant asserted that teclistamab 
meets the cost criterion. We are inviting public comment on whether 
teclistamab meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that teclistamab offers a treatment option for 
patients who are refractory to the three major classes of drugs 
currently approved for multiple myeloma (IMiDs, PIs, and monoclonal 
antibodies). The applicant also asserts that teclistamab significantly 
improves clinical outcomes such as treatment response rates, and 
minimal residual disease (MRD) rates when compared to currently 
available treatments.
    With respect to the claim that teclistamab provides a treatment 
option for patients who are refractory to the three major classes of 
drugs currently approved for multiple myeloma, the applicant asserted 
that patients treated with teclistamab demonstrate an overall response 
rate (ORR) of 65%, with 61% of patients who are triple-class refractory 
exhibiting a response. The applicant stated that while response rates 
are similar for idecabtagene vicleucel, another BCMA targeting therapy, 
access may be limited due to inability to secure a CAR T-cell treatment 
spot due to manufacturing constraints, inability and/or unwillingness 
to travel to an idecabtagene vicleucel qualified center, or the need to 
initiate immediate treatment and inability to wait weeks for CAR T-cell 
manufacturing and/or respond to bridging therapy. Additionally, the 
applicant stated some patients are not eligible for idecabtagene 
vicleucel due to fitness/frailty and CAR T-cell manufacturing may be 
unsuccessful. The applicant described the ``off-the-shelf'' nature of 
teclistamab providing a more accessible and immediate option for 
patients, not limited to certified centers, and available to more 
practitioners. Finally, the applicant asserted that frequency and 
severity of CRS and neurotoxicity are less with teclistamab than with 
some other therapies, including CAR T-cell therapies. The applicant 
asserted that no neurotoxicity was observed at the recommended phase 2 
dose (RP2D).\437\
---------------------------------------------------------------------------

    \437\ Usmani et al. Teclistamab, a B-cell maturation antigen x 
CD3 bispecific antibody, in patients with relapsed or refractory 
multiple myeloma (MajesTEC-1): A multicentre, open-label, single-
arm, phase I study, Lancet. 2021 Aug 21;398(10301):665-674. doi: 
10.1016/S0140-6736(21)01338-6. Epub 2021 Aug 10. PMID: 34388396.
---------------------------------------------------------------------------

    With respect to the claim that teclistamab improves clinical 
outcomes as compared to existing technologies, the applicant stated 
that teclistamab demonstrates a high ORR in general as well as in 
triple-class refractory patients; early and deep clinical responses; 
MRD at time of complete response and sustained results; good 
progression-free survival (PFS); predictable, limited, and manageable 
CRS, and minimal toxicity. To support these claims, the applicant 
referenced data from the MajesTEC-1 trial, which is an ongoing, open-
label, single-arm, phase 1 study of intravenous (IV) or subcutaneous 
(SQ) teclistamab in 157 patients with multiple myeloma who were 
relapsed, refractory, or intolerant to established 
therapies.438 439 The primary objectives were to identify 
the RP2D and its safety and tolerability. The study used a data cutoff 
date of March 29, 2021. Between June 8, 2017 and March 29, 2021, 
enrolled patients were administered the study drug at 0.3-19.2 ug/kg 
once every 2 weeks or 19.2-720 ug/kg once a week in the IV cohort, and 
80-3000 ug/kg once a week in the SQ cohort. Teclistamab was given to 
the 157 subjects by IV (n=84) or SC (n=73) administration. Step-up 
dosing was employed during the first week to minimize side effects, and 
the full dose was given weekly beginning on day 1 of week 2. Patients 
continued treatment until disease progression, unacceptable toxicity, 
withdrawal of consent, death, or at study completion. Patients who had 
at least one post-baseline response evaluation after teclistamab 
administration (n=40) were evaluated for secondary endpoints of ORR, 
duration of response (DOR), time to response, pharmacokinetic 
parameters, pharmacodynamics markers, and anti-teclistamab antibodies. 
The authors did not report PFS and overall survival (OS) because they 
stated that the data were not mature.
---------------------------------------------------------------------------

    \438\ Usmani et al., Teclistamab, a B-cell maturation antigen x 
CD3 bispecific antibody, in patients with relapsed or refractory 
multiple myeloma (MajesTEC-1): A multicentre, open-label, single-
arm, phase 1 study, Lancet. 2021 Aug 21;398(10301):665-674. doi: 
10.1016/S0140-6736(21)01338-6. Epub 2021 Aug 10. PMID: 34388396.
    \439\ ClinicalTrials.gov, NCT03145181.
---------------------------------------------------------------------------

    At the cutoff date, median age of enrolled patients was 63, with 
more elderly patients (>=70 years) in the IV cohort than the SQ cohort. 
The median lines of therapy received prior to the study were six. All 
patients enrolled in the study experienced treatment-emergent adverse 
events (TEAEs), with 85% experiencing grade 3 or 4. At R2PD, the 
percentage of grade 3 or 4

[[Page 28286]]

TEAEs dropped to 80%, and 50% of those were believed to be treatment 
related. The most common hematologic TEAEs were neutropenia, anemia, 
and thrombocytopenia, whereas the most common non-hematologic TEAE was 
CRS at grade 1 or 2. TEAEs occurred in 57% of all treated patients, and 
70% of those at the R2PD. Median time and duration of CRS was 1 day in 
IV cohort and 2 days in the SQ cohort. The most common non-hematologic 
adverse event (AE) was CRS, all grade 1 or 2, which occurred in 60% of 
all subjects treated with subcutaneous drug and 70% of subjects at the 
RP2D. Infections were noted in 45% of subjects at the RP2D, including 
23% with grade 3/4 infections. Neurotoxicity occurred in 1% of subjects 
treated with SC drug, including 3% at the RP2D. AEs led to cycle delays 
or dose reductions in the overall population. No subject discontinued 
treatment due to CRS. Based on data from this trial, the authors noted 
a more gradual increase in serum teclistamab in SQ administration 
compared to IV administration and established a RP2D of 1500 ug/kg SQ. 
The ORR at the RP2D was 65%, with complete response (CR) and very good 
partial response (VGPR) rates of 40% and 58%, respectively. After a 
median follow-up of 7.1 months, 22/26 (85%) responders continued on 
therapy. In a small subgroup of 33 triple-class refractory patients, 
the ORR was 61%. Authors noted that, in contrast, studies of selinexor 
and belantamab mafodotin at approved doses had response rates of 26% 
and 31%, respectively.
    The applicant also provided updated results that were presented at 
the American Society for Hematology in December 2021.\440\ This data, 
up to clinical cut-off date September 7, 2021, included longer follow-
up of the phase 1 trial (median 5.9 months, 0.2-18 month range in the 
safety analysis) as well as initial data from the phase 2 trial at 
median follow-up of 7.8 months (range 0.5+-18 months). The pivotal 
cohort now included 165 patients, with 40 in the phase 1 cohort and 125 
in the phase 2 cohort. According to the applicant, the phase 1 patients 
were relapsed, refractory, or intolerant to established therapies. The 
phase 2 patients received >3 prior lines of therapy and both cohorts 
received R2PD. There were discontinuations in both groups due to 
progressive disease, physician decision, patient withdrawal, AE, and 
death. At the time of the ASH presentation, authors noted an ORR of 62% 
(95% CI: 53.7-69.8) with median time to first response of 1.2 months 
(range 0.2-5.5 months). ORR was slightly higher in patients <75 years 
old (n=127) compared to patients >75 years (n=23) and in those with 
baseline renal function >60 ml/min/1.73 m2. Of the 165 patients, 
serious AEs occurred in 88 patients and there were 9 deaths. CRS events 
were mostly grade 1/2 with one transient-grade 3 CRS. There was 
neurotoxicity in 21 patients, with headache being the most common. At a 
data cut-off of November 7, 2021, the applicant stated that 88.2% of 
responders were alive without subsequent treatment or progressive 
disease. Median DOR has not been reached, with a 9-month PFS rate of 
59%. The applicant also stated that enrollment in phase 2 expansion 
cohorts is ongoing, and phase 3 study enrollment has been initiated.
---------------------------------------------------------------------------

    \440\ Moreau P, Usmani S, Garfall A, et al., Updated Results 
From MajesTEC-1: Phase 1/2 Study of Teclistamab, a B-Cell Maturation 
Antigen x CD3 Bispecific Antibody, in Relapsed/Refractory Multiple 
Myeloma. 63rd American Society of Hematology (ASH) Annual Meeting & 
Exposition, Atlanta, GA/Virtual, December 11-14, 2021.
---------------------------------------------------------------------------

    In support of the claim that teclistamab demonstrates a high ORR 
and early and deep clinical responses, the applicant cited MajesTEC-1 
data for 40 patients who received R2PD and were eligible for evaluation 
of response. The applicant noted that at a median follow-up of 6.1 
months, teclistamab was associated with a 65% overall response rate 
(95% CI 48-79), in patients receiving the RP2D of maintenance dose of 
1.5 mg/kg SQ weekly (n=40). Approximately 58% achieved VGPR or better, 
and 40% achieved complete response or better. For the subgroup of 
triple-class refractory patients (n=33), the applicant cited a 61% ORR 
at R2PD. Regarding early and deep clinical responses, the applicant 
noted that of the 40 patients receiving R2PD, the median time to first 
confirmed response was 1 month (IQR 1.0-1.6), very good partial 
response or better was 1 month (1.0-3.1), first confirmed complete 
response or better was 3.0 months (1.7-3.7).
    In support of the assertions that teclistamab is associated with 
high levels of response, the applicant stated that most patients at 
RP2D attained a status of MRD-negativity by the time they were 
evaluable for a CR. The applicant also stated that teclistamab 
demonstrated responses wherein myeloma cells were not detected in a 
background of 105 or 106 cells. The applicant also cited a 6-month PFS 
of 67% (95% CI 49-80) for those treated at R2PD.
    Lastly, in support of the claim that teclistamab results in 
predictable, limited, and manageable CRS and minimal toxicity, the 
applicant cited hematological and nonhematological TEAEs described 
earlier in the MajesTEC-1 trial summary. The applicant also stated that 
CRS was of limited severity, with consistent, predictable time to onset 
(median 2 days) and duration of CRS (median 2 days). Teclistamab-
related toxicity was manageable, including CRS, and did not result in 
discontinuation of therapy. In review of the applicant's data, 
neurotoxicity occurred in 4% of patients (n=7), with higher grade 
neurotoxicity (3 or 4) occurring in the IV cohort.
    The applicant also provided preclinical data regarding the 
development of JNJ-7957 (teclistamab), a novel BCMAxCD3 bispecific 
antibody.\441\ In the first paper, authors evaluated activity of this 
antibody in cell lines and bone marrow samples from patients with 
multiple myeloma and refractory disease. It was noted that JNJ-7957 was 
associated with anti-tumor activity in 48 of 49 bone marrow samples 
from multiple myeloma patients and in 5 of 6 bone marrow samples from 
primary plasma cell leukemia patients. In daratumumab-exposed effector 
cells, there appeared to be enhanced JNJ-7957 activity. The authors 
used this data to support further studies on JNJ-7957 in patients with 
multiple myeloma (MM). In a second preclinical paper, authors described 
the development of a BCMAxCD3 bispecific antibody (teclistamab [JNJ-
64007957]) to recruit and activate T cells to kill BCMA-expressing 
multiple myeloma cells.\442\ This study noted that teclistamab was 
associated with cytotoxicity of BCMA+ MM cell lines in vitro (H929 
cells, 50% effective concentration [EC50] = 0.15 nM; MM.1R cells, EC50 
= 0.06 nM; RPMI 8226 cells, EC50 = 0.45 nM) with concomitant T-cell 
activation (H929 cells, EC50 = 0.21 nM; MM.1R cells, EC50 = 0.1 nM; 
RPMI 8226 cells, EC50 = 0.28 nM) and cytokine release. According to the 
applicant, teclistamab also depleted BCMA+ cells in bone marrow samples 
from MM patients in an ex vivo assay with an average EC50 value of 1.7 
nM. Under more physiological conditions using healthy human whole 
blood, teclistamab mediated dose-dependent lysis of H929 cells and 
activation of T

[[Page 28287]]

cells. Antitumor activity of teclistamab was also observed in 2 BCMA+ 
MM murine xenograft models inoculated with human T cells (tumor 
inhibition with H929 model and tumor regression with the RPMI 8226 
model) compared with vehicle and antibody controls. According to the 
applicant, the findings of this study indicate that teclistamab is 
active against BCMA-expressing cells from MM cell lines, patient 
samples, and MM xenograft models.
---------------------------------------------------------------------------

    \441\ Frerichs et al., Preclinical Activity of JNJ-7957, a Novel 
BCMAxCD3 Bispecific Antibody for the Treatment of Multiple Myeloma, 
Is Potentiated by Daratumumab, Clin Cancer Res. 2020 May 
1;26(9):2203-2215. doi: 10.1158/1078-0432.CCR-19-2299. Epub 2020 Jan 
22. PMID: 31969333.
    \442\ Pillarisetti et al, Teclistamab is an active T cell-
redirecting bispecific antibody against B-cell maturation antigen 
for multiple myeloma, Blood Adv. 2020 Sep 22;4(18):4538-4549.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether teclistamab meets the 
substantial clinical improvement criterion. We note that all 
substantial clinical improvement claims were based on one small-sized 
open-label phase 1 study (MajesTEC-1) without control or comparator and 
that subsequently submitted phase 2 data is still in early phases. The 
application and MajesTEC-1 manuscript reported outcomes on 26 of the 40 
patients at RP2D, but further information on that smaller population 
and MRD-evaluability would be helpful. There is also no long-term 
follow-up in the published data. Additionally, of the 40 patients 
enrolled in the R2PD cohort, 70% had CRS and 18 had discontinued 
treatment at the time of publication. Updated results presented at ASH 
demonstrated that 50 patients had discontinued treatment out of the 125 
enrolled in the phase 2 cohort. The authors studied both IV and SQ 
dosing in the MajesTEC-1 trial, but it is unclear if the overall 
results that include IV doses can be generalizable. We further note 
that the median age in MajesTEC-1 was 63 years and the majority of 
elderly patients (>=70 years old) were not in the R2PD cohort. The new 
data presented at ASH included 24 patients >=75 years in the safety 
analysis. The ORR was slightly lower than what was seen in younger 
patients. It is unclear if this is mainly due to small sample size; the 
confidence interval is wider in this subgroup.
    While the applicant provided data to demonstrate that teclistamab 
is associated with a 62% ORR, this was done in a single-arm trial which 
the applicant compared to historically published data of other 
therapies such as selinexor, belantamab, and idecabtagene vicleucel. We 
note that this comparison may be subject to sample-selection bias, as 
without matching of patients or study characteristics, it is unclear 
whether these differences in ORR are due to the therapy or can be 
attributed to other factors.
    We also note that while the applicant asserted that teclistamab 
offers a treatment option for patients with limited access to or who 
are ineligible for CAR T-cell therapy due to wait time, fitness/
frailty, and other issues, we question whether there are other 
available therapies, such as belantamab and selinexor, that may be used 
to treat patients with multiple relapses or who are refractory to other 
therapies that also would not have those limitations. We are inviting 
public comments on whether teclistamab 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 teclistamab FY 
2023 application for new technology add-on payments.
    Comment: The applicant responded to questions received at the New 
Technology Town Hall Meeting. During the Q&A portion of their 
presentation, the applicant presenter was asked about the status of 
planned phase 2 studies as the data shown were from the phase I portion 
of MajesTEC-1, first presented at the American Society of Clinical 
Oncology Annual Meeting in June 2021. According to the applicant, the 
data shown were the most recent available at the time of submission of 
the FY 2023 application and slide for new technology add-on payments. 
The applicant provided updated data from the phase I and phase 2 
cohorts of MajesTEC-1 which, according to the applicant, were presented 
just the evening before at the American Society for Hematology 2021 
Annual Meeting. This update included safety and efficacy data from both 
cohorts, including longer-term follow for 150 patients at the RP2D. The 
applicant provided a summary of this update as well as the presentation 
deck from the ASH oral session. (We note that we have summarized this 
updated data in the preceding discussion of the substantial clinical 
improvement criterion for teclistamab.)
    Response: We appreciate the applicant's comments and updated data, 
as previously summarized. We will take these comments into 
consideration when deciding whether to approve new technology add-on 
payments for teclistamab.
j. TERLIVAZ[supreg] for Injection (Terlipressin)
    Mallinckrodt Pharmaceuticals submitted an application for new 
technology add-on payments for TERLIVAZ[supreg] (terlipressin) for FY 
2023. Per the applicant, TERLIVAZ[supreg] is for intravenous use in the 
treatment of adults with hepatorenal syndrome type 1 (HRS-1). 
TERLIVAZ[supreg] is a sterile, preservative-free, lyophilized powder 
for intravenous (IV) administration. We note that Mallinckrodt 
Pharmaceuticals previously submitted an application for new technology 
add-on payments for TERLIVAZTM for FY 2022, as summarized in 
the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25339 through 25344), 
that it withdrew prior to the issuance of the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44979).
    The applicant stated that TERLIVAZ[supreg] (Na-tryglycl-8-
lysinevasopressin) 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.\443\ 
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.\444\ 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.\445\
---------------------------------------------------------------------------

    \443\ 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.
    \444\ Wong F. Recent advances in our understanding of 
hepatorenal syndrome. Nat Rev Gastroenterol Hepatol. 2012;9(7):382-
391.
    \445\ 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 the leading cause of hospitalizations 
among all patients with advanced CLD.\446\ The applicant explained that 
HRS-1 most often develops in patients with CLD, including cirrhosis. 
HRS-1 does not exist in isolation, but as a co-morbidity in very ill 
patients with CLD. According to the applicant, 43.4% of estimated 
annual HRS cases in FY 2023 will be Medicare patients. 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

[[Page 28288]]

treatment options.447 448 The applicant stated that there 
are currently no FDA-approved medications available in the US indicated 
specifically for the treatment of HRS-1,\449\ 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.450 451 According to 
the applicant, this combination is concomitantly administered with 
albumin. The applicant also stated that in patients who are admitted to 
the intensive care unit (ICU), initial treatment with norepinephrine, 
also used off-label, in combination with albumin is recommended.\452\ 
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.\453\ 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.\454\
---------------------------------------------------------------------------

    \446\ 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.
    \447\ Low G, Alexander GJ, Lomas DJ. Hepatorenal syndrome: 
Aetiology, diagnosis, and treatment. Gastroenterol Res Pract. 2015; 
2015:207012.
    \448\ 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.
    \449\ 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.
    \450\ 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.
    \451\ Runyon BA. Hepatorenal syndrome. UpToDate.com. https://www.uptodate.com/contents/hepatorenal-syndrome. Updated April 13, 
2020. Accessed January 26, 2020.
    \452\ Ibid.
    \453\ Ibid.
    \454\ Sarin S, Sharma P. Terlipressin: An Asset for 
Hepatologists! Hepatology. 2011;54(2):724-728.
---------------------------------------------------------------------------

    The applicant explained that the goal of HRS-1 treatment is to 
reverse the underlying hemodynamic instability. According to the 
applicant, treatment with TERLIVAZ[supreg] accomplishes this by 
decreasing splanchnic vasodilation and improving renal hemodynamics, 
thereby ameliorating afferent renal vasoconstriction, and improving 
glomerular filtration rate (GFR). The applicant noted that recent 
research suggests that increased circulating levels of pro-inflammatory 
cytokines (which the applicant asserted TERLIVAZ[supreg] administration 
helps to reduce) also play an important role in the development of HRS. 
The applicant asserted that, overall, treatment with TERLIVAZ[supreg] 
effectively addresses multiple aspects of the fundamental 
pathophysiology responsible for HRS-1, though it does not treat the 
underlying liver disease or decompensated cirrhosis. Furthermore, the 
applicant asserted that effective timely reversal of HRS-1 helps to 
improve post-liver transplant outcomes, as well as mitigates demand for 
renal replacement therapy (RRT) and kidney transplant.
    With respect to the newness criterion, the applicant explained that 
TERLIVAZ[supreg] has not yet been granted approval from FDA for the 
proposed indication of treatment of adults with HRS-1. The applicant 
stated that in 2005, a New Drug Application (NDA) filing for 
TERLIVAZ[supreg] was granted Fast Track designation by FDA and was 
considered under Priority Review in May 2008, but a Complete Response 
Letter (CRL) was issued by FDA in November 2009. The applicant also 
stated that in 2016, Mallinckrodt Pharmaceuticals and 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 FDA voted to recommend approval 
of the investigational agent TERLIVAZ[supreg] to treat adults with HRS-
1; however, on September 11, 2020, Mallinckrodt received a CRL from FDA 
denying this NDA. The applicant stated that it will work with FDA and 
anticipates approval prior to July 1, 2022.
    According to the applicant, TERLIVAZ[supreg] is administered as an 
IV bolus injection. For the first 3 days, the recommended dosage is 1 
mg TERLIVAZ every 6 hours by slow IV bolus injection (over 2 minutes). 
On day 4, the serum creatinine level is assessed against the baseline 
level obtained prior to initiating treatment. If the serum creatinine 
has decreased by 30% or more from the baseline, then 1 mg 
TERLIVAZ[supreg] can continue to be administered every 6 hours. If the 
serum creatinine has decreased by less than 30% from the baseline, then 
TERLIVAZ[supreg] may be increased to 2 mg every 6 hours. According to 
the applicant, TERLIVAZ[supreg] can continue to be administered until 
24 hours after the patient achieves a second consecutive serum 
creatinine value of <=1.5mg/dL at least 2 hours apart or for a maximum 
of 14 days. If, by day 4, serum creatine is at or above the baseline 
serum creatinine level, then TERLIVAZ[supreg] should be discontinued. 
If a patient develops a recurrence of HRS-1 after discontinuation of 
initial treatment, TERLIVAZ may be re-administered.
    The applicant stated that, effective October 1, 2022, the following 
ICD-10-PCS codes may be used to uniquely describe procedures involving 
the administration of TERLIVAZ[supreg]: XW03367 (Introduction of 
terlipressin into peripheral vein, percutaneous approach, new 
technology group 7) and XW04367 (Introduction of terlipressin into 
central vein, percutaneous approach, new technology group 7).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the 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 TERLIVAZ[supreg] uses a different mechanism 
of action than existing, off-label treatments for HRS-1, for example, 
midodrine, octreotide, and norepinephrine. The applicant explained that 
TERLIVAZ[supreg] has a selective affinity for V1 vasopressin receptors 
predominantly located in the arterial vasculature in the splanchnic 
region. 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.
BILLING CODE 4120-01-P

[[Page 28289]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.109

BILLING CODE 4120-01-C
    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 following three MS-DRGs: (1) MS-DRG 441 (Disorders of Liver 
Except Malignancy, Cirrhosis or Alcoholic Hepatitis with Major 
Complication or Comorbidity); (2) MS-DRG 442 (Disorders of Liver Except 
Malignancy, Cirrhosis or Alcoholic Hepatitis with Complication or 
Comorbidity); and (3) MS-DRG 443 (Disorders of Liver Except Malignancy, 
Cirrhosis or Alcoholic Hepatitis without Complication or Comorbidity/
Major Complication or Comorbidity). 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 may be assigned to MS-DRGs 441, 442, and 
443.
    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 it is seeking FDA 
approval for the proposed indication of treatment of adults with HRS-1. 
Therefore, the applicant explained, TERLIVAZ[supreg] will treat the 
same type of disease when compared to existing technologies. However, 
the applicant noted that the use of the existing drugs for treatment of 
HRS-1 is off-label, while Mallinckrodt Pharmaceuticals is

[[Page 28290]]

seeking FDA approval of TERLIVAZ[supreg] specifically for the proposed 
indication of treatment of adults with HRS-1. The applicant also 
asserted that TERLIVAZ[supreg] (upon FDA approval) will not treat the 
same or a similar population when compared to existing technologies 
currently used to treat HRS-1 in the U.S. The applicant asserted that 
results from the CONFIRM trial (ClinicalTrials.gov number, NCT02770716) 
indicate there is a subset of patients for whom TERLIVAZ[supreg] will 
have efficacy and for whom current therapies, which are used off-label, 
are not effective. The applicant asserted that the patient population 
for which TERLIVAZ[supreg] offers a new treatment option (that is, 
those unresponsive to current standard of care treatments) is a subset 
of the larger patient population for which TERLIVAZ[supreg] will 
receive an FDA label. Nevertheless, the applicant stated that while the 
FDA label for TERLIVAZ[supreg] is not expected to 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.
    In summary, the applicant stated that TERLIVAZ[supreg] is not 
substantially similar to existing technologies currently available to 
Medicare beneficiaries to treat HRS-1 because it uses a different 
mechanism of action and treats a new patient population, and therefore, 
the technology meets the ``newness'' criterion. However, similar to our 
discussion in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25340), 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 subset of patients for whom TERLIVAZ[supreg] will have efficacy and 
for whom current treatments are ineffective does not necessarily speak 
to the treatment of a new patient population for HRS-1.
    We are inviting public comments on whether TERLIVAZ[supreg] is 
substantially similar to existing technologies and whether 
TERLIVAZ[supreg] meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR database 
for cases representing patients who may be eligible for 
TERLIVAZ[supreg] using patient claims bearing the ICD-10-CM code K76.7 
(Hepatorenal syndrome) to identify HRS-1 in the inpatient setting. The 
applicant stated that it filtered for HRS-1 cases by excluding cases 
with an inpatient length of stay of under two days. 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 after 
two consecutive days of diuretic withdrawal and plasma volume expansion 
with albumin is one of the diagnostic criteria of HRS-1 in patients 
with cirrhosis. The applicant stated that, accordingly, patients who do 
not fulfill this criterion cannot be considered HRS-1 cases. The 
applicant also stated that it differentiated between cases where HRS-1 
is the primary and/or admitting diagnosis code and cases where HRS-1 
can be the primary, admitting, or any secondary diagnosis. The 
applicant further defined cohorts using an ICU indicator, explaining 
that it considered the different clinical presentations of HRS-1, which 
may at times be treated in the ICU.
    The applicant then presented two analyses using six defined 
cohorts. The applicant considered the following factors in defining the 
cohorts. For Cohorts 1 and 2, the applicant included cases with an ICU 
indicator, 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-1 diagnosis or having no relationship to HRS-
1 other than a concurrent presence. For Cohorts 3 and 4, the applicant 
also included cases without an ICU indicator. For Cohorts 5 and 6, the 
applicant included all cases without differentiation in ICU 
utilization. Cohorts 1, 3, and 5 include cases where HRS is the primary 
and/or admitting diagnosis code. Cohorts 2, 4, and 6 include cases 
where HRS can be the primary, the admitting, or any secondary 
diagnosis. The applicant described the six cohorts as shown in the 
table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.110

    The applicant imputed a value of 11 cases for MS-DRGs with a case 
volume under 11 for use in the weighted average calculations. Using 
this approach, the applicant identified 318,557 cases mapping to 249 
MS-DRGs across the six cohorts. The applicant noted, however, that only 
14 MS-DRGs had a case volume >= 1% across all cohorts, as shown in the 
table, and that these MS-DRGs cumulatively represented 77.8% of all 
cases. The applicant stated that MS-DRG 441 (Disorders of Liver Except 
Malignancy, Cirrhosis or Alcoholic Hepatitis with MCC) had the highest 
case volume in each of the six cohorts in the analysis, and that only 
the first four MS-DRGs listed in the table had a case volume >=7%.

[[Page 28291]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.111

    After identifying cases in each of the cohorts, the applicant 
removed charges for prior technology as follows:
     The applicant subtracted the estimated cost of generic 
norepinephrine based on HRS-1 dosing regimens, $1,699 (AnalySource 2018 
U.S. Pricing), for ICU-only cases (Cohorts 1 and 2).
     The applicant subtracted the estimated cost of midodrine 
plus octreotide based on HRS-1 dosing regimens, $3,391 (AnalySource 
2018 U.S. Pricing), for non-ICU cases (Cohorts 3 and 4).
     The applicant noted that Cohorts 5 and 6 have a mix of 
both ICU and non-ICU cases. For the ICU cases, the applicant subtracted 
the estimated cost of generic norepinephrine, $1,699. For non-ICU 
cases, the applicant subtracted the estimated cost of midodrine plus 
octreotide, $3,391.
    The applicant then standardized the charges across the six cohorts 
using the FY 2019 impact file in the FY 2022 IPPS/LTCH PPS final rule 
and correction notice. The applicant presented two scenarios that 
varied the inflation factor used to update charges from FY 2019. Under 
the first scenario, the applicant applied the 3-year inflation factor 
of 20.5% (rounded from 1.204686), which was derived from the inflation 
factor used to calculate outlier threshold charges in the FY 2022 IPPS/
LTCH PPS final rule and correction notice (86 FR 45542), to update the 
charges from FY 2019 to FY 2022. The applicant asserted that it did not 
add charges for the new technology, as a price for TERLIVAZ[supreg] has 
not yet been established. Even without the additional charges, the 
applicant asserted that TERLIVAZ[supreg] would meet the cost criterion 
as the final inflated average case-weighted standardized charge per 
case exceeded the average case-weighted threshold amount across all six 
cohorts, as summarized in the table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.112

    Under the second scenario, the applicant applied a 4-year inflation 
factor of 28.2% (rounded from 1.281834), which was derived from the 
inflation factor used to calculate outlier threshold charges in the FY 
2022 IPPS/LTCH PPS final rule and correction notice (86 FR 45542), to 
update the standardized charges from FY 2019 to FY 2023. Similar to the 
first analysis, the applicant did not add charges for the new 
technology as the applicant asserted that a price for TERLIVAZ[supreg] 
has not yet been established. Again, the applicant asserted that even 
without the additional charges, TERLIVAZ[supreg] would meet the cost 
criterion as the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount 
across all six cohorts. We did not receive a weighted average for the 
final inflated average case-weighted standardized charge per case 
across the six cohorts for the 4-year inflation factor calculations.
     For Cohort 1, the applicant calculated a final inflated 
average case-weighted standardized charge per case of $153,342, which 
exceeded the average case-weighted threshold amount of $71,069.
     For Cohort 2, the applicant calculated a final inflated 
average case-weighted standardized charge per case of $206,064, which 
exceeded the average case-weighted threshold amount of $88,995.
     For Cohort 3, the applicant calculated a final inflated 
average case-

[[Page 28292]]

weighted standardized charge per case of $67,120, which exceeded the 
average case-weighted threshold amount of $57,341.
     For Cohort 4, the applicant calculated a final inflated 
average case-weighted standardized charge per case of $76,156, which 
exceeded the average case-weighted threshold amount of $64,420.
     For Cohort 5, the applicant calculated a final inflated 
average case-weighted standardized charge per case of $109,752, which 
exceeded the average case-weighted threshold amount of $64,125.
     For Cohort 6, the applicant calculated a final inflated 
average case-weighted standardized charge per case of $150,184, which 
exceeded the average case-weighted threshold amount of $78,597.
    Because the final inflated average case-weighted standardized 
charge per case for each of the six cohorts under both scenarios 
exceeded the average case-weighted threshold amount, the applicant 
asserted that TERLIVAZ[supreg] meets the cost criterion.
    We invite public comments on whether TERLIVAZ[supreg] meets the 
cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that TERLIVAZ[supreg] represents a substantial 
clinical improvement over existing technologies because (1) it offers a 
treatment option for HRS-1 patients unresponsive to currently available 
treatments (for example, midodrine, octreotide, and norepinephrine); 
and (2) it significantly improves clinical outcomes among HRS-1 
patients as compared to placebo as well as currently available 
treatments.
    In support of the claim that the use of TERLIVAZ[supreg] offers a 
treatment option for HRS-1 patients unresponsive to currently available 
treatments, the applicant cited the results of the CONFIRM trial 
(ClinicalTrials.gov number, NCT02770716).\455\ The CONFIRM study was a 
randomized (2:1), double-blinded 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. 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). To be counted in the primary endpoint, patients needed to be 
alive without RRT for at least 10 days after achieving verified HRS 
reversal. The secondary endpoints were as follows: HRS reversal, 
defined as a serum creatinine level of 1.5 mg per deciliter or less; 
durability of HRS reversal, defined as HRS reversal without renal-
replacement therapy to day 30; HRS reversal among patients with 
systemic inflammatory response syndrome (SIRS); and verified reversal 
of HRS without recurrence of HRS by day 30. The applicant explained 
that patient enrollment criteria for the CONFIRM trial included 
cirrhosis, ascites, and rapidly progressive kidney failure, with a 
doubling of the serum creatinine level to at least 2.25 mg per 
deciliter (199 [micro]mol per liter) within 14 days before 
randomization.
---------------------------------------------------------------------------

    \455\ Wong F, Pappas, S.C, Curry M.P, et al. Terlipressin plus 
Albumin for the Treatment of Type 1 Hepatorenal Syndrome. New 
England Journal of Medicine. 2021;384(9):818-828. doi: 10.1056/
NEJMoa2008290.
---------------------------------------------------------------------------

    The applicant stated that patients were excluded if they had a 
sustained reduction in the serum creatinine level of more than 20% or a 
decrease to below 2.25 mg per deciliter at least 48 hours after 
diuretic withdrawal and albumin infusions. The applicant explained that 
approximately three fourths of the study patients in the CONFIRM trial 
had received vasopressors prior to randomization and did not respond; 
these included midodrine, octreotide, and/or norepinephrine. The 
applicant stated that out of a total of 121 patients, 60 patients (61%) 
in the TERLIVAZ[supreg] group and 61 patients (60%) in the placebo 
group, had previously received midodrine and octreotide and had failed 
on that combination before entering the study. Therefore, the applicant 
explained that well over half of the patients treated in the CONFIRM 
trial were unresponsive to currently available (off-label) treatment 
options--the option often used in the ICU setting (norepinephrine) and 
the options typically used to treat patients on the general medical 
ward (midodrine and/or octreotide).
    In support of the claim that the use of TERLIVAZ[supreg] 
significantly improves clinical outcomes among HRS-1 patients as 
compared to the currently available treatments, the applicant stated 
that TERLIVAZ[supreg] is associated with a more rapid resolution of the 
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 that 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 disease process and a 
reduced rate of mortality compared to placebo, the applicant cited 
results from the CONFIRM study, previously described, as a well as an 
abstract of a post-hoc analysis done by Mujtaba et al. on outcomes with 
TERLIVAZ[supreg] in older patients aged >=65 years.456 457 
The applicant stated that the incidence of verified HRS reversal was 
32% in the TERLIVAZ[supreg] (treatment) group and 17% in the placebo 
(control) group (p=0.006). According to the applicant, the incidence of 
subjects with the pre-specified secondary endpoint of HRS reversal was 
36.2% in the treatment group and 16.8% in the control group (p<0.001). 
According to the applicant, the incidence of verified HRS reversal 
without HRS recurrence by Day 30 was 24.1% in the treatment group and 
15.8% in the control group (p=0.092). The applicant stated that in the 
intent-to-treat (ITT) population for patients at least 65 years old, 
34.3% of the patients in the TERLIVAZ[supreg] group demonstrated the 
pre-specified secondary endpoint of HRS reversal compared to 16.7% 
patients in the placebo group.
---------------------------------------------------------------------------

    \456\ Ibid.
    \457\ Mujtaba M, Gamilla-Cruda AK, Jamil K, et al. Terlipressin, 
in Combination with Albumin, Is an Effective Therapy for Hepatorenal 
Syndrome Type 1 in Patients Aged >=65 Years. Abstract to be 
submitted to NKF by November 30, 2021 for presentation at the NKF 
Spring Clinical Meeting (April 6-10, 2022).
---------------------------------------------------------------------------

    The applicant noted that the durability of HRS reversal was 31.7% 
in the treatment group and 15.8% in the control group (p=0.003). In 
addition, the applicant stated that TERLIVAZ[supreg] provided greater 
durability of HRS reversal in HRS-1 patients who were at least 65 years 
of age, and that in the ITT population, 31.4% of patients in the 
TERLIVAZ[supreg] arm achieved durable HRS reversal compared to 16.7% in 
the placebo arm.
    The applicant stated that TERLIVAZ[supreg] provided greater benefit 
in HRS-1 patients with SIRS and that the incidence of HRS reversal in 
the SIRS subgroup was 33.3% (n=28) in the treatment group and 6.3% 
(n=3) in the control group (p <0.001). In addition,

[[Page 28293]]

the applicant stated that TERLIVAZ[supreg] provided greater benefit in 
HRS-1 patients with SIRS who were at least 65 years of age, and that in 
the ITT population, 23.1% of patients with SIRS in the TERLIVAZ[supreg] 
arm achieved HRS reversal compared to 0.0% in the placebo arm.\458\
---------------------------------------------------------------------------

    \458\ Ibid.
---------------------------------------------------------------------------

    The applicant also reported that overall survival up to Day 90 was 
higher in subjects who achieved verified HRS reversal or HRS reversal 
while receiving treatment than in those who did not (p<0.001). The 
applicant stated that by Day 90, death occurred in 101 patients (51%) 
in the TERLIVAZ[supreg] group and in 45 patients (45%) in the placebo 
group (6% difference, 95% CI, -6 to 18). The applicant stated that 
overall survival was not a primary or secondary endpoint in the CONFIRM 
trial as the prognosis of patients with HRS-1 is poor, with a reported 
median survival of <= 3 months. The applicant stated that aggregate, 
published studies and meta-analyses suggest that TERLIVAZ[supreg] 
treatment is likely associated with improved survival for HRS-1 as a 
cause of death, but not for other causes of death.459 460 
The applicant also stated that given the high overall mortality in the 
study population, a total of 146 patients (48.8%) died during the 
CONFIRM trial.\461\ The applicant explained that while TERLIVAZ[supreg] 
improves renal function, patients with end stage liver disease 
nonetheless may continue to experience and die from other complications 
of end stage liver disease, unrelated to HRS-1. The applicant further 
explained that the CONFIRM trial was not powered to show a statistical 
difference in survival. However, the applicant stated that the 
TERLIVAZ[supreg] plus albumin arm in CONFIRM had a significantly better 
verified response rate than the albumin arm, and that better response 
confers better prognosis in these patients.\462\ The applicant also 
mentioned that similar results were seen in previous North American and 
European trials with TERLIVAZ[supreg].463 464 465
---------------------------------------------------------------------------

    \459\ Hiremath SB, Srinivas LD. Survival benefits of 
terlipressin and non-responder state in hepatorenal syndrome: A 
meta-analysis. Indian J Pharmacol. 2013;45(1):54-60.
    \460\ Facciorusso A, Chandar AK, Murad MH, et al. Comparative 
efficacy of pharmacological strategies for management of type 1 
hepatorenal syndrome: A systematic review and network meta-analysis. 
Lancet Gastroenterol Hepatol. 2017; 2: 94-102.
    \461\ Wong F, Pappas, S.C, Curry M.P, et al. Terlipressin plus 
Albumin for the Treatment of Type 1 Hepatorenal Syndrome. New 
England Journal of Medicine. 2021;384(9):818-828. doi: 10.1056/
NEJMoa2008290.
    \462\ Wong F, Pappas, S.C, Curry M.P, et al. Terlipressin plus 
Albumin for the Treatment of Type 1 Hepatorenal Syndrome. New 
England Journal of Medicine. 2021;384(9):818-828. doi: 10.1056/
NEJMoa2008290.
    \463\ Sanyal A, Boyer T, Garcia-Taso G, et al. A Randomized, 
Prospective, Double-Blind, Placebo-Controlled Trial of Terlipressin 
for Type 1 Hepatorenal Syndrome. Gastroenterology. 2008;134(5):1360-
1368.
    \464\ Martin-Llahi M, Pepin MN, Guevara M, et al. Terlipressin 
and albumin vs. albumin in patients with cirrhosis and hepatorenal 
syndrome: A randomized study. Gastroenterology. 2008;134:1352-1359.
    \465\ Boyer T, Sanyal A, Wong F, et al. Terlipressin Plus 
Albumin is More Effective Than Albumin Alone in Improving Renal 
Function in Patients with Cirrhosis and Hepatorenal Syndrome Type 1. 
Gastroenterology. 2016;150:1579-1589.
---------------------------------------------------------------------------

    To support its 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 norepinephrine, the applicant cited a 
study conducted by Arora et al.\466\ 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-AKI in patients with a diagnosis of acute chronic 
liver failure (ACLF). Patients were randomized to receive either 
TERLIVAZ[supreg] or norepinephrine in a 1:1 ratio.\467\ 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 CLD 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.
---------------------------------------------------------------------------

    \466\ 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. 2020;71(2):600-610.
    \467\ Ibid.
---------------------------------------------------------------------------

    A total of 120 patients were randomized; 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% and power of 80%, 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 ITT analysis and per protocol analysis (PPA) (ITT 40% 
(n=24) vs. 16.7% (n=10), p=0.004; PPA 43.1% (n=22) vs. 16.3% (n=9), 
p=0.002). Complete response was defined as return of serum creatinine 
to a value within 0.3 mg/dL of baseline. The applicant also stated that 
patients in the TERLIVAZ[supreg] group had higher 28-day survival 
compared to the norepinephrine group (48% versus 20%, respectively; 
p=0.001).
    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,\468\ which 
compared TERLIVAZ[supreg] plus albumin versus midodrine and octreotide 
(MID/OCT) plus albumin in a multi-center randomized controlled trial. 
The applicant stated that 27 patients were randomized to receive 
TERLIVAZ[supreg] with albumin and 22 to receive MID/OCT plus albumin. 
Patients in the study were from eight hospitals in Italy. The 
researchers hypothesized a response rate of 60% for TERLIVAZ[supreg] 
and of 30% for MID/OCT, with an alpha error of 5% and power of 80%. An 
interim analysis after enrolling half the sample set a stopping rule 
for the randomized clinical trial if the difference in renal function 
recovery was significant at p<0.01. The study was terminated after 49 
patients were enrolled according to the a priori determined stopping 
rule.
---------------------------------------------------------------------------

    \468\ 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.
---------------------------------------------------------------------------

    The applicant stated that the results showed 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% of

[[Page 28294]]

patients in the TERLIVAZ[supreg] group had a complete or partial 
response compared with 28.6% in the MID/OCT group (p=0.01); 55.5% of 
patients in the TERLIVAZ[supreg] group had a complete response compared 
with 4.8% of the MID/OCT group (p<0.001). Complete response was defined 
as a decrease in serum creatinine to <=133 mmol/L (<=1.5 mg/dL). 
Partial response was defined as a >=50% serum creatinine decrease from 
baseline to a final value >133 mmol/L (>1.5 mg/dL). No response was 
defined as a serum creatinine decrease of <50% from baseline. The 
applicant stated that mean arterial pressure (MAP) was significantly 
higher in the TERLIVAZ[supreg] group compared to the MID/OCT group 
after 3 days of treatment as well as at the midpoint of the treatment 
period.
    The applicant also stated that response to treatment (complete or 
partial) was found to be a predictor of 3-month survival in the 
univariate analysis. The difference in cumulative survival between all 
responders (partial and full responders) and nonresponders was 
statistically significant in the TERLIVAZ[supreg] group (P<0.001) but 
not in the MID/OCT group. Some nonresponders to the assigned treatment 
received a rescue treatment according to the treating physician's 
decision. Seven of 12 (58.3%) 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%) who received 
TERLIVAZ[supreg] plus albumin. Four patients had a complete response 
and one patient had a partial response. The applicant stated that in 
patients who did not receive any rescue treatment, the TERLIVAZ[supreg] 
group had a higher 3-month survival rate than the MID/OCT group (55.5% 
vs. 28.6%, P=0.06).
    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 RRT 
through the treatment period (14 days) in patients receiving 
TERLIVAZ[supreg] (23.1% (n=46)) versus the placebo (34.7% (n=35)) 
(p=0.03).\469\
---------------------------------------------------------------------------

    \469\ 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.
---------------------------------------------------------------------------

    In addition, according to the applicant, based on the ITT 
population for the integrated studies for patients at least 65 years 
old (TERLIVAZ[supreg] n=54; placebo n=36), there was a favorable trend 
of lower incidence of RRT in the subsequent follow-up periods: (1) The 
use of RRT/dialysis by Day 30 visit was 25.9% (n=14) in 
TERLIVAZ[supreg]-treated patients vs. 44.4% in placebo-treated 
patients; (2) the use of RRT/dialysis by Day 60 visit was 27.8% in 
TERLIVAZ[supreg]-treated patients vs. 44.4% in placebo-treated 
patients; and (3) the use of RRT/dialysis by Day 90 visit was 29.6% in 
TERLIVAZ[supreg]-treated patients vs. 47.2% in placebo-treated 
patients.\470\
---------------------------------------------------------------------------

    \470\ Mujtaba M, Gamilla-Cruda AK, Jamil K, et al. Terlipressin, 
in Combination with Albumin, Is an Effective Therapy for Hepatorenal 
Syndrome Type 1 in Patients Aged >=65 Years. Abstract to be 
submitted to NKF by November 30, 2021 for presentation at the NKF 
Spring Clinical Meeting (April 6-10, 2022).
---------------------------------------------------------------------------

    The applicant also stated that there was a decreased incidence of 
RRT after liver transplant in patients treated with TERLIVAZ[supreg] 
(19.6% (n=46)) versus 44.8% (n=29) in the placebo group (p=0.04).\471\ 
The applicant stated that the need for RRT post-transplant is 
predictive of poor graft function and survival.\472\ The applicant 
stated that in the ITT population, 0 of 8 TERLIVAZ[supreg]-treated 
patients 65 years and older who received liver transplant required RRT 
and 5 of 6 placebo-treated patients 65 years and older who received 
liver transplant required RRT.\473\
---------------------------------------------------------------------------

    \471\ 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.
    \472\ 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.
    \473\ Mujtaba M, Gamilla-Cruda AK, Jamil K, et al. Terlipressin, 
in Combination with Albumin, Is an Effective Therapy for Hepatorenal 
Syndrome Type 1 in Patients Aged >=65 Years. Abstract to be 
submitted to NKF by November 30, 2021 for presentation at the NKF 
Spring Clinical Meeting (April 6-10, 2022).
---------------------------------------------------------------------------

    The applicant also claimed that patients receiving TERLIVAZ[supreg] 
in the CONFIRM trial had shorter lengths of hospitalizations and ICU 
stays compared to those in the placebo group. The applicant stated that 
in the ITT population for patients at least 65 years old, the median 
number of days for hospital length of stay was 18 for TERLIVAZ[supreg]-
treated patients and 25.5 for placebo-treated patients.\474\ In 
addition, the applicant stated that patients in the TERLIVAZ[supreg] 
group stayed an average of 6.4 days in the ICU versus 13.2 days in the 
placebo group.\475\ The applicant explained that, while in CONFIRM, the 
overall incidence of admission to ICU was similar in both cohorts given 
the severe multiple pre-existing comorbidities in patients with 
decompensated cirrhosis, and that by addressing one severe complication 
(HRS-1), TERLIVAZ[supreg] facilitates management of these patients and 
reduces the burden of critical care management.
---------------------------------------------------------------------------

    \474\ Ibid.
    \475\ 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 also asserted that the overall benefit-risk profile 
of TERLIVAZ[supreg] as a treatment for HRS-1 is favorable. In support 
of this assertion, 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).\476\ The applicant stated that 88.0% (n=176) of patients 
receiving TERLIVAZ[supreg] reported AEs versus 88.9% (n=88) in the 
placebo group, and that 65.0% (n=130) of patients receiving 
TERLIVAZ[supreg] reported SAEs versus 60.6% (n=60) in the placebo 
group. The applicant also stated that: (1) The overall incidence of AEs 
was similar between groups: 91.1% in the TERLIVAZ[supreg] group and 
90.4% in the placebo group; (2) the incidence of SAEs was similar 
between groups: 65.0% in the TERLIVAZ[supreg] group and 59.8% in the 
placebo group; and (3) mortality up to 30 days after first treatment 
was 41.5% in the TERLIVAZ[supreg] group and 40.6% in the placebo 
group.\477\
---------------------------------------------------------------------------

    \476\ Ibid.
    \477\ Mallinckrodt Hospital Products Inc. 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 September 10, 2020.
---------------------------------------------------------------------------

    The applicant stated that, with appropriate labeling to help 
prevent administration to patients who are known to be at higher risk 
for SAEs, TERLIVAZ[supreg] has an acceptable safety profile for 
patients at least 65 years old, a high-morbidity patient population. 
The applicant explained that the safety profile of TERLIVAZ[supreg] is 
well-characterized, with the majority of AEs being predictable, 
recognizable, and generally manageable in the hospital setting where 
HRS-1 patients are treated. The applicant further stated that most of 
the events observed in the company-sponsored clinical studies were 
expected based on TERLIVAZ[supreg]'s V1-receptor activity and 
consistent with the known experience with TERLIVAZ[supreg] outside the 
US. Regarding the increased risk of serious or fatal respiratory 
failure, the applicant stated that TERLIVAZ[supreg] should not be 
administered in patients with pulmonary edema,

[[Page 28295]]

pneumonia, dyspnea, or tachypnea until events resolve. The applicant 
explained that patients with ACLF grade 3 are at significant risk of 
respiratory failure and fluid overload must be actively managed. 
Regarding increased mortality in patients with SCr >=5 mg/dL, the 
applicant explained that the use of TERLIVAZ[supreg] with these 
patients should be considered only when the anticipated benefit to the 
patient outweighs the potential risk.
    In support of the claim that TERLIVAZ[supreg] represents a 
substantial clinical improvement over existing technologies, based on 
real-world usage, the applicant noted that TERLIVAZ is the 
vasoconstrictor of choice for HRS-1 in much of the rest of the world, 
where it is approved and available due to its direct effect in 
reversing the fundamental hemodynamic pathophysiology of HRS-1. The 
applicant stated that both the EASL \478\ and the American Association 
for the Study of Liver Diseases (AASLD) \479\ recommend 
TERLIVAZ[supreg] plus albumin as the first-line treatment for the 
reversal of HRS-1, while other treatment options should only be used if 
TERLIVAZ[supreg] is not available.
---------------------------------------------------------------------------

    \478\ 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.
    \479\ Biggins S, Angeli P, Garcia-Tsao G, et al. Diagnosis, 
Evaluation, and Management of Ascites, Spontaneous Bacterial 
Peritonitis and Hepatorenal Syndrome: 2021 Practice Guidance by the 
American Association for the Study of Liver Diseases. Hepatology. 
2021;74(2):1014-1048. doi:10.1002/hep.31884.
---------------------------------------------------------------------------

    The applicant also described a meta-analysis study identifying a 
total of 377 patients from eight eligible studies, from which the 
authors found that: (1) TERLIVAZ[supreg] reduced the all-cause 
mortality rate by 15% (Risk Difference: -0.15%, 95% CI: -0.26 to -
0.03); and (2) the reduction in the mortality rate due to HRS at three 
months was 9% (Risk Difference: -0.09%, 95% CI: -0.18 to 0.00).\480\ 
According to the applicant, the authors concluded that TERLIVAZ[supreg] 
has long-term survival benefits of at least up to three months, but 
only with HRS as a cause of death, not for other causes of death.\481\
---------------------------------------------------------------------------

    \480\ Hiremath SB, Srinivas LD. Survival benefits of 
terlipressin and non-responder state in hepatorenal syndrome: A 
meta-analysis. Indian J Pharmacol. 2013;45(1):54-60.
    \481\ Ibid.
---------------------------------------------------------------------------

    In addition, the applicant cited a study by Moore et al. of real-
world treatment patterns and outcomes using TERLIVAZ[supreg] in 203 
patients with HRS-1/HRS-acute kidney injury (AKI) in the United 
Kingdom.\482\ The applicant stated that the authors found that the vast 
majority of patients with a clinical diagnosis of HRS-AKI were treated 
with TERLIVAZ[supreg] in the United Kingdom, consistent with EASL 
guidelines. The applicant stated that approximately 50% of patients 
treated with TERLIVAZ[supreg] in the study achieved a complete 
response, with an additional 23% experiencing partial response, and 
that initiation of TERLIVAZ[supreg] at lower serum creatinine levels 
was associated with higher rates of treatment response. The applicant 
stated that complete or partial response to TERLIVAZ[supreg] was 
associated with a higher rate of 90-day survival.
---------------------------------------------------------------------------

    \482\ Moore K, Jamil K, Verleger K, et al. Real-world treatment 
patterns and outcomes using terlipressin in 203 patients with the 
hepatorenal syndrome. Aliment Pharmacol. Ther. 2020;00:1-8. doi: 
10.1111/apt.15836.
---------------------------------------------------------------------------

    Finally, the applicant asserted that TERLIVAZ[supreg] represents a 
substantial clinical improvement because the totality of the 
circumstances 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.\483\ 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 EASL treatment guidelines for HRS-1 and that TERLIVAZ[supreg] has 
now been recommended in guidance from AASLD as first-line treatment for 
HRS reversal.\484\
---------------------------------------------------------------------------

    \483\ 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.
    \484\ 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.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether TERLIVAZ[supreg] meets the 
substantial clinical improvement criterion. As we noted in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25344), in the CONFIRM trial the 
proportion of patients with verified HRS reversal without HRS-1 
recurrence by Day 30 was numerically greater in the TERLIVAZ[supreg] 
arm than placebo; however, the difference between groups was not 
statistically significant (26% vs 17%, p=0.08) \485\ and we note that 
the potential for HRS-1 recurrence among patients treated with 
TERLIVAZ[supreg] after 30 days is unclear. We also noted in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25344) that, although 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% vs. 45%).\486\ We further noted in the FY 2022 
IPPS/LTCH PPS proposed rule 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 comorbidities in patients 
with HRS-1.\487\
---------------------------------------------------------------------------

    \485\ Wong F, Pappas, S.C, Curry M.P, et al. Terlipressin plus 
Albumin for the Treatment of Type 1 Hepatorenal Syndrome. New 
England Journal of Medicine. 2021;384(9):818-828. doi: 10.1056/
NEJMoa2008290.
    \486\ Ibid.
    \487\ Ibid.
---------------------------------------------------------------------------

    In addition, we noted in the FY 2022 IPPS/LTCH PPS proposed rule 
that the primary endpoint of the CONFIRM trial used a surrogate 
endpoint of serum creatinine as an indicator of HRS reversal, and we 
questioned whether this correlates to improvements in clinical outcomes 
such as mortality and time to transplant (86 FR 25344). We also 
question whether mortality would be a more appropriate endpoint than 
HRS reversal to demonstrate substantial clinical improvement in 
clinical outcomes. We note that we were unable to verify the following 
claims made by the applicant about the ITT population for the 
integrated studies involving patients at least 65 years old, based on 
the submitted abstract for Mujtaba et al: (1) That there was a greater 
benefit in these HRS-1 patients with SIRS, (2) that there was a 
favorable trend of lower incidence of RRT in these patients, and (3) 
that there was a shorter median number of days for hospital length of 
stay in these patients.\488\
---------------------------------------------------------------------------

    \488\ Mujtaba M, Gamilla-Cruda AK, Jamil K, et al. Terlipressin, 
in Combination with Albumin, Is an Effective Therapy for Hepatorenal 
Syndrome Type 1 in Patients Aged >=65 Years. Abstract to be 
submitted to NKF by November 30, 2021 for presentation at the NKF 
Spring Clinical Meeting (April 6-10, 2022).
---------------------------------------------------------------------------

    With regard to the applicant's claims regarding a similar incidence 
of AEs and SAEs between groups in the CONFIRM trial, we noted in the FY 
2022 IPPS/LTCH PPS proposed rule that the results show that the 
TERLIVAZ[supreg] arm had a higher incidence of SAEs up to 30 days

[[Page 28296]]

post-treatment (65% of patients receiving TERLIVAZ[supreg] reported 
SAEs vs. 60.6% in the placebo group) related to respiratory failure, 
serious infections such as sepsis and septic shock, GI bleeding, and 
abdominal pain \489\ (86 FR 25344).
---------------------------------------------------------------------------

    \489\ Ibid.
---------------------------------------------------------------------------

    Additionally, we note that death within 90 days due to respiratory 
disorders occurred in 11% of patients in the TERLIVAZ[supreg] group and 
2% of patients in the placebo group.\490\ Regarding the study conducted 
by Arora et al., we noted in the FY 2022 IPPS/LTCH PPS proposed rule 
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 \491\ (86 FR 25344). Finally, in the 
FY 2022 IPPS/LTCH PPS proposed rule, we noted 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 \492\ (86 FR 25344).
---------------------------------------------------------------------------

    \490\ Ibid.
    \491\ 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. 2020;71(2):600-610.
    \492\ 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 are inviting public comments 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].
k. Treosulfan
    Medexus Pharma, Inc. submitted an application for new technology 
add-on payments for treosulfan for FY 2023. According to the applicant, 
treosulfan is a prodrug of a bifunctional alkylating agent that is 
being studied in combination with fludarabine as a preparative regimen 
for allogenic hematopoietic stem cell transplantation (alloHSCT) in 
patients with acute myeloid leukemia (AML) or myelodysplastic syndrome 
(MDS).
    The applicant stated that the goal of alloHSCT is to cure patients 
of their disease by replacing their hematopoietic stem cells (that is, 
bone marrow stem cells) with stem cells from a healthy related or 
unrelated donor. The applicant noted that preparative or conditioning 
treatments are often used to (1) eradicate existing bone marrow tissue 
to provide space for engraftment of transplanted donor stem cells, (2) 
prevent rejection of the incoming donor stem cells by host immune 
cells, and (3) help eradicate existing disease, and that this type of 
preparation is needed for the alloHSCT process. The applicant explained 
that there are two types of conditioning regimens, myeloablative 
conditioning (MAC) and reduced intensity conditioning (RIC). According 
to the applicant, while standard MAC regimens generally lead to low 
relapse rates, they are associated with high treatment-related toxicity 
and transplantation-related mortality (TRM). Thus, patients who are not 
eligible for MAC regimens due to these risks (for example, the elderly 
and patients with comorbidities) usually receive a RIC regimen. The 
applicant described a recent study of patients with acute myeloid 
leukemia,\493\ where RIC resulted in lower treatment related mortality 
but higher relapse rates compared with MAC, with a statistically 
significant advantage in relapse-free survival with MAC. However, the 
applicant stated that certain patients are unable to tolerate MAC, 
therefore according to the applicant, treosulfan was developed in an 
effort to address the significant unmet medical need for improved 
alloHSCT conditioning regimens that can reduce treatment-related 
toxicity and the risk of TRM without increasing the incidence of 
relapse. Per the applicant, treosulfan's immunosuppressive effects are 
due to its toxicity against primitive and committed progenitor cells, T 
and NK cells, reduction of cellularity of primary and secondary 
lymphatic organs and a preclusive effect on the `cytokine storm' that 
precedes the development of graft-versus-host disease (GVHD). The 
applicant stated that these events are involved in the pathogenesis of 
hepatic sinusoidal obstruction syndrome (HSOS).
---------------------------------------------------------------------------

    \493\ Scott, BL et al. 2017. Myeloablative Versus Reduced-
Intensity Hematopoietic Cell Transplantation for Acute Myeloid 
Leukemia and Myelodysplastic Syndromes. J. Clin Oncology 11: 1154.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that 
FDA is still reviewing treosulfan's NDA which has a proposed indication 
for: (1) Use in combination with fludarabine as a preparative regimen 
for alloHSCT in adult and pediatric patients older than one year with 
AML; and (2) use in combination with fludarabine as a preparative 
regimen for alloHSCT in adult and pediatric patients older than one 
year with MDS. According to the applicant, FDA approval is anticipated 
by June 30, 2022. The applicant stated that the drug is designed to be 
administered intravenously and must be reconstituted prior to infusion. 
While not yet FDA approved, the applicant noted that the recommended 
dosage of treosulfan for adult patients is anticipated to be 10 grams 
per square meter (10g/m\2\) of body surface area (BSA) per day of 
treatment, given as a two-hour intravenous infusion, and with treatment 
provided on three consecutive days (day -4, -3, -2) in conjunction with 
fludarabine before hematopoietic stem cell infusion (which occurs on 
day 0).
    According to the applicant, there are currently no ICD-10-PCS 
procedure codes to distinctly identify procedures involving the 
administration of treosulfan. The applicant submitted a request for 
approval for a unique ICD-10-PCS code for procedures involving the 
administration of treosulfan beginning in FY 2023. The applicant also 
stated that the following ICD-10 CM diagnosis codes are potentially 
applicable for the proposed AML and MDS indications that FDA is 
currently reviewing:
BILLING CODE 4120-01-P

[[Page 28297]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.113

BILLING CODE 4120-01-C
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be

[[Page 28298]]

considered substantially similar to an existing technology and would 
not be considered new for the 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 treosulfan does not use the same or similar 
mechanism of action to achieve a therapeutic outcome as compared to 
existing busulfan- and melphalan-based MAC and RIC regimens. The 
applicant stated that treosulfan differs from both busulfan and 
melphalan in that it is a separate chemical entity that is pending FDA 
review for a fully separate and distinct New Drug Application. The 
applicant further stated that treosulfan differs from other alkylating 
agents in that it is a prodrug activated under specific pH conditions 
and that it has its own distinct cytotoxic activity toward 
hematopoietic precursor cells. The applicant described the pH-dependent 
conversion into a mono-epoxide intermediate and L-diepoxybutan. The 
applicant stated that the epoxides form alkylate and cross-link 
nucleophilic centers of deoxyribonucleic acid (DNA) and other 
biological molecules, which are involved in various physiological 
functions, and the alkylation and cross-linking are considered 
responsible for the stem cell depleting, immune-suppressive and 
antineoplastic effects of the epoxides. The applicant stated that 
treosulfan exerts broad antineoplastic and antileukemic activity. In 
further support of its assertion that treosulfan has a different 
mechanism of action, the applicant cited an in vitro to in vivo 
extrapolation (IVIVE) study modeling its potential for drug 
interactions.\494\
---------------------------------------------------------------------------

    \494\ Schaller, S. et al. 2021. Evaluation of the Drug-Drug 
Interaction Potential of Treosulfan using a Physiologically-Based 
Pharmacokinetic Modelling Approach. Br. J Clin Pharmacology (first 
published Sept. 13, 2021), available at https://bpspubs.onlinelibrary.wiley.com/doi/10.1111/bcp.15081.
---------------------------------------------------------------------------

    The applicant further stated that treosulfan-based conditioning 
regimens differ significantly from existing conditioning regimens that 
commonly utilize busulfan and melphalan. The applicant stated that MAC 
treatments typically include high-dose TBI and high-dose chemotherapy-
based regimens, while in RIC treatments, cytotoxic components of the 
regimen are reduced or replaced with less toxic but immunosuppressive 
agents. The applicant noted that busulfan and melphalan are typically 
the mainstays of MAC chemotherapy-based regimens, while fludarabine 
combined with busulfan or melphalan is commonly used in RIC regimens.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that treosulfan 
would be assigned to the same MS-DRG as other agents used for 
conditioning/preparative treatments, MS-DRG 014 (Allogeneic Bone Marrow 
Transplant) because, in a majority of cases, it is anticipated that a 
patient would undergo the treosulfan-based conditioning regimen during 
the same inpatient admission as alloHSCT itself.
    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 treosulfan is designed 
to address a broader patient population than existing MAC and RIC 
treatment regimens by providing access to improved alloHSCT 
conditioning outcomes for patients who may otherwise be ineligible for 
MAC regimens (for example, the elderly and patients with comorbidities) 
due to the increased toxicity of those regimens, without increasing 
risk of relapse. The applicant stated that treosulfan may also be used 
as a conditioning regimen appropriate for children with malignant and 
non-malignant disorders that are indicated for alloHSCT.
    In summary, the applicant believes that treosulfan is not 
substantially similar to other currently available therapies and/or 
technologies because it uses a new mechanism of action and treats a 
broader patient population as compared to existing technologies and 
therefore, the technology meets the ``newness'' criterion. However, we 
have the following concerns regarding whether treosulfan meets the 
newness criterion. We note that it is unclear how the drug interaction 
modeling study, and the separate NDA being considered for treosulfan, 
as cited by the applicant, support the assertion that its mechanism of 
action is different from other alkylating agents. We note that 
treosulfan is an alkylating agent like other drugs used in 
myeloablative conditioning such as busulfan and melphalan. 
Specifically, treosulfan appears to be structurally similar to 
busulfan, and we therefore question whether they share a similar 
mechanism of action. Additionally, we note that the applicant asserts 
that treosulfan can be used in a broader patient population than that 
eligible for MAC regimens, without increasing the risk of relapse 
associated with RIC regimens, but the references presented by the 
applicant only compare a treosulfan-containing conditioning regimen to 
another RIC regimen 495 496 and thus do not demonstrate that 
treosulfan can be used in different patient populations unable to 
receive MAC. Specifically, the studies provided by the applicant 
compare treosulfan to busulfan, both of which are RIC regimens, so this 
appears to demonstrate that a RIC regimen using treosulfan could be an 
option for patients who otherwise would have been treated with a 
busulfan regimen. We are inviting public comments on whether treosulfan 
is substanially similar to existing technologies and whether treosulfan 
meets the newness criterion.
---------------------------------------------------------------------------

    \495\ Beelen DW 2019 Treosulfan or busulfan plus fludarabine as 
conditioning treatment before allogeneic aemopoietic stem cell 
transplantation for older patients with acute myeloid leukaemia or 
myelodysplastic syndrome (MC-FludT.14/L): A randomised, non-
inferiority, phase 3 trial. The Lancet Haematol https://doi.org/10.1016/S2352-3026(19)30157-7.
    \496\ Beelen D 2019 Final Evaluation of a Clinical Phase III 
Trial Comparing Treosulfan to Busulfan-Based Conditioning Therapy 
Prior to Allogeneic Hematopoietic Stem Cell Transplantation of Adult 
Acute Myeloid Leukemia and Myelodysplastic Syndrome Patients 
Ineligible to Standard Myeloablative Regimens. Biol Blood Marrow 
Transplant 25 (2019) S3.
---------------------------------------------------------------------------

    With respect to the cost criterion, the applicant presented the 
following analysis to demonstrate that treosulfan meets the cost 
criterion. To identify cases representing patients who may be eligible 
for treatment with treosulfan, the applicant searched the FY 2019 
MedPAR dataset from the FY 2022 IPPS/LTCH PPS final rule for claims 
reporting an ICD-10-PCS procedure code that could potentially be used 
to identify procedures involving the administration of treosulfan, in 
conjunction with an ICD-10-CM diagnosis code for AML or MDS. For 
inclusion in the analysis, the applicant required at least one ICD-10-
PCS procedure code and at least one ICD-10-CM diagnosis code from the 
following tables:
BILLING CODE 4120-01-P

[[Page 28299]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.114

[GRAPHIC] [TIFF OMITTED] TP10MY22.115


[[Page 28300]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.116

BILLING CODE 4120-01-C
    Using these case selection criteria, the applicant's search 
resulted in 549 cases mapping to three MS-DRGs: MS-DRG 014 (Allogeneic 
Bone Marrow Transplant), MS-DRG 003 (ECMO or Tracheostomy with MV >96 
Hours or Principal Diagnosis Except Face, Mouth and Neck with Major 
O.R. Procedures), and MS-DRG 004 (Tracheostomy with MV >96 Hours or 
Principal Diagnosis Except Face, Mouth and Neck Without Major O.R. 
Procedures). The applicant noted that they imputed a value of 11 cases 
for MS-DRGs with a case count lower than 11 for use in the weighted 
average calculations. The applicant noted that approximately 96% of 
identified cases were in MS-DRG 014, approximately 2% of identified 
cases were in MS-DRG 003, and approximately 2% of identified cases were 
in MS-DRG 004. The applicant stated that the cost threshold would still 
be exceeded even if the cases from DRGs 003 and 004 were excluded.
    The applicant then removed charges for the technology being 
replaced. According to the applicant, 100% of charges associated with 
drugs (revenue centers 025X, 026X, and 063X) were removed from the 
identified claims. The applicant stated that, while some other drugs 
would still be required for patients treated with treosulfan during 
their inpatient hospital stay, the applicant removed 100% of total drug 
charges to be as conservative as possible. Next, the applicant 
standardized charges using the FY 2022 IPPS/LTCH PPS final rule impact 
file and applied a 4-year inflation factor (1.281834) based on the 
inflation factor used in the FY 2022 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges. As the price of treosulfan 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 divide the wholesale acquisition cost (WAC) of treosulfan (per 
gram) by the national CCR for drugs from the FY 2022 IPPS/LTCH PPS 
final rule (0.187) to calculate estimated average hospital charges 
associated with treosulfan. The applicant also noted that no other 
charges related to the administration of treosulfan are expected to be 
added.
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $363,789, which exceeded the average 
case-weighted threshold amount of $260,833. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that 
treosulfan meets the cost criterion.
    We note that the applicant did not remove claims from PPS-excluded 
cancer hospitals that can be identified by a ``V'' in the fifth 
position of their provider number or an ``E'' or ``F'' in the sixth 
position in their Medicare certification number. We further note that 
many HSCTs are done by cancer centers not paid under IPPS and typically 
have higher charges, which may inflate the cost calculation. Since 
these hospitals are not paid under IPPS, their claims should not be 
included in the calculation of the charges for cases. We believe 
estimates from an analysis excluding PPS-exempt hospitals would be more 
appropriate for this cost analysis. Finally, we also note that the 
leukemia patients in treosulfan's clinical evidence \497\ were in 
remission and posit that codes only specifying remission should be 
included in the cost analysis. We invite public comments on whether 
treosulfan meets the cost criterion.
---------------------------------------------------------------------------

    \497\ Beelen DW 2019 Treosulfan or busulfan plus fludarabine as 
conditioning treatment before allogeneic aemopoietic stem cell 
transplantation for older patients with acute myeloid leukaemia or 
myelodysplastic syndrome (MC-FludT.14/L): A randomised, non-
inferiority, phase 3 trial. The Lancet Haematol https://doi.org/10.1016/S2352-3026(19)30157-7.
---------------------------------------------------------------------------

    With respect to the substantial clinical improvement criterion, the 
applicant asserted that treosulfan represents a substantial clinical 
improvement over existing technologies because it was designed to 
provide access to improved alloHSCT conditioning outcomes for patients 
that may otherwise be ineligible for MAC regimens due to its increased 
toxicity (for example, the elderly and patients with comorbidities), 
without the increased risk of relapse that is demonstrated to occur 
with RIC regimens. The applicant also asserted that treosulfan 
significantly improves clinical outcomes relative to services or

[[Page 28301]]

technologies previously available, including increased event free 
survival and overall survival at 24 months post-alloHSCT, reduced 
cumulative incidence of non-relapse mortality (NRM) at 24 months post-
alloHSCT, reduced cumulative incidence of treatment-related mortality 
(TRM) at 24 months post-alloHSCT, increased rate of graft-versus-host 
disease (GVHD)-free and relapse/progression-free survival at 24 months 
post-alloHSCT. To support its claims, the applicant provided two 
published articles, one published abstract, and two background 
articles.
    To support its claim that treosulfan represents a substantial 
clinical improvement over existing technologies because it was designed 
to provide access to improved alloHSCT conditioning outcomes for 
patients that may otherwise be ineligible for MAC regimens without the 
increased risk of relapse that is demonstrated to occur with RIC 
regimens, the applicant asserted that treosulfan-based regimens retain 
the beneficial properties from both MAC and RIC regimens with an 
efficacy profile comparable with that of conventional MAC regimens as 
they are associated with rapid engraftment, high levels of donor 
chimerism, and relatively low post-transplantation relapse 
rates.498 499 The applicant also cited background studies, 
which indicated that MAC regimens are currently the preferred standard 
of care for young patients given the reduced relapse rates for MAC 
patients as compared to RIC patients showing that MAC regimens produced 
less recurrence of disease.500 501
---------------------------------------------------------------------------

    \498\ Dietrich Wilhelm Beelen, et al., Treosulfan or Busulfan 
plus Fludarabine as Conditioning Treatment Before Allogeneic 
Haemopoietic Stem Cell Transplantation for Older patients with Acute 
Myeloid Leukemia or Myelodysplastic Syndrome (MC-Flud.T.14/L): A 
Randomised, Non-Inferiority, Phase 3 Trial, THE LANCET HAEMATOLOGY, 
Oct. 9, 2019.
    \499\ Dietrich Wilhelm Beelen, et al., Final Evaluation of a 
Clinical Phase III Trial Comparing Treosulfan to Busulfan-Based 
Conditioning Therapy Prior to Allogeneic Hematopoietic Stem Cell 
Transplantation of Adult Acute Myeloid Leukemia and Myelodysplastic 
Syndrome Patients Ineligible to Standard Myeloablative Regimens, 
BIOLOGY OF BLOOD AND MARROW TRANSPLANTATION, 2019; 25(3): S3.
    \500\ Scott, BL et al. 2017. Myeloablative Versus Reduced-
Intensity Hematopoietic Cell Transplantation for Acute Myeloid 
Leukemia and Myelodysplastic Syndromes. J. Clin Oncology 11: 1154.
    \501\ Dhere V et al. 2018. Myeloablative busulfan/cytoxan 
conditioning versus reduced-intensity fludarabine/melphalan 
conditioning for allogeneic hematopoietic stem cell transplant in 
patients with acute myelogenous leukemia Leuk Lymphoma. 2018 April; 
59(4): 837-843. doi:10.1080/10428194.2017.1361027.
---------------------------------------------------------------------------

    To support its claim that treosulfan significantly improves 
clinical outcomes relative to services or technologies previously 
available, the applicant provided a phase 3 open-label, non-
inferiority, randomized study of the use of treosulfan as part of a 
conditioning regimen in 31 transplant centers in 5 European 
countries.\502\ The authors compared a RIC regimen of treosulfan 10 gm/
m\2\ daily for 3 days (days 4 to 2 prior to the alloHSCT) plus 
fludarabine 30 mg/m\2\ daily for 5 days (6 to 2 days prior to the 
alloHSCT) to a RIC regimen containing busulfan (another alkylating 
agent) 0.8 mg/kg at 6 hour intervals on days 4 and 3 prior to the 
alloHSCT with the same dose of fludarabine. The initial protocol used a 
treosulfan dose of 14 gm/m\2\, but the protocol was modified to 10 gm/
m\2\, but the protocol was modified to 10 gm/m\2\ daily because of the 
prolonged neutropenia and subsequent infections with that dose. 
Eligible patients were aged 18 to 70 years with either AML in a first 
or complete remission or MDS with bone marrow blast counts >20% who 
were identified as appropriate for treatment with alloHSCT but were 
considered high risk for myeloablative conditioning because of age 
greater than or equal to 50 or comorbidities. 476 patients were 
enrolled (240 patients in the busulfan group received treatment and 
transplantation and were included in the full analysis population; 221 
patients in the treosulfan group received treatment, but only 220 
patients received transplantation and were included in the full 
analysis population). Study discontinuations were mainly due to disease 
progression prior to conditioning.
---------------------------------------------------------------------------

    \502\ Beelen DW 2019 Treosulfan or busulfan plus fludarabine as 
conditioning treatment before allogeneic aemopoietic stem cell 
transplantation for older patients with acute myeloid leukaemia or 
myelodysplastic syndrome (MC-FludT.14/L): A randomised, non-
inferiority, phase 3 trial. The Lancet Haematol https://doi.org/10.1016/S2352-3026(19)30157-7.
[GRAPHIC] [TIFF OMITTED] TP10MY22.117

    The applicant noted that other results from this study demonstrated 
no significant differences in engraftment with neutrophils, leukocytes, 
and platelets and graft versus host disease (overall, acute and 
chronic). The applicant also noted that the treosulfan treated group 
had higher incidences of complete chimerism at both 28- and 100-days 
post alloHSCT.
    The applicant also submitted an abstract \503\ containing a final 
evaluation of the results from the phase 3 study reported in the 
earlier publication.\504\ The authors of the abstract noted that the 
previous study was a confirmatory interim analysis (based on 476 
patients), and that results of the final analysis of all 570 randomized 
patients including post surveillance data were provided in this 
analysis. The full analysis in the abstract consisted of 551 patients: 
352 with AML and 199 with MDS. Treosulfan was given to 268 patients and 
busulfan was given to 283 patients. The median age of patients was 60 
years

[[Page 28302]]

(range 21-70). The median follow-up time was 29 months. The findings 
are shown in the following table.
---------------------------------------------------------------------------

    \503\ Beelen D 2019 Final Evaluation of a Clinical Phase III 
Trial Comparing Treosulfan to Busulfan-Based Conditioning Therapy 
Prior to Allogeneic Hematopoietic Stem Cell Transplantation of Adult 
Acute Myeloid Leukemia and Myelodysplastic Syndrome Patients 
Ineligible to Standard Myeloablative Regimens. Biol Blood Marrow 
Transplant 25 (2019) S3.
    \504\ Beelen DW 2019 Treosulfan or busulfan plus fludarabine as 
conditioning treatment before allogeneic aemopoietic stem cell 
transplantation for older patients with acute myeloid leukaemia or 
myelodysplastic syndrome (MC-FludT.14/L): A randomised, non-
inferiority, phase 3 trial. The Lancet Haematol https://doi.org/10.1016/S2352-3026(19)30157-7.
[GRAPHIC] [TIFF OMITTED] TP10MY22.118

    The applicant stated that the results of the phase 3 trial 
demonstrated that the treosulfan treatment group had increased event 
free survival (EFS) and overall survival (OS), with statistically 
significant improvements in EFS (p=0.0005787) and OS at 24 months post-
alloHSCT (p=0.0037) compared to the busulfan treatment group. The 
applicant also stated that the results of the phase 3 trial 
demonstrated that the treosulfan treatment group had reduced cumulative 
incidence of NRM and TRM, noting a statistically significant reduced 
cumulative incidence of NRM at 24 months post-alloHSCT (p=0.0343), as 
well as a reduced cumulative incidence of TRM at 24 months post-
alloHSCT (adjusted p value of 0.0043) compared to the busulfan 
treatment group. The applicant also cited a statistically significantly 
lower cumulative incidence of TRM caused by infections (adjusted p 
value of 0.0371) and lower cumulative incidence of TRM related to 
causes of death other than infections (adjusted p value of 0.0423). 
Furthermore, the applicant stated that the incidence of complete donor 
type chimerism was statistically significantly higher in the treosulfan 
treatment group compared with the busulfan treatment group (adjusted p 
value of 0.0381). Finally, the applicant stated that the results of the 
phase 3 trial demonstrated that the treosulfan treatment group had an 
increased rate of GVHD-free and relapse/progression-free survival at 24 
months post-alloHSCT compared to the busulfan treatment group (adjusted 
p value of 0.00087), as well as a higher chronic GVHD-free and relapse/
progression-free survival at 24 months (adjusted p value of 
0.003).505 506
---------------------------------------------------------------------------

    \505\ Ibid.
    \506\ Beelen D 2019 Final Evaluation of a Clinical Phase III 
Trial Comparing Treosulfan to Busulfan-Based Conditioning Therapy 
Prior to Allogeneic Hematopoietic Stem Cell Transplantation of Adult 
Acute Myeloid Leukemia and Myelodysplastic Syndrome Patients 
Ineligible to Standard Myeloablative Regimens. Biol Blood Marrow 
Transplant 25 (2019) S3.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether treosulfan meets the 
substantial clinical improvement criterion. We note that we were unable 
to verify the applicant's claims that the treosulfan treatment group 
had a statistically significant increased rate of acute and chronic 
GVHD-free and relapse/progression-free survival at 24 months post-
alloHSCT compared to the busulfan treatment group. We note that the 
Beelen et al. abstract cited by the applicant only provided an analysis 
of GVHD rates up to the 28-day follow-up visit, and stated that the 
incidences of acute and chronic GVHD were comparable between the two 
regimens (treosulfan and busulfan). We also note that the cumulative 
incidence of acute GVHD in the Beelen et al. interim analysis of 473 
patients submitted by the applicant was only analyzed at 100 days, and 
did not describe a statistically significant difference between the 
treosulfan and busulfan groups (acute GVHD grade 2-4, p=0.13; grade 3-
4, p=0.21); similarly, the cumulative incidence of chronic GVHD at 24 
months were not significantly different (chronic GVHD, p=0.52; 
extensive chronic GVHD, p=0.11). Furthermore, we note that the 
treosulfan and busulfan treatment groups did not have a statistically 
significant difference in cumulative incidence of relapse or 
progression incidence at 24 months (p=0.50).507 508
---------------------------------------------------------------------------

    \507\ Beelen D 2019 Final Evaluation of a Clinical Phase III 
Trial Comparing Treosulfan to Busulfan-Based Conditioning Therapy 
Prior to Allogeneic Hematopoietic Stem Cell Transplantation of Adult 
Acute Myeloid Leukemia and Myelodysplastic Syndrome Patients 
Ineligible to Standard Myeloablative Regimens. Biol Blood Marrow 
Transplant 25 (2019) S3.
    \508\ Beelen DW 2019 Treosulfan or busulfan plus fludarabine as 
conditioning treatment before allogeneic aemopoietic stem cell 
transplantation for older patients with acute myeloid leukaemia or 
myelodysplastic syndrome (MC-FludT.14/L): A randomised, non-
inferiority, phase 3 trial. The Lancet Haematol https://doi.org/10.1016/S2352-3026(19)30157-7.
---------------------------------------------------------------------------

    Finally, we note that the phase 3 trial \509\ was a non-inferiority 
trial, which is not designed to demonstrate superiority over other 
regimens, and may be subject to observer bias due to the lack of 
blinding. We also note that the studies provided were not powered to 
show that the treosulfan 10mg/m\2\ improved outcomes for patients 65 
and older, and therefore question whether the results may be 
generalizable to the Medicare population. Furthermore, the comparison 
of treosulfan with busulfan represents the testing of only one 
potential RIC regimen, and we note that there are other possible 
treatment regimens. For example, the applicant asserted that 
combination treatments including treosulfan can provide patients who 
are ineligible for MAC regimens access to a new treatment option. 
However, the applicant did not provide evidence that this treosulfan 
treatment combination improved outcomes relative to other current RIC 
regimens, besides busulfan and fludarabine used in their cited studies. 
We note that while the applicant stated that treosulfan demonstrates 
improved outcomes (reduces treatment-related toxicity and risk of TRM 
without increasing risk of relapse) as compared to MAC regimens and 
that it therefore offers a treatment option for patients ineligible for 
MAC, the proposed indications for treosulfan do not limit use to 
patients ineligible for MAC. We would appreciate additional information 
comparing outcomes with treosulfan-based regimens to MAC regimens. We 
are inviting public comments on whether treosulfan meets the 
substantial clinical improvement criterion.
---------------------------------------------------------------------------

    \509\ Ibid.
---------------------------------------------------------------------------

    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 
treosulfan.

[[Page 28303]]

l. UPLIZNA[supreg] (inebilizumab-cdon)
    HTI-DAC, the manufacturer under the distributor Horizon 
Therapeutics USA, Inc., submitted an application for new technology 
add-on payment for UPLIZNA[supreg] (inebilizumab-cdon) for FY 2023. Per 
the applicant, UPLIZNA[supreg] is the first FDA-approved anti-cluster 
of differentiation 19 (CD19) B-cell depleter for the treatment of 
neuromyelitis optica spectrum disorder (NMOSD) in adults who are anti-
aquaporin-4 (AQP4) antibody positive, for which 80% of all patients 
with NMOSD test positive.\510\ According to the applicant, the goal of 
UPLIZNA[supreg] is to reduce the risk of relapse and disability 
progression. The applicant explained UPLIZNA[supreg] is a CD19+ B cell-
directed humanized afucosylated immunoglobulin F1 (IgG1) monoclonal 
antibody. The applicant further explained that CD19 is a cell surface 
antigen expressed on a broad range of B lymphocytes. Per the applicant, 
UPLIZNA[supreg] is a B-cell depleter that binds specifically to CD19, 
allowing it to target an extended range of B-cells that play a role in 
NMOSD. The applicant stated that following cell surface binding to 
CD19+ B lymphocytes, UPLIZNA[supreg] causes antibody-dependent cellular 
cytolysis (ADCC), resulting in significant and robust B-cell depletion.
---------------------------------------------------------------------------

    \510\ Wingerchuck, D. (2009, November 15). Neuromyelitis optica: 
Effect of gender. Journal of the Neurological Sciences. Retrieved 
October 6, 2021, from https://pubmed.ncbi.nlm.nih.gov/19740485/.
---------------------------------------------------------------------------

    NMOSD is a rare, severe autoimmune disease of the central nervous 
system that causes damage to the optic nerve, spinal cord, and brain 
stem. NMOSD affects approximately 10,000-15,000 people in the United 
States, and the incidence rate may be up to 9 times higher for women 
than for men, with prevalence approximately 2- to 3-fold higher among 
Black and Asian populations.\511\ According to the applicant, NMOSD is 
characterized by unpredictable, recurrent attacks of inflammation of 
the optic nerve (optic neuritis) and/or of the spinal cord (transverse 
myelitis), and may also affect regions of the brain. The applicant 
stated that attacks can be severe and result in life-altering permanent 
disability, such as blindness and paralysis, and that recurring attacks 
can have cumulative effects resulting in significant morbidity. 
According to the applicant, aquaporin-4 antibodies are highly specific 
to NMOSD and AQP4 is expressed on astrocytes throughout the central 
nervous system. Per the applicant, in NMOSD, AQP4 antibodies bind to 
AQP4, resulting in astrocyte cell death and inflammation. The applicant 
stated that a sub-population of B-lineage cells, CD19+ plasmablasts, 
produce AQP4 antibodies and that certain CD19+ B-cells are increased in 
the blood of AQP4-seropositive individuals with NMOSD, with the highest 
levels observed during an attack. According to the applicant, by 
depleting a wide range of B-cells that express CD19 (including 
plasmablasts and some plasma cells), UPLIZNA[supreg] reduces the risk 
of relapses or attacks that may lead to permanent disability in NMOSD 
patients.
---------------------------------------------------------------------------

    \511\ Flanagan, E.P. et al. (2016, April 4). Epidemiology of 
aquaporin[hyphen]4 autoimmunity and Neuromyelitis Optica Spectrum. 
Wiley Online Library. Retrieved October 6, 2021, from https://onlinelibrary.wiley.com/doi/10.1002/ana.24617.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that 
UPLIZNA[supreg] was designated as a Breakthrough Therapy and received 
Orphan Drug designation on February 10, 2016 for the treatment of 
NMOSD.\512\ Per the applicant, UPLIZNA[supreg] received FDA approval on 
June 11, 2020, for the treatment of NMOSD in adult patients who are 
AQP4 antibody positive (BLA #761142). The applicant stated that 
UPLIZNA[supreg] became commercially available on July 9, 2020, 
following FDA approval. According to the applicant, UPLIZNA[supreg] is 
administered as an intravenous infusion, and titrated to completion, 
over approximately 90 minutes under the close supervision of an 
experienced healthcare professional. The applicant stated that the 
recommended initial dose is a 300 mg intravenous infusion followed 2 
weeks later by a second 300 mg intravenous infusion. The applicant also 
stated that subsequent doses, starting 6 months from the first 
infusion, consist of a single 300 mg intravenous infusion every 6 
months.
---------------------------------------------------------------------------

    \512\ U.S. Food and Drug Administration website: https://www.accessdata.fda.gov/scripts/opdlisting/oopd/listResult.cfm.
---------------------------------------------------------------------------

    According to the applicant, there are currently no ICD-10-PCS 
procedure codes that uniquely identify the use of UPLIZNA[supreg]. 
However, the applicant stated that the following procedure codes may be 
used to identify administration of UPLIZNA[supreg] in the inpatient 
setting, though they are not specific to UPLIZNA[supreg]: 3E033GC 
(Introduction of other therapeutic substance into the peripheral vein, 
percutaneous approach) or 3E043GC (Introduction of other therapeutic 
substance into central vein, percutaneous approach). The applicant 
submitted a request for approval of a unique ICD-10-PCS procedure code 
to identify use of the technology beginning in FY 2023. 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 purposes of new technology add-on payments. 
According to the applicant, the only approved treatments for NMOSD are 
UPLIZNA[supreg], Soliris[supreg] (eculizumab), and 
ENSPRYNGTM (satralizumab). We note that 
ENSPRYNGTM and Soliris[supreg] previously submitted 
applications for new technology add-on payments. Please see discussion 
of ENSPRYNGTM in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45019 through 45028) and Soliris[supreg] in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58684 through 58689).
    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 UPLIZNA[supreg] is the only treatment for 
NMOSD that targets B-cells and causes B-cell depletion. The applicant 
contrasted the mechanism of action of UPLIZNA[supreg] with those of 
Soliris[supreg] and ENSPRYNGTM. Per the applicant, the 
mechanism of action of Soliris[supreg] is the inhibition of aquaporin-
4-antibody induced terminal complement C5b-9 deposition.\513\ The 
applicant explained that Soliris[supreg] specifically binds to 
complement protein C5, inhibiting its cleavage to C5a and C5b and 
preventing the generation of C5b-9. The applicant also stated that 
ENSPRYNGTM is a recombinant humanized anti-human 
interleukin-6 (IL-6) receptor monoclonal antibody. Per the applicant, 
the mechanism of action of ENSPRYNGTM involves the 
inhibition of IL-6-mediated signaling through binding to soluble and 
membrane-bound IL-6 receptors.\514\ Thus, the applicant asserted that 
each of the three FDA approved treatments for NMOSD--UPLIZNA[supreg], 
Soliris[supreg], and ENSPRYNGTM--bind to a different 
molecular target and have different mechanisms of action.
---------------------------------------------------------------------------

    \513\ U.S. Food and Drug Administration. (2019, June). Soliris 
Prescribing Information. Retrieved October 6, 2021, from https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/125166s431lbl.pdf.
    \514\ Genentech. (2020, August). ENSPRYNG Factsheet. Retrieved 
October 6, 2021, from https://www.gene.com/download/pdf/genentech_enspryng_factsheet.pdf.
---------------------------------------------------------------------------

    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 cases representing patients who 
may be eligible for treatment with UPLIZNA[supreg] map to MS-DRGs 058, 
059, or 060 (Multiple Sclerosis and Cerebellar Ataxia with

[[Page 28304]]

MCC, with CC, or without CC/MCC, respectively), which are the same MS-
DRGs to which existing technologies may also be assigned.
    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 asserted that, while UPLIZNA[supreg] 
treats a patient population with the same type of disease (NMOSD) as 
Soliris[supreg] or ENSPRYNGTM, it offers a treatment option 
for a subset of this patient population, which differentiates it from 
existing technologies. Per the applicant, UPLIZNA[supreg] has not been 
shown to carry an increased risk of meningitis and may be used in 
patient populations who are unvaccinated with the meningococcal vaccine 
and/or are not able to use prophylactic antibiotics. The applicant 
noted that while patients with NMOSD who are unvaccinated with the 
meningococcal vaccine can still receive other approved treatments for 
NMOSD, such as Soliris[supreg] or ENSPRYNGTM, they need to 
have a risk reduction protocol instituted at the time of treatment and, 
in some cases, may require two weeks of prophylactic antibacterial 
treatment first.515 516
---------------------------------------------------------------------------

    \515\ Soliris[supreg] prescribing details: https://solirispro.com/pdf/Soliris_USPI.pdf.
    \516\ ENSPRYNGTM prescribing information: https://www.gene.com/download/pdf/enspryng_prescribing.pdf.
---------------------------------------------------------------------------

    In summary, the applicant maintained that UPLIZNA[supreg] is not 
substantially similar to other currently available therapies and/or 
technologies because it uses a new mechanism of action and treats a 
different subset of the patient population with NMOSD compared to an 
existing technology.
    We note that the applicant asserts that UPLIZNA[supreg] treats a 
different subset of the patient population with NMOSD compared to 
existing technologies, specifically patients who are unvaccinated with 
the meningococcal vaccine. However, we question whether this subset is 
considered a new patient population since, as previously discussed in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45021), 
ENSPRYNGTM is also not contraindicated in patients with 
unresolved serious Neisseria meningitidis infections, and therefore, 
may be a treatment option for patients with meningococcal disease as 
well as UPLIZNA[supreg]. Furthermore, as we previously stated in the FY 
2022 IPPS/LTCH PPS final rule, individuals that are not vaccinated 
against Neisseria mengitidis are not considered a separate patient 
population because eligibility can be easily attained via a widely 
available vaccine (86 FR 45027). Additionally, we question whether the 
additional requirements for patients taking Soliris[supreg]--namely 
participation in a risk reduction protocol related to the associated 
risk of meningococcal infections, and prophylactic antibiotic treatment 
that may result in a 2-week delay for treatment--constitute a new 
patient population for technologies without those requirements.
    We are inviting public comments on whether UPLIZNA[supreg] is 
substantially similar to existing technologies and whether 
UPLIZNA[supreg] meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 Medicare 
Provider Analysis and Review (MedPAR) Hospital Limited Data Set (LDS) 
for cases with ICD-10-CM diagnosis code G36.0 for Neuromyelitis optica 
[Devic] (NMOSD) coded in the first diagnosis position. The applicant 
determined that cases representing patients who may be eligible for 
treatment with UPLIZNA[supreg] would map to MS-DRGs 058, 059, or 060 
(Multiple Sclerosis and Cerebellar Ataxia with MCC, with CC, or without 
CC/MCC, respectively).
    The applicant determined a case count of 257 after imputing a value 
of 11 for MS-DRGs with a case volume under 11. The applicant then 
removed 100% of the drug charges to estimate the potential decrease in 
costs due to the use of UPLIZNA[supreg]. The applicant noted that, 
although use of UPLIZNA[supreg] would replace current drug charges for 
therapies such as azathioprine, methotrexate, and rituximab, it is not 
possible to differentiate between drug costs on MedPAR claims, and so 
it removed all drug charges to be conservative. The applicant then 
standardized the charges and applied a 4-year inflation factor of 
1.281834, or 28.1834%, based on the inflation factor used to update the 
outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542). The applicant added charges for the new technology by dividing 
the estimated cost of UPLIZNA[supreg] by the national average CCR for 
drugs which is 0.187, from the FY 2022 IPPS/LTCH PPS final rule (86 FR 
44966).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $764,547, which exceeded the average 
case-weighted threshold amount of $48,165. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant asserted that 
UPLIZNA[supreg] meets the cost criterion.
    We are inviting public comments on whether UPLIZNA[supreg] meets 
the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant made two assertions. First, the applicant asserted that 
UPLIZNA[supreg] offers a treatment option for a patient population that 
is ineligible for currently available treatments. Specifically, the 
applicant asserted that UPLIZNA[supreg] is a new treatment option for 
patients who carry an increased risk of meningitis, patients following 
treatments with more frequent and burdensome dosing schedules, and 
patient populations more likely to be impacted by health disparities. 
Finally, the applicant asserted that UPLIZNA[supreg] significantly 
improves clinical outcomes relative to currently available technologies 
because it reduced the risk of NMOSD attacks and disability progression 
among patients with NMOSD when compared to placebo in the N-MOmentum 
trial, which the applicant asserted is the largest NMOSD study 
conducted.\517\
---------------------------------------------------------------------------

    \517\ Marignier, R. et al., (2021, March 26). Disability 
Outcomes in the N-MOmentum Trial of Inebilizumab in Neuromyelitis 
Optica Spectrum Disorder. Neurology[supreg] neuroimmunology & 
neuroinflammation. Retrieved October 6, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054974/.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that UPLIZNA[supreg] is a 
substantial clinical improvement over existing technologies because it 
represents a new treatment option for a patient population ineligible 
for currently available treatments, the applicant stated that 
UPLIZNA[supreg] may be used in patient populations who are unvaccinated 
with the meningococcal vaccine and/or are not able to use prophylactic 
antibiotics because UPLIZNA[supreg] has not been shown to carry an 
increased risk of meningitis, as compared with Soliris[supreg].
    To support this claim, the applicant cited an article from the CDC 
explaining that patients taking complement inhibitors, such as 
Soliris[supreg], are at an increased risk for meningococcal disease 
\518\ and referenced the CDC's recommendation that patients receive the 
meningococcal vaccination prior to initiating treatment with a 
complement inhibitor. The applicant also cited a

[[Page 28305]]

study by McNamara et al.\519\ that identified 16 cases in the U.S. 
between 2008 and 2016 of patients who were taking Soliris[supreg] who 
had meningococcal disease despite having received at least 1 dose of 
meningococcal vaccine before disease onset. Referring to the same 
article by McNamara et al., the applicant stated that some healthcare 
providers recommend prophylactic antibiotics even for vaccinated 
patients during treatment with Soliris[supreg], exposing them to long-
term antibiotic use, which carries the risk of developing antimicrobial 
resistance.
---------------------------------------------------------------------------

    \518\ Centers for Disease Control and Prevention. (2019, May 
31). Taking complement inhibitors increases risk for meningococcal 
disease/CDC. Centers for Disease Control and Prevention. Retrieved 
October 1, 2021, from https://www.cdc.gov/meningococcal/about/soliris-patients.html.
    \519\ McNamara, L. et al. (2017, July 7). High Risk for Invasive 
Meningococcal Disease Among Patients Receiving Eculizumab (Soliris) 
Despite Receipt of Meningococcal Vaccine Retrieved October 6, 2021, 
from https://www.cdc.gov/mmwr/volumes/66/wr/pdfs/mm6627e1.pdf.
---------------------------------------------------------------------------

    Furthermore, the applicant claimed that UPLIZNA[supreg] represents 
a new treatment option for patients following treatments with more 
frequent and burdensome dosing schedules than UPLIZNA[supreg]. Per the 
applicant, the dosing schedule for UPLIZNA[supreg] consists of 2 
initial doses delivered 2 weeks apart, followed by 1 dose every 6 
months after that.\520\ In comparison, based on the FDA prescribing 
information for Soliris[supreg], the applicant asserted that 
UPLIZNA[supreg]'s 6-month dosing regimen is less frequent than that of 
Soliris[supreg], and, therefore, is less burdensome to follow.\521\ The 
applicant asserted the dosing schedule for UPLIZNA[supreg] is more 
amenable to NMOSD patients for whom more frequent intravenous infusions 
may be burdensome and stated that its characteristics as a treatment 
regimen, compared to SolirisTM, may help to improve 
medication adherence and decrease likelihood of relapse and 
hospitalization relative to placebo. To further demonstrate that 
UPLIZNA[supreg] may help to improve long-term patient adherence, 
compared to SolirisTM, the applicant provided a review by 
Vlasnik et al.\522\ noting that medication regimen complexity is one 
factor that can negatively affect adherence. The applicant emphasized 
that, for NMOSD, medication adherence to maintain immune suppression is 
essential for reducing the risk of attacks, which can lead to 
hospitalization, vision loss and paralysis. Finally, the applicant 
stated that UPLIZNA[supreg] poses less of a barrier for patient access, 
as it does not require patients or providers to participate in FDA's 
Risk Evaluation and Mitigation Strategy (REMS) program, or receive 
additional counselling regarding the program, as required by 
Soliris[supreg].\523\
---------------------------------------------------------------------------

    \520\ U.S. Food and Drug Administration. (2007, March). 
Highlights of prescribing information administration. Retrieved 
October 6, 2021, from https://www.accessdata.fda.gov/drugsatfda_docs/label/2007/125166lbl.pdf.
    \521\ U.S. Food and Drug Administration. Alexion briefing 
information for the November 18, 2014, meeting of the Drug Safety 
and Risk Management Advisory Committee. https://www.fda.gov/advisory-committees/human-drug-advisory-committees/drug-safety-and-risk-management-advisory-committee.
    \522\ Vlasnik, J.J., Aliotta, S.L., & DeLor, B. (2005, April 7). 
Medication adherence: Factors influencing compliance with prescribed 
medication plans. The Case Manager. Retrieved October 6, 2021, from 
https://www.sciencedirect.com/science/article/abs/pii/S1061925905000263?via%3Dihub.
    \523\ Alexion Pharmaceutical, Inc. (2020). Soliris REMS. 
Retrieved October 6, 2021, from https://solirisrems.com/.
---------------------------------------------------------------------------

    To support its claim that UPLIZNA[supreg] is a new treatment option 
for populations that are more likely to be impacted by health 
disparities, the applicant noted UPLIZNA[supreg]'s durable efficacy and 
favorable safety profile among African Americans with NMOSD. To support 
this claim, the applicant cited the safety results published by Cree et 
al.\524\ from both a randomized control period (RCP) and an open label 
period (OLP) of the N-MOmentum trial. The RCP phase of N-Momentum was a 
multicenter, double-blind, \2/3\ study conducted at 99 outpatient 
specialty clinics or hospitals in 25 countries that lasted up to 197 
days. The primary endpoint was time to onset of an NMOSD attack, as 
determined by the investigator and adjudication committee. Eligible 
participants were randomized in a 3:1 ratio to receive either 300 mg 
intravenous UPLIZNA[supreg] (n=174) or a saline placebo (n=56) on days 
1 and 15. Participants continued through the RCP for up to 28 weeks 
unless they had a confirmed NMOSD attack, at which point they could 
choose to continue in the OLP phase of the trial. The OLP included 
eligible adult participants (n=230) who had had at least 1 NMOSD attack 
in the year before screening or at least 2 attacks requiring rescue 
therapy in the 2 years before screening. During the OLP, all patients 
received UPLIZNA[supreg] for at least 2 years. As recommended by an 
independent committee, enrollment in the RCP phase stopped prior to 
study completion due to the early findings where 21 of 174 participants 
(12%) receiving UPLIZNA[supreg] had an attack as compared with 22 of 
the 56 placebo recipients (39%). Marignier et al. (2021) assessed 
treatment effects in N-MOmentum by measuring score worsening of the 
Expanded Disability Status Scale (EDSS) and modified Rankin Scale (mRS) 
scores.\525\ EDSS scores were measured at baseline, then at RCP study 
weeks 12 and 28, and every 3 months during the OLP, and within 5 days 
of a potential attack. mRS scores were measured at baseline, and at 
weeks 4, 8, 12, 16, 22, and 28 of the RCP. The Marignier results from 
the N-MOmentum study found the annualized attack rate for African 
Americans was lower at 0.06 compared to an annualized attack rate of 
0.09 in the overall group exposed to UPLIZNA[supreg]. The applicant 
stated that among the 19 African American participants who received 
UPLIZNA[supreg] or placebo during the RCP and/or OLP of the N-MOmentum 
trial, three had attacks 18, 29, and 104 days after their first 
UPLIZNA[supreg] dose. The summary of baseline demographics and 
characteristics of the intent-to-treat population notes that there were 
14 African American participants who received UPLIZNA[supreg] and 5 who 
received the placebo.\526\
---------------------------------------------------------------------------

    \524\ Cree BAC, Bennett J.L., Kim H.J., Weinshenker B.G., 
Pittock S.J., Wingerchuk D.M., Fujihara K., Paul F., Cutter G.R., 
Marignier R., Green A.J., Aktas O., Hartung H.P., Lublin F.D., 
Drappa J., Barron G., Madani S., Ratchford J.N., She D., Cimbora D., 
Katz E.; N-MOmentum study investigators. Inebilizumab for the 
treatment of neuromyelitis optica spectrum disorder (N-MOmentum): a 
double-blind, randomised placebo-controlled phase \2/3\ trial. 
Lancet. 2019 Oct 12;394(10206):1352-1363. doi: 10.1016/S0140-
6736(19)31817-3. Epub 2019 Sep 5. PMID: 31495497.
    \525\ Marignier R., Bennett J.L., Kim H.J., Weinshenker B.G., 
Pittock S.J., Wingerchuk D., Fujihara K., Paul F., Cutter G.R., 
Green A.J., Aktas O., Hartung H.P., Lublin F.D., Williams I.M., 
Drappa J., She D., Cimbora D., Rees W., Smith M., Ratchford J.N., 
Katz E., Cree BAC; N-MOmentum Study Investigators. Disability 
Outcomes in the N-MOmentum Trial of Inebilizumab in Neuromyelitis 
Optica Spectrum Disorder. Neurol Neuroimmunol Neuroinflamm. 2021 Mar 
26;8(3):e978. doi: 10.1212/NXI.0000000000000978. PMID: 33771837; 
PMCID: PMC8054974.
    \526\ Ibid.
---------------------------------------------------------------------------

    With respect to its claim that UPLIZNA[supreg] significantly 
improves clinical outcomes relative to previously available treatment 
options, the applicant stated that patients taking UPLIZNA[supreg] had 
a reduced risk of NMOSD attacks and disability progression when 
compared to placebo in the N-MOmentum trial. The applicant again 
referenced the results of the N-MOmentum trial reported by Cree et al., 
where 21 (12%) of the 174 participants receiving UPLIZNA[supreg] had an 
attack by the time enrollment ended versus 22 (39%) of the 56 
participants receiving placebo (hazard ratio (HR) 0[middot]272 [95% CI 
0[middot]150-0[middot]496]; p<0[middot]0001). The applicant also 
referred to the N-MOmentum results from the OLP and asserted that they 
show long-term treatment with UPLIZNA[supreg] provided a sustained 
reduction in NMOSD attack risk, MRI lesions, and NMOSD-related 
hospitalizations regardless of treatment provided during the RCP. The 
applicant

[[Page 28306]]

referenced the disability data published by Marignier et al.\527\ from 
the results of the N-MOmentum trial on the use of UPLIZNA[supreg] and 
asserted that they showed favorable results among patients with NMOSD 
when compared to placebo. Specifically, Marignier et al. assessed the 
treatment effects of UPLIZNA[supreg] in comparison with placebo by 
using a worsening score of the Expanded Disability Status Scale (EDSS) 
to measure confirmed disability progression (CDP). The applicant 
asserted that the results show UPLIZNA[supreg] reduced the risk of 3-
month CDP compared with placebo (HR: 0.375; 95% CI: 0.148-0.952; p = 
0.0390). The applicant also stated that UPLIZNA[supreg] showed a 
significantly lower risk of relapse among patients with NMOSD when 
compared to placebo. The applicant cited results from Pittock et 
al.,\528\ a randomized, double-blind, time-to-event trial in which 143 
adult subjects were randomly assigned to receive either UPLIZNA[supreg] 
or placebo weekly and continued use of an immunosuppressive therapy, as 
needed. The primary endpoint was the first adjudicated relapse, while 
secondary endpoints included the adjudicated annualized relapse rate. 
Pittock et al. reported that adjudicated relapses occurred in 3 of 96 
patients (3%) in the UPLIZNA[supreg] group and 20 of 47 (43%) in the 
placebo group (hazard ratio 0.06; 95% confidence interval [CI], 0.02 to 
0.20; P<0.001). The adjudicated annualized relapse rate was 0.02 in the 
eculizumab group and 0.35 in the placebo group (rate ratio, 0.04; 95% 
CI, 0.01 to 0.15; P<0.001). Referring to the results from the Pittock 
et al. study, the applicant asserted that UPLIZNA[supreg] showed a 
consistent effect in reducing the risk of attack compared to placebo, 
regardless of baseline disability status, attack history, or disease 
duration.\529\
---------------------------------------------------------------------------

    \527\ Marignier R., Bennett J.L., Kim H.J., Weinshenker B.G., 
Pittock S.J., Wingerchuk D., Fujihara K., Paul F., Cutter G.R., 
Green A.J., Aktas O., Hartung H.P., Lublin F.D., Williams I.M., 
Drappa J., She D., Cimbora D., Rees W., Smith M., Ratchford J.N., 
Katz E., Cree BAC; N-MOmentum Study Investigators. Disability 
Outcomes in the N-MOmentum Trial of Inebilizumab in Neuromyelitis 
Optica Spectrum Disorder. Neurol Neuroimmunol Neuroinflamm. 2021 Mar 
26;8(3): e978. doi: 10.1212/NXI.0000000000000978. PMID: 33771837; 
PMCID: PMC8054974.
    \528\ Pittock S.J., Berthele A., Fujihara K., Kim H.J., Levy M., 
Palace J., Nakashima I., Terzi M., Totolyan N., Viswanathan S., Wang 
K.C., Pace A., Fujita K.P., Armstrong R., Wingerchuk D.M. Eculizumab 
in Aquaporin-4-Positive Neuromyelitis Optica Spectrum Disorder. N 
Engl J Med. 2019 Aug 15;381(7):614-625. doi: 10.1056/NEJMoa1900866. 
Epub 2019 May 3. PMID: 31050279.
    \529\ Ibid.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we have 
the following concerns regarding whether UPLIZNA[supreg] meets the 
substantial clinical improvement criterion. First, we note that while 
the applicant provided data comparing UPLIZNA[supreg] to placebo, we 
did not receive any data to demonstrate improved outcomes over existing 
FDA approved treatments. Additional information comparing outcomes such 
as relapse rate, risk of relapse, and disability progression for 
patients receiving UPLIZNA[supreg] versus other currently available 
treatments would help inform our assessment of whether UPLIZNA[supreg] 
demonstrates a substantial clinical improvement over existing 
technologies. Second, while the applicant asserted that UPLIZNA[supreg] 
represents a new treatment option for patients who are unvaccinated 
with the meningococcal vaccine, similar to the discussion in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45021) in response to a similar 
assertion with respect to ENSPRYNGTM, we note that 
ENSPRYNG[supreg] is also not contraindicated in patients with 
unresolved serious Neisseria meningitidis infection and therefore may 
also be a treatment option for patients with meningococcal disease. We 
further note that the use of ENSPRYNGTM to treat patients 
with NMOSD also does not require a meningococcal vaccination. We note 
that the applicant sought to support its claim that UPLIZNA[supreg] 
represents a new treatment option for patients who are unvaccinated 
against Neisseria meningitidis through the inference that 
Soliris[supreg] has a high risk of causing meningitis; however, we have 
concerns about the applicant's claim because Neisseria meningitidis may 
easily be mitigated through the use of a common vaccine or 
antimicrobials. As discussed in the FY 2022 IPPS/LTCH PPS final rule in 
response to similar claims with respect to ENSPRYNG[supreg], and as 
noted previously, individuals that are not vaccinated against Neisseria 
mengitidis are not considered a separate patient population because 
eligibility can be easily attained via a widely available vaccine and 
are also able to receive treatment with UPLIZNA[supreg] which does not 
require a vaccine (86 FR 45027).
    With regard to the applicant's claim that UPLIZNA[supreg] is a new 
treatment option for patients following treatments with more frequent 
dosing schedules, we are unsure whether these patients may be 
considered as a separate patient population ineligible for currently 
available treatments. For example, although the applicant compared the 
UPLIZNA[supreg] dosing regimen against Soliris[supreg], it did not 
provide a similar comparison against ENSPRYNGTM, which--
similar to UPLIZNA[supreg]--does not require frequent intravenous 
infusions or participation in the FDA REMS program (see 86 FR 45020). 
Therefore, it is unclear whether UPLIZNA[supreg] provides a treatment 
option for a separate patient population that is ineligible for 
currently available treatments, when there are other available 
treatments, like ENSPRYNGTM, without the limitations that 
the applicant described with respect to Soliris[supreg]. In addition, 
while the applicant stated that UPLIZNA[supreg]'s dosing regimen may 
help to improve long-term patient medication adherence and decrease the 
likelihood of relapse and hospitalization, we question the strength of 
the correlation between UPLIZNA's[supreg] dosing regimen and these 
outcomes. We are also interested in additional information on the 
efficacy results of UPLIZNA[supreg] among African Americans with NMOSD, 
as cited by the applicant, as we understand that NMOSD 
disproportionately affects African American and Asian populations at 
rates approximately 2- to 3-fold higher than their Caucasian 
counterparts.\530\ Specifically, we question whether the retrospective 
analysis of the results from the N-MOmentum trial on the annualized 
attack rate for African Americans (0.06 compared with 0.09 in the 
overall group) is generalizable to larger populations because the study 
included low numbers of participants. Of the 20 African American 
participants randomized in N-Momentum, 19 were AQP4 antibody positive 
and 1 was AQP4 antibody negative. As a result, of the 19 participants, 
14 received UPLIZNA[supreg], and only 5 received 
placebo.531 532 We further note that the applicant did not 
provide comparative data on the efficacy of UPLIZNA[supreg], 
Soliris[supreg], and ENSPRYNGTM in these populations.
---------------------------------------------------------------------------

    \530\ Flanagan, E.P. et al. (2016, April 4). Epidemiology of 
aquaporin[hyphen]4 autoimmunity and Neuromyelitis Optica Spectrum. 
Wiley Online Library. Retrieved October 6, 2021, from https://onlinelibrary.wiley.com/doi/10.1002/ana.24617.
    \531\ Bernitsas, E., Cimbora, D., Dinh, Q., She, D., Katz, E. 
Safety and Efficacy of Inebilizumab in African Americans with 
Neuromyelitis Optica Spectrum Disorder. Poster presentation at the 
15th World Congress on Controversies in Neurology (CONy Virtual). 
September 23-26, 2021.
    \532\ Cree BAC, Bennett JL, Kim HJ, Weinshenker BG, Pittock SJ, 
Wingerchuk DM, Fujihara K, Paul F, Cutter GR, Marignier R, Green AJ, 
Aktas O, Hartung HP, Lublin FD, Drappa J, Barron G, Madani S, 
Ratchford JN, She D, Cimbora D, Katz E; N-MOmentum study 
investigators. Inebilizumab for the treatment of neuromyelitis 
optica spectrum disorder (N-MOmentum): A double-blind, randomised 
placebo-controlled phase \2/3\ trial. Lancet. 2019 Oct 
12;394(10206):1352-1363. doi: 10.1016/S0140-6736(19)31817-3. Epub 
2019 Sep 5. PMID: 31495497.
---------------------------------------------------------------------------

    We are inviting public comments on whether UPLIZNA[supreg] meets 
the

[[Page 28307]]

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 
UPLIZNA[supreg].
m. XENOVIEW (hyperpolarized Xenon-129 [HP \129\Xe] gas for inhalation)
    Polarean, Inc. and The Institute for Quality Resource Management 
(collectively referred to as ``applicant'') submitted an application 
for new technology add-on payments for XENOVIEW for FY 2023. Per the 
applicant, XENOVIEW is a gas blend used in chest magnetic resonance 
imaging (MRI) that is processed to consist of 89% Helium, 10% Nitrogen, 
and 1% Xenon. The applicant stated that the 1% Xenon in the gas blend 
is hyperpolarized (HP) to create Xenon-129 (\129\Xe) (that is, 80% 
purity of \129\Xe isotope), which allows for high resolution 3-
dimensional (3-D) images of the lungs and assessment of the lungs' 
functional status when inhaled by a patient during a pulmonary MRI 
scan. The applicant stated that XENOVIEW rapidly and directly 
quantifies regional lung function without ionizing radiation or 
compromising patient comfort and aids clinical decision-making by 
directly quantifying gas exchange across three compartments (airspace 
and ventilation, interstitial barrier tissues, and transfer to red 
blood cells (RBCs)) to provide a complete picture of lung function. The 
applicant stated that this makes it well-suited for longitudinal 
therapeutic evaluation and assessment of disease progression.\533\
---------------------------------------------------------------------------

    \533\ Wang Z, Rankine L, Bier EA, Mummy D, Lu J, et al. Using 
hyperpolarized \129\Xe gas exchange MRI to model the regional 
airspace, membrane and capillary contributions to diffusing 
capacity. J Appl Physiology 130: 1398-1409, 2021.
---------------------------------------------------------------------------

    The applicant stated that hyperpolarization of \129\Xe gas is 
generated by using the combination hyperpolarization system consisting 
of the \129\Xe gas cylinder, Hyperpolarizer, Measurement Station, and 
Dose Delivery Bag. The applicant noted that hospital trained clinical 
personnel use this drug system to activate the XENOVIEW from the 
initial gas blend cylinder, and to make HP \129\Xenon immediately prior 
to patient administration. The applicant explained that collectively, 
these components hyperpolarize (using the Xenon Hyperpolarizer) and 
measure the hyperpolarization of \129\Xe gas (using the Polarization 
Measurement Station), and then the clinician administers the XENOVIEW 
Dose Equivalent (DE) to the patient using the Polarean DE Dose Delivery 
Bag during a pulmonary MRI scan.
    According to the applicant, XENOVIEW MRIs can be used to spatially 
characterize disease burden across a range of pulmonary disorders and 
lung abnormalities, including asthma, cystic fibrosis (CF), 
bronchiolitis obliterans, interstitial lung disease, patients 
recommended for surgical lung resection, post-lung transplant patients, 
and people diagnosed with chronic obstructive pulmonary disease (COPD). 
The applicant noted specifically that defects in all three compartments 
of lung function are commonly seen in COPD, and that XENOVIEW has been 
used to assess regional lung function in patients recommended for 
surgical lung resection as well as in post-lung transplant patients to 
sooner diagnose a failing transplant (where corrective action is needed 
to save the lung). Per the applicant, the estimated patient prevalence 
of these conditions is over 40 million diagnoses in the United States.
    With respect to the newness criterion, the applicant stated it is 
pursuing an NDA from FDA for XENOVIEW as a drug combination for the 
evaluation of pulmonary function and imaging of the lungs using MRI. 
The applicant reported that on October 5, 2021, it received a complete 
response letter from FDA. The applicant stated that it intends to 
address FDA's concerns and resubmit the NDA, with FDA approval 
anticipated by July 1, 2022. The applicant anticipates commercial 
availability for XENOVIEW after FDA approval. Per the applicant, the 
recommended dosage for XENOVIEW is 75 mL Dose Equivalent (DE, where DE 
= total volume Xe gas x \129\Xe isotopic enrichment x polarized%) of HP 
\129\Xe (250-750 mL total Xe) mixed with nitrogen NF (99.999% purity) 
as an inert buffer to ensure that the total volume of gas contained in 
the XENOVIEW Dose Delivery Bag is 1L.
    According to the applicant, there are currently no ICD-10-PCS 
procedure codes to distinctly identify cases involving the use of 
XENOVIEW. The applicant submitted a request for approval for a unique 
ICD-10-PCS procedure code for XENOVIEW beginning in FY 2023.
    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 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 explained that HP \129\Xe identifies regional function in 
the entire lung, facilitating more informed treatment decisions while 
reducing the patient's risk of receiving more invasive procedures, such 
as a right heart catherization. The applicant stated that the 
hyperpolarization and isotopic properties used by XENOVIEW are 
different from traditional MRI imaging, which is based on imaging of 
the hydrogen nucleus. Further, the applicant stated that XENOVIEW 
provides a completely new image requiring novel hardware, pulse 
sequence programming, post-processing interpretation software, and 
physician training for evaluation of lung function. Per the applicant, 
alternatives to XENOVIEW include nuclear scintigraphy methods using 
\133\Xe ventilation and/or Technetium (99mTc) perfusion (ventilation/
perfusion [V/Q] scan) or spirometry measurements, which, according to 
the applicant, do not provide regional information and pose added 
ionizing radiation to the patient. The applicant stated that 
experimental computed tomography (CT) imaging using parametric modeling 
has also been used to infer function from structural imaging; however, 
unlike XENOVIEW, it does not directly measure function.
    With respect to the second criterion, whether a product is assigned 
to the same or different MS-DRG when compared to an existing 
technology, the applicant stated that XENOVIEW has not been assigned to 
an MS-DRG and cannot be compared to an existing technology, nor is 
there data reflecting the cost of XENOVIEW in the MS-DRGs as it has not 
yet been billed to Medicare. However, the applicant noted that XENOVIEW 
is intended to aid diagnoses for patients with pulmonary disease 
frequently assigned to MS-DRGs 190-192 and 202-203, provided in the 
table.

[[Page 28308]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.119

    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 asserted that XENOVIEW is available 
to a new population of patients whose underlying morbidities cannot 
safely tolerate standard lung imaging. The applicant noted that only 
13% of patients within MS-DRGs 190-192 and 202-203 are without a 
complication or major complication, and that subjecting these patients 
to additional radiation exposure--such as that through single-photon 
emission computed tomography (SPECT)/CT, high-resolution CT, or 
nephrotoxicity from MRI--is not appropriate. The applicant further 
stated that an analysis of imaging ICD-10-PCS codes within these MS-
DRGs indicates that less than 8% of these patients receive inpatient 
imaging. The applicant stated that XENOVIEW enables patients with 
comorbidities to have safe and effective MRIs to monitor their disease 
response to treatment or to identify loss of lung function. The 
applicant stated that XENOVIEW addresses an unmet medical need for a 
diagnostic agent that evaluates pulmonary function using more modern 
and precise imaging techniques (for example, MRI) without requiring 
patients to be exposed to radiation or nephrotoxicity.
    In summary, the applicant stated that XENOVIEW is not substantially 
similar to other currently available therapies and/or technologies 
because it has a unique mechanism of action compared to existing lung 
imaging modalities, has not been assigned to an MS-DRG, and treats a 
new patient population. Therefore, the applicant asserted that XENOVIEW 
meets the ``newness'' criterion.
    We note that although the applicant states that XENOVIEW has not 
been assigned to an MS-DRG and cannot be compared to an existing 
technology, we believe that based on its proposed FDA indication, cases 
involving the use of XENOVIEW would be assigned to the same MS-DRGs as 
cases involving the use of other MRIs and imaging modalities for 
pulmonary function and imaging of the lungs. We also believe that 
XENOVIEW may use the same or similar mechanism of action as other 
inhaled gases (\133\Xe) and oxygen-enhanced pulmonary imaging, and we 
invite public comments on whether XENOVIEW's mechanism of action for 
the diagnosis and assessment of certain lung abnormalities is different 
than existing technologies. Further, we also invite public comments on 
whether XENOVIEW's safety profile allows patients with certain 
underlying morbidities access to previously contraindicated pulmonary 
testing and whether those patients with previous contraindication to 
current pulmonary imaging techniques should be considered a new patient 
population. We note that the proposed FDA indication for this 
technology is the evaluation of pulmonary function and imaging of the 
lungs using MRI, which is not unique to XENOVIEW, and does not mention 
the subset of patients with comorbidities that the applicant asserts is 
a new patient population.
    We are inviting public comments on whether XENOVIEW is 
substantially similar to existing technologies and whether XENOVIEW 
meets the newness criterion.
    With respect to the cost criterion, the applicant presented three 
analyses which varied the charges added for the new technology. For all 
three analyses, the applicant determined that cases representing 
patients potentially eligible for treatment with XENOVIEW (that is, 
patients with lung disease, exacerbations of lung disease, or those who 
require an inpatient admission to better monitor their response to or 
the side effects of pharmacologic therapy) mapped to five MS-DRGs, 
listed in the table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.120

    The applicant explained that it initially identified 255,651 cases 
as reported for the MS-DRGs in the preceding table in the FY 2019 
MedPAR data. However, the applicant stated that because the cases it 
identified were 96% of total FY 2019 MS-DRG discharges reported in the 
FY 2023 threshold table, it decided to use the case counts from the FY 
2023 Threshold Table, which resulted in a total of 267,158 cases. The 
applicant stated that it did not remove charges for prior drugs. The 
applicant then standardized the charges and applied a 4-year inflation 
factor of 1.281834 or 28.1834% based on the inflation factor used in 
the FY 2022 IPPS/LTCH PPS final rule and correction notice to calculate 
outlier threshold charges (86 FR 45542).
    The applicant then added charges for the new technology by dividing 
the cost of XENOVIEW by the national average CCR for: (1) Drugs and 
radiology; (2) drugs alone; and (3) radiology alone. The applicant used 
the national average CCRs published in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 44966).
    In the first analysis, the applicant applied the national average 
CCR for

[[Page 28309]]

drugs, which is 0.187, to costs associated with the gas blend 
preparation, and the national average CCR for radiology, which is 
0.136, for preparation of the hyperpolarized dose equivalent. Under 
this analysis, the applicant calculated a final inflated average case-
weighted standardized charge per case of $51,418 which exceeded the 
average case-weighted threshold amount of $42,424.
    In the second analysis, the applicant added charges for the new 
technology by dividing the cost of XENOVIEW by the national average CCR 
for drugs, which is 0.187, for costs associated with the gas blend 
preparation as well as costs associated with preparation of the 
hyperpolarized dose equivalent. Under this analysis, the applicant 
calculated a final inflated average case-weighted standardized charge 
per case of $49,012 which exceeded the average case-weighted threshold 
amount of $42,424.
    In the third analysis, the applicant added charges for the new 
technology by dividing the total cost of XENOVIEW by the national 
average CCR for radiology, which is 0.136. Under this analysis, the 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $52,622 which exceeded the average 
case-weighted threshold amount of $42,424.
[GRAPHIC] [TIFF OMITTED] TP10MY22.121

    Because the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount in 
each analysis, the applicant asserted that XENOVIEW meets the cost 
criterion.
    We are inviting public comments on whether XENOVIEW meets the cost 
criterion, including whether it is appropriate to assume that no 
charges should be removed for the prior technology or the technologies 
being replaced for the cases assigned to the identified MS-DRGs, 
particularly as the applicant noted 13% of patients within MS-DRGs 190-
192 and 202-203 are without a complication or major complication, and 
therefore might be able to handle additional radiation exposure such as 
that through SPECT/CT or high-resolution CT, or nephrotoxicity from 
MRI. For this reason, we invite comment on whether any charges should 
be removed within the specified MS-DRGs to account for prior technology 
XENOVIEW would be replacing.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that XENOVIEW offers: (1) A new service or treatment 
option for patients with early symptoms of breathing difficulty, 
including those with an uncertain diagnosis that are unresponsive to, 
or ineligible for, currently available treatments; (2) the ability to 
diagnose a medical condition in a patient population where the medical 
condition is currently undetectable; (3) the ability to diagnose a 
medical condition earlier than currently available methods; (4) 
improved outcomes such as novel actionable information to inform 
treatment decisions; and (5) the ability to safely monitor unexplained 
dyspnea.
    In support of its first assertion that XENOVIEW can help patients 
with early symptoms of breathing difficulty, the applicant noted that 
these patients--which include those with suspected COPD, asthma, or 
those living with idiopathic pulmonary fibrosis or inflammatory 
pulmonary disease--can benefit from XENOVIEW's safety profile as it 
allows them to receive medically necessary diagnostic treatment to aid 
their treatment decisions. The applicant stated that these patients are 
particularly vulnerable to gadolinium contrast enhanced MRI, lung 
SPECT, or thoracic CT imaging. According to the applicant, XENOVIEW can 
aid in treatment management and would be able to be used for clinical 
decision making to reduce a COPD exacerbation, preempt asthma 
exacerbation, and support therapies for interstitial lung disease.
    The applicant also asserted that XENOVIEW can help identify the 
ventilation defect percentage (VDP) in patients with early symptoms, 
including patients in early phase COPD or asthma, and can provide 
diagnostic information with lesser risk than other pulmonary function 
tests (PFTs) and lung imaging methods. The applicant cited an opinion 
paper by Usmani et al.,\534\ which discusses small airways disease in 
the context of asthma and COPD, as background to highlight gaps in 
current knowledge that impede earlier identification of obstructive 
lung disease and the development and standardization of novel small 
airways-specific end points for use in clinical trials. The applicant 
stated that because XENOVIEW is intended to help assess small airways, 
it could help address the gaps in current knowledge discussed in the 
opinion paper.
---------------------------------------------------------------------------

    \534\ Usmani OS, Han MK, Kaminsky DA, Hogg J, Hjobert J, et al. 
Seven pillars of small airway disease in Asthma and COPD. CHEST 
2021; 160(1):114-134.
---------------------------------------------------------------------------

    The applicant asserted that detailed imaging through the 23 
branches of the lung that can be provided by XENOVIEW is an ideal way 
to preemptively manage the patients with lung disease. In support of 
this claim, the applicant cited a narrative review by Crisafulli et 
al.\535\ as background on AECOPD and the current treatment options. In 
this narrative, the authors conducted a review of 160 citations, based 
on a search of Medline completed in the month of May 2018, to update 
the scientific evidence about the in-hospital pharmacological (inhaled 
bronchodilators, steroids, antibiotics) and non-pharmacological 
treatments (oxygen, high flow nasal cannulae (HFNC) oxygen, non-
invasive mechanical ventilation (NIMV), pulmonary rehabilitation (PR)) 
used in the management of a severe COPD exacerbation as well as studies 
about non-conventional drugs for severe AECOPD. The applicant asserted 
that HP \129\Xe MRI has been shown to identify signs of COPD earlier 
than conventional techniques and can therefore enable earlier 
rehabilitation for the patient, which was identified in the

[[Page 28310]]

study as one factor that could improve treatment of AECOPD.
---------------------------------------------------------------------------

    \535\ Crisafulli, E., Barbeta, E., Ielpo, A., Torres, A. (2018) 
Management of severe acute exacerbations of COPD: An updated 
narrative review. Multidiscip Respir Med 13: 36.
---------------------------------------------------------------------------

    In support of its claim that XENOVIEW offers the ability to 
diagnose a medical condition earlier in a patient population than 
allowed by currently available methods, the applicant cited additional 
references. The applicant asserted that use of HP \129\Xe MRI 
correlates with asthma severity, health care utilization and oral 
corticosteroid use. The applicant referenced an article by Lin et 
al.\536\ in which children with asthma have a higher VDP (p = 0.002) 
and a higher number of defects per image slice than children without 
asthma (p = 0.0001). The article noted that children with asthma who 
had higher defects per image slice had a higher rate of health care 
utilization correlation (r) (r = 0.48; p = 0.03) and oral 
corticosteroid use (r = 0.43, p = 0.05). Asthma severity can be 
difficult to assess in children and the authors postulate that HP 
\129\Xe MRI can be used to identify children at a higher risk for 
exacerbations and improve outcomes. The applicant stated that VDP 
detected by HP \129\Xe was significantly different between the healthy 
cohort (n = 16 subjects), mild/moderate asthma cohort (n = 8 subjects), 
and severe asthma cohort (n = 13 subjects) as well as between the 
healthy cohort and the combined asthma cohorts (all p < 0.002). The 
applicant also noted that the forced expiratory volume in 1 second 
(FEV1) pulmonary function test did not detect significant 
differences between any of the cohorts (p = 0.15) whereas the 
FEV1 to forced vital capacity (FVC) ratio did (p = 0.009).
---------------------------------------------------------------------------

    \536\ Lin NY, Roach DJ, Willmer MM, Walkup LL, Hossain M, et al. 
\129\Xe MRI as a measure of clinical disease severity for pediatric 
asthma. 2021; Journal of Allergy and Clinical Immunology 147(6): 
2146-2153.
---------------------------------------------------------------------------

    The applicant also cited the opinion paper by Usmani et al.\537\ 
discussed in its first claim regarding the importance of assessing 
small airways. The applicant again asserted that HP \129\XE offers the 
diagnostic ability needed to assess small airways, is minimally 
invasive, and does not require additional ionizing radiation. The 
applicant states that this combination is not found in any other 
existing diagnostic tool for pulmonary function.
---------------------------------------------------------------------------

    \537\ Usmani OS, Han MK, Kaminsky DA, Hogg J, Hjobert J, et al. 
Seven pillars of small airway disease in Asthma and COPD. CHEST 
2021; 160(1):114-134.
---------------------------------------------------------------------------

    The applicant also asserted that XENOVIEW has been demonstrated to 
detect early stages of lung disease in smokers before progression to 
COPD and could help diagnose patients more accurately than the use of 
FEV1 and related pulmonary function tests, which the 
applicant asserted can impair spirometry results. In support of this 
claim, the applicant provided background from a study performed by 
Fortis et al.,\538\ a retrospective cohort study to evaluate whether 
slow vital capacity (SVC) instead of FVC increased the sensitivity of 
spirometry to identify patients with early or mild obstructive lung 
disease. The study included 854 current and former smokers in the U.S. 
aged 40-80 years from the Sub-populations and Intermediate Outcome 
Measures in COPD Study cohort with a postbronchodilator 
FEV1/FVC >= 0.7 and FEV1% predicted of >= 80% at 
enrollment. Characteristics, chest CT scan features, exacerbations, and 
progression to COPD (postbronchodilator FEV1/FVC, < 0.7) 
were compared to the baseline during the follow-up period between 734 
participants with postbronchodilator FEV1/SVC of >= 0.7 and 
120 with postbronchodilator FEV1/SVC < 0.7 at the 
enrollment. The study included multivariate linear and logistic 
regression models and negative binomial and interval-censored 
proportion hazards regression models adjusted for demographics and 
smoking exposure to examine the association of FEV1/SVC < 
0.7 with those characteristics and outcomes.
---------------------------------------------------------------------------

    \538\ Fortis, S., Comellas, A.P., Bhatt, S.P., Hoffman, E.A., 
Han, M.K., Bhakta, N.R., Barjaktarevic, I. (2021) Ratio of FEV1/slow 
vital capacity of < 0.7 is associated with clinical, functional, and 
radiologic features of obstructive lung disease in smokers with 
preserved lung function. CHEST 160(1): 94-103.
---------------------------------------------------------------------------

    Of the 854 current and former smokers with normal spirometry 
results at enrollment, 120 participants showed a post bronchodilator 
FEV1/SVC less than 0.7, and 734 participants showed an 
FEV1/SVC greater than or equal to 0.7. Participants with a 
postbronchodilator FEV1/SVC of less than 0.7 experienced 
more emphysema, gas trapping and severe exacerbations and manifested 
more COPD symptoms relative to those patients with FEV1/SVC 
greater than or equal to 0.7. They also found similar results in 
patients with a prebronchodilator FEV1/SVC of less than 0.7 
or FEV1/SVC less than the lower limit of normal with chest 
CT scan features and progression to COPD. In conclusion, the authors 
believed that FEV1/SVC less than 0.7 or the lower limit of 
normal may be used as a metric of early obstruction and may be a useful 
tool in identifying individuals at increased risk of COPD. The authors 
noted that the study had some limitations as the analysis was limited 
to a cohort of heavy smokers older than 40 years and cautioned that the 
study findings may not be generalizable. The authors also stated that 
they did not take into consideration other risk factors for obstructive 
lung disease such as occupational exposure. Fortis et al. also noted 
that because FEV1/SVC ratios are not widely used, there are 
no widely accepted reference values so they used 0.7 as a cutoff for 
the FEV1 to true vital capacity (VC) for the main 
analysis.\539\ The applicant stated that FEV1 and related 
pulmonary function tests can result in increased intrathoracic 
pressure, which could shorten exhalation time and impair accurate 
spirometry results, and that this issue is not prevalent with HP 
\129\Xe MRI.
---------------------------------------------------------------------------

    \539\ Ibid.
---------------------------------------------------------------------------

    The applicant stated that XENOVIEW can provide critical diagnostic 
information for patients that cannot perform spirometry or tolerate the 
risk of standard lung imaging, and/or require detailed information on 
ventilation differences. The applicant also asserted that the safety 
profile of XENOVIEW for MRI lung diagnostics is superior to alternative 
lung imaging options, including PFT, because XENOVIEW does not use any 
ionizing radiation or impart any ionizing radiation in the procedure, 
and it offers visualization of MRI images without nephrotoxicity (in 
contrast to CT images), which permits it to be used for longitudinal 
therapeutic evaluation and assessment of disease progression.
    The applicant asserted that HP \129\Xe MRI is able to depict airway 
obstructions in mild to moderate asthma and significantly correlates 
with PFTs. In support of this claim, the applicant referenced a study 
by Ebner et al.,\540\ which investigated ventilation in mild to 
moderate asthmatic patients and age-matched controls using HP \129\Xe 
MRI and correlated findings with PFTs. In this study, 30 subjects (10 
young asthmatic patients, 26  6 years; three males, seven 
females; 10 older asthmatic patients, 64  6 years; three 
males, seven females; 10 healthy controls) were enrolled. After 
repeated PFTs 1 week apart, the subjects underwent two MRI scans within 
10 minutes, inhaling 1-L volumes containing 0.5 to 1 L of HP \129\Xe. 
The applicant stated that HP \129\Xe MRI detected significant 
differences between young healthy subjects and young asthmatic subjects

[[Page 28311]]

(p = 0.03), between young asthmatic subjects and old asthmatic subjects 
(p = 0.02), and between young healthy subjects and old healthy subjects 
(p = 0.05), whereas FEV1% only detected a significant 
difference between young healthy subjects and young asthmatic subjects 
(p = 0.01).
---------------------------------------------------------------------------

    \540\ Ebner L., He M., Virgincar R.S., Heacock T., Kaushik S.S., 
et al. Hyperpolarized \129\xenon magnetic resonance imaging to 
quantify regional ventilation differences in mild to moderate 
asthma: A prospective comparison between semiautomated ventilation 
defect percentage calculation and pulmonary function tests. 2017; 
Investigative Radiology 52: 120-127.
---------------------------------------------------------------------------

    The applicant also asserted that in patients with COPD, the VDP 
obtained with HP \129\Xe is significantly greater than that with HP 
\3\He MRI, suggesting incomplete or delayed filling of lung regions 
that may be related to the different properties inherent to HP \129\Xe 
gas and physiologic and/or anatomic abnormalities in COPD. The 
applicant provided a peer-reviewed journal article by Kirby et al.\541\ 
on HP \3\He and HP \129\Xe MRI imaging in healthy volunteers and 
patients with COPD. Kirby et al. quantitatively compared HP \3\He and 
HP \129\Xe MRI images in healthy volunteers and patients with COPD with 
measurements from spirometry and plethysmography. In the study, 8 
healthy patients and 10 COPD patients underwent MRI (5 minutes between 
HP \3\He MRI and HP \129\Xe MRI), spirometry and plethysmography. VDPs 
were calculated in HP \3\He and HP \129\Xe MRIs. HP \129\Xe VDP was 
significantly greater than HP \3\He VDPs for patients with COPD (p < 
0.0001) but not for healthy volunteers (p = 0.35).
---------------------------------------------------------------------------

    \541\ Kirby M., Svenningsen S., Owrangi A., Wheatley A., Farag 
A., et al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
2012;Radiology 265(2): 600-610.
---------------------------------------------------------------------------

    The applicant asserted that functional alveolar wall thickness 
assessed by HP \129\Xe MRI allows discrimination between healthy 
subjects and healthy smokers and the applicant asserted its belief that 
HP \129\Xe could be a useful tool for detecting early-stage lung 
disease. The applicant referenced a prospective cohort study by Ruppert 
et al.\542\ that hypothesized that the functional alveolar wall 
thickness as assessed by HP \129\Xe MR spectroscopy would be elevated 
in clinically healthy smokers before HP \129\Xe MR diffusion 
measurements would indicate emphysematous tissue destruction. The 
researchers used HP \129\Xe MR to measure the functional septal wall 
thickness and apparent diffusion coefficient of the gas phase in 16 
subjects with smoking-related COPD, 9 clinically healthy current or 
former smokers, and 10 healthy never-smokers. The applicant stated that 
the study results reported that in healthy never-smokers, the septal 
wall thickness increased by 0.04 [mu]m per year of age, while that the 
healthy smoker cohort exhibited normal PFT measures that did not 
significantly differ from the never-smoker cohort. The applicant stated 
that the study results noted that age-corrected septal wall thickness 
correlated well with diffusion capacity for carbon monoxide (R\2\ = 
0.56) and showed a statistically significant difference between healthy 
subjects and COPD patients (p < 0.001) but was the only measure that 
actually discriminated healthy subjects from healthy smokers (p < 
0.006). The applicant stated that this suggests HP \129\Xe MRI can be 
used to detect early stages of lung disease, and that detecting early 
COPD could enable lifestyle changes and encourage patients to gain 
insight into their disease to aid their health.
---------------------------------------------------------------------------

    \542\ Ruppert K., Qing K., Patrie J.T., Altes T.A., Mugler J.P.. 
Using hyperpolarized xenon-129 MRI to quantify early-stage lung 
disease in smokers. Acad. Radiol. 2019 March; 26(3): 355-366. 
doi:10.1016/j.acra.2018.11.005.
---------------------------------------------------------------------------

    According to the applicant, the unique properties of HP \129\Xe are 
well-suited to evaluate pulmonary function in patients with lung cancer 
and HP \129\Xe has a potential advantage over other imaging modalities 
such as a ventilation-perfusion (VQ) scan since both gaseous and 
dissolved phases can be measured to provide a more comprehensive 3-D 
evaluation of ventilation and interstitial thickening. In support of 
this claim, the applicant cited a case report by Song et al.\543\ 
involving a 64-year-old male who presented with dyspnea. In the study, 
the patient's chest CT revealed a seven cm right lung mass with 
mediastinal invasion and compression of the right mainstem bronchus 
while bronchoscopy showed a 90% obstructing mass in the right mainstem 
bronchus. Pathology was consistent with adenocarcinoma. The mass was 
hypermetabolic on PET/CT with involvement of mediastinal lymph nodes. 
The patient was under concurrent radiation therapy (RT) and 
chemotherapy and subsequently enrolled in the HP \129\Xe study after 
institutional review board approval. The study design involved the 
evaluation of HP \129\Xe before and after RT. The patient's right lung 
was completely expanded at diagnosis, yet the patient displayed 
significant dyspnea. The applicant stated that HP \129\Xe MRI detected 
non-ventilation to the right lung despite the right lung appearing 
inflated in the CT scan, and that the increased FEV1 values 
from pre- to post-treatment reflected re-ventilation induced by 
treatment resulting from detected non-ventilation by the HP \129\Xe 
MRI. The study authors noted that post-treatment HP \129\Xe MRI 
confirmed re-ventilation of the lung.
---------------------------------------------------------------------------

    \543\ Song, E.J., Kelsey, C.R., Driehuys, B., Rankine, L. (2018) 
Functional airway obstruction observed with hyperpolarized 
\129\xenon-MRI. J Med Imaging Radiat Oncol 62: 91-98.
---------------------------------------------------------------------------

    The applicant further asserted that emphysema index based on HP 
\3\He and HP \129\Xe diffusion MRI provides a repeatable measure of 
emphysema burden, independent of gas or b value, with similar 
diagnostic performance as quantitative CT or pulmonary function 
metrics. The applicant referenced an article from Tafti et al.,\544\ a 
retrospective study that sought to introduce and test a quantitative 
framework with which to characterize emphysema burden based on HP \3\He 
and HP \129\Xe apparent diffusion coefficient (ADC) maps and compare 
its diagnostic performance with CT-based emphysema metrics and PFTs. 
The authors indicated that emphysema is a disease characterized by 
irreversible destruction of alveolar walls that causes loss of lung 
elastic recoil and impaired gas exchange. The study investigated 27 
patients with mild, moderate, or severe COPD and 13 age-matched healthy 
control subjects participated in this retrospective study. Participants 
underwent CT and multiple b value diffusion-weighted HP \3\He and HP 
\129\Xe MRI examinations and standard PFTs between August 2014 and 
November 2017. The ADC-based emphysema index was computed separately 
for each gas and b value as the fraction of lung voxels with ADC values 
greater than in the healthy group 99th percentile. The resulting values 
were compared with quantitative CT results (relative lung area <-950 
HU) as the reference standard. Diagnostic performance metrics included 
area under the receiver operating characteristic curve (AUC). Spearman 
rank correlations and Wilcoxon rank sum tests were performed between 
ADC-, CT-, and PFT-based metrics, and intraclass correlation was 
performed between repeated measurements. The study concluded that an 
emphysema index based on HP \3\He and HP \129\Xe diffusion MRI provides 
a repeatable measure of emphysema burden, independent of gas or b 
value, with similar diagnostic performance as quantitative CT or 
pulmonary function metrics. The applicant stated that HP \129\Xe MRI 
offered higher sensitivity in detecting pulmonary obstruction, as

[[Page 28312]]

19% of subjects with COPD appeared healthy based on CT scans, and 
emphysematous based on HP \3\He and HP \129\Xe MRI ADC, whereas no 
subjects with COPD appeared healthy based on HP \3\He and HP \129\Xe 
MRI ADC.
---------------------------------------------------------------------------

    \544\ Tafti, S., Garrison, W.J., Mugler III, J.P., Shim, Y.M., 
Altes, T.A., Mata, J.F., de Lange, E.E., Cates, G.D., Ropp, A.M., 
Wang, C., Miller, G W. (2020) Emphysema index based on 
hyperpolarized \3\He or \129\Xe diffusion MRI: Performance and 
comparison with quantitative CT and pulmonary function tests. 
Radiology 297: 201-210.
---------------------------------------------------------------------------

    The applicant asserted that HP \129\Xe MRI could develop into a 
tool that can guide individualized patient care and the use of HP 
\129\Xe MRI may have a role as a tool for both patient selection and 
measuring treatment response in future COPD clinical trials. To support 
its claim that HP \129\Xe MRI provides a quantitative, reproducible 
measure of treatment effectiveness, the applicant cited a study by 
Mummy et al.,\545\ a prospective study characterizing changes in HP 
\129\Xe gas transfer function following administration of an inhaled 
long[hyphen]acting beta[hyphen]agonist/long[hyphen]acting muscarinic 
receptor antagonist (LABA/LAMA) bronchodilator. The study involved 17 
COPD study participants with a GOLD II/III classification per Global 
Initiative for Chronic Obstructive Lung Disease criteria. The study 
participants were imaged before and after 2 weeks of LABA/LAMA therapy. 
According to the applicant, the study concluded that LABA/LAMA therapy 
tended to preferentially improve ventilation in those subjects with 
relatively preserved measures of HP \129\Xe barrier uptake and 
DLCO (carbon monoxide) and noted that even in study 
participants with improved ventilation, newly ventilated lung regions 
often revealed persistent HP \129\Xe red blood cell (RBC) transfer 
defects, an aspect of LABA/LAMA therapy response that is opaque to 
spirometry. The study indicated that these results add to the body of 
knowledge regarding COPD phenotypes and indicate a possible role for HP 
\129\Xe gas transfer MRI as a tool for both patient selection and 
measuring treatment response in future COPD clinical trials. The study 
also concluded that as health care develops therapies that demonstrably 
improve not only ventilation but also RBC transfer, HP \129\Xe may 
develop into a tool that can guide individualized patient care.\546\
---------------------------------------------------------------------------

    \545\ Mummy, D.G., Coleman, E.M., Wang, Z., Bier, E.A., Lu, J., 
Driehuys, B., Huang, Y.C. (2021) Regional gas exchange measured by 
\129\Xe magnetic resonance imaging before and after combination 
bronchodilators treatment in chronic obstructive pulmonary disease. 
J Magn Reson Imaging 54(3): 964-974. DOI: 10.1002/jmri.27662.
    \546\ Mummy, D.G., Coleman, E.M., Wang, Z., Bier, E.A., Lu, J., 
Driehuys, B., Huang, Y.C. (2021) Regional gas exchange measured by 
\129\Xe magnetic resonance imaging before and after combination 
bronchodilators treatment in chronic obstructive pulmonary disease. 
J Magn Reson Imaging 54(3): 964-974. DOI: 10.1002/jmri.27662.
---------------------------------------------------------------------------

    The applicant asserted HP \129\Xe is a useful imaging tool for 
conducting pulmonary assessments on a patient-specific scale and allows 
for a deeper examination of underlying pathologies and pulmonary 
function test results. In support, the applicant referenced an article 
by Wang et al.\547\ that indicated that HP \129\Xe MRI has emerged as a 
novel means to evaluate pulmonary function via 3-D mapping of 
ventilation, interstitial barrier uptake, and RBC transfer, and the 
physiological interpretation of these measurements has yet to be firmly 
established. The authors proposed a model that uses the three 
components of HP \129\Xe MRI to estimate accessible alveolar volume 
(VA), membrane conductance, and capillary blood volume 
contributions to carbon monoxide (DLCO). The model was built 
on a cohort of 41 healthy subjects and 101 patients with pulmonary 
disorders. The study concluded that the ability to use HP \129\Xe MRI 
measures of ventilation, barrier uptake, and RBC transfer to estimate 
each of the underlying constituents of DLCO clarifies the 
interpretation of these images while enabling their use to monitor 
these aspects of gas exchange independently and regionally. The 
applicant stated that HP \129\Xe MRI-derived DLCO values and 
measured DLCO values were significantly correlated (p 
<0.001), while ventilated volume, barrier transfer, and red blood cell 
transfer were significantly different between the healthy cohort and 
the individual disease cohorts.
---------------------------------------------------------------------------

    \547\ Wang Z., Rankine L., Bier E.A., Mummy D., Lu J., et al. 
Using hyperpolarized \129\Xe gas exchange MRI to model the regional 
airspace, membrane and capillary contributions to diffusing 
capacity. J Appl Physiol 130: 1398-1409, 2021. First published March 
18, 2021; doi:10.1152/japplp.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that XENOVIEW will 
provide novel actionable information that will lead to improved 
treatment decisions because it will provide clinicians with information 
beyond current lung imaging techniques, the applicant summarized a Song 
et al.\548\ case study of a 64-year-old with dyspnea, discussed 
previously. The applicant asserted that HP \129\Xe identified the right 
lung to be unventilated despite a fairly normal CT appearance. The 
applicant stated that XENOVIEW can safely monitor unexplained dyspnea 
and that a prospective study is underway to validate the value HP 
\129\Xe MRI can add to evaluate pulmonary function in patients with 
lung cancer. The applicant asserted that this case report and prior 
studies consistently found that HP \129\Xe MRI has imaging capabilities 
above those of reporting VQ scans because both gaseous and dissolved 
phases can be measured to provide more comprehensive 3-D evaluation of 
ventilation and interstitial thickening. The applicant stated that 
further analysis of the benefit of established regional lung function 
and ventilation, when added to analysis of gaseous exchange, will 
enable better patient identification for surgical planning and RT and 
that dose-dependent functional changes of radiation could be evaluated 
allowing guided radiation administration to limit the RT to the most 
highly functional regions in the lung, reducing long-term effects of 
the therapy.
---------------------------------------------------------------------------

    \548\ Song, E.J., Kelsey, C.R., Driehuys, B., Rankine, L. (2018) 
Functional airway obstruction observed with hyperpolarized 
\129\xenon-MRI. J Med Imaging Radiat Oncol 62: 91-98.
---------------------------------------------------------------------------

    Based on the information provided by the applicant in support of 
the substantial clinical improvement criterion, we have the following 
concerns. With respect to the applicant's claim that XENOVIEW offers a 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments, we note that XENOVIEW 
is a diagnostic test and does not itself provide a treatment, but can 
be used in monitoring patients with pulmonary pathologies.
    With respect to the applicant's claim that XENOVIEW is able to 
diagnose a medical condition in a patient population where the medical 
condition is currently undetectable and diagnose a medical condition 
earlier than currently available methods, we note that the studies do 
not appear to provide evidence showing that use of the technology to 
make a diagnosis affected the management of the patients, as under 
Sec.  412.87(b)(1)(ii)(B). We also note that one of the studies cited 
utilized a pediatric cohort of patients, which is a patient population 
largely distinct from the Medicare population.\549\ We note that, in 
other instances, the journal articles provided for review were for 
clinical studies with contributors outside the U.S. such as the Ebner 
et

[[Page 28313]]

al.\550\ and Crisafulli et al.\551\ articles, and that there may be 
differing standards of care that could affect the detection of these 
medical conditions as well as the subsequent management of the 
patients. We also note that the narrative review by Crisafulli et al. 
does not address the use of XENOVIEW, but rather discusses potential 
future improvements in the treatment of AECOPD. As the study does not 
measure the effect of XENOVIEW on actual treatment outcomes, we are 
uncertain if the technology will lead to improvement in clinical 
outcomes. We invite public comments as to whether the studies discussed 
previously can be generalized to the Medicare population.
---------------------------------------------------------------------------

    \549\ Lin N.Y., Roach D.J., Willmer M.M., Walkup L.L., Hossain 
M., et al. \129\Xe MRI as a measure of clinical disease severity for 
pediatric asthma. 2021; Journal of Allergy and Clinical Immunology 
147(6): 2146-2153.
    \550\ Ebner L., He M., Virgincar R.S., Heacock T., Kaushik S.S., 
et al. Hyperpolarized \129\xenon magnetic resonance imaging to 
quantify regional ventilation differences in mild to moderate 
asthma: A prospective comparison between semiautomated ventilation 
defect percentage calculation and pulmonary function tests. 2017; 
Investigative Radiology 52: 120-127.
    \551\ Crisafulli, E., Barbeta, E., Ielpo, A., Torres, A. (2018) 
Management of severe acute exacerbations of COPD: An updated 
narrative review. Multidiscip Respir Med 13: 36.
---------------------------------------------------------------------------

    With respect to the applicant's claim that XENOVIEW used in MRI 
will provide novel actionable information that will lead to improved 
treatment decisions, we question whether the results of a single case 
report, consisting of only one patient, are generalizable to the 
Medicare population as a whole. We also question whether XENOVIEW's use 
in Song et al.\552\ was used to inform the patient treatment decision, 
as it appears from the case study that the treatment for the right lung 
collapse was radiation therapy for the adenocarcinoma, and that this 
radiation planning was informed via CT imaging. In addition, while the 
applicant asserts that XENOVIEW can provide actionable information by 
early detection of lung diseases such as asthma/COPD, we question 
whether this is relevant to patients in the inpatient setting. We also 
note that the studies provided by the applicant do not appear to assess 
the use of XENOVIEW to significantly improve clinical outcomes over 
existing technologies, as they are primarily feasibility/correlation 
studies,553 554 555 556 and that the studies assume but do 
not provide evidence that earlier diagnosis and potentially earlier 
treatment would result in better clinical outcomes. We also note that 
some studies appeared to describe the use of non-XENOVIEW HP \129\Xe 
(that is, xenon hyperpolarized using the XeBox-E10, which is 
manufactured by Xemed, LLC), and we question whether the results of 
these studies using non-XENOVIEW HP \129\Xe MRI can be extrapolated to 
the use of XENOVIEW HP \129\Xe MRI.557 558 We would also be 
interested in additional evidence that demonstrates how the use of 
XENOVIEW results in a change in patient disease management, improved 
clinical decisions, as well as improvement in clinical outcomes based 
on earlier diagnosis and/or enhanced imaging.
---------------------------------------------------------------------------

    \552\ Song, E.J., Kelsey, C.R., Driehuys, B., Rankine, L. (2018) 
Functional airway obstruction observed with hyperpolarized 
\129\xenon-MRI. J Med Imaging Radiat Oncol 62: 91-98.
    \553\ Ebner L., He M., Virgincar R.S., Heacock T., Kaushik S.S., 
et al. Hyperpolarized \129\Xenon magnetic resonance imaging to 
quantify regional ventilation differences in mild to moderate 
asthma: A prospective comparison between semiautomated ventilation 
defect percentage calculation and pulmonary function tests. 2017; 
Investigative Radiology 52: 120-127.
    \554\ Tafti, S., Garrison, W.J., Mugler III, J.P., Shim, Y.M., 
Altes, T.A., Mata, J.F., de Lange, E.E., Cates, G.D., Ropp, A.M., 
Wang, C., Miller, G.W. (2020) Emphysema index based on 
hyperpolarized \3\He or \129\Xe diffusion MRI: Performance and 
comparison with quantitative CT and pulmonary function tests. 
Radiology 297: 201-210.
    \555\ Kirby M., Svenningsen S., Owrangi A., Wheatley A., Farag 
A., Ourladov A., Santyr G.E., Etemad-Rezai R., Coxson H.O., 
McCormack D.G., Parraga G.. Hyperpolarized \3\He and \129\Xe MR 
imaging in healthy volunteers and patients with chronic obstructive 
pulmonary disease. Radiology. 2012;265(2):600-610.
    \556\ Wang Z., Rankine L., Bier E.A., Mummy D., Lu J., et al. 
Using hyperpolarized \129\Xe gas exchange MRI to model the regional 
airspace, membrane and capillary contributions to diffusing 
capacity. J Appl Physiol 130: 1398-1409, 2021. First published March 
18, 2021; doi:10.1152/japplp.
    \557\ Ruppert K., Qing K., Patrie J.T., Altes T.A., Mugler III 
J.P. Using hyperpolarized xenon-129 MRI to quantify early-stage lung 
disease in smokers. Acad Radiol. 2019;26(3):355-366. doi: 10.1016/
j.acra.2018.11.005
    \558\ Tafti, S., Garrison, W.J., Mugler III, J.P., Shim, Y.M., 
Altes, T.A., Mata, J.F., de Lange, E.E., Cates, G.D., Ropp, A.M., 
Wang, C., Miller, G.W. (2020) Emphysema index based on 
hyperpolarized \3\He or \129\Xe diffusion MRI: Performance and 
comparison with quantitative CT and pulmonary function tests. 
Radiology 297: 201-210.
---------------------------------------------------------------------------

    We are inviting public comments on whether XENOVIEW 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 XENOVIEW.
    Comment: The applicant submitted a public comment in response to 
three questions posed at the December 2021 New Technology Town Hall 
meeting and provided additional studies. First, the applicant was asked 
whether there are studies in the medical literature that have shown 
that early detection of disease using XENOVIEW and followed 
longitudinally have better outcomes than patients who are monitored 
with PFTs or other diagnostic tools. In response, the applicant stated 
that HP \129\Xe is currently under review by FDA as a drug used in MRI 
and that there are no published studies reporting early detection of 
disease using XENOVIEW and following longitudinally reported outcomes.
    The applicant then cited the Mummy D.G., et al.\559\ prospective 
study about 67 asthmatics comparing HP \3\He VDP and PFTs over 2 years 
to correlate VDP levels with outcomes. The Mummy et al. study found 
that HP \3\He at levels greater than 4.28% were associated with an 
exacerbation incidence ratio of 2.5 (95% CI 1.3-4.7) compared to VDP 
less than 4.28%. The applicant also stated that XENOVIEW VDP correlates 
well with HP \3\He VDP and is more sensitive than spirometry.\560\ 
Further, the applicant stated that HP \129\Xe allows radiologists and 
pulmonologists to evaluate images within the patient's own thoracic 
cavity and contrasted HP \129\Xe with PFTs, which the applicant asserts 
requires comparisons to reference equations that depend on age, sex, 
height, and ethnicity.
---------------------------------------------------------------------------

    \559\ Mummy D.G., Carey K.J., Evans M.D., et al. Ventilation 
defects on hyperpolarized helium-3 MRI in asthma are predictive of 
2-year exacerbation frequency [published online ahead of print March 
13, 2020]. J Allergy Clin Immunol.
    \560\ Kirby M., Svenningsen S., Owrangi A., Wheatley A., Farag 
A., et al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology: Volume 265: Number 2--November 2012.
---------------------------------------------------------------------------

    Next, the applicant stated additional studies report HP \129\Xe MRI 
being correlated with the apparent diffusion coefficient-based 
emphysema index (ADC) obtained with quantitative computed tomography 
(CT).561 562 563 According to the applicant VDP, 
FEV1, FEV1/FVC and ADC are measures relied upon 
by pulmonologists to follow a patient's response to treatment, to 
refine the patient's diagnosis and to aid patient compliance. The 
applicant stated that

[[Page 28314]]

HP \129\Xe MRI provides these measures with a high degree of accuracy 
and correlates well to disease clinical signs and symptoms.
---------------------------------------------------------------------------

    \561\ Kirby M, Svenningsen S, Owrangi A, Wheatley A, Farag A, 
Ourladov A, Santyr GE, Etemad-Rezai R, Coxson HO, McCormack DG, 
Parraga G. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology. 2012;265(2):600-610.
    \562\ Tafti S, Garrison WJ, Mugler III JP, Shim YM, Altes TA, 
Mata JF, de Lange EE, Cates GD, Ropp AM, Wang C, Miller GW. 
Emphysema index based on hyperpolarized \3\He or \129\Xe diffusion 
MRI: Performance and comparison with quantitative CT and pulmonary 
function tests. Radiology. 2020;297:201-210.
    \563\ Doganay O, Matin T, Chen M, Kim M, McIntyre A, McGowan DR, 
Bradley KM, Povey T, Gleeson FV. Time-series hyperpolarized xenon-
129 MRI of lobar lung ventilation of COPD in comparison to V/Q-
SPECT/CT and CT. Eur Radiol. 2019;29:4058-4067.
---------------------------------------------------------------------------

    Next, the applicant provided a ``summary of evidence'' by first 
citing a Horn et al. study that measured HP \3\He MRI to determine its 
effectiveness at treatment response mapping (TRM) in response to 
respiratory therapeutic agents in the lungs.\564\ According to the 
applicant, 20 patients with asthma were examined in this analysis using 
TRM to quantify regional physiologic response to a bronchodilator and 
provide regional quantitative information on changes in inhaled gas 
ventilation in response to therapy. The applicant stated that the study 
concluded that TRM has potential to aid treatment decisions for the 
assessment of regional lung interventions such as anti-inflammatory 
therapies or targeted therapies such as thermoplasty, endobronchial 
valve therapy, and lung volume reduction surgery. The applicant 
asserted the findings are applicable to measurements derived from HP 
\129\Xe and that HP \129\Xe can be used to provide regional insight 
into alterations of both the structure and function of the lungs, and 
that this is increasingly being used as an outcome measure in the 
early-phase evaluation of respiratory therapeutic agents. The applicant 
also noted that regionally specific therapies, such as bronchial 
thermoplasty, require regional information so the efficacy of the 
intervention can be assessed. The applicant also noted, but did not 
cite, that previous studies have used computed tomography (CT) and 
computational fluid dynamics-derived markers of airflow to assess 
functional changes after bronchodilator therapy.
---------------------------------------------------------------------------

    \564\ Horn FC, Marshall H, Collier GJ, Kay R, Siddiqui S, 
Brightling CE, Parra-Robles J, Wild JM. Regional Ventilation Changes 
in the Lung: Treatment Response Mapping by Using Hyperpolarized Gas 
MR Imaging as a Quantitative Biomarker. Radiology 2017;284(3):854-
861.
---------------------------------------------------------------------------

    The applicant also cited Rayment JH, et al. who performed a study 
measuring the VDP in 15 CF patients between the ages of 8-18 who 
underwent HP \129\Xe MRI, spirometry, plethysmography and multiple-
breath nitrogen washout at the beginning and end of inpatient treatment 
of a pulmonary exacerbation. Per the applicant, VDP was calculated from 
HP \129\Xe MRI obtained during a static breath hold using semi-
automated k-means clustering and linear binning approaches. The 
applicant stated that Rayment et al. reported that imaging, spirometric 
FEV1, lung clearance index, plethysmographic, MBW, and 
symptom score outcomes improved with treatment. The applicant noted 
that the study reported that VDP showed the largest relative 
improvement compared to all outcome measures (-42.1%, 95% CI -52.1--
31.9%, p<0.0001). The applicant suggested that this technique can 
generate outcomes that are responsive to treatment regardless of the 
image analysis technique used, and that using HP Xe-129 MRI to measure 
VDP as a metric of outcome response is expected to aid understanding of 
the individual patient response to treatment.\565\
---------------------------------------------------------------------------

    \565\ Rayment JH, Couch MJ, McDonald N, Kanhere N, Manson D, 
Santyr G, Ratjen F. Hyperpolarised \129\Xe magnetic resonance 
imaging to monitor treatment response in children with cystic 
fibrosis. Eur Respir J 2019;53(5).
---------------------------------------------------------------------------

    The applicant also cited an Altes et al.\566\ blinded study on a 
population of CF patients >12 years of age with a G551D-CFTR mutation 
to measure the effect of short- and long-term ivacaftor treatment on HP 
\3\He MRI defined ventilation defects. According to the applicant, the 
study design included: Part A (single-blind) comprised 4 weeks of 
ivacaftor treatment; and Part B (open-label) comprised 48 weeks of 
treatment. The applicant noted that the study's primary outcome measure 
was the change from baseline in total ventilation defect (TVD; total 
defect volume: Total lung volume ratio). The applicant reported that 
the study findings revealed that the mean change in TVD ranged from -
8.2% (p = 0.0547) to -12.8% (p = 0.0078) in Part A (n = 8) and -6.3% (p 
= 0.1953) to -9.0% (p = 0.0547) in Part B (n = 8) as assessed by human 
reader and computer algorithm, respectively. The applicant stated that 
the study concluded that TVD responded to ivacaftor therapy, and that 
HP \3\He MRI provided an individual quantification of disease burden 
that may be able to detect aspects of the disease missed by population-
based spirometry metrics.
---------------------------------------------------------------------------

    \566\ Altes TA, Johnson M, Fidler M, Botfield M, Tustison NJ, 
Leiva-Salinas C, de Lange EE, Froh D, Mugler JP. Use of 
hyperpolarized helium-3 MRI to assess response to ivacaftor 
treatment in patients with cystic fibrosis. J Cyst Fibros 
2017;16(2):267-274.
---------------------------------------------------------------------------

    The applicant also re-submitted the New Technology Town Hall slide 
discussing the Thomen et al.\567\ study in patients with mild CF to 
illustrate that HP \129\Xe MRI is a more sensitive measure than 
spirometry. The applicant also provided additional evidence of HP 
\129\Xe's quantitative measurement of pulmonary function from Doganay 
et al.\568\ in which HP \129\Xe MRI was compared to PFT imaging 
standards relied upon by pulmonologists when following patients 
recommended for pharmacologic therapy. The applicant stated that in the 
study, 12 COPD subjects who were subjected to rapid time-series HP 
\129\Xe MRI imaging and compared to ventilation/perfusion single-photon 
emission computed tomography (V/Q-SPECT), high-resolution CT and PFTs 
for measuring lobar percentage ventilation. The applicant stated that 
the study concluded that lobar ventilation with HP \129\Xe MRI showed a 
strong correlation with lobar ventilation and perfusion measurements 
derived from SPECT/CT (r = 0.644; p < 0.001 for percentage ventilation 
SPECT and r = 0.767; p <0.001 for perfusion SPECT) and that the 
measured whole lung HP \129\Xe MRI percentage ventilation correlated 
with the PFT measurements (FEV1 with r = -0.886, p < 0.001, 
and FEV1/FVC with r = -0.861, p < 0.001) better than the 
emphysema score obtained from high resolution CT (FEV1 with 
r = -0.635, p = 0.027; and FEV1/FVC with r = -0.652, p = 
0.021).
---------------------------------------------------------------------------

    \567\ Thomen RP, Walkup LL, Roach DJ, Cleveland ZI, Clancy JP, 
Woods JC. Hyperpolarized \129\Xe for investigation of mild cystic 
fibrosis lung disease in pediatric patients. J Cyst Fibros 
2017;16(2):275-282.
    \568\ Doganay O, Matin T, Chen M, Kim M, McIntyre A, McGowan DR, 
Bradley KM, Povey T, Gleeson FV. Time-series hyperpolarized xenon-
129 MRI of lobar lung ventilation of COPD in comparison to V/Q-
SPECT/CT and CT. Eur Radiol. 2019;29:4058-4067.
---------------------------------------------------------------------------

    The applicant repeated an assertion that XENOVIEW's sensitivity of 
pulmonary regions that cannot be imaged by CT or SPECT/CT has been 
found to identify signs of COPD disease earlier and more accurately 
than conventional techniques,\569\ which enables clinicians to identify 
patients at risk of readmission.\570\
---------------------------------------------------------------------------

    \569\ Crisafulli E, Barbeta E, Ielpo A, Torres A. Management of 
severe acute exacerbations of COPD: An updated narrative review. 
Multidiscip Respir Med. 2018;13:36.
    \570\ Press VG, Konetzka RT, White SR. Insights about the 
economic impact of COPD readmissions post implementation of the 
Hospital Readmission Reduction Program. Curr Opin Pulm Med. 
2018;24(2):138-146.
---------------------------------------------------------------------------

    Next, the applicant asserted that Kirby et al. validated HP \3\He 
VDP measurements to HP \129\Xe VDP measurements.\571\ The applicant 
then stated HP \3\He was the most commonly studied MRI agent; however 
HP \129\Xe MRI has evolved into the ``favored'' inhaled gas for 
functional pulmonary MRI due to the lower cost and higher availability 
of HP \129\Xe as well as advances in hyperpolarization physics that 
have allowed for greater

[[Page 28315]]

polarization efficiency of HP \129\Xe.\572\ Next, the applicant stated 
that studies using HP \3\He MR images reporting treatment response 
correlate well to HP \129\Xe MR images. The applicant also referenced a 
table excerpted from Kirby et al., and reports that there are 
significant correlations between HP \3\He and HP \129\Xe MR imaging 
measurements of VDP with FEVI.\573\
---------------------------------------------------------------------------

    \571\ Kirby M, Svenningsen S, Owrangi A, Wheatley A, Farag A, et 
al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology: Volume 265: Number 2--November 2012.
    \572\ Mugler JP, Altes TA. Hyperpolarized \129\Xe MRI of the 
human lung. J Magn Reson Imaging 2013; 37: 313-331.
    \573\ Kirby M, Svenningsen S, Owrangi A, Wheatley A, Farag A, et 
al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology: Volume 265: Number 2--November 2012.
---------------------------------------------------------------------------

    According to the applicant, VDP obtained from HP \3\He MRI was 
found to be a predictor of asthma severity and predict exacerbation in 
a population of asthma and COPD patients.574 575 576 The 
applicant stated that HP \129\Xe VDP can be relied upon as 
quantitatively similar or better than HP \3\He VDP.\577\ According to 
the applicant, HP \3\He and HP \129\Xe MR images were quantitatively 
compared to results from spirometry and those from plethysmography in a 
population of 8 healthy volunteers and 10 patients with COPD. According 
to the applicant, quantitative gold standard measurements included VDPs 
of HP \3\He and HP \129\Xe MR imaging, compared to measurements of 
FEVI, FEV1/FVC ratio, ADC, and CT emphysema 
score. The applicant stated that tables in Kirby et al. provided a 
comparison of the correlation of HP \129\Xe to gold standard PF 
measurements relied upon by pulmonologists.
---------------------------------------------------------------------------

    \574\ Mummy DG, Kruger SJ, Zha W, et al. Ventilation defect 
percent in helium-3 magnetic resonance imaging as a biomarker of 
severe outcomes in asthma. J Allergy Clin Immunol. 2018;141(3):1140-
1141 e1144.
    \575\ Mummy DG, Carey KJ, Evans MD, et al. Ventilation defects 
on hyperpolarized helium-3 MRI in asthma are predictive of 2-year 
exacerbation frequency [published online ahead of print March 13, 
2020]. J Allergy Clin Immunol.
    \576\ Kirby M, Pike D, Coxson HO, McCormack DG, Parraga G. 
Hyperpolarized (3)He ventilation defects used to predict pulmonary 
exacerbations in mild to moderate chronic obstructive pulmonary 
disease. Radiology 2014;273(3):887-896.
    \577\ Kirby M, Svenningsen S, Owrangi A, Wheatley A, Farag A, et 
al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology: Volume 265: Number 2--November 2012.
---------------------------------------------------------------------------

    The applicant asserted that the predictive power of VDP obtained 
from HP \3\He identified COPD patients with a higher likelihood of 
increased hospitalization due to exacerbation, therefore HP \129\Xe MRI 
VDP can be relied upon to be equally predictive. The applicant stated 
that Kirby et al. concluded that, in patients with COPD, the VDP 
obtained with HP \129\Xe MRI was ``significantly greater'' than that 
obtained with HP \3\He, and that this was likely due to HP \129\Xe's 
ability to fill lung spaces even in the presence of the physiologic 
and/or anatomic abnormalities in COPD patients.\578\ The applicant 
stated that because HP \129\Xe is delivered and imaged in the same 
manner as HP \3\He, XENOVIEW likely shares that predictive power while 
also providing more extensive detail of alveolar gas-exchange compared 
to HP \3\He MRI.
---------------------------------------------------------------------------

    \578\ Kirby M, Svenningsen S, Owrangi A, Wheatley A, Farag A, et 
al. Hyperpolarized \3\He and \129\Xe MR imaging in healthy 
volunteers and patients with chronic obstructive pulmonary disease. 
Radiology: Volume 265: Number 2--November 2012.
---------------------------------------------------------------------------

    Next, the applicant noted that numerous studies, including a Mummy 
et al.\579\ study and a Svenningsen et al.,\580\ study have suggested 
that HP \129\Xe is a useful resource to guide patient treatment 
decisions of COPD and asthma, respectively, based on the deeper 
understanding it provides of patient response to treatment (for 
example, bronchodilators).
---------------------------------------------------------------------------

    \579\ Mummy DG, Coleman EM, Wang Z, Bier EA, Lu J, Driehuys B, 
Huang YC. Regional gas exchange measured by \129\Xe magnetic 
resonance imaging before and after combination bronchodilators 
treatment in chronic obstructive pulmonary disease. J Magn Reson 
Imaging. 2021;54(3):964-974. doi: 10.1002/jmri.27662.
    \580\ Svenningsen S, Eddy RL, Lim HF, Cox PG, Nair P, Parrage G. 
Sputum eosinophilia and magnetic resonance imaging ventilation 
heterogeneity in severe asthma. Am J Respir Crit Care Med. 
2018;197(7):876-884. doi: 10.1164/rccm.201709-1948OC.
---------------------------------------------------------------------------

    In summary, the applicant stated in response to the first question 
asked at the New Technology Town Hall meeting that HP \129\Xe MRI 
provides pulmonologists with relied upon measurements of pulmonary 
function to inform treatment decisions. The applicant stated that lung 
CT can only image the first six airway branches. The applicant stated 
earlier disease and more subtle response to pharmacologic treatment has 
been quantified because XENOVIEW provides regional function and 
ventilation on 23 branches of the airway tree. Per the applicant, 
XENOVIEW MRIs enable identification of COPD or lung tissue 
abnormalities, leading to reduced elasticity earlier than spirometry or 
lung CT.\581\
---------------------------------------------------------------------------

    \581\ Doganay O, Chen M, Matin T, Kim M, McIntyre A, et al. 
Magnetic resonance imaging of the time course of hyperpolarized. 
\129\Xe gas exchange in the human lungs and heart. Eur Radiol. 
2019;29:2283-2292.
---------------------------------------------------------------------------

    The next two questions asked at the New Technology Town Hall 
meeting pertained to the ``gold standard'' for diagnosis when comparing 
sensitivity for HP \129\Xe and FEV1, and a request to share 
``receiver operator characteristics'' for the comparison of diagnostic 
accuracy. The applicant stated that the evidence for these answers was 
related and provided a combined response.
    According to the applicant, pulmonary function is reported using 
FEV1 measured by spirometry for FEV1/FVC <0.7, 
yet lacks accuracy at the individual patient level.\582\ Next, the 
applicant stated high resolution CT (HRCT) and in some cases SPECT/(CT) 
have been added to aid accuracy in diagnosis to inform treatment 
decisions. The applicant stated that these diagnostic tools are the 
gold standard(s) for measuring pulmonary function as a measure of 
diminished lung capacity.\583\
---------------------------------------------------------------------------

    \582\ Salzman SH. Which Pulmonary Function Tests Best 
Differentiate Between COPD Phenotypes? Respiratory Care. 2012;57:50-
60.
    \583\ Mallallah F, Packham A, Lee E, Hind D. Is hyperpolarised 
gas magnetic resonance imaging a valid and reliable tool to detect 
lung health in cystic fibrosis patients? A COSMIN systematic review. 
2021; Journal of Cystic Fibrosis online 14 January 2021.
---------------------------------------------------------------------------

    The applicant explained that due to the versatility of HP \129\Xe 
MRI, XENOVIEW can produce different measurements for PF related to 
disease with the accuracy reported by receiver operator characteristics 
(ROC). The applicant referenced Ebner, et al., a retrospective study 
that reported ROC data on the relationship of the ventilation defect 
scores (VDSs) derived from HP \129\Xe MRI identified with clinically 
relevant airway obstruction. The applicant stated that healthy 
volunteers (n=27) were compared to patients with asthma (n=20), and 
COPD (n=8), and that all the subjects underwent spirometry 1 day before 
MRI to establish the presence of airway obstruction (FEV1/
FVC <70%). The applicant stated that five blinded readers assessed the 
degree of ventilation impairment and assigned a VDS (range, 0-100%). 
According to the applicant, the study found that VDS measured with HP 
\129\Xe MRI correlated with the severity of airway obstruction and is 
significantly different between healthy control subjects and patients 
with mild to moderate airway obstruction. The applicant stated that 
while FEV1/FVC is an imperfect gold standard, Ebner et al 
applied HP \129\Xe MRI, a less effort-dependent and reproducible test, 
to establish a threshold for clinically significant ventilation defects 
to enable informed treatment decisions.\584\
---------------------------------------------------------------------------

    \584\ Ebner L, Virgincar R, He M, Choudhury KR, Robertson SH et 
al. Multi-Reader Determination of Clinically Significant Airway 
Obstruction using Hyperpolarized \129\Xe Ventilation MRI. AJR Am J 
Roentgenol. 2019 April; 212(4): 758-7.
---------------------------------------------------------------------------

    According to the applicant, Ruppert et al.\585\ were able to detect 
early stages of

[[Page 28316]]

lung disease in smokers before it progressed to COPD detected by 
spirometry. The applicant stated that in this study, the functional 
septal wall thickness and apparent diffusion coefficient of the gas 
phase was compared across 16 patients with smoking-related COPD, 9 
clinically healthy current or former smokers, and 10 healthy never 
smokers. The applicant stated that a table from Ruppert et al. showed 
the ROC area under curve (AUC) provides evidence to aid in 
understanding HP \129\Xe MRI when considering the metrics of early-
stage lung disease.\586\ According to the applicant, HP \129\Xe MRI 
produced favorable metrics for determining early-stage lung disease 
compared to FEV1. The applicant reported while the study had 
a small sample size, the ROC and AUC indicate HP \129\Xe MR imaging 
does detect patients with early lung disfunction.
---------------------------------------------------------------------------

    \585\ Ruppert K, Qing K, Patrie JT, Altes TA, Mugler III JP. 
Using hyperpolarized xenon-129 MRI to quantify early-stage lung 
disease in smokers. Acad Radiol. 2019;26(3):355-366. doi: 10.1016/
j.acra.2018.11.005.
    \586\ Ruppert K, Qing K, Patrie JT, Altes TA, Mugler III JP. 
Using hyperpolarized xenon-129 MRI to quantify early-stage lung 
disease in smokers. Acad Radiol. 2019;26(3):355-366. doi: 10.1016/
j.acra.2018.11.005.
---------------------------------------------------------------------------

    The applicant stated that in a separate study by Tafti et al.,\587\ 
a table reported that ADC yielded a much higher ROC AUC of >=0.92 
[0.83, 1.00] when used to determine emphysema. The applicant stated 
that the ADC emphysema index showed near-perfect sensitivity in a 
sample of 17 patients, all of whom were measured with both HP \3\He and 
HP \129\Xe (95% CI: 94%, 100%), but somewhat lower specificity (14 of 
19 = 74% for HP \3\He [95% CI: 49%, 99%]; 13 of 19 = 68% for HP \129\Xe 
[95% CI: 42%, 94%]).
---------------------------------------------------------------------------

    \587\ Tafti S, Garrison WJ, Mugler III JP, Shim YM, Altes TA, 
Mata JF, de Lange EE, Cates GD, Ropp AM, Wang C, Miller GW. 
Emphysema index based on hyperpolarized \3\He or \129\Xe diffusion 
MRI: Performance and comparison with quantitative CT and pulmonary 
function tests. Radiology. 2020;297:201-210.
---------------------------------------------------------------------------

    The applicant stated that Lin et al.\588\ showed, in a population 
of children with asthma, a difference in HP \129\Xe compared to 
spirometry related to patient's clinical signs and symptoms. The 
applicant stated that in this study of 37 children with asthma, \129\Xe 
MRI was able to distinguish between control patients and patients with 
disease, whereas spirometry did not. The applicant stated Lin et al. 
demonstrated sensitivity, specificity and PPV values of HP \129\Xe to 
provide reliable prediction of asthma severity. The applicant stated 
that currently, there are no adequate predictive diagnostic tools to 
clearly measure clinical severity of pediatric asthma that concurrently 
provide information about regional ventilation differences.\589\ The 
applicant stated that results from HP \129\Xe MRI are correlated with 
increased asthma severity, as well as increased healthcare utilization 
(HCU) and oral corticosteroid (OCS) use. According to the applicant, 
even with relatively modest cohort numbers, ROC analysis demonstrated 
that VDP and image scoring can predict increased asthma severity and 
HCU in a pediatric asthma cohort. The applicant stated that the 
improved predictive value, high safety profile, and short and tolerable 
imaging process allows for longitudinal follow-up in children. 
According to the applicant, the ROC curves from Lin et al. demonstrated 
that the number of defects (AUC, 0.83) is more predictive of healthcare 
utilization (HCU) than VDP (AUC, 0.73), and that the number of defects 
is more predictive of severe asthma (AUC, 0.86) than is VDP (AUC, 
0.80).\590\ The applicant stated that these findings are consistent 
with HP \129\Xe MRI (similar to HP \3\He) VDP in COPD patients as 
predictive of a higher likelihood of increased hospitalization.
---------------------------------------------------------------------------

    \588\ Lin NY, Roach DJ, Willmer MM, Walkup LL, Hossain M, et al. 
\129\Xe MRI as a measure of clinical disease severity for pediatric 
asthma. 2021; Journal of Allergy and Clinical Immunology 147(6): 
2146-2153.
    \589\ Teague WG, Tustison NJ, Altes TA. Ventilation 
heterogeneity in asthma. J Asthma 2014;51:677-84.
    \590\ Lin NY, Roach DJ, Willmer MM, Walkup LL, Hossain M, et al. 
\129\Xe MRI as a measure of clinical disease severity for pediatric 
asthma. 2021; Journal of Allergy and Clinical Immunology 147(6): 
2146-2153.
---------------------------------------------------------------------------

    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 XENOVIEW. Regarding XENOVIEW, we 
note the applicant stated there are no published studies reporting 
early detection of disease using XENOVIEW that followed longitudinally 
reported outcomes. We also note that many of the articles submitted by 
the applicant were not about XENOVIEW, but rather described the usage 
of hyperpolarized 3-Helium (or HP \3\He) imaging and the correlation of 
measurements obtained through HP \3\He imaging with existing standard 
of care imaging modalities such as spirometry. We question whether 
results from studies that utilize HP \3\He MRI can be extrapolated to 
the use of HP \129\Xe MRI. We also note that several citations provided 
by the applicant are limited to pediatric populations, and we question 
whether the results would be generalizable to a Medicare population.
7. Proposed FY 2023 Applications for New Technology Add-On Payments 
(Alternative Pathways)
    As discussed previously, beginning with applications for FY 2021, 
under the regulations at Sec.  412.87(c), 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, under the 
regulations at Sec.  412.87(d), a medical product that is designated by 
FDA as a QIDP and has received marketing authorization for the 
indication covered by the QIDP designation, and, beginning with FY 
2022, a medical product that is a new medical product approved under 
FDA's 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 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 be within the 2-3 year newness period to be 
considered ``new,'' and must also 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

[[Page 28317]]

medical technology will no longer be considered ``new'' under the 
criterion of this section.
    We received 19 applications for new technology add-on payments for 
FY 2023 under the new technology add-on payment alternative pathways. 
Six applicants withdrew applications prior to the issuance of this 
proposed rule. Of the remaining 13 applications, 11 of the technologies 
received a Breakthrough Device designation from FDA, 1 has a pending 
Breakthrough Device designation from FDA, and the remaining application 
was designated as a QIDP by FDA and is also requesting approval under 
the LPAD pathway from FDA.
    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 (e)(3) which provides for 
conditional approval for a technology for which an application is 
submitted under the alternative pathway for certain antimicrobial 
products (QIDPs and LPADs) at Sec.  412.87(d) that does not receive FDA 
marketing authorization by the July 1 deadline specified in Sec.  
412.87(e)(2), provided that the technology receives FDA marketing 
authorization by July 1 of the particular fiscal year for which the 
applicant applied for new technology add-on payments. We refer the 
reader to the FY 2021 IPPS/LTCH PPS final rule for a complete 
discussion of this policy (85 FR 58737 through 58742).
    As we did in the FY 2022 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 13 applications for FY 2023 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 2023. 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 further discussion of the 
alternative new technology add-on payment pathways for these 
technologies.
a. Alternative Pathway for Breakthrough Devices
(1) CERAMENT[supreg] G
    BONESUPPORT AB submitted an application for new technology-add on 
payments for CERAMENT[supreg] G for FY 2023. 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. We note that BONESUPPORT 
Inc. previously submitted an application for new technology add-on 
payments for CERAMENT[supreg] G for FY 2022, as summarized in the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25368 through 25373) but the 
technology did not meet the deadline of July 1, 2021, for FDA approval 
or clearance of the technology and, therefore, was not eligible for 
consideration for new technology add-on payments for FY 2022 (86 FR 
45126 through 45127).
    According to the applicant, 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. The applicant indicated that it 
anticipates FDA will grant its De Novo classification request in the 
second quarter of calendar year 2022. The applicant applied for and 
received a unique ICD-10-PCS procedure code to identify cases involving 
the administration of CERAMENT[supreg] G in 2021. Effective October 1, 
2021, CERAMENT[supreg] G administration can be identified by ICD-10-PCS 
procedure code XWOV0P7 (Introduction of antibiotic eluting bone void 
filler into bones, open approach, new technology group 7), which is 
unique to CERAMENT[supreg] G administration. The applicant stated that 
the following existing ICD-10-CM codes for osteomyelitis appropriately 
describe the proposed indication for which the device received 
Breakthrough Device designation (``Breakthrough Device Indication''):
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.280

    With respect to the cost criterion, the applicant identified 
candidate cases using ICD-10-PCS procedure and ICD-10-CM diagnosis 
codes, which are detailed in the tables in this section. With these 
codes identified, the

[[Page 28318]]

applicant then went through the Grouper logic in the MS-DRG v39.0 
Definitions Manual and located where cases with these codes would be 
assigned in the MS-DRG system. This process yielded 13 MS-DRGs which 
the applicant used for their analysis. The applicant also submitted an 
additional subanalysis using only cases from the applicant's top three 
identified MS-DRGs (464, 493, and 504), to demonstrate that the 
technology meets the cost criterion.
    Under the first analysis, the applicant searched claims in the FY 
2019 MedPAR final rule dataset within the 13 identified MS-DRGs that 
reported one of the M86 ICD-10-CM diagnosis codes listed previously in 
combination with the ICD-10-PCS procedure codes listed in the following 
table, which identify procedures that could involve the use of 
CERAMENT[supreg] G as an adjunct to systemic antibiotic therapy and 
surgical debridement where there is a need for supplemental bone void 
filler material.
[GRAPHIC] [TIFF OMITTED] TP10MY22.281


[[Page 28319]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.282


[[Page 28320]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.283


[[Page 28321]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.284

    The applicant identified 11,620 cases across 13 MS-DRGs as 
identified in the table that follows.
[GRAPHIC] [TIFF OMITTED] TP10MY22.285


[[Page 28322]]


BILLING CODE 4120-01-C
    The applicant noted that candidate cases for CERAMENT[supreg] G 
with osteomyelitis would qualify for the CC/MCC MS-DRGs because 
osteomyelitis is listed in the Grouper as a CC condition. Therefore, 
the applicant concluded that cases with osteomyelitis would not be 
grouped in the uncomplicated MS-DRGs (for example, 465, 494, etc.). The 
applicant stated that because osteomyelitis is never assigned to 
uncomplicated surgical MS-DRGs, it excluded uncomplicated MS-DRGs from 
its analysis.
    The applicant then removed charges for the 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.\591\ Then the 
applicant converted costs to charges by dividing costs by the Supplies 
& Equipment CCR of 0.297 (86 FR 44966). Using this CCR, $444 per 5cc 
and $727 per 10cc yielded an estimated hospital charge of prior 
technologies of $1,495 per 5cc and $2,449 per 10cc. The applicant 
explained that the total amount of antibiotics depends on the amount of 
product required for different sized bones. The applicant then 
standardized the charges and applied a 4-year inflation factor of 
1.281834 based on the inflation factor used to update the outlier 
threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45542).
---------------------------------------------------------------------------

    \591\ The applicant's analysis was informed by 2019 and 2020 
data for Osteoset, Stimulan, and Calcigen S (calcium sulfates mixed 
with antibiotics), Palacos, Cobalt (PMMA manually mixed with 
antibiotics), Cobalt G, Biomet Bone Cement R, and Refobacin Bone 
Cement R (PMMA pre-loaded with antibiotics) 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 added estimated charges for the new technology by 
dividing the estimated, expected hospital list price for the device 
(based on expected 5/10/15 cc costs for CERAMENT[supreg] G, by MS-DRG), 
by the aforementioned Supplies & Equipment CCR of 0.297.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $135,258 and an average case-weighted 
threshold of $86,603. 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.
    The applicant also provided an alternate cost analysis using the 
applicant's top three identified MS-DRGs (464, 493, and 504), which 
together constituted more than half of the applicant's identified 
cases. Using the same methodology and data sources above, the applicant 
calculated a final inflated case-weighted average standardized charge 
per case of $112,316 and an average case-weighted threshold of $77,375. 
The applicant maintained that CERAMENT[supreg] G meets the cost 
criterion under this alternate analysis.
    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, 2022, we are proposing 
to approve CERAMENT[supreg] G for new technology add-on payments for FY 
2023.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the total cost of CERAMENT[supreg] G for a typical 
patient is $7,567 per procedure. Per the applicant, the amount of 
CERAMENT[supreg] G used per patient depends on the complexity of the 
patient's injury, subsequent comorbidities, as well as the location and 
size of the bone void. The applicant expects that an average patient 
will require ~10cc per procedure, based on the case weighted volume of 
expected utilization across the MS-DRGs. From this weighted average, 
the applicant derived the average, weighted cost of $7,567 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% of the average cost of 
the technology, or 65% 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 $4,918.55 for FY 2022 (that is, 65% of the 
average cost of the technology).
    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 2023, 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, 2022.
(2) GORE[supreg] TAG[supreg] Thoracic BranchEndoprosthesis (TBE Device)
    W.L. Gore and Associates, Inc., submitted an application for new 
technology add-on payments for the GORE[supreg] TAG[supreg] Thoracic 
Branch Endoprosthesis (TBE) device for FY 2023. According to the 
applicant, the GORE[supreg] TAG[supreg] TBE device is a modular device 
consisting of three components, an Aortic Component, a Side Branch 
Component, and an optional Aortic Extender Component, each of which is 
pre-mounted on a catheter delivery system for treatment of thoracic 
aortic aneurysms, traumatic aortic transection, and aortic dissection.
    According to the applicant, the GORE[supreg] TAG[supreg] TBE device 
was granted designation under the Expedited Access Pathway (EAP) by FDA 
(and is therefore considered part of the Breakthrough Devices Program 
by FDA) on July 17, 2015, for endovascular repair of descending 
thoracic aortic and aortic arch for patients who have appropriate 
anatomy. The applicant indicated that it anticipates receiving 
premarket approval of the GORE[supreg] TAG[supreg] TBE device as a 
Class III device from FDA in Spring 2022 with a proposed indication for 
endovascular repair of lesions of the descending thoracic aorta, while 
maintaining flow into the left subclavian artery, in patients who have 
adequate iliac/femoral access, and eligible proximal aorta, left 
subclavian, or distal landing zones (isolated lesion patients only). 
Since the indication for which the applicant anticipates receiving 
premarket approval is included within the scope of the EAP designation, 
it appears that the proposed PMA indication is appropriate for new 
technology add-on payment under the alternative pathway criteria.
    The applicant noted that a combination of two existing ICD-10-PCS 
procedure codes can be used to uniquely identify the GORE[supreg] 
TAG[supreg] TBE: 02VW4EZ (Restriction of thoracic aorta, descending 
with branched or fenestrated intraluminal device, one or two arteries, 
percutaneous endoscopic approach), in combination with 02VX4EZ 
(Restriction of thoracic aorta, ascending/arch with branched or 
fenestrated intraluminal device, one or two arteries, percutaneous 
endoscopic approach). Per the applicant, the GORE[supreg] TAG[supreg] 
TBE device is placed such that it

[[Page 28323]]

straddles two anatomic regions, the descending thoracic aorta and 
thoracic aortic arch, thereby necessitating the use of both ICD-10-PCS 
procedure codes to accurately describe the use of the device.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR dataset from the FY 2022 IPPS proposed rule for cases 
reporting a combination of a thoracic endovascular repair (TEVAR) 
procedure and a bypass procedure. The applicant listed the following 
ICD-10-PCS codes for TEVAR procedures and bypass procedures, which the 
applicant used to identify potential cases that may be eligible for 
treatment with the GORE[supreg] TAG[supreg] TBE device. Per the 
applicant, cases with at least one ICD-10-PCS procedure code from each 
category were included in the analysis.
[GRAPHIC] [TIFF OMITTED] TP10MY22.286

[GRAPHIC] [TIFF OMITTED] TP10MY22.287

    The applicant identified 210 cases mapping to five MS-DRGs. The 
applicant then removed charges for the technology being replaced. The 
applicant stated that the use of TAG[supreg] Conformable devices in 
cases that also use the GORE[supreg] TAG[supreg] TBE device is entirely 
dependent on the patient's anatomy. The applicant explained that the 
average case utilizing the GORE[supreg] TAG[supreg] TBE device uses 0.6 
TAG[supreg] Conformable devices, compared to an average of 1.4 
TAG[supreg] Conformable devices per procedure for current TEVAR cases, 
resulting in a difference of 0.8 TAG[supreg] Conformable devices which 
will no longer be used in cases utilizing the GORE[supreg] TAG[supreg] 
TBE device. Accordingly, 80% of all device implant charges were removed 
from the claims to be conservative, per the applicant. The applicant 
then removed other charges related to the prior technology. According 
to the applicant, a research study \592\ that compared 24 patients 
treated with TBE to 31 patients treated with the traditional method at 
one facility found that TBE device cases have a 19% reduction in 
operating room (OR) time compared to the OR time for the combined 
procedures (TEVAR with a bypass procedure), and a 48% reduction in 
length of stay. Accordingly, the applicant removed 19% of OR charges 
(revenue code 0360), removed 48% of routine charges (revenue code 01XX) 
when a claim showed routine charges, and removed 48% of intensive care 
unit (ICU) charges if a claim included no routine charges. The 
applicant then standardized the charges and applied a 4-year inflation 
factor of 1.2818 based on the inflation factor used in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45538), to update the charges from FY 
2019 to FY 2023. The applicant then added charges for the new 
technology by dividing the average per patient cost of the GORE[supreg] 
TAG[supreg] TBE device by the national CCR for implantable devices 
(0.293) from the FY 2022 IPPS/LTCH PPS final rule (86 FR 44966). The 
applicant calculated a final inflated case-weighted average 
standardized charge per case of $400,515 and an average case-weighted 
threshold of $217,182. Because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold

[[Page 28324]]

amount, the applicant asserted that the technology meets the cost 
criterion.
---------------------------------------------------------------------------

    \592\ Shultze W, Baxter R, Gable C, et al. Comparison Of 
Surgical Debranching Versus Branched Endografts In Zone 2 TEVAR. 
Oral presentation at the Society for Vascular Surgery Meeting; March 
2021, Miami FL. https://symposium.scvs.org/abstracts/2021/M76.cgi.
---------------------------------------------------------------------------

    We note that the charges removed for prior technology are based on 
length of stay in a small study conducted at a single institution. 
Specifically, the study involved 24 patients who received the TBE 
device during elective procedures and 31 who had the procedures with 
bypass. Three of these procedures were emergent and only 14 and 17, 
respectively, were procedures in Zone 2 where the GORE[supreg] 
TAG[supreg] TBE would be indicated. Given the small percentage of 
procedures that directly relate to the proposed GORE[supreg] 
TAG[supreg] TBE indication, we question the extent to which these 
results are generalizable to the cost analysis performed above and the 
greater Medicare population. Additionally, the applicant did not 
specify the revenue codes used to identify and remove intensive care 
unit charges. We note the applicant listed two ICD-10-PCS codes 
(03S43ZZ and 03SQ3ZZ) in their analysis which are percutaneous 
procedures and question whether the inclusion of these codes is 
appropriate as the devices currently used to repair the aortic arch 
require the creation of a bypass performed in an open surgery. We also 
question whether the cases that the applicant identified are 
appropriately representative of cases eligible for treatment with 
GORE[supreg] TAG[supreg] TBE and request additional information to 
clarify this issue.
    Subject to the applicant adequately addressing these concerns, we 
would agree that the technology meets the cost criterion and therefore 
are proposing to approve the GORE[supreg] TAG[supreg] TBE device for 
new technology add-on payments for FY 2023, subject to the technology 
receiving FDA marketing authorization for the proposed indication by 
July 1, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the per-patient anticipated hospital cost of the 
GORE[supreg] TAG[supreg] TBE device is $42,780. 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% of the average cost of the technology, or 65% of 
the costs in excess of the MS-DRG payment for the case. In the event we 
receive supplemental information from the applicant to adequately 
address our concerns regarding the cost criterion, and we were to 
approve new technology add-on payments for the GORE[supreg] TAG[supreg] 
TBE device in the final rule, the maximum new technology add-on payment 
for a case involving the use of the GORE[supreg] TAG[supreg] TBE device 
would be $27,807 for FY 2023 (that is, 65% of the average cost of the 
technology).
    We are inviting public comments on whether the GORE[supreg] 
TAG[supreg] TBE device meets the cost criterion and our proposal to 
approve new technology add-on payments for the GORE[supreg] TAG[supreg] 
TBE device for FY 2023, subject to the technology receiving FDA 
marketing authorization for the proposed indication that corresponds to 
the EAP designation by July 1, 2022.
(3) iFuse Bedrock Granite Implant System
    SI-BONE, Inc., submitted an application for new technology add-on 
payments for the iFuse Bedrock Granite Implant System for FY 2023. 
According to the applicant, the iFuse Bedrock Granite Implant System is 
a sterile, single-use permanent implant intended to provide sacropelvic 
fusion of the sacroiliac joint and fixation to the pelvis when used in 
conjunction with commercially available pedicle screw fixation systems 
as a foundational element for segmental spinal fusion. The applicant 
states that the joint fusion occurs as a result of the device's porous 
surface and interstices, and fixation occurs through the device's 
helical threaded design and traditional posterior fixation rod 
connection. Per the applicant, the iFuse Bedrock Granite Implant System 
can be placed into the pelvis in two trajectories: Sacroalar-iliac 
(SAI) trajectory (that is, into the sacrum, across the SI joint and 
into the ilium) or directly into the ilium, and joint fusion occurs 
only when the SAI trajectory is used.
    According to the applicant, the iFuse Bedrock Granite Implant 
System received FDA Breakthrough Device designation on November 23, 
2021 for sacropelvic fixation and as an adjunct for sacroiliac joint 
fusion (when used with commercially available sacroiliac joint fusion 
promoting devices) in conjunction with commercially available posterior 
pedicle screw systems for the treatment of the acute and chronic 
instabilities or deformities of the thoracic, lumbar, and sacral spine; 
degenerative disc disease (DDD) as defined by back pain of discogenic 
origin with degeneration of the disc confirmed by patient history and 
radiographic studies; severe spondylolisthesis (Grades 3 and 4) of the 
L5-S1 vertebra in skeletally mature patients receiving fusions by 
autogenous bone graft having implants attached to the lumbar and sacral 
spine (L3 to sacrum) with removal of the implants after the attainment 
of a solid fusion; spondylolisthesis; trauma (that is, fracture or 
dislocation); spinal stenosis; deformities or curvatures (that is, 
scoliosis, kyphosis, and/or lordosis); spinal tumor; pseudarthrosis; 
and/or failed previous fusion. The applicant is seeking 510(k) 
clearance from FDA for the same indication.
    The applicant stated that ICD-10-PCS codes that may be utilized to 
describe the placement of an internal fixation device into the pelvic 
bone or acetabulum, listed in the following table, do not distinctly 
identify the iFuse Bedrock Granite Implant System. The applicant 
submitted a request to the ICD-10 Coordination and Maintenance 
Committee for approval of a unique code for FY 2023 to identify the 
technology.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.288

    With regard to the cost criterion, the applicant conducted two 
analyses based on 100% of identified claims and 78% of identified 
claims. To identify potential cases where the iFuse Bedrock Granite 
Implant System could be

[[Page 28325]]

utilized, the applicant searched the FY 2019 MedPAR final rule file for 
claims reporting a combination of at least one of the ICD-10-PCS 
procedure codes for the placement of an internal fixation device into 
the pelvic bone or acetabulum, noted previously, and at least one of 
the following ICD-10-CM diagnosis codes used to describe the indication 
under the Breakthrough Device designation.
[GRAPHIC] [TIFF OMITTED] TP10MY22.289

    For the analysis using 100% of cases, the applicant identified 
2,165 cases mapping to the following 26 MS-DRGs:

[[Page 28326]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.290


[[Page 28327]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.291

BILLING CODE 4120-01-C
    The applicant then removed 50% of the charges associated with 
medical supplies and implantable devices (revenue centers 027x and 
0624). The applicant stated that the removal of 50% of the charges 
associated with medical supplies and implantable devices reflects a 
conservative estimate as the iFuse Bedrock Granite Implant System is 
used in conjunction with commercially available pedicle screw fixation 
systems as a foundational element for segmental spinal fusion. The 
applicant then standardized the charges and applied the three-year 
inflation factor of 20.4% used to update the outlier threshold in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45542) to update the charges 
from FY 2019 to FY 2022. The applicant then added charges for the new 
technology by dividing the per-patient anticipated hospital cost of the 
iFuse Bedrock Granite Implant System by the national average cost-to-
charge ratio for implantable devices (0.239) from the FY 2022 IPPS/LTCH 
PPS final rule. Under the analysis based on 100% of identified claims, 
the applicant calculated a final inflated case-weighted average 
standardized charge per case of $254,264 and an average case-weighted 
threshold of $159,841.
    For the analysis using 78% of cases, the applicant identified 1,682 
cases mapping to 4 MS-DRGs. The applicant conducted the same analysis 
noted previously and determined a final inflated case-weighted average 
standardized charge per case of $253,333 and an average case-weighted 
threshold of $164,561. 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 iFuse Bedrock Granite Implant 
System meets the cost criterion and therefore are proposing to approve 
the iFuse Bedrock Granite Implant System for new technology add-on 
payments for FY 2023, subject to the technology receiving FDA marketing 
authorization for the indication corresponding to the Breakthrough 
Device designation by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the per-patient anticipated hospital cost of the 
iFuse Bedrock Granite Implant System is $15,120. 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% of the average cost of the technology, or 65% 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 iFuse Bedrock Granite Implant System would be 
$9,828 for FY 2023 (that is, 65% of the average cost of the 
technology).
    We are inviting public comments on whether the iFuse Bedrock 
Granite Implant System meets the cost criterion and our proposal to 
approve new technology add-on payments for the iFuse Bedrock Granite 
Implant System for FY 2023, subject to the technology receiving FDA 
marketing authorization for the indication corresponding to the 
Breakthrough Device designation by July 1, 2022.
(4) LigaPASS 2.0 PJK Prevention System
    Medtronic submitted an application for new technology add-on 
payments for the LigaPASS 2.0 PJK Prevention System for FY 2023. Per 
the applicant, the LigaPASS 2.0 PJK Prevention System is intended to 
mitigate the risk of post-operative proximal junctional kyphosis (PJK) 
and proximal junctional failure (PJF) in patients with spinal

[[Page 28328]]

deformities. The applicant states that the LigaPASS 2.0 PJK Prevention 
System is designed to restore balance and stability as a complement to 
a posterior thoracolumbar fixation system, and provides surgeons the 
ability to mimic anatomical muscle and ligament functionality and 
stabilization between vertebrae adjacent to fused levels in a spine 
surgery. According to the applicant, the LigaPASS 2.0 PJK Prevention 
System consists of a polyester (PET) band and titanium alloy medial 
open connector with two set screws. The applicant indicates the 
LigaPASS 2.0 PJK Prevention System bands are laced around the vertebra 
independently of the vertebra anatomy and then connected to a LigaPASS 
2.0 PJK Prevention System connector to make the rod-bone connection, 
allowing the surgeon to create a posterior vertebra anchorage without 
the use of a pedicle screw or hook.
    According to the applicant, the LigaPASS 2.0 PJK Prevention System 
was granted Breakthrough Device designation on September 2, 2021, for 
spinal trauma surgery, used in sublaminar or facet wiring techniques; 
spinal reconstructive surgery, incorporated into construct for the 
purpose of correction of spinal deformities such as idiopathic and 
neuromuscular scoliosis in patients 8 years of age and older, adult 
scoliosis and kyphosis; spinal degenerative surgery as an adjunct to 
spinal fusions; intended for use at the non-fused level(s) adjacent to 
a posterior spinal instrumentation construct when ligament augmentation 
is considered appropriate to mitigate the risk of post-operative PJK 
and PJF. The applicant noted that a 510(k) has been submitted to FDA 
for the same indication (K213659). The applicant stated that the 
LigaPASS 2.0 PJK Prevention System includes components from two 
predicate devices: The LigaPASS 2.0 connector (K172021), previously 
cleared to provide temporary stabilization as a bone anchor during the 
development of solid bony fusion, and the LigaPASS 2.0 band (K173506), 
previously cleared to aid in the repair of bone fractures. According to 
the applicant, there are no technological differences between the 
subject device and its predicates; the only difference would be the 
added PJK/PJF indication covered by the Breakthrough Device 
designation. The applicant indicated that it is seeking new technology 
add-on payment only for the LigaPASS 2.0 PJK Prevention System's 
proposed new PJK and PJF indication for which the device has been 
designated as a Breakthrough Device by FDA. According to the applicant, 
there are no ICD-10-PCS codes that uniquely identify procedures 
involving the use of the LigaPASS 2.0 PJK Prevention System. The 
applicant also noted there are no unique ICD-10-CM diagnosis codes that 
describe the indication for prophylactic use of the LigaPASS 2.0 PJK 
Prevention System for PJK/PJF prevention covered by the Breakthrough 
Device designation. The applicant has submitted a request for a unique 
ICD-10-CM diagnosis code and a unique ICD-10-PCS code that can be used 
together to uniquely identify cases involving use of the technology for 
the Breakthrough Device designation for the technology.
    With regard to the cost criterion, the applicant provided the 
following cost analysis to demonstrate that the LigaPASS 2.0 PJK 
Prevention System meets the cost criterion. The applicant searched the 
FY 2019 MedPAR dataset for cases representing patients who may be 
eligible for LigaPASS 2.0 PJK Prevention System. The applicant stated 
they conducted a thorough review of ICD-10-PCS codes for procedures in 
which the LigaPASS 2.0 PJK Prevention System might be placed into the 
spine to prevent PJK/PJF in an adult patient who is diagnosed with 
spinal deformity. The applicant provided the following ICD-10-PCS 
procedure codes and ICD-10-CM diagnosis codes used to identify cases 
representing patients who may be eligible for the LigaPASS 2.0 PJK 
Prevention System.
BILLING CODE 4120-01-P
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    The applicant identified 433,845 cases using the combination of 
ICD-10-PCS and ICD-10-CM codes which mapped to the following 11 MS-
DRGs:
[GRAPHIC] [TIFF OMITTED] TP10MY22.134

BILLING CODE 4120-01-C
    The applicant did not remove charges for prior technology. The 
applicant standardized the charges and applied a 4-year inflation 
factor of 1.281834 based on the inflation factor used to update the 
outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542), to update the charges from FY 2019 to FY 2023. The applicant 
then added charges for the new technology by dividing the per-patient 
anticipated hospital cost of the LigaPASS 2.0 PJK Prevention System by 
the national average cost-to-charge ratio for implantable devices 
(0.239) from the FY 2022 IPPS/LTCH PPS final rule (86 FR 44966). The 
applicant also added related charges for the new technology, estimated 
by the cost of 15 additional minutes of operating room time and 15 
additional minutes of nursing time divided by the national average 
cost-to-charge ratios for Operating Room (0.167) and Other Services 
(0.344), respectively, from the FY 2022 IPPS/LTCH PPS final rule (86 FR 
44966). The applicant calculated a final inflated case-weighted average 
standardized charge per case of $386,183 and an average case-weighted 
threshold of $165,473. 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 LigaPASS 2.0 PJK Prevention 
System meets the cost criterion and therefore are proposing to approve 
the LigaPASS 2.0 PJK Prevention System for new technology add-on 
payments for FY 2023, subject to the technology receiving FDA marketing 
authorization for the indication corresponding to the Breakthrough 
Device designation by July 1, 2022.
    Based on the preliminary information from the applicant at the time 
of this proposed rule, the cost per case of the LigaPASS 2.0 PJK 
Prevention System is $17,392, which includes $10,458 for 2 bands and 
$6,934 for 2 connectors per surgery. 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% of the average cost of the technology, or 65% 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 LigaPASS 2.0 PJK Prevention System would be 
$11,305 for FY 2023 (that is, 65% of the average cost of the 
technology).
    We are inviting public comments on whether the LigaPASS 2.0 PJK 
Prevention System meets the cost criterion and our proposal to approve 
new technology add-on payments for LigaPASS 2.0 PJK Prevention System 
for FY 2023, subject to the technology receiving FDA marketing 
authorization for the indication corresponding to the Breakthrough 
Device designation by July 1, 2022.
(5) Magnus Neuromodulation System With SAINT Technology
    Magnus Medical, Inc. submitted an application for new technology 
add-on payments for Magnus Neuromodulation System (MNS) with Stanford 
Accelerated Intelligent Neuromodulation Therapy (SAINT) technology for 
FY 2023. Per the applicant, the Magnus Neuromodulation System with 
SAINT technology is a transcranial magnetic stimulation (TMS) device 
with intermittent theta burst (iTBS) capability and includes a 
neuronavigation system to direct neurostimulation to individualized 
targets, and has target identification software that identifies 
individualized targets in the brain for stimulation using structural 
and functional MRI outputs. According to the applicant, the Magnus 
Neuromodulation System with SAINT technology utilizes magnetic pulses 
delivered to the prefrontal cortex in order to treat major depressive 
disorder (MDD), and has redesigned aspects of TMS to personalize the 
treatment and optimize individual patient response. These aspects 
include the identification of a target for stimulation, the dose or 
amount of stimulation, and the stimulation pattern.
    The applicant stated that on July 2, 2021, the FDA designated the 
Magnus Transcranial Magnetic Stimulation (TMS) System with MINT (Magnus 
Intelligent Neuromodulation Therapy) as a Breakthrough Device for the 
treatment of major depressive disorder (MDD) in adult patients who have 
failed to receive satisfactory improvement

[[Page 28340]]

from prior antidepressant medication in the current episode. According 
to the applicant, the Magnus Neuromodulation System with SAINT 
technology is the same system that received the Breakthrough Device 
designation, but with a revised name. Per the applicant, Magnus 
Neuromodulation System with SAINT technology is a Class II device. The 
applicant stated that it is seeking FDA 510(k) clearance for the same 
indication, which the applicant expects to receive by June 1, 2022.
    According to the applicant, there are currently no ICD-10-PCS codes 
to distinctly identify the Magnus Neuromodulation System with SAINT 
technology. The applicant submitted a request for approval for a unique 
ICD-10-PCS procedure code for Magnus Neuromodulation System with SAINT 
technology beginning in FY 2023. The applicant stated that the 
following ICD-10-CM diagnosis codes may be used to identify cases 
corresponding to the proposed Breakthrough Device indication for use of 
Magnus Neuromodulation System with SAINT technology: F32.2 (Major 
depressive affective disorder, single episode, severe, without mention 
of psychotic behavior) and F33.3 (Major depressive affective disorder, 
recurrent episode, severe, without mention of psychotic behavior).
    With respect to the cost criterion, the applicant completed an 
analysis, as well as an additional subanalysis including only cases 
containing the ICD-10-CM diagnosis codes that correspond to their 
Breakthrough Device indication, to demonstrate that the Magnus 
Neuromodulation System with SAINT technology meets the cost criterion.
    Under the main analysis, after determining that cases representing 
patients who may be eligible for treatment with Magnus Neuromodulation 
System with SAINT technology would map to MS-DRG 885 (Psychoses), the 
applicant determined a case count of 68,602 based on the number of 
cases reported for MS-DRG 885 in the FY 2023 New Technology Thresholds 
data file published with the FY 2022 IPPS/LTCH PPS final rule. The 
applicant then searched the FY 2020 Inpatient Standard Analytic File 
(IPSAF) for claims incurred during FY 2020 with an MS-DRG of 885. The 
applicant aggregated the charges at the facility level and calculated a 
weighted average of covered charges across all facilities.
    The applicant stated that it declined to remove charges for prior 
technology, as the applicant determined that analogous technologies are 
currently used almost exclusively on an outpatient basis. The applicant 
then standardized the charges using inputs from the FY 2022 
Standardizing File and the geographic adjustment factor (GAF) from the 
IPPS FY 2022 final rule impact file. The applicant applied the 3-year 
inflation factor used in the FY 2022 IPPS/LTCH PPS final rule and 
correction notice to calculate outlier threshold charges, which the 
applicant stated as 1.204686 (86 FR 45542). The applicant then added 
charges for the new technology by dividing the cost of Magnus 
Neuromodulation System with SAINT technology by the national average 
CCR for the Other Services, which is 0.334 (86 FR 44966), and inflating 
the charges using the same three year-inflation factor. The applicant 
added costs using the Outpatient Standard Analytic File (OPSAF) for FY 
2020 data to populate estimated charges related to the technology and 
specifically included the following charges related to procedures from 
the OSPAF 2020:
     Brain Stimulation Consultation (completed on day 1 or 2 of 
the admission): Average weighted charges for CPT codes 99253-99255 
($481.91).
     Neuro Navigation (completed on day 1 or 2 of the 
admission): Average weighted charges for CPT code 61782 ($3,871.77). 
This procedure is performed every day before stimulation treatment and 
the day of the fMRI (Functional MRI) (6 instances on separate days).
     Functional MRI (fMRI) (completed on day 1 or day 2 of the 
admission): Average charges for CPT code 70554 ($3,333.89).
     Motor Threshold Determination (completed on the first day 
of the brain stimulation sessions): Average charges for CPT code 90867 
within revenue code 900 ($639.05).
     Brain Stimulation Sessions (10 sessions a day across 5 
treatment days, that is 50 sessions): Average charges for CPT code 
90868 within revenue code 900 ($502.63).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $120,840 which exceeded the average 
case-weighted threshold amount of $34,073. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that Magnus 
Neuromodulation System with SAINT technology meets the cost criterion.
    Under the subanalysis, the applicant included only cases within MS-
DRG 885 reporting an ICD-10-CM diagnosis code of F32.2 or F33.3, as 
these two diagnosis codes match their Breakthrough Device indication. 
The applicant identified 2,787 cases containing either of these two 
ICD-10-CM diagnosis codes within MS-DRG 885. The applicant then applied 
the same methodology for calculations as in the main analysis. The 
calculations in this sub-analysis resulted in a case-weighted average 
standardized charge per case of $29,882 and a final inflated average 
case weight standardized charge per case of $125,152. The final 
inflated average case-weighted standardized charge per case under this 
subanalysis also exceeded the average case-weighted threshold amount of 
$34,073.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the applicant anticipated the total cost of the 
Magnus Neuromodulation System with SAINT technology to the hospital to 
be a $12,500 fee per patient. The applicant stated that the cost of the 
technology consists of the three individual components of the Magnus 
Neuromodulation System with SAINT technology: The neurostimulation 
hardware, the neuronavigation hardware, and the target identification 
software. The applicant also noted that none of these were operating 
costs. 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 payment of 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 (86 FR 45145). Based on the information from the 
applicant, it appears that the costs of the Magnus Neuromodulation 
System with SAINT technology only include capital costs. Therefore, 
even if the technology meets the cost criterion, it appears that the 
Magnus Neuromodulation System with SAINT technology is not eligible for 
new technology add-on payment 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 Magnus Neuromodulation System with SAINT 
technology has any operating costs, and if it meets the cost criterion. 
If the Magnus Neuromodulation System with SAINT technology does have 
operating costs, since it appears to meet the cost criterion, we are 
proposing to approve

[[Page 28341]]

new technology add-on payments for only the operating costs of the 
Magnus Neuromodulation System with SAINT technology for FY 2023, 
subject to the technology receiving FDA marketing authorization for the 
treatment of MDD in adult patients who have failed to receive 
satisfactory improvement from prior antidepressant medication in the 
current episode, by July 1, 2022.
(6) Nelli[supreg] Seizure Monitoring System
    Neuro Event Labs, Inc. submitted an application for new technology 
add-on payments for the Nelli[supreg] Seizure Monitoring System for FY 
2023. Per the applicant, the Nelli[supreg] Seizure Monitoring System is 
software designed to automate the analysis of audio and video data to 
identify seizure events with a positive motor component as an adjunct 
to seizure monitoring in a hospital inpatient or home setting for 
adults and children 6 years of age and older. The applicant stated that 
data is collected while the patient is `observed' using the 
Nelli[supreg] Seizure Monitoring System hardware (Personal Recording 
Unit [PRU]), which temporarily stores and pre-processes raw media data 
to extract only periods likely to contain clinically relevant activity. 
The applicant then stated that data is transmitted via a secure 
internet connection to the Nelli[supreg] Seizure Monitoring System 
software running on a remote server where it is processed using 
analysis algorithms which create and categorize media samples that may 
be indicative of epileptic seizure events. Per the applicant, the 
software provides objective summaries of semiological components of 
identified events (including velocity and acceleration of movements, 
seizure frequency, seizure duration, heart rate, and respiratory rate) 
to enable the detection and classification of epileptic events using 
pretrained artificial intelligence (AI).
    According to the applicant, the Nelli[supreg] Seizure Monitoring 
System received Breakthrough Device designation from FDA on October 9, 
2020 for the automated analysis of audio and video data to identify 
seizure events with a positive motor component in children and adults 
as well as to characterize seizures and peri-ictal events. The 
applicant stated that the Nelli[supreg] Seizure Monitoring System is 
not yet commercially available as it is awaiting 510(k) clearance of 
the device from the FDA for the same indication, which the applicant 
submitted on August 17, 2021.
    According to the applicant, there are currently no ICD-10-PCS 
procedure codes to distinctly identify the Nelli[supreg] Seizure 
Monitoring System. The applicant stated that the inpatient population 
for which the Nelli[supreg] Seizure Monitoring System is indicated 
would undergo standard video EEG monitoring, which is described by the 
ICD-10-PCS code 4A10X4Z (Monitoring of central nervous electrical 
activity, external approach). The applicant has submitted a request to 
the ICD-10 Coordination and Maintenance Committee for approval of a 
unique code for FY 2023 to identify the technology.
    With respect to the cost criterion, the applicant conducted two 
analyses to demonstrate that the Nelli[supreg] Seizure Monitoring 
System meets the cost criterion, one based on 100% of identified 
claims, and second based on 91.1% of identified claims.
    Under the first scenario, which included 100% of claims, the 
applicant searched the FY 2020 MedPAR database for cases representing 
patients who may be eligible for the Nelli[supreg] Seizure Monitoring 
System. The applicant extracted all inpatient claims for which ICD-10-
PCS code 4A10X4Z (Monitoring of central nervous electrical activity, 
external approach) appeared in conjunction with any of the ICD-10-CM 
codes listed in the table below. The applicant stated this approach to 
identifying cases is based on the methodology used in a recent paper, 
which assessed the ability of using code-based queries to identify 
inpatient epilepsy monitoring unit (EMU) admissions from billing 
records in a large academic medical center over a 4-year period, 2016-
2019.\593\
---------------------------------------------------------------------------

    \593\ Kamitaki B.K., Rishty S., Mani R., et al. Using ICD-10 
codes to identify elective epilepsy monitoring unit admissions from 
administrative billing data: A validation study. Epilepsy Behav. 
2020;111:107194.
[GRAPHIC] [TIFF OMITTED] TP10MY22.135


[[Page 28342]]


    After imputing a case count of 11 for those MS-DRGs with fewer than 
11 cases, the applicant identified 9,506 claims mapping to the 
following 11 MS-DRGs, with over 90% of cases mapping to MS-DRGs 100 
(Seizures with MCC) and 101 (Seizures without MCC):
[GRAPHIC] [TIFF OMITTED] TP10MY22.136

    The applicant did not remove charges for prior technology as it 
asserted there is no technology being replaced when the Nelli[supreg] 
Seizure Monitoring System is used in a hospital inpatient setting. The 
applicant then standardized the charges by applying the 3-year 
inflation factor of 1.204686 used in the FY 2022 IPPS/LTCH PPS final 
rule and correction notice to calculate outlier threshold charges (86 
FR 45542). The applicant then added charges for the new technology by 
dividing the cost of the Nelli[supreg] Seizure Monitoring System by the 
national average CCR for ``Other Services,'' which is 0.344 as 
published in the FY 2022 IPPS/LTCH IPPS final rule (86 FR 44966).
    The applicant calculated a case-weighted average standardized 
charge per case of $56,770 and a final inflated average case-weighted 
standardized charge per case of $71,297, both of which exceeded the 
average case-weighted threshold amount of $48,474.
    Under the second scenario, the applicant included only cases 
mapping to MS-DRGs 100 and 101 (seizures with and without MCC, 
respectively) as these two MS-DRGs represented 91.1% of patients 
undergoing video EEG, which the applicant identified using the ICD-10-
PCS code 4A10X4Z (Monitoring of central nervous electrical activity, 
external approach). Per the applicant, 30.2% of the procedures mapped 
to MS-DRG 100 and 60.9% of the procedures mapped to MS-DRG 101. The 
applicant asserted that these patients more likely represent the 
inpatient EMU population for which the Nelli[supreg] Seizure Monitoring 
System would be especially applicable. The applicant identified 6,182 
cases mapping to these 2 MS-DRGs. The applicant then applied the same 
methodology for calculations as in the first analysis. The calculations 
in this sub-analysis resulted in a case-weighted average standardized 
charge per case of $55,524 and a final inflated average case weight 
standardized charge per case of $69,796. Both of these amounts exceed 
the case-weighted threshold amount of $48,404.
    Because the final inflated case-weighted average standardized 
charge per case for each scenario exceeded the average case-weighted 
threshold amount for all scenarios, the applicant asserted that the 
Nelli[supreg] Seizure Monitoring System meets the cost criterion.
    We agree that the Nelli[supreg] Seizure Monitoring System meets the 
cost criterion and therefore are proposing to approve the Nelli[supreg] 
Seizure Monitoring System for new technology add on payments for FY 
2023, subject to the technology receiving FDA marketing authorization 
for the automated analysis of audio and video data to identify seizure 
events with a positive motor component in children and adults by July 
1, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the applicant anticipated the non-capital cost of 
the Nelli[supreg] Seizure Monitoring System to the hospital to be 
$1,000 per patient for the semiological report and seizure detection 
notification produced following patient assessment. 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. The applicant based the cost per case of its technology on 
two pricing models that it currently uses in Europe. The first pricing 
model consists of an approximately $350 per day charge for the 
technology. The applicant stated that this results in a typical cost to 
the hospital of around $1,000 USD (excluding capital costs) for an 
average patient stay of 3-4 days in an EMU. The applicant stated that 
the second pricing model is a single 1000 [euro] per-patient fee for 
measurement of readings and producing the report, regardless of the 
number of days the system is used. Therefore, based on the information 
provided by the applicant, it appears that the average cost per case 
for the use of the Nelli[supreg] Seizure Monitoring System is $1000 
USD. Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65% of the average cost of the technology, or 65% 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 Nelli[supreg] Seizure Monitoring System would 
be $650 for FY 2023 (that is 65% of the average cost of the 
technology).
    We are inviting public comments on whether the Nelli[supreg] 
Seizure Monitoring System meets the cost criterion and our proposal to 
approve new technology add-on payments for the Nelli[supreg] Seizure 
Monitoring System for FY 2023, subject to the technology receiving FDA 
marketing authorization for the automated analysis of audio and video 
data to identify seizure events with a positive motor component in 
children and adults by July 1, 2022.
(7) Phagenyx[supreg] System
    Phagenesis Ltd. submitted an application for new technology-add on 
payments for the Phagenyx[supreg] System for

[[Page 28343]]

FY 2023. The Phagenyx[supreg] System (Phagenyx[supreg]) is a 
neurostimulation device for the treatment of neurogenic dysphagia, 
which is often seen after stroke, traumatic brain injury, or prolonged 
mechanical ventilation. Per the applicant, the system is comprised of a 
sterile single-use per patient catheter (the PNX-1000 catheter), 
introduced nasally and extending as far as the patient's stomach; and 
the (reusable) EPSB3 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 applicant is requesting new technology add-on payments 
for the PNX-1000 catheter only. We note that Phagenesis Ltd. previously 
submitted an application for new technology add-on payments for the 
Phagenyx[supreg] System for FY 2022, as summarized in the FY 2022 IPPS/
LTCH PPS proposed rule (86 FR 25382 through 25384) but the technology 
did not meet the deadline of July 1, 2021, for FDA approval or 
clearance of the technology and, therefore, was not eligible for 
consideration for new technology add-on payments for FY 2022 (86 FR 
45126 through 45127).
    Per the applicant, Phagenyx[supreg] received Breakthrough Device 
designation on December 4, 2019 for use in treating neurogenic 
dysphagia in adult tracheotomized patients weaned from ventilation. The 
Breakthrough Device designation was revised on January 29, 2021 to 
include the treatment of nonprogressive neurogenic dysphagia in adult 
patients, for which the applicant indicated that it anticipates FDA 
will grant a De Novo classification request in the second quarter of 
calendar year 2022.
    The applicant applied for and received a unique ICD-10-PCS 
procedure code to identify cases involving the administration of 
Phagenyx[supreg] effective for FY 2022. Phagenyx[supreg] administration 
can now be identified by the ICD-10-PCS procedure code XWHD7Q7 
(Insertion of neurostimulator lead into mouth and pharynx, via natural 
or artificial opening, new technology group 7), which is unique to 
Phagenyx[supreg] administration.
    With respect to the cost criterion, the applicant provided an 
analysis, as well as an additional subanalysis containing only MS-DRGs 
having at least 1% of the entire sample volume, to demonstrate that the 
technology meets the cost criterion. Under the first analysis, the 
applicant first identified discharges from the 2019 MedPAR final rule 
dataset reporting one of the following ICD-10-CM codes for dysphagia:
[GRAPHIC] [TIFF OMITTED] TP10MY22.137

    The applicant then removed all discharges reporting one of the 
following ICD-10-CM codes for a progressive neurodegenerative disease 
or condition:
[GRAPHIC] [TIFF OMITTED] TP10MY22.138

The applicant included only inpatient fee-for-service discharges (claim 
type ``60'') and excluded Medicare Advantage discharges.
    After imputing a value of 11 cases for any MS-DRG with a discharge 
count under 11, the applicant identified 391,136 cases spanning 722 MS-
DRGs. The applicant explained that it did not remove charges for prior 
technology as Phagenyx[supreg] does not replace any existing therapy 
for treating neurogenic dysphagia. The applicant then standardized the 
charges using the FY 2019 final rule and correction notice impact file 
and excluded any discharges without a standardized charge. The 
applicant applied a 4-year inflation factor of 1.281834 to update the 
charges from FY 2019 to FY 2023, based on the inflation factor used to 
update the outlier threshold in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45542). The applicant then added charges for the new technology 
by dividing the estimated cost of Phagenyx[supreg] by the national 
cost-to-charge ratio for supplies and equipment of .297 from the FY 
2022 IPPS/LTCH PPS final rule (86 FR 44966). The applicant determined a 
final inflated case weighted average standardized charge per case of 
$115,910, which exceeded the case weighted threshold of $68,761. 
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.
    The applicant submitted an additional analysis containing only 
cases mapping to MS-DRGs with at least 1% of the

[[Page 28344]]

entire sample volume. This secondary analysis contained 19 MS-DRGs (vs. 
722 MS-DRGs in the original analysis). Using the same methodology 
above, the applicant determined a final inflated case weighted 
standardized charge per case of $102,682 and a case-weighted threshold 
of $60,674. Because the final inflated case weighted standardized 
charge per case exceeded the case-weighted threshold under this second 
analysis, the applicant maintained that the technology meets the cost 
criterion.
    We agree with the applicant that Phagenyx[supreg] meets the cost 
criterion and are therefore proposing to approve Phagenyx[supreg] for 
new technology add-on payments for FY 2023, subject to the technology 
receiving FDA marketing authorization for the indication corresponding 
to the Breakthrough Device designation by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of Phagenyx[supreg] is $5,000 per 
catheter, which is the subject of this application. 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% of the average cost of the technology, or 
65% 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 Phagenyx[supreg] would be $3,250 for FY 
2023 (that is, 65% of the average cost of the technology).
    We are inviting public comments on whether Phagenyx[supreg] meets 
the cost criterion and our proposal to approve new technology add-on 
payments for Phagenyx[supreg] for FY 2023 for the indication 
corresponding to the updated Breakthrough Device designation, subject 
to Phagenyx[supreg] receiving FDA marketing authorization for that 
indication by July 1, 2022.
(8) Precision TAVITM Coronary Obstruction Module
    DASI Simulations submitted an application for new technology add-on 
payments for the Precision Transcatheter Aortic Valve Implantation 
(TAVI)\TM\ Coronary Obstruction Module for FY 2023. According to the 
applicant, the Precision TAVI Coronary Obstruction Module, which would 
be an added feature of the Precision TAVI Software System, is intended 
to provide intelligent decision support powered by artificial 
intelligence (AI) and machine learning to help physicians accurately 
predict potential coronary artery obstructions in transcatheter aortic 
valve replacement (TAVR) procedures. The applicant stated that the 
technology may assist physicians in the evaluation of patients with 
severe aortic stenosis when considering surgical replacement as opposed 
to trans-catheter replacement procedures, as well as other 
interventional or protection measures, when used with the Precision 
TAVI\TM\ Software System.
    The applicant stated that the Precision TAVI\TM\ Coronary 
Obstruction Module has not yet received FDA Breakthrough Device 
designation, but that it expects to receive Breakthrough Device 
designation for the following indication: Precision TAVITM 
Coronary Obstruction Module utilizes an additional proprietary software 
to analyze the results of the simulation module and output coronary 
obstruction risk biomarkers corresponding to each implantation 
simulation scenario. For scenarios involving TAVR in a failed surgical 
valve or a failed transcatheter valve, the computational test will also 
include use of anatomic characteristics before and after simulated 
bioprosthetic or native aortic scallop intentional laceration to 
prevent iatrogenic coronary artery obstruction (BASILICA) procedure. 
The applicant indicated that it anticipates receiving 510(k) clearance 
for the Precision TAVITM Coronary Obstruction Module from 
FDA by July 1, 2022 for the same indication. According to the 
applicant, the device will be available on the market immediately after 
receiving FDA clearance. We note that the proposed indication as stated 
in the application does not describe a disease or population to be 
treated and we therefore question whether this information is the 
expected indication or some other description of the technology.
    According to the applicant, there are currently no ICD-10-PCS codes 
that uniquely identify the Precision TAVI\TM\ Coronary Obstruction 
Module. The applicant submitted a request to the ICD-10 Coordination 
and Maintenance Committee for approval of a unique code for FY 2023 to 
identify the Precision TAVITM Coronary Obstruction Module.
    With regard to the cost criterion, the applicant provided the 
following analysis. To identify potential cases where the Precision 
TAVI\TM\ Coronary Obstruction Module could be utilized, the applicant 
searched the FY 2019 MedPAR Limited Data Set for cases reporting either 
of the two ICD-10-PCS procedure codes to describe TAVR procedures, 
02RF38Z (Replacement of aortic valve with zooplastic tissue, 
percutaneous approach) and 02RF38H (Replacement of aortic valve with 
zooplastic tissue, transapical, percutaneous approach), consistent with 
the indication for which the applicant anticipates receiving 
Breakthrough Device designation.
    The applicant identified 40,407 total claims across 60 MS-DRGs. The 
applicant stated that it did not remove charges associated with 
Medical/Surgical Supplies and Devices (revenue centers 027x and 0624) 
because the use of the Precision TAVI\TM\ Coronary Obstruction Module 
is additive, and does not replace other supplies or devices utilized in 
the TAVR procedures analyzed. The applicant then standardized the 
charges and applied the 3-year inflation factor of 1.204686 used to 
update the outlier threshold in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45542) to update the charges from FY 2019 to FY 2022. The 
applicant then added charges for the new technology. The applicant 
multiplied the cost of the technology by the national cost-to-charge 
ratio for radiology from the FY2022 IPPS/LTCH PPS final rule (0.136) 
(86 FR 44966) to calculate estimated average hospital charges 
associated with the device.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $240,685 and an average case-weighted 
threshold of $181,410. 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 have the following concern regarding the applicant's analysis. 
We note that the applicant used the ICD-10-PCS codes for TAVR to 
identify cases where the Precision TAVI\TM\ Coronary Obstruction Module 
may be used. However, according to the applicant, the software can 
identify cases where TAVR should not be performed. We question whether 
these potentially lower cost cases are reflected in the applicant's 
cost analysis, as a TAVR procedure code would not be on the claim.
    Subject to the applicant adequately addressing this concern, we 
would agree that the technology meets the cost criterion and propose to 
approve the Precision TAVITM Coronary Obstruction Module for 
new technology add-on payments for FY 2023, subject to the technology 
receiving Breakthrough Device designation and FDA marketing 
authorization for the same indication by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
this

[[Page 28345]]

proposed rule, the cost of Precision TAVITM Coronary 
Obstruction Module is $1,995 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% of the average cost of the technology, or 65% 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 Precision TAVITM Coronary Obstruction 
Module would be $1,296.75 for FY 2023 (that is, 65% of the average cost 
of the technology). We are inviting public comments on whether the 
Precision TAVI\TM\ Coronary Obstruction Module meets the cost criterion 
and our proposal to approve new technology add-on payments for the 
Precision TAVI\TM\ Coronary Obstruction Module for FY 2022 subject to 
the technology receiving Breakthrough Device designation and FDA 
marketing authorization by July 1, 2022 for the same indication as 
described previously.
(9) ThoraflexTM Hybrid Device
    Terumo Aortic submitted an application for new technology-add on 
payments for the ThoraflexTM Hybrid Device 
(ThoraflexTM) for FY 2023. 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. We 
note that Terumo Aortic previously submitted an application for new 
technology add-on payments for the ThoraflexTM Hybrid Device 
for FY 2022, as summarized in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25390) which was withdrawn prior to the issuance of the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45127).
    According to the applicant, the ThoraflexTM Hybrid 
Device received Breakthrough Device designation on March 20, 2020 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 premarket approval of the device for the same 
indication. According to the applicant, the ICD-10 Coordination and 
Maintenance Committee approved the following ICD-10-PCS codes to 
specifically describe the use of the ThoraflexTM Hybrid 
Device, effective October 1, 2021: X2RX0N7 (Replacement of thoracic 
aorta arch with branched synthetic substitute with intraluminal device, 
new technology group 7) and X2VW0N7 (Restriction of thoracic descending 
aorta with branched synthetic substitute with intraluminal device, new 
technology group 7).
    With respect to the cost criterion, the applicant conducted two 
analyses based on 100% of identified claims and 74% 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 following ICD-10-PCS codes for 
thoracic aortic replacement procedures: 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).
    For the analysis using 100% 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% of charges associated with medical/
surgical supplies and devices (revenue centers 027x and 0624). The 
applicant then standardized the charges and applied the 3-year outlier 
inflation factor of 1.204686 used to update the outlier threshold in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45542) to update the 
charges from FY 2019 to FY 2022. The applicant then added charges for 
the new technology. The applicant multiplied the cost of the technology 
by the national cost-to-charge ratio for implantable devices from the 
FY 2022 IPPS/LTCH PPS final rule (0.293) to calculate estimated average 
hospital charges associated with the device. Under this analysis, based 
on 100% of identified claims, the applicant calculated a final inflated 
case-weighted average standardized charge per case of $420,924 and an 
average case-weighted threshold of $230,659.
    Under the analysis based on 74% of cases, the applicant used the 
same methodology, which identified 3,980 cases across MS-DRGs 219 and 
220. The applicant determined the average case-weighted threshold of 
$211,423 and a final inflated average standardized charge per case of 
$373,273. 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 2023, 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, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the cost of ThoraflexTM Hybrid Device is 
$35,000 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% of the average cost of the technology, or 65% 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 ThoraflexTM Hybrid Device would be 
$22,750 per patient for FY 2023 (that is, 65% of the average cost of 
the technology).
    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 2023, subject to 
ThoraflexTM Hybrid Device receiving FDA marketing 
authorization by July 1, 2022 for the open surgical repair or 
replacement of damaged or diseased

[[Page 28346]]

vessels of the aortic arch and descending aorta, with or without 
involvement of the ascending aorta, in cases of aneurysm and/or 
dissection.
(10) TOPS\TM\ System
    Premia Spine, Inc., submitted an application for new technology 
add-on payments for the TOPS\TM\ System for FY 2023. According to the 
applicant, the TOPS\TM\ System is a motion preserving device comprised 
of a titanium construct with an interlocking polycarbonate urethane 
articulating core that is inserted into the lumbar vertebral joint and 
anchored using pedicle screws after posterior spinal decompression 
surgery. The applicant stated that the TOPS\TM\ System replaces 
anatomical structures, such as the lamina and the facet joints, which 
are removed during spinal decompression treatment to alleviate pain. 
Per the applicant, unlike spinal fusion, the TOPSTM System 
preserves normal biomechanical motion while providing spinal 
stabilization after decompression.
    According to the applicant, the TOPS\TM\ System received 
Breakthrough Device designation from FDA on October 26, 2020, for 
patients between 35 and 80 years of age suffering from neurogenic 
claudication resulting from degenerative spondylolisthesis up to Grade 
I with moderate to severe lumbar spinal stenosis and either the 
thickening of the ligamentum flavum or scaring facet joint capsule at 
one level from L2 to L5. The applicant indicated that it expects to 
receive FDA premarket approval of the TOPS\TM\ System by Q2, 2022 for 
the same indication.
    According to the applicant, ICD-10-PCS procedure code 0SH00DZ 
(Insertion of facet replacement spinal stabilization device into lumbar 
vertebral joint, open approach) may be used to identify the TOPS\TM\ 
System, but the code does not uniquely identify the technology. The 
applicant submitted a request to the ICD-10 Coordination & Maintenance 
Committee for a new ICD-10-PCS code to uniquely identify the TOPS\TM\ 
System.
    With respect to the cost criterion, the applicant provided the 
following cost analysis. To identify cases representing patients who 
may be eligible for the TOPS\TM\ System, the applicant searched the FY 
2019 MedPAR dataset for cases reporting a combination of ICD-10-PCS 
procedure code 0SH00DZ (Insertion of facet replacement spinal 
stabilization device into lumbar vertebral joint, open approach) with a 
relevant diagnosis code. The applicant identified the following MS-DRG 
for the TOPS\TM\ System: 518 (Back and Neck Procedures except Spinal 
Fusion with MCC or Disc Device or Neurostimulator).
    The applicant identified 2,614 cases mapping to MS-DRG 518. The 
applicant then removed charges for prior technology. The applicant 
stated that in analyzing the MedPAR data, 100% of charges associated 
with Medical/Surgical Supplies and Devices (revenue centers 027x and 
0624) were removed. The applicant explained that use of the TOPS\TM\ 
System will replace a portion of devices included in these claims but 
will not replace all devices, nor any medical supplies required to 
perform the procedure. The applicant noted that an estimate of the 
percentage of total charges for devices that would be replaced could 
not be determined and therefore, to be as conservative as possible, the 
analysis removed 100% of these charges. The applicant then standardized 
the charges and applied the three-year inflation factor of 20.4% used 
to update the outlier threshold in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45542), to update the charges from FY 2019 to FY 2022. The 
applicant then added charges for the new technology by dividing the 
per-patient anticipated hospital cost of the TOPS\TM\ System by the 
national average cost-to-charge ratio for implantable devices (0.239) 
from the FY 2022 IPPS/LTCH PPS final rule. The applicant calculated a 
final inflated case-weighted average standardized charge per case of 
$152,935 and an average case-weighted threshold of $109,174. 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 TOPS\TM\ System meets the cost 
criterion and therefore are proposing to approve the TOPS\TM\ System 
for new technology add-on payments for FY 2023, subject to the 
technology receiving FDA marketing authorization for the indication 
corresponding to the Breakthrough Device designation by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the per-patient anticipated hospital cost of the 
TOPS\TM\ 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% of the average cost of the technology, or 65% 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 TOPS System would be $9,750 for FY 2023 (that 
is, 65% of the average cost of the technology).
    We are inviting public comments on whether the TOPS\TM\ System 
meets the cost criterion and our proposal to approve new technology 
add-on payments for the TOPS\TM\ System for FY 2023, subject to the 
technology receiving FDA marketing authorization for the indication 
corresponding to the Breakthrough Device designation by July 1, 2022.
(11) VITARIA[supreg] System
    LivaNova, PLC submitted an application for new technology add-on 
payments for the VITARIA[supreg] System for FY 2023. According to the 
applicant, the VITARIA[supreg] System is an active implantable 
neuromodulation system that uses vagus nerve stimulation to deliver 
autonomic regulation therapy. The applicant reported the 
VITARIA[supreg] System includes a pulse generator and an electrical 
lead, which are implanted under the skin, without requiring a vascular 
procedure. Per the applicant the electrical lead attaches the pulse 
generator to the 10th cranial nerve (vagus nerve). The applicant stated 
that after implantation is completed, a hand-held wand positioned on 
the skin over the implanted pulse generator and a computer tablet are 
used together externally to adjust the intensity of the electrical 
impulses delivered from the pulse generator through the electrical lead 
to stimulate the vagus nerve. Per the applicant, the VITARIA[supreg] 
System is intended for use in patients with moderate to severe heart 
failure (New York Heart Association classification of Class II or Class 
III) and left ventricular dysfunction (ejection fraction (EF) of 35% or 
less) who remain symptomatic despite receiving medical treatment in 
line with current treatment guidelines.
    According to the applicant, the VITARIA[supreg] System received 
designation under the EAP (and is therefore considered part of the 
Breakthrough Devices Program by FDA \594\) on October 24, 2016, for 
patients who have moderate to severe heart failure (NYHA Class II/III), 
with left ventricular dysfunction (EF of 40% or less), who remain 
symptomatic despite stable, optimal heart failure drug therapy and are 
not candidates for cardiac resynchronization therapy (CRT). Per the 
applicant, FDA approved an amendment to its investigational device 
exemption (IDE) trial on November 16,

[[Page 28347]]

2018, to include CRT or CRT-D recipients who have been receiving 
cardiac resynchronization therapy (CRT) according to guideline directed 
medical therapy (GDMT) and meet all of the other indications for use. 
According to the applicant, FDA premarket approval of the 
VITARIA[supreg] System is expected by June 30, 2022 for the proposed 
indication for the symptomatic improvement of heart failure patients 
who have reduced left ventricular ejection fraction and chronic heart 
failure despite guideline-directed medical treatment. We note that, as 
previously stated, under the eligibility criteria for approval under 
the alternative pathway for certain transformative devices, only the 
use of the technology for the indication that corresponds to the 
technology's Breakthrough Device designation would be eligible for the 
new technology add-on payment for FY 2023. The applicant stated that 
the indication for which they are seeking the new technology add-on 
payment is for patients who have moderate to severe heart failure (NYHA 
Class II/III), with left ventricular dysfunction, who remain 
symptomatic despite stable, optimal heart failure drug therapy and are 
not candidates for cardiac resynchronization therapy (CRT).
---------------------------------------------------------------------------

    \594\ https://www.fda.gov/medical-devices/how-study-and-market-your-device/breakthrough-devices-program.
---------------------------------------------------------------------------

    Per the applicant, ICD-10-PCS procedure codes that can currently be 
used to identify procedures involving the use of the VITARIA[supreg] 
System are not unique to the VITARIA[supreg] System and may also be 
used for other cranial nerve stimulators: 00HE0MZ (Insertion of 
neurostimulator lead into cranial nerve, open approach) and 0JH60BZ 
(Insertion of single array stimulator generator into chest subcutaneous 
tissue and fascia, open approach). The applicant submitted a request to 
the ICD-10 Coordination and Maintenance Committee for approval of a 
code for FY 2023 to uniquely identify procedures involving the use of 
the VITARIA[supreg] System. Additionally, the applicant submitted a FY 
2023 MS-DRG reclassification request, as discussed further in section 
II.D.3.b. of the preamble of this proposed rule.
    The applicant also stated that the ICD-10-CM diagnosis codes in the 
following table identify the EAP designation.
[GRAPHIC] [TIFF OMITTED] TP10MY22.139

    We note that the ICD-10-CM diagnosis codes listed by the applicant 
include those for diastolic heart failure, which is not part of the 
indication for which the applicant stated the device had received EAP 
designation. As such, we would appreciate additional information 
regarding the rationale for inclusion of codes I50.30 through I50.33. 
In addition, we believe that the following additional 13 ICD-10 CM 
diagnosis codes could also be used to identify the EAP designation for 
which the applicant is seeking the new technology add-on payment:

[[Page 28348]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.140

    We invite public comment regarding the extent to which this is the 
most appropriate list of ICD-10 CM diagnosis codes and is reflective of 
the indication for which the applicant is seeking the new technology 
add-on payment.
    With respect to the cost criterion, the applicant provided the 
following cost analysis. To identify potential cases where the 
VITARIA[supreg] System could be utilized, the applicant searched the FY 
2019 MedPAR dataset for claims reporting the aforementioned ICD-10-PCS 
codes (00HE0MZ and 0JH60BZ). Using the FY 2022 MS-DRG Grouper (Version 
39.0), the applicant identified three MS-DRGs to which the preceding 
ICD-10-PCS codes mapped and limited discharges to these MS-DRGs: 252 
(Other Vascular Procedures with MCC, 253 (Other Vascular Procedures 
with CC, and 254 (Other Vascular Procedures without CC/MCC).
    The applicant identified 66,438 cases mapping to the three MS-DRGs. 
The applicant then removed charges for medical/surgical supplies and 
devices at revenue centers 027x and 0624, since the applicant expects 
the VITARIA[supreg] System to replace all of the current device charges 
included in the claims. The applicant then standardized the charges and 
applied the three-year inflation factor of 20.4% used to update the 
outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45538), to update the charges from FY 2019 to FY 2022. The applicant 
did not add charges for the new technology because the applicant has 
not yet determined the average sales price for the device. According to 
the applicant, no other charges related to the new technology were 
included in the cost calculations, as the applicant assumes no other 
charges are required to implant the VITARIA[supreg] System. Under the 
analysis, the applicant calculated a final inflated case-weighted 
average standardized charge per case of $97,567 and an average case-
weighted threshold of $93,472. 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.
    With regard to the cost criterion for the VITARIA[supreg] System, 
we note that the applicant identified MS-DRGs which may represent a 
population broader than those cases which are eligible for treatment by 
the VITARIA[supreg] System, and we question whether this cost analysis 
is sufficiently representative of cases which would be eligible for 
treatment with the technology.
    Subject to the applicant adequately addressing this concern, we 
would agree with the applicant that the VITARIA[supreg] System meets 
the cost criterion and therefore are proposing to approve the 
VITARIA[supreg] System for new technology add-on payments for FY 2023, 
subject to the technology receiving FDA marketing authorization by July 
1, 2022 for patients who have moderate to severe heart failure (NYHA 
Class II/III), with left ventricular dysfunction (EF<=40%), who remain 
symptomatic despite stable, optimal heart failure drug therapy and are 
not candidates for cardiac resynchronization therapy (CRT).
    Per the applicant, the anticipated cost for the VITARIA[supreg] 
System will be available once the device receives FDA approval. While 
the applicant has not stated which components of the system would 
comprise the cost, the applicant has stated that the system is used in 
conjunction with a computer tablet and hand-held wand that are used 
together externally, which appear to be capital expenses. We note that 
as discussed in prior rulemaking (86 FR 45134) and 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. Because the applicant has not provided 
an estimate for the cost of the VITARIA[supreg] System 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 
VITARIA[supreg] System 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% of the average cost of the technology, or 65% of the 
costs in excess of the MS-DRG payment for the case.
    We are inviting public comments on whether the VITARIA[supreg] 
System meets the cost criterion and our proposal to approve new 
technology add-on payments for the VITARIA[supreg] System for FY 2023, 
subject to the technology receiving FDA marketing authorization by July 
1, 2022 for patients who have moderate to severe heart failure (NYHA 
Class II/III), with left ventricular dysfunction (EF<=40%), who remain 
symptomatic despite stable, optimal heart failure drug therapy and are 
not

[[Page 28349]]

candidates for cardiac resynchronization therapy (CRT).
(12) ViviStim[supreg] Paired VNS System
    MicroTransponder, Inc. submitted an application for new technology 
add-on payments for the ViviStim[supreg] Paired VNS System for FY 2023. 
According to the applicant, the ViviStim[supreg] Paired VNS System is a 
paired vagus nerve stimulation therapy intended to stimulate the vagus 
nerve during rehabilitation therapy to reduce upper extremity motor 
deficits and improve motor function in chronic ischemic stroke patients 
with moderate to severe arm impairment. The applicant stated that the 
Vivistim[supreg] Paired VNS System is comprised of an Implantable Pulse 
Generator (IPG), an implantable stimulation Lead, and an external 
paired stimulation controller which is composed of the external 
Wireless Transmitter (WT) and the external Stroke Application and 
Programming Software (SAPS). According to the applicant, the external 
paired stimulation controller (SAPS and WT) enables the implanted 
components (the IPG and Lead) to stimulate the vagus nerve during 
rehabilitation. The applicant stated that patients undergo 25-30 hours 
of in-clinic rehabilitation over 6 weeks, where the ViviStim[supreg] 
Paired VNS System is actively paired with rehabilitation by a 
therapist. The applicant further stated that following this in-clinic 
rehabilitation period, when directed by a physician and with 
appropriate programming to the IPG, the patient can initiate at-home 
use by swiping a magnet over the IPG implant site which activates the 
IPG to deliver stimulation while rehabilitation movements are 
performed.
    The applicant stated that the ViviStim[supreg] Paired VNS System 
was designated as a Breakthrough Device on February 10, 2021 for use in 
stimulating the vagus nerve during rehabilitation therapy in order to 
reduce upper extremity motor deficits and improve motor function in 
chronic ischemic stroke patients with moderate to severe arm 
impairment. According to the applicant, the ViviStim[supreg] Paired VNS 
System received FDA premarket approval on August 27, 2021 as a Class 
III implantable device for the same indication. The applicant stated 
that the technology is not yet commercially available due to 
manufacturing delays.
    According to the applicant, there are no unique ICD-10-PCS 
procedure codes to report the implantation of the device. The applicant 
noted that together the following two ICD-10-PCS codes describe the 
insertion of the ViviStim[supreg] Paired VNS System: 0JH60BZ (Insertion 
of single array stimulator generator into chest subcutaneous tissue and 
fascia, open approach) and 00HE0MZ (Insertion of neurostimulator lead 
into cranial nerve, open approach). The applicant noted that these 
codes may be used for any cranial nerve stimulator insertion procedure, 
including VNS therapy for treatment resistant depression, VNS therapy 
for refractory epilepsy, and upper airway stimulation to treat 
obstructive sleep apnea. 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 insertion of the ViviStim[supreg] Paired 
VNS System.
    The applicant also provided the ICD-10-CM diagnosis codes in the 
table below. The applicant stated that moderate to severe upper limb 
impairment is described in the ICD-10-CM as monoplegia (single limb) or 
hemiplegia (single laterality, including upper limb). The applicant 
stated that the FY 2021 ICD-10-CM code set \595\ includes monoplegia 
and hemiplegia as a sequela of infarction (stroke), and delineates 
codes based upon stroke type (hemorrhagic versus ischemic). Therefore, 
the applicant states that the ICD-10-CM diagnosis codes in the table 
below describe chronic moderate to severe upper arm impairment as a 
sequela of ischemic stroke, and are related to the use of the 
ViviStim[supreg] Paired VNS System.
---------------------------------------------------------------------------

    \595\ https://www.cms.gov/medicare/icd-10/2021-icd-10-cm, 
effective October 1, 2020 through September 30, 2021.
[GRAPHIC] [TIFF OMITTED] TP10MY22.141

    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR claims 
data set released with the FY 2022 IPPS/LTCH PPS final rule for cases 
representing patients who may be eligible for the ViviStim[supreg] 
Paired VNS System. The applicant identified cases reporting the ICD-10-
PCS codes 0JH60BZ and 00HE0MZ in combination with one of the ICD-10-CM 
diagnosis codes above describing moderate to severe upper limb 
impairment. The applicant then mapped the cases to the appropriate MS-
DRGs using MS-DRG Grouper Version 39.0. After imputing a case count of 
11 for those MS-DRGs with fewer than 11 cases, the applicant identified 
285 claims mapping to 12 MS-DRGs, with 65% of cases mapping to MS-DRGs 
024 (Craniotomy with Major Device Implant or Acute Complex CNS 
Principal Diagnosis without MCC), 041 (Peripheral Cranial Nerve and 
Other Nervous System Procedures with CC or Peripheral Neurostimulator) 
and 042 (Peripheral Cranial Nerve and Other Nervous System Procedures 
without CC/MCC).
    The applicant then removed 100% of charges associated with Medical/
Surgical Supplies and Devices (prior technology, revenue centers 027X, 
and

[[Page 28350]]

0624). The applicant asserted that the use of the Vivistim[supreg] 
Paired VNS System is expected to replace the majority of existing 
technologies, although some devices will still be required to perform 
the procedure. The applicant stated that because it could not determine 
the estimated percentage of the total charges that would be replaced, 
it removed 100% of these total charges to be as conservative as 
possible. The applicant did not remove charges related to the 
technology being replaced, stating that the financial impact of 
utilizing the Vivistim[supreg] Paired VNS System on hospital resources 
compared to prior technologies other than on Medical Supplies is 
minimal, and that 100% of charges for Medical/Surgical Supplies had 
been removed in the previous step.
    The applicant standardized the charges by applying the three-year 
inflation factor of 1.20469 used in the FY 2022 IPPS/LTCH PPS final 
rule and correction notice to calculate outlier threshold charges (86 
FR 45542). The applicant then added charges for the new technology by 
dividing the cost of the ViviStim[supreg] Paired VNS System by the 
national average CCR for implantable devices which is 0.293 as 
published in the FY 2022 IPPS/LTCH IPPS final rule (86 FR 44966). The 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $200,398 which exceeded the average 
case-weighted threshold amount of $107,963. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that the 
ViviStim[supreg] Paired VNS System meets the cost criterion.
    We agree with the applicant that the ViviStim[supreg] Paired VNS 
System meets the cost criterion and are therefore proposing to approve 
the ViviStim[supreg] Paired VNS System for new technology add-on 
payments for FY 2023.
    Based on preliminary information from the applicant at the time of 
this proposed rule, the applicant anticipated the total cost of the 
ViviStim[supreg] Paired VNS System to the hospital to be $36,000 per 
patient. According to the applicant, this cost represents the entire 
per-patient cost of the system to hospital providers--specifically for 
the cost of the Implantable Pulse Generator and stimulation lead. Per 
the applicant, there is no charge associated with the external paired 
stimulation controller and the magnet/take-home patient programmer. The 
applicant stated that the external paired stimulation controller may be 
used on multiple patients and that it retains a service agreement with 
each provider to own, maintain, and update the hardware and software 
that resides on that device component. The applicant has also stated 
that they have this service agreement with providers for the magnet/
take-home patient programmer. Therefore, as the applicant has stated 
they retain and maintain the reusable hardware components at no charge 
to the providers, it appears that capital components are not included 
in the cost of the technology. We welcome public comment on the cost 
information provided by the applicant for the purpose of calculating 
the new technology add-on payment amount.
    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% of the 
average cost of the technology, or 65% 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 ViviStim[supreg] Paired VNS System would be $23,400 for FY 2023 
(that is, 65% of the average cost of the technology).
    We invite public comments on whether the ViviStim[supreg] Paired 
VNS System meets the cost criterion and our proposal to approve new 
technology add-on payments for the ViviStim[supreg] Paired VNS System 
for FY 2023 for use in stimulating the vagus nerve during 
rehabilitation therapy in order to reduce upper extremity motor 
deficits and improve motor function in chronic ischemic stroke patients 
with moderate to severe arm impairment.
b. Alternative Pathways for Qualified Infectious Disease Products 
(QIDPs)
(1) DefenCathTM (Solution of Taurolidine (13.5 mg/mL) and 
Heparin (1000 USP Units/mL))
    CorMedix Inc. submitted an application for new technology add-on 
payments for DefenCathTM (solution of taurolidine (13.5 mg/
mL) and heparin (1000 USP Units/mL)) for FY 2023. The applicant stated 
that DefenCathTM is a proprietary formulation of 
taurolidine, a thiadiazinane antimicrobial, and heparin, an anti-
coagulant, that is under development for use as catheter lock solution, 
with the aim of reducing the risk of catheter-related bloodstream 
infections (CRBI) from in-dwelling catheters in patients undergoing 
hemodialysis (HD) through a central venous catheter (CVC). According to 
the applicant, in vitro studies of DefenCathTM indicate 
broad antimicrobial activity against gram-positive and gram-negative 
bacteria, including antibiotic resistant strains as well as 
mycobacteria and clinically relevant fungi. The applicant stated that 
DefenCathTM is available in a single-dose vial, which is 
sufficient to fill both lumens of the HD catheter, and is instilled 
into the catheter lumen as a lock solution at the conclusion of each 
dialysis session and aspirated at the beginning of the next dialysis 
session. The applicant noted that DefenCathTM cannot be 
flushed or injected into the patient and that dosing is calibrated to 
the volume of the catheter lumens.
    Per the applicant, DefenCathTM was designated by FDA as 
a Qualified Infectious Disease Product (QIDP) in 2015 for the 
prevention of CRBSI in patients with end-stage renal disease (ESRD) 
receiving HD through a central venous catheter, and has been granted 
FDA Fast Track status. The applicant indicated that it is pursuing an 
NDA under FDA's LPAD for the same indication, which the applicant also 
stated received Priority Review. The applicant noted that FDA issued a 
Complete Response Letter in 2021 denying the NDA due to concerns with 
the third-party manufacturing facility. The applicant stated that the 
NDA has been resubmitted and anticipates approval before July 1, 2022. 
We note that, as an application submitted under the alternative pathway 
for certain antimicrobial products at Sec.  412.87(d), 
DefenCathTM is eligible for conditional approval for new 
technology add-on payments if it 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 (that is, July 1, 2023).
    According to the applicant, there are no ICD-10-PCS codes that 
specifically identify catheter lock solutions. The applicant submitted 
a request for approval of a unique ICD-10-PCS procedure code to 
identify use of DefencathTM beginning FY 2023.
    With regard to the cost criterion, the applicant provided two 
analyses to demonstrate that DefenCathTM meets the cost 
criterion. The applicant first searched the FY 2019 MedPAR file 
released with the FY 2022 IPPS final rule for claims based on the 
presence of one of the following ICD-10-CM diagnosis codes used to 
identify ESRD, chronic kidney disease (CKD), acute kidney injury (AKI) 
or acute tubular necrosis (ATN).

[[Page 28351]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.142

    Per the applicant, DefenCathTM will be used for patients 
receiving HD through a CVC. The applicant stated that coding to 
identify this population is difficult because the available CVC codes 
only describe the insertion of a CVC. The applicant asserted that it is 
not possible to identify in the MedPAR file those patients who had 
previously received a CVC and are now hospitalized and receiving HD. 
Therefore, the applicant developed two sets of selection criteria: 
Claims with codes for HD (Analysis A) and claims with codes for both HD 
and CVC (Analysis B). The applicant asserted that Analysis A overstates 
the population of patients eligible for DefenCathTM because 
it includes any patient receiving HD, regardless of whether a central 
venous catheter is used. The applicant also asserted that Analysis B 
undercounts the potential cases because CVC codes are not always 
available on inpatient claims.
    In the first analysis (Analysis A), which included only claims with 
codes for chronic HD, the applicant searched for claims based on the 
presence of one of the ICD-10-CM diagnosis codes listed above and then 
limited the selection criteria to claims including ICD-10-CM diagnosis 
code Z49.31 (encounter for adequacy testing for HD) or one of the 
following ICD-10-PCS procedure codes for HD:
[GRAPHIC] [TIFF OMITTED] TP10MY22.143

    After imputing a case count of 11 to any MS-DRG with fewer than 11 
cases in the FY 2019 MedPAR file released with the FY 2022 IPPS final 
rule, the applicant identified a total of 490,790 cases mapping to 512 
MS-DRGs. The table below shows the top 20 MS-DRGs, which account for 
57% of all cases included in Analysis A.

[[Page 28352]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.144

    For Analysis B, the applicant used the same case selection criteria 
as Analysis A (the presence of an ICD-10- procedure or diagnosis code 
for HD only) but further limited cases to those that include one of the 
following ICD-10 procedure codes for the insertion of a CVC.
[GRAPHIC] [TIFF OMITTED] TP10MY22.145

    The applicant asserted that the patient population in Analysis B 
(HD and central venous catheter) is more likely to receive 
DefenCathTM during an inpatient stay. After imputing a case 
count of 11 to any MS-DRG with fewer than 11 cases, the applicant 
identified a total of 60,679 cases mapping to 408 MS-DRGs. The table 
below shows the top 20 MS-DRGs by case count, which account for 72% of 
all cases included in Analysis B.

[[Page 28353]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.146

    In both analyses, the applicant did not remove charges for prior 
technology because DefenCathTM would not replace other 
therapies a patient may receive during an inpatient stay. The applicant 
standardized the charges using the FY 2022 IPPS final rule impact file 
and applied a 4-year inflation factor of 1.281834 to update the charges 
from FY 2019 to FY 2023 based on the inflation factor used to update 
the outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542). The applicant did not add charges for new technology as the 
cost of DefenCathTM has not yet been determined but believes 
that the technology meets the cost criterion without the additional 
charges.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $116,221 for Analysis A and a final 
inflated case-weighted average standardized charge per case of $203,746 
for Analysis B. The applicant also determined an average case weighted 
threshold amount of $77,290 in Scenario A and $96,645 in Scenario B. 
Because the final inflated case-weighted average standardized charge 
per case for each scenario exceeded the average case-weighted threshold 
amount for both scenarios, the applicant asserted that 
DefenCathTM meets the cost criterion.
    We agree that the technology meets the cost criterion and are 
therefore proposing to approve DefenCathTM for new 
technology add on payments for FY 2023, subject to the technology 
receiving FDA approval for the prevention of CRBSI in patients with 
ESRD receiving HD through a central venous catheter by July 1, 2022.
    The applicant has not provided an estimate for the cost of 
DefenCathTM 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 DefenCathTM would be subject 
to our policy under Sec.  412.88(a)(2) where we limit new technology 
add-on payments for QIDPs to the lesser of 75% of the average cost of 
the technology, or 75% of the costs in excess of the MS-DRG payment for 
the case.
    We are inviting comments on whether DefenCathTM meets 
the cost criterion and our proposal to approve DefenCathTM 
for new technology add-on payments for FY 2023, subject to the 
technology receiving marketing authorization consistent with its QIDP 
designation by July 1, 2022.
8. Proposed Use of National Drug Codes (NDCs) To Identify Cases 
Involving Use of Therapeutic Agents Approved for New Technology Add-On 
Payment
    As discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49434 
through 49435), as a part of the transition to the ICD-10-CM diagnosis 
and ICD-10-PCS procedure coding system from the ICD-9-CM coding system, 
CMS established the use of Section ``X'' New Technology codes within 
the ICD-10-PCS classification to more specifically identify new 
technologies or procedures that have historically not been captured 
through ICD-9-CM codes, or to more precisely describe information on a 
specific procedure or technology than is found with the other sections 
of ICD-10-PCS. However, CMS has continued to receive comments from 
stakeholders, including representatives from hospital associations, 
software vendors, professional societies, and coding professionals, 
opposing the continued creation of new ICD-10-PCS (for example, Section 
X) procedure codes for the purpose of administering the new technology 
add-on payment for drugs and biologics. Specifically, public comments 
from the ICD-10 Coordination and Maintenance Committee Meetings have 
stated that the ICD-10-PCS classification system was not intended to 
represent unique drugs/therapeutic agents and is not an appropriate 
code set for this purpose. Commenters explained that, since the 
implementation of ICD-10, Section X codes have been established for 
procedures describing the administration of a drug/therapeutic agent, 
which historically were not typically coded in the inpatient hospital 
setting. Commenters stated their belief

[[Page 28354]]

that it was not logical nor should it be expected for hospital coding 
professionals to seek codes for the administration of drugs within the 
ICD-10-PCS classification system. In addition, we note that over the 
past three years, the number of applications for new technology add-on 
payments has continued to increase, which has subsequently resulted in 
an increasing number of requests for unique ICD-10-PCS (for example, 
Section X) procedure codes specifically for the purposes of 
administering the new technology add-on payments.
    The current process of requesting, proposing, finalizing and 
assigning new ICD-10-PCS procedure codes to identify and describe the 
administration of drugs involves several steps, as described further in 
this section, and frequently results in a number of procedure codes 
that are created unnecessarily when the drug/therapeutic agents do not 
receive approval for the new technology add-on payments, as the 
administration of drugs/therapeutic agents is not typically coded in 
the inpatient hospital setting. Applicants seeking a unique ICD-10-PCS 
(for example, Section X) procedure code to identify the use of their 
technology for purposes of new technology add-on payments must complete 
the code request process prior to learning the outcome of their new 
technology add-on payment application. This process involves a number 
of steps, including: Gathering relevant information and submitting the 
ICD-10-PCS code request; developing a slide deck for the ICD-10 
Coordination and Maintenance Committee Meeting; and reviewing the 
background paper draft for the ICD-10 Coordination and Maintenance 
Committee Meeting agenda and meeting materials. CMS also expends 
significant time, effort, and resources to administer this process, 
which is compounded by the increasing number of requests for unique 
ICD-10-PCS (for example, Section X) procedure codes. CMS must work with 
applicants to review, prepare, and present the code proposals at ICD-10 
Coordination and Maintenance Committee Meetings, then review and 
summarize public comments received in response to the meetings, and 
ultimately make a decision on the codes requested for new technology 
add-on payment policy purposes before the outcome of the new technology 
add-on payment application (approval or denial) is known. Following the 
end of the three-year timeframe for which a code was created in 
connection with a new technology add-on payment application, the 
disposition of the Section X code is addressed at a later ICD-10 
Coordination and Maintenance Committee meeting and CMS subsequently 
receives public comments that must be reviewed regarding this 
disposition.
    Stakeholders submitted comments that suggested alternative options 
to the use of Section X procedure codes to identify therapeutic agents 
for the administration of the new technology add-on payment policy. The 
majority of commenters supported using National Drug Codes (NDCs), 
because it would avoid creating duplicate codes within the ICD-10-PCS 
and NDC code sets to identify the same technology/product, which would 
allow for predictive and efficient coding. Commenters also stated that 
using NDCs would generate product data on inpatient claims that would 
allow for outcomes analyses, thus providing the same benefit as a 
unique ICD-10-PCS code. Some commenters suggested using the 3E0 
Administration Table within the ICD-10-PCS code set, as opposed to 
Section X, as they stated this would be a more intuitive location for 
coders to look for ICD-10-PCS procedure codes describing the 
administration of therapeutic agents. However, a commenter noted that 
this would be unsustainable due to the potentially large number of new 
products coming to market. A few commenters also suggested using 
different drug terminologies, such as RxNorm, in lieu of using Section 
X codes for the time period needed to administer the new technology 
add-on payment.
    We also note that we have previously established the use of NDCs as 
an alternative code set for the purposes of administering the new 
technology add-on payment in circumstances where an ICD-10-PCS code was 
not available to uniquely identify the use of the technology. In the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53351 through 53354), we 
established the use of the NDC code set to identify oral medications 
where no inpatient procedure was associated, to report the oral 
administration of the drug DIFICIDTM. We finalized that the 
NDC for DIFICIDTM would be used in conjunction with an ICD-
9-CM diagnosis code to uniquely identify the indication for which 
administration of the drug (technology) was performed for new 
technology add-on payment purposes. In the FY 2019 IPPS/LTCH PPS final 
rule (83 FR 41311), we stated that we believed that the circumstances 
with respect to the identification of eligible cases reporting the use 
of VABOMERETM, which was administered by IV infusion, were 
similar to those addressed in the FY 2013 IPPS/LTCH PPS final rule with 
regard to DIFICIDTM because we also did not have current 
ICD-10-PCS code(s) to uniquely identify the use of 
VABOMERETM to make the new technology add-on payments. 
Therefore, consistent with our approach in FY 2013, we stated that we 
would identify cases involving the use of VABOMERETM that 
were eligible for FY 2019 new technology add-on payments using its NDCs 
65293-0009-01 or 70842-0120-01 \596\ (VABOMERETM Meropenem-
Vaborbactam Vial). At the time of its new technology add-on payment 
application approval, VABOMERETM was not assigned a 
corresponding ICD-10-PCS procedure or ICD-10-CM diagnosis code along 
with its NDCs. In addition, cases involving the use of two therapeutic 
agents that qualify for NCTAP, which is administered similarly to the 
new technology add-on payment, are identified using the NDCs for these 
products for the purposes of the NCTAP, because there are not currently 
ICD-10-PCS procedure codes that uniquely describe the administration of 
these therapies.\597\
---------------------------------------------------------------------------

    \596\ We note that these are not the FDA assigned NDCs, but 
rather have been converted from 10-digit NDCs assigned by FDA to the 
HIPAA compliant 11-digit format.
    \597\ New COVID-19 Treatments Add-On Payment (NCTAP) https://www.cms.gov/medicare/covid-19/new-covid-19-treatments-add-payment-nctap.
---------------------------------------------------------------------------

    We believe that our previous policies regarding the use of NDCs to 
identify the administration of certain therapeutic agents can be 
consistently applied toward broader future usage of the NDCs to 
identify therapeutic agents eligible for the new technology add-on 
payment. Additionally, we believe that the use of an existing code set 
to identify therapeutic agents eligible for the new technology add-on 
payment would address concerns raised by commenters regarding the use 
of the ICD-10-PCS classification system to identify these agents, and 
reduce the need for applicants to seek a unique ICD-10-PCS code through 
the ICD-10-PCS Section X code request process in advance of a 
determination on their new technology add-on payment applications. 
Therefore, as we discuss further in this section, we are proposing for 
FY 2024 to instead use NDCs to identify cases involving the use of 
therapeutic agents approved for the new technology add-on payment. We 
anticipate that this proposal would reduce work for hospital coding 
professionals in becoming familiar with newly created ICD-10-PCS 
Section X codes to describe the administration of

[[Page 28355]]

therapeutic agents and in searching for these codes within the 
documentation and within the classification in what may be non-
intuitive locations. We also expect this proposed change would address 
concerns regarding the creation of duplicative codes within the ICD-10-
PCS procedure coding system to describe the administration of 
therapeutic agents, which would also reduce the need for vendors to 
incorporate additional procedure codes into their coding products; for 
educators to provide training on these codes; and for programmers to 
maintain codes that may be seldom reported on inpatient claims but for 
the purposes of the new technology add-on payment, in their databases. 
It would also reduce efforts associated with determining the 
disposition of procedure codes describing therapeutic agents that have 
reached the end of their three-year new technology add-on payment 
timeframe.
    Furthermore, we believe that NDCs are a viable alternative to 
Section X codes for the administration of the new technology add-on 
payment for therapeutic agents. We believe inpatient hospital staff are 
familiar with using NDCs, and as stated earlier, we have also 
previously utilized NDCs to administer the new technology add-on 
payment. However, to allow for adequate time to implement this regular 
usage of NDCs with the new technology add-on payment for health care 
providers and hospital coding professionals, we are proposing a 
transitional period for FY 2023. During this transitional period, we 
would utilize NDCs to identify the administration of therapeutic agents 
for new technology add-on payment purposes. However, we would also 
utilize ICD-10-PCS Section X codes, including codes newly created for 
FY 2023, for therapeutic agents during the FY 2023 new technology add-
on payment application cycle. Beginning with the FY 2024 new technology 
add-on payment application cycle, we would utilize only NDCs to 
identify claims involving the administration of therapeutic agents 
approved for the new technology add-on payment, with the exception of 
claims involving therapeutic agents that are not assigned an NDC by FDA 
(for example, blood, blood products, etc.) and are approved for the new 
technology add-on payment. Cases involving the use of these 
technologies approved for the new technology add-on payment would 
continue to be identified based on the assigned ICD-10-PCS procedure 
code. A unique ICD-10-PCS procedure code would also still be needed to 
identify cases involving the use of CAR T-cell and other 
immunotherapies that may be assigned to Pre-MDC MS-DRG 018, because the 
ICD-10 MS-DRG GROUPER logic for assignment to Pre-MDC MS-DRG 018 is 
comprised of the procedure codes describing these CAR T-cell and other 
immunotherapy products. Therefore, under this proposal, beginning with 
FY 2024 new technology add-on payment applications submitted for a 
therapeutic agent, CMS would review the information and inform the 
applicant, in advance of the deadline for submitting an ICD-10-PCS 
procedure code request to the ICD-10 Coordination and Maintenance 
Committee for consideration at the March meeting, if it would be 
necessary to submit such a code request for purposes of identifying 
cases involving the use of the therapeutic agent for the new technology 
add-on payment, if approved, or if, based on the information made 
available with the application, the NDC could be used to identify such 
cases, and therefore, the applicant would not need to submit an ICD-10-
PCS procedure code request. For each applicable technology that may be 
approved for new technology add-on payment, we would indicate the 
NDC(s) to use to identify cases involving the administration of the 
therapeutic agent for purposes of the new technology add-on payment.
    Specifically, we are proposing that, during the transitional period 
beginning with discharges on or after October 1, 2022 (FY 2023), the 
administration of therapeutic agents newly approved for new technology 
add-on payments would be uniquely identified using either their 
respective NDC(s) or ICD-10-PCS procedure code(s), in combination with 
ICD-10-CM codes when appropriate. As stated in our FY 2013 IPPS/LTCH 
PPS final rule, the use of the NDCs ``does not preclude CMS from using 
additional ICD-9-CM procedure or diagnosis codes to identify cases for 
this new technology in conjunction with this alternative code set'' (77 
FR 53352). Therefore, when necessary, we may require the use of 
additional ICD-10-PCS procedure and/or ICD-10-CM diagnosis codes to 
uniquely identify cases using these technologies. We would continue the 
use of the existing ICD-10-PCS procedure codes to identify the 
administration of therapeutic agents previously approved for the new 
technology add-on payment and that remain eligible for the new 
technology add-on payment for FY 2023.
    We are further proposing that, beginning with discharges on or 
after October 1, 2023 (FY 2024), the administration of therapeutic 
agents newly approved for the new technology add-on payments beginning 
FY 2024 or a subsequent fiscal year would be uniquely identified only 
by their respective NDC(s), along with the corresponding existing ICD-
10 code(s) required to uniquely identify the therapeutic agents, when 
necessary, to make the new technology add-on payments. For technologies 
that were newly approved for new technology add-on payments for FY 2023 
(beginning with discharges on or after October 1, 2022) and remain 
eligible for the new technology add-on payment for FY 2024 or a 
subsequent fiscal year, we would continue to allow the use of either 
the existing ICD-10-PCS procedure codes or NDCs to identify the 
administration of those therapeutic agents. For technologies that were 
newly approved for new technology add-on payments prior to FY 2023 and 
remain eligible for the new technology add-on payment for FY 2024 or a 
subsequent fiscal year, we would continue to use the existing ICD-10-
PCS procedure codes to identify the administration of those therapeutic 
agents.
    We are inviting public comments on our proposal to utilize NDCs to 
identify claims involving the use of therapeutic agents approved for 
new technology add-on payments, including any potential concerns 
regarding adoption of this code set for the identification of 
therapeutic agents for purposes of new technology add-on payments.
9. Proposal to Publicly Post New Technology Add-On Payment Applications
    As noted in section II.F.1.f. of the preamble of this proposed 
rule, applicants for new technology add-on payments for new medical 
services or technologies 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), along with a significant sample of data to 
demonstrate the new medical service or technology meets the high-cost 
threshold (OMB-0938-1347). See section II.F.1.f. of the preamble of 
this proposed rule for further details on the data and evidence that 
can be submitted. We post complete application information and final 
deadlines for submitting a full application on the CMS website at

[[Page 28356]]

https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech. We also post on the same website tracking 
forms completed by each applicant, which include the name of each 
applicant, name of the technology, and a brief description so that 
interested parties can identify the new medical services or 
technologies under review before the annual proposed rule. 
Additionally, section 1886(d)(5)(K)(viii) of the Act provides for a 
mechanism for public input before the publication of a proposed rule 
regarding whether a medical service or technology represents a 
substantial clinical improvement. Consistent with the Act, we hold an 
annual Town Hall meeting, typically in December following notice of the 
meeting in the Federal Register.
    As set forth in 42 CFR 412.87(e)(1), CMS considers whether a 
technology meets the criteria for the new technology add-on payment and 
announces the results as part of its annual updates and changes to the 
IPPS. Accordingly, in drafting the proposed rule, CMS reviews each new 
technology add-on payment application it receives under the pathway 
specified by the applicant at the time of application submission, along 
with supplemental information \598\ obtained from the applicant, 
information provided at the Town Hall meeting, and comments received in 
response to the Town Hall meeting. In the proposed rule, CMS summarizes 
the information contained in the application, including the applicant's 
explanation of what the technology does, background on the disease 
process, information about the FDA approval/clearance, and the 
applicant's assertions and supporting data on how the technology meets 
the new technology add-on payment criteria under Sec.  412.87. In 
summarizing this information for inclusion in the proposed rule, CMS 
restates or paraphrases information contained in the application and 
attempts to avoid misrepresenting or omitting any of an applicant's 
claims. CMS also tries to ensure that sufficient information is 
provided in the proposed rule to facilitate public comments on whether 
the medical service or technology meets the new technology add-on 
payment criteria. Currently, however, CMS does not make the 
applications themselves, as completed by the applicants, publicly 
available. In addition, CMS generally does not take into consideration 
information that is marked as confidential when determining whether a 
technology meets the criteria for new technology add-on payments.
---------------------------------------------------------------------------

    \598\ For the FY 2023 new technology add-on payment 
applications, the supplemental information deadline to guarantee 
inclusion in the IPPS proposed rule was December 17, 2021.
---------------------------------------------------------------------------

    We note that in the past, CMS has received requests from the public 
to access and review the new technology add-on payment applications to 
further facilitate comment on whether a technology meets the new 
technology add-on payment criteria. In consideration of this issue, we 
agree that review of the original source information from the 
applications for new technology add-on payments may help to inform 
public comment. Further, making this information publicly available may 
foster greater input from experts in the stakeholder community based on 
their review of the completed application forms and related materials. 
Accordingly, as we discuss further in this section, we believe that 
providing additional information to the public by publicly posting the 
applications and certain related materials online may help to further 
engage the public and foster greater input and insights on the various 
new medical services and technologies presented annually for 
consideration for new technology add-on payments.
    We also believe that posting the applications online would reduce 
the risk that we may inadvertently omit or misrepresent relevant 
information submitted by applicants, or are perceived as 
misrepresenting such information, in our summaries in the rules. It 
also would streamline our evaluation process, including the 
identification of critical questions in the proposed rule, particularly 
as the number and complexity of the applications have been increasing 
over time. That is, by making the applications available to the public 
online, we would afford more time for CMS to process and analyze the 
supporting data and evidence rather than reiterate parts of the 
application in the rule.
    Therefore, to increase transparency, enable increased stakeholder 
engagement, and further improve and streamline our evaluation process, 
we are proposing to publicly post online future applications for new 
technology add-on payments. Specifically, beginning with the FY 2024 
application cycle, we propose to post online the completed application 
forms and certain related materials (for example, attachments, uploaded 
supportive materials) that we receive from applicants. Additionally, we 
propose to post information acquired subsequent to the application 
submission (for example, comments received after the New Technology 
Town Hall, updated application information, additional clinical 
studies, etc.). We propose that we would not post the cost and volume 
information the applicant provides in the application form itself or as 
attached materials, or any material included with the application that 
the applicant indicates is not releasable to the public because the 
applicant does not own the copyright or the applicant does not have the 
appropriate license to make the material available to the public, as 
further described in the next paragraph. We propose that we would 
publicly post the completed application forms and related materials no 
later than the issuance of the proposed rule, which would afford the 
public the full public comment period to review the information 
provided by the applicant in its application.
    With respect to copyrighted materials, we propose that on the 
application form itself, the applicant would be asked to provide a 
representation that the applicant owns the copyright or otherwise has 
the appropriate license to make all the copyrighted material included 
with its application public with the exception of those materials 
identified by the applicant as not releasable to the public, as 
applicable. For any material included with the application that the 
applicant indicates as copyrighted and/or not otherwise releasable to 
the public, we propose that the applicant must either provide a link to 
where the material can be accessed or provide an abstract or summary of 
the material that CMS can make public, and CMS will then post that link 
or abstract or summary online, along with the other posted application 
materials. We invite comments on this proposal.
    Under our current practice, we include in the final rule 
information on the cost of each technology that is approved for the new 
technology add-on payment for the purposes of calculating the maximum 
add-on payment, and information on the anticipated volume of the 
technology for purposes of the impact analysis. For the proposed rule, 
specifically for applications submitted under the alternative pathway, 
our current practice is to propose whether or not to approve the 
application based on the eligibility criteria for the alternative 
pathway under 42 CFR 412.87(c) or (d) and, where cost information is 
available from the applicant, to use this information in proposing a 
maximum add-on payment amount. Where cost information is not yet 
available, we note our expectation is that the applicant will submit 
cost information prior to the final rule, and indicate that we will 
provide an update

[[Page 28357]]

regarding the new technology add-on payment amount for the technology, 
if approved, in the final rule. We note that we would continue this 
same approach with respect to including cost and volume information in 
the proposed and final rules. However, as noted, under our proposal to 
post online the new technology add-on payment applications, we would 
not include cost and volume information for either traditional or 
alternative pathway applications as part of the application materials 
that would be posted online.
    We note that at times an applicant may furnish information marked 
as proprietary or trade secret information along with its application 
for new technology add-on payments. Currently, the application 
specifies that data provided in the application or tracking form may be 
subject to disclosure and instructs the applicant to mark any 
proprietary or trade secret information so that CMS can attempt, to the 
extent allowed under Federal law, to keep the information protected 
from public view.\599\ This instruction would change under our proposal 
such that information included in the application, other than cost and 
volume information, would be made publicly available online through 
posting of the application. Therefore, the applicant should not submit 
as part of its application any such proprietary or trade secret 
information that it does not want to be made publicly available online. 
As noted, under our existing practice we generally do not consider 
information that is marked as confidential, proprietary, or trade 
secret when determining whether a technology meets the criteria for new 
technology add-on payments.
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    \599\ See new technology add-on payment application included in 
the FY 2023 New Technology Application Packet, available at: https://www.cms.gov/files/zip/fy-2023-new-technology-application-packet.zip; and FY 2023 Tracking Forms, available at: https://www.cms.gov/files/document/fy-2023-tracking-forms-applicants.pdf.
---------------------------------------------------------------------------

    This proposal would not change the current timeline or evaluation 
process for new technology add-on payments, the criteria used to assess 
applications, or the deadlines for various data submissions. 
Additionally, we do not expect added burdens on prospective applicants 
as a result of this proposal since we are not proposing to 
fundamentally change the information collected in the application 
itself or the supplemental information that would be furnished to 
support the application. As noted, the aim of this proposed policy 
change is to increase accuracy, transparency, and efficiency for both 
CMS and stakeholders.
    In connection with this proposal to post the new technology 
applications online, we expect we would also make changes to the 
summaries that appear in the annual proposed and final rules, given 
that the public would have access to the submitted applications 
themselves (excluding certain information and materials as described 
previously), while also continuing to provide sufficient information in 
the rules to facilitate public comments on whether a medical service or 
technology meets the new technology add-on payment criteria. 
Specifically, we do not anticipate summarizing each entire application 
in the Federal Register as we have in the past, given the expanded and 
public access to the applications under the proposal. In some 
instances, such as the discussion of the substantial clinical 
improvement criterion, we expect to provide a more concise summary of 
the evidence or a more targeted discussion of the applicant's claims 
about how that criterion is met based on the evidence and supporting 
data (although this may vary depending on the application, new medical 
service or technology, and the nature of supporting materials 
provided). We expect that we would continue to generally include, at a 
high-level, the following information in the proposed and final rules: 
The technology and applicant name; a description of what the technology 
does; background on the disease process; the FDA approval/clearance 
status; and a summary of the applicant's assertions. We also expect to 
provide more succinct information as part of the summaries in the 
proposed and final rules regarding the applicant's assertions as to how 
the medical service or technology meets the newness, cost, and 
substantial clinical improvement criteria. For example, we would 
provide a list of the applicant's assertions for whether the technology 
meets the three sub-criteria under the substantial clinical improvement 
criterion \600\ and a list of the sources of data submitted in support 
of the assertions, along with references to the application in support 
of these lists. In the proposed rule, we would also continue to provide 
discussion of the concerns or issues we identified with respect to 
applications submitted under the traditional pathway, and for an 
alternative pathway application, we intend to continue to propose 
whether to approve or disapprove the application, including noting any 
concerns we have identified, and, as applicable, the maximum add-on 
payment amount, where cost information is available. In the final rule, 
we would continue to provide an explanation of our determination of 
whether a medical service or technology meets the applicable new 
technology add-on payment criteria and, for approved technologies, the 
final add-on payment amounts. As noted, we believe the proposal to post 
online the completed application forms and other information described 
previously would afford greater transparency during the annual 
rulemaking, for purposes of determining whether a medical service or 
technology is eligible for new technology add-on payments.
---------------------------------------------------------------------------

    \600\ Sub-criteria referenced are those listed in Question 36 of 
the new technology add-on payment application, specifically 
Questions 36a-36c.
---------------------------------------------------------------------------

    We are seeking public comment on our proposal to publicly post 
online the completed application forms and certain related materials 
and updated application information submitted subsequent to the initial 
application submission for new technology add-on payments, beginning 
with applications for FY 2024.

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 2023 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, IV. The OMB control number for this information 
collection request is 0938-0050, which expired on March 31, 2022. A 
reinstatement of the information collection request is currently being 
developed. The public will have an opportunity to review and submit

[[Page 28358]]

comments on the reinstatement through a public notice and comment 
period separate from this rulemaking. 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 2023 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 2023 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. 
(The OMB control number for approved collection of this information is 
0938-0907, which expires on September 30, 2022.) A discussion of the 
occupational mix adjustment that we are proposing to apply to the FY 
2023 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 2023 
Hospital Wage Index

    The wage index is calculated and assigned to hospitals on the basis 
of the labor market area in which the hospital is located. Under 
section 1886(d)(3)(E) of the Act, beginning with FY 2005, we delineate 
hospital labor market areas based on OMB-established Core-Based 
Statistical Areas (CBSAs). The current statistical areas (which were 
implemented beginning with FY 2015) are based on revised OMB 
delineations issued on February 28, 2013, in OMB Bulletin No. 13-01. 
OMB Bulletin No. 13-01 established revised delineations for 
Metropolitan Statistical Areas, Micropolitan Statistical Areas, and 
Combined Statistical Areas in the United States and Puerto Rico based 
on the 2010 Census, and provided guidance on the use of the 
delineations of these statistical areas using standards published in 
the June 28, 2010, Federal Register (75 FR 37246 through 37252). We 
refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951 
through 49963 and 49973 through 49982)) for a full discussion of our 
implementation of the OMB statistical area delineations beginning with 
the FY 2015 wage index.
    Generally, OMB issues major revisions to statistical areas every 10 
years, based on the results of the decennial census. However, OMB 
occasionally issues minor updates and revisions to statistical areas in 
the years between the decennial censuses through OMB Bulletins. On July 
15, 2015, OMB issued OMB Bulletin No. 15-01, which provided updates to 
and superseded OMB Bulletin No. 13-01 that was issued on February 28, 
2013. The attachment to OMB Bulletin No. 15-01 provided detailed 
information on the update to statistical areas since February 28, 2013. 
The updates provided in OMB Bulletin No. 15-01 were based on the 
application of the 2010 Standards for Delineating Metropolitan and 
Micropolitan Statistical Areas to Census Bureau population estimates 
for July 1, 2012, and July 1, 2013. In the FY 2017 IPPS/LTCH PPS final 
rule (81 FR 56913), we adopted the updates set forth in OMB Bulletin 
No. 15-01 effective October 1, 2016, beginning with the FY 2017 wage 
index. For a complete discussion of the adoption of the updates set 
forth in OMB Bulletin No. 15-01, we refer readers to the FY 2017 IPPS/
LTCH PPS final rule. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38130), we continued to use the OMB delineations that were adopted 
beginning with FY 2015 to calculate the area wage indexes, with updates 
as reflected in OMB Bulletin No. 15-01 specified in the FY 2017 IPPS/
LTCH PPS final rule.
    On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which 
provided updates to and superseded OMB Bulletin No. 15-01 that was 
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 
provided detailed information on the update to statistical areas since 
July 15, 2015, and were based on the application of the 2010 Standards 
for Delineating Metropolitan and Micropolitan Statistical Areas to 
Census Bureau population estimates for July 1, 2014 and July 1, 2015. 
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41363), we 
adopted the updates set forth in OMB Bulletin No. 17-01 effective 
October 1, 2018, beginning with the FY 2019 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
17-01, we refer readers to the FY 2019 IPPS/LTCH PPS final rule. In the 
FY 2020 IPPS/LTCH PPS final rule (84 FR 42300 through 42301), we 
continued to use the OMB delineations that were adopted beginning with 
FY 2015 (based on the revised delineations issued in OMB Bulletin No. 
13-01) to calculate the area wage indexes, with updates as reflected in 
OMB Bulletin Nos. 15-01 and 17-01.
    On April 10, 2018 OMB issued OMB Bulletin No. 18-03 which 
superseded the August 15, 2017, OMB Bulletin No. 17-01. On September 
14, 2018, OMB issued OMB Bulletin No. 18-04 which superseded the April 
10, 2018 OMB Bulletin No. 18-03. Historically OMB bulletins issued 
between decennial censuses have only contained minor modifications to 
CBSA delineations based on changes in population counts. However, OMB's 
2010 Standards for Delineating Metropolitan and Micropolitan 
Statistical Areas to Census Bureau population estimates created a 
larger mid-decade redelineation that takes into account commuting data 
from the American Commuting Survey. As a result, the September 14, 
2018, OMB Bulletin No. 18-04 included more modifications to the CBSAs 
than are typical for OMB bulletins issued between decennial censuses.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58743 through 58755) 
we adopted the updates set forth in OMB Bulletin No. 18-04 effective 
October 1, 2020, beginning with the FY 2021 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
18-04, we refer readers to the FY 2021 IPPS/LTCH PPS final rule.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04 that was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018, and were based on the application of the 2010 Standards for 
Delineating Metropolitan and Micropolitan Statistical Areas to Census 
Bureau population estimates for July 1, 2017, and July 1, 2018. After 
reviewing OMB Bulletin No. 20-01, we determined that the changes in 
Bulletin 20-01 encompassed delineation changes that would not affect 
the Medicare wage index for FY 2022. While we adopted the updates set 
forth in OMB Bulletin No. 20-01 in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45163 through

[[Page 28359]]

45164) consistent with our general policy of adopting OMB delineation 
updates, we also noted that specific wage index updates would not be 
necessary for FY 2022 as a result of adopting these updates. In other 
words, the updates set forth in OMB Bulletin No. 20-01 would not affect 
any hospital's geographic area for purposes of the wage index 
calculation for FY 2022. For a complete discussion of the adoption of 
the updates set forth in OMB Bulletin No. 20-01, we refer readers to 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45163 through 45164. For FY 
2023, 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, 18- 04 and 20-01, although 
as noted previously OMB Bulletin No. 20-01 did not require any wage 
area updates.
    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 was set to expire at the end of FY 2021. However, given the 
unprecedented nature of the ongoing COVID-19 public health emergency 
(PHE), we adopted a policy in the FY 2022 IPPS/LTCH PPS final rule to 
apply an extended transition to the FY 2022 wage index for hospitals 
that received the transition in FY 2021. Specifically, we continued a 
wage index transition for FY 2022 (for hospitals that received the 
transition in FY 2021) under which we applied a 5 percent cap on any 
decrease in the hospital's wage index compared to its wage index for FY 
2021 to mitigate significant negative impacts of, and provide 
additional time for hospitals to adapt to, the CMS decision to adopt 
the revised OMB delineations. We also applied a budget neutrality 
adjustment to the standardized amount so that our transition in FY 2022 
was implemented in a budget neutral manner under our authority in 
section 1886(d)(5)(I) of the Act. We refer the reader to the FY 2022 
IPPS/LTCH PPS final rule (85 FR 45164 through 45165) for a complete 
discussion of this transition. We also refer readers to section III.N. 
of the preamble of this proposed rule which discusses our proposal with 
regard to a permanent wage index transition for a hospital's wage index 
that applies a 5 percent cap on any decrease in the hospital's wage 
index compared to its wage index from the prior fiscal year.
3. Codes for Constituent Counties in CBSAs
    CBSAs are made up of one or more constituent counties. Each CBSA 
and constituent county has its own unique identifying codes. There are 
two different lists of codes associated with counties: Social Security 
Administration (SSA) codes and Federal Information Processing Standard 
(FIPS) codes. Historically, CMS has listed and used SSA and FIPS county 
codes to identify and crosswalk counties to CBSA codes for purposes of 
the hospital wage index. As we discussed in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38129 through 38130), we have learned that SSA county 
codes are no longer being maintained and updated. However, the FIPS 
codes continue to be maintained by the U.S. Census Bureau. We believe 
that using the latest FIPS codes will allow us to maintain a more 
accurate and up-to-date payment system that reflects the reality of 
population shifts and labor market conditions.
    The Census Bureau's most current statistical area information is 
derived from ongoing census data received since 2010; the most recent 
data are from 2020. The Census Bureau maintains a complete list of 
changes to counties or county equivalent entities on the website at 
https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html. We believe that it is important to 
use the latest counties or county equivalent entities in order to 
properly crosswalk hospitals from a county to a CBSA for purposes of 
the hospital wage index used under the IPPS.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through 
38130), we adopted a policy to discontinue the use of the SSA county 
codes and began using only the FIPS county codes for purposes of cross 
walking counties to CBSAs. In addition, in the same rule, we 
implemented the latest FIPS code updates, which were effective October 
1, 2017, beginning with the FY 2018 wage indexes. These updates have 
been used to calculate the wage indexes in a manner generally 
consistent with the CBSA-based methodologies finalized in the FY 2005 
IPPS final rule and the FY 2015 IPPS/LTCH PPS final rule. We refer the 
reader to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through 
38130) for a complete discussion of our adoption of FIPS county codes.
    Based on the latest information included in the Census Bureau's 
website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.2010.html, the Census Bureau has made the 
following updates to the FIPS codes for counties or county equivalent 
entities:
     Chugach Census Area, AK (FIPS State County Code 02-063) 
and Copper River Census Area, AK (FIPS State County Code 02-066), were 
created from former Valdez-Cordova Census Area (02-261) which was 
located in CBSA 02. The CBSA code for these two new county equivalents 
remains 02.
    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 addition, we believe that using the latest FIPS 
codes allows us to maintain a more accurate and up-to-date payment 
system that reflects the reality of population shifts and labor market 
conditions. Therefore, we are proposing to implement these FIPS code 
updates listed previously, effective October 1, 2022, beginning with 
the FY 2023 wage indexes. We are proposing to use these update changes 
to calculate area wage indexes in a manner that is generally consistent 
with the CBSA-based methodologies finalized in the FY 2005 IPPS final 
rule (69 FR 49026 through 49034) and the 2015 IPPS/LTCH PPS final rule 
(79 FR 49951 through 49963). We note that while the county update 
changes listed above changed the county names, the CBSAs to which these 
counties map did not change from the prior counties. Therefore, there 
would be no impact or change to hospitals in these counties for 
purposes of the hospital wage index as a result of our implementation 
of these FIPS code updates.
    For FY 2023, 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. We are inviting public comments 
on our proposals.

B. Worksheet S-3 Wage Data for the Proposed FY 2023 Wage Index

    The proposed FY 2023 wage index values are based on the data 
collected from the Medicare cost reports submitted by hospitals for 
cost reporting periods beginning in FY 2019 (the FY 2022 wage indexes 
were based on data

[[Page 28360]]

from cost reporting periods beginning during FY 2018).
1. Included Categories of Costs
    The proposed FY 2023 wage index includes all of the following 
categories of data associated with costs paid under the IPPS (as well 
as outpatient costs):
     Salaries and hours from short-term, acute care hospitals 
(including paid lunch hours and hours associated with military leave 
and jury duty).
     Home office costs and hours.
     Certain contract labor costs and hours, which include 
direct patient care, certain top management, pharmacy, laboratory, and 
nonteaching physician Part A services, and certain contract indirect 
patient care services (as discussed in the FY 2008 final rule with 
comment period (72 FR 47315 through 47317)).
     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 modified in the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49505 through 49508)) and other deferred compensation costs.
2. Excluded Categories of Costs
    Consistent with the wage index methodology for FY 2022, the 
proposed wage index for FY 2023 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 2023 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 2023 wage index were obtained 
from Worksheet S-3, Parts II, III and IV of the Medicare cost report, 
CMS Form 2552-10 for cost reporting periods beginning on or after 
October 1, 2018, and before October 1, 2019. (As noted in section 
III.A.1 of the preamble of this proposed rule, the OMB control number 
for this information collection request is 0938-0050, which expired on 
March 31, 2022. A reinstatement of the information collection request 
is currently being developed. The public will have an opportunity to 
review and submit comments on the reinstatement through a public notice 
and comment period separate from this rulemaking). For wage index 
purposes, we refer to cost reports beginning on or after October 1, 
2018, and before October 1, 2019 as the ``FY 2019 cost report,'' the 
``FY 2019 wage data,'' or the ``FY 2019 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 FY 2023 wage index includes FY 2019 data submitted to us as of 
February 5, 2022. As in past years, we performed an extensive review of 
the wage data, mostly through the use of edits designed to identify 
aberrant data.
    Consistent with the IPPS and LTCH PPS ratesetting, our policy 
principles with regard to the wage index include generally using the 
most current data and information available which is usually data on a 
four year lag (for example, for the FY 2022 wage index we used cost 
report data from FY 2018) . 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 2023 IPPS/LTCH PPS proposed rule 
given the potential impact of the public health emergency (PHE) for the 
Coronavirus Disease (COVID-19). For the FY 2023 wage index, the best 
available data typically would be from the FY 2019 wage data. Our 
review and analysis of the FY 2019 wage data shows that the data is not 
significantly impacted by COVID-19 PHE. A comparison of providers shows 
similar trends in those with cost reports ending during the PHE as 
compared to providers without cost reports ending during the PHE. The 
data also shows that changes in the Average Hourly Wage (AHW) for 
providers were consistent between providers with cost reports ending 
during the PHE as compared to providers without cost reports ending 
during the PHE. It appears that the overall impact of the COVID-19 PHE 
on the FY 2019 wage data has been minimal.
    Additionally, the changes in the wage data from FY 2018 to FY 2019 
show similar trends in the change of the data from FY 2017 to FY 2018. 
Therefore, we are proposing to use the FY 2019 wage data for the FY 
2023 wage index.
    We asked our MACs to revise or verify data elements that result in 
specific edit failures. For the proposed FY 2023 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 2023 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, 2022.
    In constructing the proposed FY 2023 wage index, we included the 
wage data for facilities that were IPPS hospitals in FY 2019, inclusive 
of those facilities that have since terminated their participation in 
the program as hospitals, as long as those data did not fail any of our 
edits for reasonableness. We believe that including the wage data for 
these hospitals is, 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

[[Page 28361]]

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, 2021, the cut-off date for CAH exclusion from the 
FY 2022 wage index, and through and including January 21, 2022, the 
cut-off date for CAH exclusion from the FY 2023 wage index. In summary, 
we calculated the proposed FY 2023 wage index using the Worksheet S-3, 
Parts II and III wage data of 3,112 hospitals.
    For the proposed FY 2023 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 2023 
wage index associated with this proposed rule (available via the 
internet on the CMS website), includes separate wage data for the 
campuses of 26 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
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[[Page 28362]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.148

BILLING CODE 4120-01-C
    We note that, in past years, in Table 2, we have placed a ``B'' to 
designate the subordinate campus in the fourth position of the hospital 
CCN. However, for the FY 2019 IPPS/LTCH PPS proposed and final rules 
and subsequent rules, we have moved the ``B'' to the third position of 
the CCN. Because all IPPS hospitals have a ``0'' in the third position 
of the CCN, we believe that placement of the ``B'' in this third 
position, instead of the ``0'' for the subordinate campus, is the most 
efficient method of identification and interferes the least with the 
other, variable, digits in the CCN.

D. Method for Computing the Proposed FY 2023 Unadjusted Wage Index

    The method used to compute the proposed FY 2023 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 2023, these were data from cost reports for cost reporting periods 
beginning on or after October 1, 2018, and before October 1, 2019). In 
addition, we included data from some hospitals that had cost reporting 
periods beginning before October 2018 and reported a cost reporting 
period covering all of FY 2019. 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 2019 data. We note 
that, if a hospital had more than one cost reporting period beginning 
during FY 2019 (for example, a hospital had two short cost reporting 
periods beginning on or after October 1, 2018, and before October 1, 
2019), 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,

[[Page 28363]]

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 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, 2018, through April 15, 
2020, for private industry hospital workers from the Bureau of Labor 
Statistics' (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 2023. 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)

[[Page 28364]]

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 2023 
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 Public Law 105-33 provides that, for 
discharges on or after October 1, 1997, the area wage index applicable 
to any hospital that is located in an urban area of a State may not be 
less than the area wage index applicable to hospitals located in rural 
areas in that State. The areas affected by this provision are 
identified in Table 2 listed in section VI. of the Addendum to the 
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, 2018, through April 15, 
2020, 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 2023. 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 28365]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.149

    For example, the midpoint of a cost reporting period beginning 
January 1, 2019, and ending December 31, 2019, is June 30, 2019. An 
adjustment factor of 1.01630 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, 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 
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 2023, there is no Puerto Rico-
specific overall average hourly wage or wage index.
    Based on the methodology, as previously discussed, the proposed FY 
2023 unadjusted national average hourly wage is the following:
[GRAPHIC] [TIFF OMITTED] TP10MY22.150

BILLING CODE 4120-01-C

E. Proposed Occupational Mix Adjustment to the FY 2023 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 
2023 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

[[Page 28366]]

care hospital participating in the Medicare program. As discussed in 
the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25402 through 25403) and 
final rule (86 FR 45173), we collected data in 2019 to compute the 
occupational mix adjustment for the FY 2022, FY 2023, and FY 2024 wage 
indexes. The FY 2023 occupational mix adjustment is based on the 
calendar year (CY) 2019 survey. Hospitals were required to submit their 
completed 2019 surveys (Form CMS-10079, OMB Number 0938-0907, 
expiration date September 30, 2022) to their MACs by September 3, 2020. 
It should be noted that this collection of information was approved 
under OMB control number 0938-0907 with an expiration date of September 
30, 2022. Prior to the expiration date, CMS will submit an extension 
request to OMB. The extension request will be announced in the Federal 
Register via the required 60-day and 30-day notice and comment periods. 
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 2023
    For FY 2023, 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 2023 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 2023 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 2023 wage index. For the proposed FY 2023 wage 
index, we are using the Worksheet S-3, Parts II and III wage data of 
3,112 hospitals, and we used the occupational mix surveys of 3,010 
hospitals for which we also had Worksheet S-3 wage data, which 
represented a ``response'' rate of 97 percent (3,010/3,112). For the 
proposed FY 2023 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 2023 occupational mix adjusted national average hourly wage 
is the following:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.151

F. Analysis and Implementation of the Proposed Occupational Mix 
Adjustment and the Proposed FY 2023 Occupational Mix Adjusted Wage 
Index

    As discussed in section III.E. of the preamble of this proposed 
rule, for FY 2023, we are applying the occupational mix adjustment to 
100 percent of the FY 2023 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 proposed FY 2023 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] TP10MY22.152


[[Page 28367]]


    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 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] TP10MY22.153

    We compared the proposed FY 2023 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] TP10MY22.154

BILLING CODE 4120-01-C
    These results indicate that a smaller percentage of urban areas 
(55.8 percent) would benefit from the occupational mix adjustment than 
would rural areas (57.4 percent).

III. Proposed Changes to the Hospital Wage Index for Acute Care 
Hospitals

G. Application of the Rural Floor, Application of the Imputed 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). For FY 2023, we are proposing to 
continue to calculate the rural floor without the wage data of 
hospitals that have reclassified as rural under Sec.  412.103. 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)

[[Page 28368]]

of the Act. We are proposing to continue to apply this policy for FY 
2023.
    We note that the FY 2020 rural floor policy and the related budget 
neutrality adjustment are the subject of pending litigation, including 
in Citrus HMA, LLC, d/b/a Seven Rivers Regional Medical Center v. 
Becerra, No. 1:20-cv-00707 (D.D.C.) (hereafter referred to as Citrus). 
On April 8, 2022, the district court in Citrus granted in part the 
plaintiff hospitals' motion for summary judgment and denied the 
Secretary's cross-motion for summary judgment. The court found that the 
Secretary did not have authority under section 4410(a) of the Balanced 
Budget Act of 1997 to establish a rural floor lower than the rural wage 
index for a state. While Citrus involves only FY 2020, the court's 
decision--which is subject to potential appeal--may have implications 
for FY 2023 payment rates. We are continuing to evaluate the court's 
decision, and although we are proposing for the rural floor wage index 
policy (and the related budget neutrality adjustment) to continue for 
FY 2023, we may decide to take a different approach in the final rule, 
depending on public comments or developments in the court proceedings.
    Based on the FY 2023 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 
192 hospitals would receive an increase in their FY 2023 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 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)(4)(vi), we 
apply the higher of the value determined under the original or 
alternative methodology for calculating a minimum wage index, or 
imputed floor, for all-urban States effective beginning with FY 2022. 
We note that the rural floor values used in the alternative methodology 
at Sec.  412.64(h)(4)(vi)(A) and (B) would not include the wage data of 
hospitals reclassified under Sec.  412.103, because we currently 
calculate the rural floor without the wage data of such hospitals.
    Unlike the imputed floor that was in effect from FYs 2005 through 
2018, section 1886(d)(3)(E)(iv)(III) of the Act provides that the 
imputed floor wage index shall not be applied in a budget neutral 
manner. Specifically, section 9831(b) of Public Law 117-2 amends 
section 1886(d)(3)(E)(i) of the Act to exclude the imputed floor from 
the budget neutrality requirement under section 1886(d)(3)(E)(i) of the 
Act. In other words, the budget neutrality requirement under section 
1886(d)(3)(E)(i) of the Act, as amended, must be applied without taking 
into account the imputed floor adjustment under section 
1886(d)(3)(E)(iv) of the Act. When the imputed floor was in effect from 
FY 2005 through FY 2018, to budget neutralize the increase in payments 
resulting from application of the imputed floor, we calculated the 
increase in payments resulting from the imputed floor together with the 
increase

[[Page 28369]]

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 apply the imputed floor after the application of the rural floor and 
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.
    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 consider a 
hospital to be classified as rural under section 1886 of the Act if it 
is assigned the State's rural area wage index value. Therefore, under 
the definition at section 1886(d)(3)(E)(iv)(IV) of the Act, ``a State 
in which there are no hospitals classified as rural under this 
section'' includes 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) are 
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 (Medicare Geographic Classification 
Review Board (MGCRB) reclassifications) are not 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 one State, 
Connecticut, that would be eligible for the imputed floor because there 
are currently no hospitals in Connecticut that are classified as rural 
under section 1886(d) for purposes of the wage index--in other words, 
there are no hospitals that receive the rural wage index. There is 
currently one rural county in Connecticut. All hospitals in this county 
are either deemed urban under section 1886(d)(8)(B) of the Act or 
receive an MGCRB reclassification under section 1886(d)(10) of the Act. 
While several Connecticut hospitals were approved for rural 
reclassification under section 1886(d)(8)(E) of the Act, at this point 
all have received a subsequent urban reclassification under section 
1886(d)(10) of the Act.
    Additionally, under section 1861(x) of the Act, the term State has 
the meaning given to it in section 210(h) of the Act. Because section 
210(h) of the Act defines the word State to also include the District 
of Columbia and the Commonwealth of Puerto Rico, Washington, DC and 
Puerto Rico may also qualify as all-urban States for purposes of the 
imputed floor if the requirements of section 1886(d)(3)(E)(iv)(IV) of 
the Act are met. Based on data available for 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 2023: New Jersey, Rhode Island, 
Delaware, Connecticut, and Washington, DC.
    In the FY 2022 IPPS/LTCH PPS final rule, we revised 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. The imputed floor 
will be applied for FY 2023 in accordance with the policies adopted in 
the FY 2022 IPPS/LTCH PPS final rule. For more information regarding 
our implementation of the imputed floor required by section 
1886(d)(3)(E)(iv) of the Act, we refer readers to the discussion in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45176 through 45178).
3. State Frontier Floor for FY 2023
    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 2023 IPPS/
LTCH PPS proposed rule, we are not proposing any changes to the 
frontier floor policy for FY 2023. In this proposed rule, 44 hospitals 
would receive the frontier floor value of 1.0000 for their FY 2023 
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 2023 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 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) our intention 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. We note that the FY 2020 
low wage index hospital policy and the related budget neutrality 
adjustment are the subject of pending litigation, including in 
Bridgeport Hospital, et al., v. Becerra, No. 1:20-cv-01574 (D.D.C.) 
(hereafter referred to as Bridgeport). On March 2, 2022, the district 
court in Bridgeport granted in part the plaintiff hospitals' motion for 
summary judgment and denied the Secretary's cross-motion for summary 
judgment. The court found that the

[[Page 28370]]

Secretary did not have authority under section 1886(d)(3)(E) or 
1886(d)(5)(I)(i) of the Act to adopt the low wage index hospital policy 
and ordered additional briefing on the appropriate remedy. While 
Bridgeport involves only FY 2020, the court's decision--which is not 
final at this time and is also subject to potential appeal--may have 
implications for FY 2023 payment rates. We are continuing to evaluate 
the court's decision, and although we are proposing for the low wage 
index hospital policy (and the related budget neutrality adjustment, 
proposed below) to continue for FY 2023, we may decide to take a 
different approach in the final rule, depending on public comments or 
developments in the court proceedings.
    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 2023 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 FYs 
2020, 2021, and 2022, as a uniform budget neutrality factor applied to 
the standardized amount. We refer readers to section II.A.4.f. of the 
addendum to this proposed rule for further discussion of the budget 
neutrality adjustment for FY 2023. For purposes of the low wage index 
hospital policy, based on the data for this proposed rule, the table 
displays the 25th percentile wage index value across all hospitals for 
FY 2023.
[GRAPHIC] [TIFF OMITTED] TP10MY22.155

H. Proposed FY 2023 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 2023 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 2023.

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). 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 through 56930), in which 
we finalized the April 21, 2016 IFC, 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).
    On May 10, 2021, we published an interim final rule with comment 
period

[[Page 28371]]

(IFC) in the Federal Register (86 FR 24735 through 24739) that included 
provisions amending our regulations to allow hospitals with a rural 
redesignation to reclassify through the MGCRB using the rural 
reclassified area as the geographic area in which the hospital is 
located. We revised our regulation so that the redesignated rural area, 
and not the hospital's geographic urban area, is considered the area a 
Sec.  412.103 hospital is located in for purposes of meeting MGCRB 
reclassification criteria, including the average hourly wage 
comparisons required by Sec.  412.230(a)(5)(i) and (d)(1)(iii)(C). 
Similarly, we revised the regulations to consider the redesignated 
rural area, and not the geographic urban area, as the area a Sec.  
412.103 hospital is located in for the prohibition at Sec.  
412.230(a)(5)(i) on reclassifying to an area with a pre-reclassified 
average hourly wage lower than the prereclassified average hourly wage 
for the area in which the hospital is located. Effective for 
reclassification applications due to the MGCRB for reclassification 
beginning in FY 2023, a Sec.  412.103 hospital could apply for a 
reclassification under the MGCRB using the state's rural area as the 
area in which the hospital is located. We refer readers to the May 10, 
2021 IFC (86 FR 24735 through 24739) and the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45187 through 45190), in which we finalized the May 
10, 2021 IFC, for a full discussion of these policies.
2. MGCRB Reclassification and Redesignation Issues for FY 2023
a. FY 2023 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 2023 reclassification requests. Based on 
such reviews, there are 491 hospitals approved for wage index 
reclassifications by the MGCRB starting in FY 2023. Because MGCRB wage 
index reclassifications are effective for 3 years, for FY 2023, 
hospitals reclassified beginning in FY 2021 or FY 2022 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 288 hospitals approved for wage index reclassifications in 
FY 2021 that will continue for FY 2023, and 304 hospitals approved for 
wage index reclassifications in FY 2022 that will continue for FY 2023. 
Of all the hospitals approved for reclassification for FY 2021, FY 2022 
and FY 2023, based upon the review at the time of the proposed rule, 
1,083 hospitals are in a MGCRB reclassification status for FY 2023 
(with 192 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).
    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 2023, the CBSAs assigned in the FY 2021 IPPS/LTCH 
final rule continue to be in effect.
    Applications for FY 2024 reclassifications are due to the MGCRB by 
September 1, 2022. We note that this is also the deadline for canceling 
a previous wage index reclassification withdrawal or termination under 
42 CFR 412.273(d). Applications and other information about MGCRB 
reclassifications may be obtained beginning in mid-July 2022, via the 
internet on the CMS website at https://www.cms.gov/Regulations/andGuidance/Review/Boards/MGCRB/index.html, or by calling the MGCRB at 
(410) 786-1174. This collection of information was previously approved 
under OMB Control Number 0938-0573 which expired on January 31, 2021. A 
reinstatement of this PRA package is currently being developed. The 
public will have an opportunity to review and submit comments regarding 
the reinstatement of this PRA package through a public notice and 
comment period separate from this rulemaking.
b. Clarification of Method for Submission Under Sec.  412.273
    The regulations at 42 CFR 412.273 set forth the procedures for 
withdrawing an MGCRB application, terminating an approved 3-year 
reclassification, or canceling a previous withdrawal or termination 
(also referred to as a reinstatement). The timing of such requests is 
specified at Sec.  412.273(c) for terminations and withdrawals and at 
paragraph (d)(2) for canceling a previous withdrawal or termination. 
However, the method of submission is not clearly specified in the 
regulations, other than the requirement that a request to cancel a 
previous withdrawal or termination (a reinstatement), or to withdraw an 
application or terminate an approved reclassification, be in writing 
according to Sec.  412.273(d)(2) and (e). It has come to our attention 
that this may be a source of confusion for hospital representatives 
seeking to submit such requests. It is possible that hospital 
representatives would attempt to send such requests to the MGCRB via 
mail, email, or fax, rather than in the manner that the MGCRB can most 
efficiently track and process.
    Beginning with applications from hospitals to reclassify for FY 
2020, the MGCRB requires applications, supporting documents, and 
subsequent correspondence to be filed electronically through the MGCRB 
module of the Office of Hearings Case and Document Management System 
(``OH CDMS''). The MGCRB issues all of its notices and decisions via 
email and these documents are accessible electronically through OH 
CDMS. Registration instructions and the system user manual are 
available at https://www.cms.gov/Regulations-and-Guidance/ReviewBoards/MGCRB/Electronic-Filing.html.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42313), we revised 
the regulations at Sec.  412.256(a)(1) to require

[[Page 28372]]

applications for reclassification to be submitted to the MGCRB 
according to the method prescribed by the MGCRB. However, the 
regulations at Sec.  412.273 for withdrawals, terminations, or 
cancelations of a previous withdrawal or termination (reinstatement) do 
not similarly specify a required manner of submission. Therefore, to 
eliminate potential confusion about how to submit withdrawal, 
termination, or cancelation (reinstatement) requests, we are proposing 
to align the regulations at Sec.  412.273 for withdrawal, termination, 
or cancelation (reinstatement) requests with the regulations at Sec.  
412.256 for new applications by specifying that withdrawal, 
termination, or cancelation (reinstatement) requests also must be 
submitted to the MGCRB according to the method prescribed by the MGCRB.
    Specifically, we are proposing to revise Sec.  412.273(d)(2) for 
timing and process of cancellation requests and Sec.  412.273(e) for 
withdrawal and termination requests. We are proposing to revise Sec.  
412.273(d)(2) to state that cancellation requests must be submitted in 
writing to the MGCRB according to the method prescribed by the MGCRB no 
later than the deadline for submitting reclassification applications 
for the following fiscal year, as specified in Sec.  412.256(a)(2). We 
are also proposing to revise Sec.  412.273(e) by adding that requests 
to withdraw an application or terminate an approved reclassification 
must be submitted in writing to the MGCRB according to the method 
prescribed by the MGCRB. We believe these proposed revisions to the 
regulations would eliminate potential confusion; align our policy for 
withdrawals, terminations, and cancelations (reinstatements) with our 
policy for applications; and ensure requests are submitted to the MGCRB 
through the method for submission that they can most efficiently 
process.
3. Redesignations Under Section 1886(d)(8)(B) of the Act (Lugar Status 
Determinations)
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51599 through 
51600), we adopted the policy that, beginning with FY 2012, an eligible 
hospital that waives its Lugar status in order to receive the out-
migration adjustment has effectively waived its deemed urban status 
and, thus, is rural for all purposes under the IPPS effective for the 
fiscal year in which the hospital receives the outmigration adjustment. 
In addition, in that rule, we adopted a minor procedural change that 
would allow a Lugar hospital that qualifies for and accepts the out-
migration adjustment (through written notification to CMS within 45 
days from the publication of the proposed rule) to waive its urban 
status for the full 3-year period for which its out-migration 
adjustment is effective. By doing so, such a Lugar hospital would no 
longer be required during the second and third years of eligibility for 
the out-migration adjustment to advise us annually that it prefers to 
continue being treated as rural and receive the out-migration 
adjustment. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56930), we 
further clarified that if a hospital wishes to reinstate its urban 
status for any fiscal year within this 3-year period, it must send a 
request to CMS within 45 days of publication of the proposed rule for 
that particular fiscal year. We indicated that such reinstatement 
requests may be sent electronically to [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 [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)

[[Page 28373]]

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 2023, 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 2023, 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 2023, 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 2023 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 2023 identified by FIPS county code, the proposed FY 
2023 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

    Under section 1886(d)(8)(E) of the Act, a qualifying prospective 
payment hospital located in an urban area may apply for rural status 
for payment purposes separate from reclassification through the MGCRB. 
Specifically, section 1886(d)(8)(E) of the Act provides that, not later 
than 60 days after the receipt of an application (in a form and manner 
determined by the Secretary) from a subsection (d) hospital that 
satisfies certain criteria, the Secretary shall treat the hospital as 
being located in the rural area (as defined in paragraph (2)(D)) of the 
State in which the hospital is located. We refer readers to the 
regulations at 42 CFR 412.103 for the general criteria and application 
requirements for a subsection (d) hospital to reclassify from urban to 
rural status in accordance with section 1886(d)(8)(E) of the Act. The 
FY 2012 IPPS/LTCH PPS final rule (76 FR 51595 through 51596) includes 
our policies regarding the effect of wage data from reclassified or 
redesignated hospitals. We refer readers to the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42332 through 42336) for a discussion on our current 
policy to calculate the rural floor without the wage data of urban 
hospitals reclassifying to rural areas under 42 CFR 412.103.
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41369 through 
41374), we codified certain policies regarding multicampus hospitals in 
the regulations at 42 CFR 412.92, 412.96, 412.103, and 412.108. We 
stated that reclassifications from urban to rural under 42 CFR 412.103 
apply to the entire hospital (that is, the main campus and its remote 
location(s)). We also stated that a main campus of a hospital cannot 
obtain an SCH, RRC, or MDH status, or rural reclassification under 42 
CFR 412.103, independently or separately from its remote location(s), 
and vice versa. However, we are aware that some urban hospitals operate 
one or more remote location(s) in a State's rural area. In light of 
this scenario, we wish to clarify that rural reclassification under 42 
CFR 412.103 applies to the main campus and any remote location located 
in an urban area. Under section 1886(d)(8)(E) of the Act, rural 
reclassification is available only to a hospital that is located in an 
urban area and satisfies the criteria specified in the statute. Thus, a 
remote location that is located in a rural area would not qualify for 
rural reclassification under section 1886(d)(8)(E) of the Act, as 
implemented under 42 CFR 412.103. We are proposing to add 42 CFR 
412.103(a)(8) to clarify that for a multicampus hospital, approved 
rural reclassification status applies to the main campus and any remote 
location located in an urban area, including a main campus or any 
remote location deemed urban under section 1886(d)(8)(B) of the Act.
    We are also aware that CMS has not consistently reflected the 
412.103 rural reclassification status in Table 2 of the annual IPPS/
LTCH PPS rulemaking for certain remote locations of hospitals that are 
located in a different CBSA than the main campus. If a remote location 
of a hospital is located in a different CBSA than the main campus of 
the hospital, it is CMS's longstanding policy to assign that remote 
location a wage index based on its own geographic area in order to 
comply with the statutory requirement to adjust for geographic 
differences in hospital wage levels (section 1886(d)(3)(E) of the Act). 
Hospitals are required to identify and allocate wages and hours based 
on FTEs for remote locations located in different CBSA on Worksheet S-
2, Part I, Lines 165 and 166 of form CMS-2552-10. In calculating wage 
index values, CMS identifies the allocated wage data for these remote 
locations in Table 2 with a ``B'' in the 3rd position of the CCN.
    As discussed previously, for a multicampus hospital, rural 
reclassification under 42 CFR 412.103 applies to the main campus and 
any remote location located in an urban area. The wage index 
implications of this policy are that, barring another form of wage 
index reclassification (for example, MGCRB reclassification), a main 
campus or remote location with approved 412.103 rural reclassification 
status would be assigned the rural wage index of its State. For FY 
2023, we will list the 412.103 rural reclassification status for remote 
locations (a remote location is listed with a ``B'' in the third digit 
of the CCN) in Table 2 of the appendix to the proposed rule. We note 
that, as of the date this proposed rule is issued, only one ``B'' 
location (36B020) would be assigned its State's rural wage index in FY 
2023 due to the 412.103 rural reclassification status of the main 
provider (360020). This location appears to have ceased inpatient 
activities, so we do not expect a negative financial impact for FY 
2023. However, hospitals with 412.103 rural reclassification status and 
a remote location in a different CBSA should evaluate potential wage 
index outcomes for its remote location(s) when withdrawing or 
terminating MGCRB reclassification, or canceling 412.103 rural 
reclassification status. For example, if a hospital with 412.103 rural 
reclassification status withdraws a separate active MGCRB 
reclassification for a remote location, that remote location may be 
assigned the State's rural wage index value, effective for FY 2023.

L. Process for Requests for Wage Index Data Corrections

1. Process for Hospitals To Request Wage Index Data Corrections
    The preliminary, unaudited Worksheet S-3 wage data files and the CY 
2019 occupational mix data files for the proposed FY 2023 wage index 
were

[[Page 28374]]

made available on May 24, 2021 through the internet on the CMS website 
at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page.
    On January 28, 2022, we posted a public use file (PUF) at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page containing FY 2023 wage index 
data available as of January 28, 2022. 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, 
2018 through September 30, 2019; that is, FY 2019 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 28, 2022 
wage data PUF, and a tab containing the CY 2019 occupational mix data 
of the hospitals deleted from the January 28, 2022 occupational mix 
PUF. In a memorandum dated January 20, 2022, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
January 28, 2022 wage index data PUFs, and the process and timeframe 
for requesting revisions in accordance with the FY 2023 Hospital Wage 
Index Development Time Table available at https://www.cms.gov/files/document/fy2023-wi-time-table.pdf.
    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 May 11, 2021, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
preliminary wage index data files and the CY 2019 occupational mix 
survey data files posted on May 24, 2021, and the process and timeframe 
for requesting revisions.
    If a hospital wished to request a change to its data as shown in 
the May 24, 2021, preliminary wage data files and occupational mix 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 2, 2021. 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. We note, CMS issued a waiver due to Hurricane Ida and modified 
the September 2, 2021, deadline specified in the FY 2023 Hospital Wage 
Index Development Time Table for certain hospitals. Specifically, CMS 
granted an extension until October 4, 2021, for hospitals in the States 
of Louisiana and Mississippi to request revisions to and provide 
documentation for their FY 2019 Worksheet S-3 wage data and CY 2019 
occupational mix data as included in the May 24, 2021 preliminary 
Public Use Files (PUFs), respectively. According to the waiver, MACs 
must receive the revision requests and supporting documentation by 
October 4, 2021. If hospitals encountered difficulty meeting the 
extended deadline, hospitals were to communicate their concerns to CMS 
via their MAC for CMS to consider an additional extension if CMS 
determined it was warranted. Details regarding this waiver are 
available on the CMS website at https://www.cms.gov/current-non-covid-emergencies, Additional IPPS Hospital Blanket Waivers (https://www.cms.gov/files/document/hurrican-ida-additional-ipps-hospital-blanket-waivers.pdf). November 15, 2021, 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 4, 2021, was the date by when MACs notified State hospital 
associations regarding hospitals that failed to respond to issues 
raised during the desk reviews. Additional revisions made by the MACs 
were transmitted to CMS throughout January 2022. CMS published the wage 
index PUFs that included hospitals' revised wage index data on January 
28, 2022. Hospitals had until February 15, 2022, to submit requests to 
the MACs to correct errors in the January 28, 2022 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 28, 
2022, 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 15, 2022, for the FY 2023 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 18, 2022. 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 1, 
2022. Data that were incorrect in the preliminary or January 28, 2022 
wage index data PUFs, but for which no correction request was received 
by the February 15, 2022 deadline, are not considered for correction at 
this stage. In addition, April 1, 2022, was the deadline for hospitals 
to dispute data corrections made by CMS of which the hospital was 
notified after the January 28, 2022, PUF and at least 14 calendar days 
prior to April 1, 2022 (that is, March 18, 2022), 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 1, 2022, for the 
FY 2023 wage index). We refer readers to the FY 2023 Hospital Wage 
Index Development Time Table 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-2023-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 2023 wage index which was constructed from FY 2019 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 2022.
    We plan to post the final wage index data PUFs in late April 2022 
on the CMS website at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page. 
The April 2022 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

[[Page 28375]]

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 18, 2022, 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 2022 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 18, 2022.
     Requests for correction of errors that were not, but could 
have been, identified during the hospital's review of the January 28, 
2022, 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 2022 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 
27, 2022. May 27, 2022, 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 1, 2022 (that is, March 19, 
2022), and at least 14 calendar days prior to May 27, 2022 (that is, 
May 13, 2022), 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 27, 2022 (that is, 
May 14, 2022), may be appealed to the Provider Reimbursement Review 
Board (PRRB)). In accordance with the FY 2023 Hospital Wage Index 
Development Time Table posted on the CMS website at https://www.cms.gov/files/document/fy2023-wi-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 FY 2023 Hospital Wage Index Development Time Table 
for complete details.
    Verified corrections to the wage index data received timely (that 
is, by May 27, 2022) by CMS and the MACs will be incorporated into the 
final FY 2023 wage index, which will be effective October 1, 2022.
    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 2023 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.
    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 2022, 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 2023 wage index by August 
2022, and the implementation of the FY 2023 wage index on October 1, 
2022. 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 27, 
2022, 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 27, 2022, for the FY 2023 
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 27, 2022, deadline for the 
FY 2023 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.

[[Page 28376]]

    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 27, 2022 deadline for the FY 2023 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 28 Public Use 
File (PUF)
    The process set forth with the wage index time table 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 28 PUF, and throughout the remainder of the 
wage index development process. In addition, the fact that CMS analyzes 
the data from a regional and even national level, unlike the review 
performed by the MACs that review a limited subset of hospitals, can 
facilitate additional editing of the data that may not be readily 
apparent to the MACs. In these occasional instances, an error may be of 
sufficient magnitude that the wage index of an entire CBSA is affected. 
Accordingly, CMS uses its authority to ensure that the wage index 
accurately reflects the relative hospital wage level in the geographic 
area of the hospital compared to the national average hospital wage 
level, by continuing to make corrections to hospital wage data upon 
discovering incorrect wage data, distinct from instances in which 
hospitals request data revisions.
    We note that CMS corrects errors to hospital wage data as 
appropriate, regardless of whether that correction will raise or lower 
a hospital's average hourly wage. For example, as discussed in section 
III.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41364), in situations where a hospital did not have documentable 
salaries, wages, and hours for housekeeping and dietary services, we 
imputed estimates, in accordance with policies established in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). Furthermore, 
if CMS discovers after conclusion of the desk review, for example, that 
a MAC inadvertently failed to incorporate positive adjustments 
resulting from a prior year's wage index appeal of a hospital's wage-
related costs such as pension, CMS would correct that data error and 
the hospital's average hourly wage would likely increase as a result.
    While we maintain CMS' authority to conduct additional review and 
make resulting corrections at any time during the wage index 
development process, in accordance with the policy finalized in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156) and as first 
implemented with the FY 2019 wage index (83 FR 41389), hospitals are 
able to request further review of a correction made by CMS that did not 
arise from a hospital's request for a wage index data correction. 
Instances where CMS makes a correction to a hospital's data after the 
January 28 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 28 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 2023 Hospital 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 2023 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

[[Page 28377]]

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 2022 IPPS/LTCH PPS final rule (86 FR 45194 through 
45208), we rebased and revised the hospital market basket. We 
established a 2018-based IPPS hospital market basket to replace the FY 
2014-based IPPS hospital market basket, effective October 1, 2021. 
Using the 2018-based IPPS market basket, we finalized a labor-related 
share of 67.6 percent for discharges occurring on or after October 1, 
2021. In addition, in FY 2022, we implemented this revised and rebased 
labor-related share in a budget neutral manner (86 FR 45193). 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.
    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. In the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45204 through 45207), we 
included in the labor-related share the national average proportion of 
operating costs that are attributable to the following cost categories 
in the 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. In this proposed rule, 
for FY 2023, we are not proposing to make any further changes to the 
labor-related share. For FY 2023, we are proposing to continue to use a 
labor-related share of 67.6 percent for discharges occurring on or 
after October 1, 2022.
    As discussed in section V.A. 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 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 2023, 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 2023 IPPS/LTCH PPS proposed rule and available via 
the internet on the CMS website, reflect the proposed national labor-
related share. Table 1C, in section VI. of the Addendum to this FY 2023 
IPPS/LTCH PPS proposed rule and available via the internet on the CMS 
website, reflects the proposed national labor-related share for 
hospitals located in Puerto Rico. For FY 2023, 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 2023, we are proposing to apply the wage 
index to a proposed labor-related share of 67.6 percent of the national 
standardized amount.

N. Proposed Permanent Cap on Wage Index Decreases

1. Proposed Permanent Cap Policy for the Wage Index
    In the FY 2020 IPPS/LTCH PPS final rule, CMS implemented a 
transition policy for FY 2020 to place a 5 percent cap on any decrease 
in a hospital's wage index from the hospital's final wage index in FY 
2019 so that a hospital's final wage index for FY 2020 will not be less 
than 95 percent of its final wage index for FY 2019 (84 FR 42336 
through 42337). We implemented this transition due to the combined 
effect of the policy changes for the FY 2020 wage index (including 
policies to address wage index disparities between high and low wage 
index hospitals), which we believed could lead to significant decreases 
in the wage index values for some hospitals. We stated that this 
transition would allow the effects of our proposed policies to be 
phased in over 2 years with no estimated reduction in the wage index of 
more than 5 percent in FY 2020 (that is, no cap would be applied the 
second year). We also stated that we believed 5 percent is a reasonable 
level for the cap because it would effectively mitigate any significant 
decreases in the wage index for FY 2020. We applied a budget neutrality 
adjustment factor to the FY 2020 standardized amount for all hospitals 
to achieve budget neutrality for the transition policy (84 FR 42337 
through 42338).
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58753 through 
58755), to mitigate the effect of our adoption of the revised OMB 
delineations in OMB Bulletin 18-04, we implemented for FY 2021 the same 
5 percent cap transition policy that we had implemented for FY 2020. 
Specifically, we placed a 5 percent cap 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 will not be less than 95 
percent of its final wage index for FY 2020. We stated that for FY 
2021, we did not believe it was necessary to implement the multifaceted 
transitions (including a 1-year blended wage index) we established in 
FY 2015 for the adoption of the new OMB delineations based on the new 
decennial census data. The 5 percent cap transition policy resulted in 
some hospitals receiving a transition adjustment that were not directly 
affected by the adoption of the revised OMB delineations (85 FR 58754). 
We applied a budget neutrality adjustment to the FY 2021 standardized 
amount to achieve budget neutrality for the transition policy (85 FR 
58755).

[[Page 28378]]

    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25397), given the 
unprecedented nature of the ongoing COVID-19 PHE, we solicited comments 
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. We received several 
comments strongly recommending CMS extend a transition policy similar 
to that implemented in FY 2020 and FY 2021. Commenters also recommended 
CMS consider making a permanent 5 percent maximum reduction policy to 
protect hospitals from large year-to-year variations in wage index 
values as a means to reduce overall volatility. While we did not adopt 
the commenters' suggestion for a permanent 5 percent cap policy, we did 
finalize a transition policy for FY 2022 in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45164). Specifically, for hospitals that received the 
transition in FY 2021, we continued a wage index transition for FY 2022 
under which we apply a 5 percent cap on any decrease in the hospital's 
wage index compared to its wage index for FY 2021 to mitigate 
significant negative impacts of, and provide additional time for 
hospitals to adapt to, the CMS decision to adopt the revised OMB 
delineations. We applied a budget neutrality adjustment to the FY 2022 
standardized amount so that the transition is implemented in a budget 
neutral manner (86 FR 45165).
    For FY 2023 and subsequent years, we have further considered the 
comments we received during the FY 2022 rulemaking recommending a 
permanent 5 percent cap policy to prevent large year-to-year variations 
in wage index values as a means to reduce overall volatility for 
hospitals. In the past, we have established temporary transition 
policies (as described above) when there have been significant changes 
to wage index policy, and we have limited the duration of each 
transition in order to phase in the effects of those policy changes. In 
taking this temporary approach in the past, we have sought to mitigate 
short-term instability and fluctuations that can negatively impact 
hospitals. We also recognize that, absent any specific change in wage 
index policy, significant year-to-year fluctuations in an area's wage 
index can occur due to external factors beyond a hospital's control, 
such as the COVID-19 PHE. For an individual hospital, these 
fluctuations can be difficult to predict. We recognize that 
predictability in Medicare payments is important to enable hospitals to 
budget and plan their operations.
    In light of these considerations, we are proposing a permanent 
approach to smooth year-to-year decreases in hospitals' wage indexes. 
We are proposing a policy that we believe increases the predictability 
of IPPS payments for hospitals and mitigates instability and 
significant negative impacts to hospitals resulting from changes to the 
wage index. We also believe our proposed permanent policy would 
eliminate the need for temporary and potentially uncertain transition 
adjustments to the wage index in the future due to specific policy 
changes or circumstances outside hospitals' control (for example, in 
the event we adopt any future OMB revisions to the CBSA delineations). 
As a result of this proposed policy, an otherwise rare but relatively 
large year-to-year decrease in the wage index value for an individual 
hospital would be phased in, providing the hospital with additional 
time to plan appropriately and explore potential reclassification 
options, if applicable. For example, if a change in OMB delineations 
resulted in a hospital's wage index decreasing by more than 10 percent 
in any given year, this proposed policy could provide at least one 
additional year to phase in the decrease beyond a single ``transition'' 
year methodology, such as the transition policy finalized in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49957 through 49962).
    Typical year-to-year variation in the wage index has historically 
been within 5 percent, and we expect this will continue to be the case 
in future years. Because hospitals are usually experienced with this 
level of wage index fluctuation, we believe applying a 5-percent cap on 
all wage index decreases each year, regardless of the reason for the 
decrease, would effectively mitigate instability in IPPS payments due 
to any significant wage index decreases that may affect hospitals in a 
year. In addition, we believe that the predictability resulting from a 
5 percent cap on all wage index decreases would enable hospitals to 
more effectively budget and plan their operations. Because applying a 
5-percent cap on all wage index decreases would represent a small 
overall impact on the labor market area wage index system, we believe 
it would ensure the wage index is a relative measure of the value of 
labor in prescribed labor market areas. We estimate that applying a 5-
percent cap on all wage index decreases would have a very small effect 
on the proposed budget neutrality factor associated with the proposed 
cap applied to the standardized amount for FY 2023 (discussed in 
section III.N.2 of the preamble of this proposed rule). Because the 
wage index is a measure of the value of labor (wage and wage-related 
costs) in a prescribed labor market area relative to the national 
average, we anticipate that in the absence of proposed policy changes 
most hospitals will not experience year-to-year wage index declines 
greater than 5 percent in any given year. Therefore, we anticipate that 
the impact to the proposed budget neutrality factor associated with the 
proposed cap in future years would continue to be minimal. We also 
believe that when the 5-percent cap would be applied under this 
proposal, in general it is likely that it would be applied similarly to 
all hospitals in the same labor market area, as the hospital average 
hourly wage data in the CBSA (and any relative decreases compared to 
the national average hourly wage) would be similar. While in certain 
circumstances this policy may result in some hospitals in a CBSA 
receiving a higher wage index than others in the same area, we believe 
the impact would be temporary.
    For the reasons discussed in this section, we believe a 5-percent 
cap on wage index decreases would be appropriate for the IPPS. 
Therefore, for FY 2023 and subsequent years, we are proposing to apply 
a 5-percent cap on any decrease to a hospital's wage index from its 
wage index in the prior FY, regardless of the circumstances causing the 
decline. That is, we are proposing that a hospital's wage index for FY 
2023 would not be less than 95 percent of its final wage index for FY 
2022, and that for subsequent years, a hospital's wage index would not 
be less than 95 percent of its final wage index for the prior FY. This 
also means that if a hospital's prior FY wage index is calculated with 
the application of the 5-percent cap, the following year's wage index 
would not be less than 95 percent of the hospital's capped wage index 
in the prior FY. For example, if a hospital's wage index for FY 2023 is 
calculated with the application of the 5-percent cap, then its wage 
index for FY 2024 would not be less than 95 percent of its capped wage 
index in FY 2023. We would reflect the proposed wage index cap policy 
at 42 CFR 412.64(h). Specifically, we are proposing to add a new 
paragraph at 42 CFR 412.64(h)(7) to state that beginning with fiscal 
year 2023, if CMS determines that a hospital's wage index value for a 
fiscal year would decrease by more than 5 percent as compared to the 
hospital's wage index value for the prior fiscal year, CMS limits the 
decrease to 5 percent for the fiscal year.

[[Page 28379]]

    We have authority to implement this proposed wage index cap policy 
and the associated proposed budget neutrality adjustment (discussed 
below in section III.N.2. of the preamble of this proposed rule) under 
section 1886(d)(3)(E) of the Act, which gives the Secretary broad 
authority to adjust 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, and requires those adjustments to 
be budget neutral. In addition, we have authority to implement this 
proposed wage index cap policy and the associated proposed budget 
neutrality adjustment (discussed below in section III.N.2. of the 
preamble of this proposed rule) as an adjustment under section 
1886(d)(5)(I)(i) of the Act, which similarly gives the Secretary broad 
authority to provide by regulation for such other exceptions and 
adjustments to such payment amounts under subsection (d) as the 
Secretary deems appropriate.
    We are proposing to apply the proposed wage index cap policy 
described above for a FY using the final wage index applicable to the 
hospital on the last day of the prior FY (except for newly opened 
hospitals, as discussed below). In general, the final wage index 
applicable to the hospital on the last day of the prior FY would be the 
wage index value listed for the hospital in Table 2 of the IPPS/LTCH 
PPS final rule for that prior FY (including any correction notices, if 
applicable). In rulemaking for a FY, we intend to relist the wage index 
values from Table 2 of the IPPS/LTCH PPS final rule for the prior FY, 
with updates as described below. Under the proposed wage index cap 
policy described above, we would use these values to determine a 
hospital's wage index for a FY by capping it at 95 percent of the final 
wage index applicable to the hospital on the last day of the prior FY 
(in general, the wage index value listed for the hospital in Table 2 of 
the IPPS/LTCH PPS final rule for the prior FY). We note, consistent 
with our past application of the 5 percent cap transition policy (see 
the FY 2020 IPPS/LTCH PPS final rule (84 FR 42337)), the proposed wage 
index cap policy described above would apply to hospitals whose wage 
index is reduced by obtaining a urban to rural reclassification under 
42 CFR 412.103. Specifically, a hospital that obtains a rural 
reclassification under 42 CFR 412.103 may be assigned its State's rural 
wage index.\601\ While other forms of wage index reclassification are 
effective with the start of a Federal fiscal year, pursuant to 42 CFR 
412.103(d)(1), the effective date of an approved rural reclassification 
is the filing date of the application. Therefore, the wage index values 
for hospitals that obtain rural reclassification under 42 CFR 412.103 
may change in the middle of a Federal fiscal year and thus may not be 
reflected in Table 2 of the IPPS/LTCH PPS final rule for that year. For 
example, if a hospital was assigned its geographic wage index of 1.0001 
in Table 2 of the FY 2022 IPPS/LTCH PPS final rule, but obtained a 
rural reclassification on December 1, 2021 and was assigned its state's 
rural wage index of 0.9600 for the remainder of FY 2022; the FY 2023 
cap would be based on the 0.9600 value, not the 1.0001 value listed in 
Table 2 of the FY 2022 IPPS/LTCH PPS final rule. As in previous years, 
we would instruct hospitals that obtain a rural reclassification under 
42 CFR 412.103 to contact their MAC to ensure that their assigned wage 
index does not result in a greater than 5 percent decrease from the 
hospital's prior year wage index value (see the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42337) and the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58754)).
---------------------------------------------------------------------------

    \601\ As discussed in the FY 2016 IFC (81 FR 23428 through 
23438), hospitals with simultaneous reclassifications under 412.103 
and either Lugar or MGCRB reclassification process are not assigned 
their State's rural wage index.
---------------------------------------------------------------------------

    In Table 2 associated with this proposed rule, which is available 
via the internet on the CMS website, we list the FY 2022 final wage 
index value for all hospitals in column C. For additional clarity, we 
have identified hospitals that have obtained rural reclassification 
after the FY 2022 lock-in date, as described in 42 CFR 412.103(b)(6), 
and that were assigned a different wage index than what was listed in 
Table 2 associated with the FY 2022 IPPS/LTCH PPS correction notice 
(available on the internet at https://www.cms.gov/files/zip/fy-2022-ipps-fr-tables-2-3-4a-4b.zip). In Table 2 associated with this proposed 
rule, the FY 2022 wage index column for these hospitals will not use 
the values listed in Table 2 associated with the FY 2022 IPPS/LTCH PPS 
correction notice (available on the internet at https://www.cms.gov/files/zip/fy-2022-ipps-fr-tables-2-3-4a-4b.zip), but will instead be 
updated with the wage index value that is currently assigned to the 
hospitals. Under our proposal described above, we would apply the 
proposed wage index cap using the actual final wage index value 
assigned to the hospital on the last day of the prior Federal fiscal 
year rather than the value listed in Table 2 of the prior FY final 
rule. We are providing a supplemental data file (posted on the FY 2023 
proposed rule web page at https://www.cms.gov/medicare/medicare-fee-
for-service-payment/acuteinpatientpps) which lists all hospitals that 
have obtained rural reclassification under 42 CFR 412.103 after the FY 
2022 lock-in date and that have no other form of wage index 
reclassification applicable to them at this time. This list will be 
revised for the final rule to add additional hospitals without another 
form of reclassification that obtain rural reclassification under 42 
CFR 412.103 before the FY 2023 lock-in date as described in 42 CFR 
412.103(b)(6).
    Hospitals that obtain rural reclassification after the FY 2023 
lock-in date will not be listed as being reclassified as rural in the 
FY 2023 IPPS/LTCH PPS final rule. If we finalize the proposed wage 
index cap policy described above, these hospitals should contact their 
MAC to ensure that the assigned rural wage index value is not less than 
95 percent of their final wage index value for FY 2022 (that is, the 
wage index assigned to the hospital as of September 30, 2022).
    For newly opened hospitals, we propose to apply the proposed wage 
index cap policy described previously for a FY using the wage index 
value the hospital was assigned for the prior FY. A new hospital would 
be paid the wage index for the area in which it is geographically 
located for its first full or partial fiscal year, and it would not 
receive a cap for that first year because it would not have been 
assigned a wage index in the prior year. Also, it is possible a new 
hospital may not be listed in Table 2 for several years since the 
hospitals listed in Table 2 are based on historical data. If we 
finalize the proposed wage index cap policy described above, a new 
hospital may contact their MAC to ensure that their assigned wage index 
value for the upcoming FY is not less than 95 percent of the value 
assigned to them for the prior Federal fiscal year. For example, if a 
hospital begins operations on July 1, 2022, and is assigned its area 
wage index of 0.9000 for the remainder of FY 2022, its FY 2023 wage 
index would be capped at 95 percent of that value, and could not be 
lower than 0.8550 (0.95 x 0.9000) regardless of whether it was listed 
in Table 2 in the FY 2022 IPPS/LTCH PPS final rule. A hospital that 
opens on December 1, 2022 would not be eligible for a capped wage index 
in FY 2023, as it was not assigned a wage index during FY 2022.We 
finally note

[[Page 28380]]

that if we adopt these proposals as final policy, we would examine the 
effects of the policy on an ongoing basis in the future in order to 
assess whether it effectively and appropriately accomplishes the goal 
of increasing predictability and stability in IPPS payments.
2. Proposed Permanent Cap Budget Neutrality
    We are proposing to implement the proposed wage index cap policy 
(discussed above in section III.N.1 of the preamble of this proposed 
rule) in a budget neutral manner through a national adjustment to the 
standardized amount each fiscal year as we have implemented similar 
past transition policies involving a cap on wage index decreases (for 
example, see the FY 2021 IPPS/LTCH PPS final rule (85 FR 58755) and the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45164 through 45165)). We 
believe application of the proposed wage index cap policy should not 
increase estimated aggregate Medicare payments beyond the payments that 
would be made had we never applied the cap.
    Specifically, we are proposing to apply a budget neutrality 
adjustment to ensure that estimated aggregate payments under our 
proposed wage index cap policy for hospitals that would have a decrease 
in their wage indexes for the upcoming fiscal year of more than 5 
percent would equal what estimated aggregate payments would have been 
without the proposed wage index cap policy. To determine the proposed 
associated budget neutrality factor, we compare estimated aggregate 
IPPS payments with and without the proposed wage index cap policy. As 
discussed above in section III.N.1 of the preamble of this proposed 
rule, we have authority to implement this proposed budget neutrality 
adjustment under sections 1886(d)(3)(E) and (d)(5)(I)(i) of the Act. We 
note that the proposed budget neutrality adjustment would be updated, 
as appropriate, based on the final rule data. We refer readers to the 
Addendum of this proposed rule for further information regarding the 
proposed budget neutrality calculations.

IV. Proposed Payment Adjustment for Medicare Disproportionate Share 
Hospitals (DSHs) for FY 2023 (Sec.  412.106)

A. General Discussion

    Section 1886(d)(5)(F) of the Act provides for additional Medicare 
payments to subsection (d) hospitals that serve a significantly 
disproportionate number of low-income patients. The Act specifies two 
methods by which a hospital may qualify for the Medicare 
disproportionate share hospital (DSH) adjustment. Under the first 
method, hospitals that are located in an urban area and have 100 or 
more beds may receive a Medicare DSH payment adjustment if the hospital 
can demonstrate that, during its cost reporting period, more than 30 
percent of its net inpatient care revenues are derived from State and 
local government payments for care furnished to patients with low 
incomes. This method is commonly referred to as the ``Pickle method.'' 
The second method for qualifying for the DSH payment adjustment, which 
is the most common, is based on a complex statutory formula under which 
the DSH payment adjustment is based on the hospital's geographic 
designation, the number of beds in the hospital, and the level of the 
hospital's disproportionate patient percentage (DPP). A hospital's DPP 
is the sum of two fractions: The ``Medicare fraction'' and the 
``Medicaid fraction.'' The Medicare fraction (also known as the ``SSI 
fraction'' or ``SSI ratio'') is computed by dividing the number of the 
hospital's inpatient days that are furnished to patients who were 
entitled to both Medicare Part A and Supplemental Security Income (SSI) 
benefits by the hospital's total number of patient days furnished to 
patients entitled to benefits under Medicare Part A. The Medicaid 
fraction is computed by dividing the hospital's number of inpatient 
days furnished to patients who, for such days, were eligible for 
Medicaid, but were not entitled to benefits under Medicare Part A, by 
the hospital's total number of inpatient days in the same period.
    Because the DSH payment adjustment is part of the IPPS, the 
statutory references to ``days'' in section 1886(d)(5)(F) of the Act 
have been interpreted to apply only to hospital acute care inpatient 
days. Regulations located at 42 CFR 412.106 govern the Medicare DSH 
payment adjustment and specify how the DPP is calculated as well as how 
beds and patient days are counted in determining the Medicare DSH 
payment adjustment. Under Sec.  412.106(a)(1)(i), the number of beds 
for the Medicare DSH payment adjustment is determined in accordance 
with bed counting rules for the IME adjustment under Sec.  412.105(b).
    Section 3133 of the Patient Protection and Affordable Care Act, as 
amended by section 10316 of the same Act and section 1104 of the Health 
Care and Education Reconciliation Act (Pub. L. 111-152), added a 
section 1886(r) to the Act that modifies the methodology for computing 
the Medicare DSH payment adjustment. (For purposes of this 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

[[Page 28381]]

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 was established 
through the exercise of the Secretary's discretion in implementing the 
capital IPPS under section 1886(g)(1)(A) of the Act.
    Finally, section 1886(r)(3) of the Act provides that there shall be 
no administrative or judicial review under section 1869, section 1878, 
or otherwise of any estimate of the Secretary for purposes of 
determining the factors described in section 1886(r)(2) of the Act or 
of any period selected by the Secretary for the purpose of determining 
those factors. Therefore, there is no administrative or judicial review 
of the estimates developed for purposes of applying the three factors 
used to determine uncompensated care payments, or the periods selected 
in order to develop such estimates.

B. 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). For this proposed rule, we estimated DSH status for all 
hospitals using the most recent available SSI ratios and information 
from the most recent available Provider Specific File. We note FY 2019 
SSI ratios available on the CMS website are the most recent available 
SSI ratios at the time of developing this proposed rule. If more recent 
data on DSH eligibility become available before the final rule, then we 
would use such data in the final rule. Our final determination on a 
hospital's eligibility for uncompensated care payments will be based on 
the hospital's actual DSH status at cost report settlement for that 
payment year.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and in the 
rulemaking for subsequent fiscal years, we have specified our policies 
for several specific classes of hospitals within the scope of section 
1886(r) of the Act. In this FY 2023 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 2023 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 2023, 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

[[Page 28382]]

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 interim empirically justified Medicare DSH and interim 
uncompensated care payments as we do for all other IPPS hospitals.
    We note that there has not been legislation at the time of 
development of this proposed rule that would extend the MDH program 
beyond September 30, 2022. However, if the MDH program were to be 
extended beyond its current expiration date, similar to how it was 
extended under the Bipartisan Budget Act of 2018, we would continue to 
make a determination concerning an MDH's eligibility for interim 
uncompensated care payments based on the hospital's estimated DSH 
status for the applicable 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. The BPCI Advanced Model's 
final performance year will end on December 31, 2023. For further 
information regarding the BPCI Advanced model, we refer readers to the 
CMS website at https://innovation.cms.gov/initiatives/bpci-advanced/.
     IPPS hospitals that participate in the Comprehensive Care 
for Joint Replacement Model (80 FR 73300) continue to be paid under the 
IPPS and, therefore, are eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments. 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). In that interim final rule, we 
extended the Model's Performance Year 5 to September 30, 2021. In a 
subsequent final rule that appeared in the May 3, 2021 Federal Register 
(86 FR 23496), we further extended the Model for an additional three 
performance years. The Model's Performance Year 8 will end on December 
31, 2024.
     Hospitals participating in the Rural Community Hospital 
Demonstration Program are not eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments under section 
1886(r) of the Act because they are not paid under the IPPS (78 FR 
50625 and 79 FR 50008). The Rural Community Hospital Demonstration 
Program was originally authorized for a 5-year period by section 410A 
of the Medicare Prescription Drug, Improvement, and Modernization Act 
of 2003 (MMA) (Pub. L. 108-173), and extended for another 5-year period 
by sections 3123 and 10313 of the Affordable Care Act (Pub. L. 114-
255). The period of performance for this 5-year extension period ended 
December 31, 2016. Section 15003 of the 21st Century Cures Act (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 period of performance for 
this 5-year extension period ended December 31, 2021. The Consolidated 
Appropriations Act, 2021 (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. The period of participation 
for the last hospital in the demonstration under this most recent 
legislative authorization would extend until June 30, 2028, as outlined 
in section V.K. of the preamble of this proposed rule. 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. 
At the time of development of this proposed rule, we believe 26 
hospitals may participate in the demonstration program at the start of 
FY 2023.

C. 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 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 https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2014-Transmittals-Items/R5P240.html.

D. 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

[[Page 28383]]

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 the preamble of 
this proposed rule, we discuss the data sources and methodologies for 
computing each of these factors, our final policies for FYs 2014 
through 2022, and our proposed policies for FY 2023.
1. Proposed Calculation of Factor 1 for FY 2023
    Section 1886(r)(2)(A) of the Act establishes Factor 1 in the 
calculation of the uncompensated care payment. Section 1886(r)(2)(A) of 
the Act states that this factor is equal to the difference between: (1) 
The aggregate amount of payments that would be made to subsection (d) 
hospitals under section 1886(d)(5)(F) of the Act if section 1886(r) of 
the Act did not apply for such fiscal year (as estimated by the 
Secretary); and (2) the aggregate amount of payments that are made to 
subsection (d) hospitals under section 1886(r)(1) of the Act for such 
fiscal year (as so estimated). Therefore, section 1886(r)(2)(A)(i) of 
the Act represents the estimated Medicare DSH payments that would have 
been made under section 1886(d)(5)(F) of the Act if section 1886(r) of 
the Act did not apply for such fiscal year. Under a prospective payment 
system, we would not know the precise aggregate Medicare DSH payment 
amount that would be paid for a Federal fiscal year until cost report 
settlement for all IPPS hospitals is completed, which occurs several 
years after the end of the Federal fiscal year. Therefore, section 
1886(r)(2)(A)(i) of the Act provides authority to estimate this amount, 
by specifying that, for each fiscal year to which the provision 
applies, such amount is to be estimated by the Secretary. Similarly, 
section 1886(r)(2)(A)(ii) of the Act represents the estimated 
empirically justified Medicare DSH payments to be made in a fiscal 
year, as prescribed under section 1886(r)(1) of the Act. Again, section 
1886(r)(2)(A)(ii) of the Act provides authority to estimate this 
amount. Therefore, Factor 1 is the difference between our estimates of: 
(1) The amount that would have been paid in Medicare DSH payments for 
the fiscal year, in the absence of the new payment provision; and (2) 
the amount of empirically justified Medicare DSH payments that are made 
for the fiscal year, which takes into account the requirement to pay 25 
percent of what would have otherwise been paid under section 
1886(d)(5)(F) of the Act. In other words, this factor represents our 
estimate of 75 percent (100 percent minus 25 percent) of our estimate 
of Medicare DSH payments that would otherwise be made, in the absence 
of section 1886(r) of the Act, for the fiscal year.
    In this FY 2023 IPPS/LTCH PPS proposed rule, in order to determine 
Factor 1 in the uncompensated care payment formula for FY 2023, we are 
proposing to continue the policy established in the FY 2014 IPPS/LTCH 
PPS final rule (78 FR 50628 through 50630) and in the FY 2014 IPPS 
interim final rule with comment period (78 FR 61194) of determining 
Factor 1 by developing estimates of both the aggregate amount of 
Medicare DSH payments that would be made in the absence of section 
1886(r)(1) of the Act and the aggregate amount of empirically justified 
Medicare DSH payments to hospitals under section 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 2023 IPPS/LTCH PPS final rule.
    Therefore, in order to determine the two elements of proposed 
Factor 1 for FY 2023 (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 
2020 through FY 2023 are discussed in the table titled ``Factors 
Applied for FY 2020 through FY 2023 to Estimate Medicare DSH 
Expenditures Using FY 2019 Baseline.''
    For purposes of calculating Factor 1 and modeling the impact of 
this FY 2023 IPPS/LTCH PPS proposed rule, we used the Office of the 
Actuary's January 2022 Medicare DSH estimates, which were based on data 
from the September 2021 update of the Medicare Hospital Cost Report 
Information System (HCRIS) and the FY 2022 IPPS/LTCH PPS final rule 
IPPS Impact File, published in conjunction with the publication of the 
FY 2022 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 2022 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 2022 Medicare DSH estimates. The 26 hospitals 
that are anticipated to participate in the Rural Community Hospital 
Demonstration Program in FY 2023 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 uncompensated 
care payments.
    For this proposed rule, using the data sources as previously 
discussed, the Office of the Actuary's January 2022 estimate of 
Medicare DSH payments for FY 2023 without regard to the application of 
section 1886(r)(1) of the Act, is approximately $13.266 billion. 
Therefore, also based on the January 2022 estimate, the estimate of 
empirically justified Medicare DSH payments for FY 2023, with the 
application of section 1886(r)(1) of the Act, is approximately $3.316 
billion (or 25 percent of the total amount of estimated Medicare DSH 
payments for FY 2023). Under Sec.  412.106(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 2023 would 
be $9,949,258,556.56, which is equal to 75 percent of the total amount 
of estimated Medicare DSH payments for FY 2023 ($13,266 million minus 
$3,316 million). 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 2023 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

[[Page 28384]]

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 ``2021 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 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 the 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 2023 for this proposed 
rule began with a baseline of $13.808 billion in Medicare DSH 
expenditures for FY 2019. The following table shows the factors applied 
to update this baseline through the current estimate for FY 2023:
[GRAPHIC] [TIFF OMITTED] TP10MY22.156

    In this table, the discharges column shows the changes in the 
number of Medicare fee-for-service (FFS) inpatient hospital discharges. 
The discharge figures for FY 2020 and FY 2021 are based on Medicare 
claims data that have been adjusted by a completion factor to account 
for incomplete claims data. We note that these claims include the 
impact of the pandemic. The discharge figure for FY 2022 is based on 
preliminary data. The discharge figure for FY 2023 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 
2023 reflect the actual impact and estimated future 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 2020 and FY 
2021 are based on actual claims data adjusted by a completion factor. 
We note that these claims include the impact of the pandemic. The case-
mix figure for FY 2022 is based on preliminary data. The case-mix 
factor figures for FY 2020 to FY 2023 reflect the actual impact and 
estimated future impact of the COVID-19 pandemic. 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 
2021-2023 and approximately 75 percent in 2024 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

[[Page 28385]]

most recent available data, Medicaid enrollment is estimated to change 
as follows: 2.0 percent in FY 2020, 9.5 percent in FY 2021, 4.2 percent 
in FY 2022, and -5.7 percent in FY 2023.
    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/Researc/Statistics/Data/and/Systems/Research/ActuarialStudies/MedicaidReport. 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 at the time of developing this proposed rule, the 
OACT assumed per capita spending for Medicaid beneficiaries who 
enrolled due to the expansion to be 80 percent of the average per 
capita expenditures for a pre-expansion Medicaid beneficiary due to the 
better health of these beneficiaries. The 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. In the future, the assumption about the average per-
capita expenditures of Medicaid beneficiaries who enrolled due to the 
COVID-19 pandemic may change, given that the pandemic is ongoing.
    The following table shows the factors that are included in the 
``Update'' column of the previous table:
[GRAPHIC] [TIFF OMITTED] TP10MY22.157

2. Calculation of Proposed Factor 2 for FY 2023
(a) 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. We are proposing to use a methodology 
similar to the one that was used in FY 2018 through FY 2022 to 
determine Factor 2 for FY 2023.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38197 and 38198), we 
explained that we determined the data source for the rate of 
uninsurance that, on balance, best meets all of our considerations and 
is consistent with the statutory requirement that the estimate of the 
rate of uninsurance be based on data from the Census Bureau or other 
sources the Secretary determines appropriate 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. We note that the NHEA estimates of uninsurance 
are for the total resident-based U.S. population, including all people 
who usually reside in the 50 States or the District of Columbia, but 
excluding individuals 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 the U.S., plus a 
small (typically less that 0.2 percent of population) adjustment to 
reflect Census undercounts. Thus, the NHEA estimates of uninsurance are 
for U.S. residents of all ages and are not limited to a specific age 
cohort, such as the population under the age of 65. As we explained in 
the FY 2018 IPPS/

[[Page 28386]]

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 U.S. that influence uncompensated care for hospitals than an 
estimate that reflects only legal residents.
    The NHEA includes comprehensive enrollment estimates for total 
private health insurance (PHI) (including direct and employer-sponsored 
plans), Medicare, Medicaid, the Children's Health Insurance Program 
(CHIP), and other public programs, and estimates of the number of 
individuals who are uninsured. Estimates of total PHI enrollment are 
available for 1960 through 2020, 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 2020. 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 https://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 
2018, OACT extrapolates from the 2009 CPS data through 2018 using data 
from the National Health Interview Survey (NHIS). 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). The 2019 estimate was extrapolated using the 2019/
2018 trend from the American Community Survey (ACS). The 2020 estimate 
was extrapolated using the 2020/2018 trend from the CPS as published by 
the Census Bureau. The U.S. Census Bureau is the data collection agent 
for the NHIS, the ACS, and the CPS. 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/
. For information regarding the data collection issues regarding the 
2020 ACS, we refer readers to the Census Bureau's website at https://www.census.gov/newsroom/blogs/random-samplings/2021/10/pandemic-impact-on-2020-acs-1-year-data.html. Since the 2020 ACS data were not 
available, the ACS data were not used for purposes of estimating the 
number of uninsured individuals for 2020.
    The next metrics needed to compute Factor 2 for FY 2023 are 
projections of the rate of uninsurance in both CY 2022 and CY 2023. On 
an annual basis, OACT projects enrollment and spending trends for the 
coming 10-year period. The most recent projections are for 2021 through 
2030. 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 and 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.
(b) Proposed Factor 2 for FY 2023
    Using these data sources and the previously described 
methodologies, OACT estimated that the uninsured rate for the 
historical, baseline year of 2013 was 14 percent and for CYs 2022 and 
2023 is 8.9 percent and 9.3 percent, respectively. As required by 
section 1886(r)(2)(B)(ii) of the Act, the Chief Actuary of CMS has 
certified these estimates. We refer readers to OACT's Memorandum on 
Certification of Rates of Uninsured prepared for this FY 2023 IPPS/LTCH 
PPS proposed rule for further details on the methodology and 
assumptions that were used in the projection of these rates of 
uninsurance.\602\
---------------------------------------------------------------------------

    \602\ OACT Memorandum on Certification of Rates of Uninsured. 
March 28, 2022. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInPatientPPS/dsh.html.
---------------------------------------------------------------------------

    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 2023.
    The OACT has certified the estimate of the rate of uninsurance for 
FY 2023 determined using this weighted average approach to be 
reasonable and appropriate for purposes of section 1886(r)(2)(B)(ii) of 
the Act. We note that 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 2023.
    The calculation of the proposed Factor 2 for FY 2023 is as follows:
    Percent of individuals without insurance for CY 2013: 14 percent.
    Percent of individuals without insurance for CY 2022: 8.9 percent.
    Percent of individuals without insurance for CY 2023: 9.3 percent.

[[Page 28387]]

    Percent of individuals without insurance for FY 2023 (0.25 times 
0.089) + (0.75 times 0.093): 9.2 percent.

1-[verbar]((0.092-0.14)/0.14)[verbar] = 1-0.3429 = 0.6571 (65.71 
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 2023 would be 65.71 percent.
    The proposed FY 2023 uncompensated care amount is equivalent to 
this proposed rule's Factor 1 multiplied by this proposed rule's Factor 
2, which is $9,949,258,556.56 * 0.6571 = $6,537,657,797.52.
[GRAPHIC] [TIFF OMITTED] TP10MY22.158

    In addition, it has recently come to our attention that the 
provision of the regulations that addresses Factor 2 inadvertently 
omits any reference to the statutory methodology in section 
1886(r)(2)(B)(ii) of the Act for determining Factor 2 for FY 2018 and 
subsequent fiscal years. Accordingly, we are proposing a technical 
change to the regulation at Sec.  412.106 to update paragraph 
(g)(1)(ii) to reflect the statutory requirements governing the 
determination of Factor 2 for FY 2018 and subsequent fiscal years. We 
have determined Factor 2 for FY 2018 through FY 2022 consistent with 
the plain language of section 1886(r)(2)(B)(ii) of the Act; therefore, 
this proposed technical change is intended merely to update our 
regulations to reflect the methodology for determining Factor 2 that 
has applied since FY 2018 and will continue to apply for FY 2023 and 
subsequent fiscal years.
    We are inviting public comments on our proposed Factor 2 for FY 
2023 and on the proposed technical change to the regulation at Sec.  
412.106(g)(1)(ii).
3. Calculation of Proposed Factor 3 for FY 2023
(a) 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. We 
refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38201 
through

[[Page 28388]]

38203) for a complete discussion of these analyses.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38206), we 
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. 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, which 
reflected the most recent available information regarding these 
hospitals' low-income insured days before any expansion of Medicaid (82 
FR 38208 through 38212).
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41414), we stated 
that 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 were currently available for FY 2014 or FY 2015 that 
would be a better proxy for the costs of subsection (d) hospitals for 
treating individuals who are uninsured. 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 3 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.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42368), we finalized 
our proposal to use a single year of audited 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 more recent 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 
explained that mixing audited and unaudited data for individual 
hospitals by averaging multiple years of data could potentially lead to 
a less smooth result. We also 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 would be an 
appropriate methodology to determine Factor 3 for FY 2021 and 
subsequent years, except for IHS and Tribal hospitals and hospitals 
located in Puerto Rico. For IHS and Tribal hospitals and Puerto Rico 
hospitals, we finalized the use of a low-income insured days proxy to 
determine Factor 3 for FY 2021. We did not finalize a methodology to 
determine Factor 3 for IHS and Tribal hospitals and Puerto Rico 
hospitals for FY 2022 and subsequent years because we believed further 
consideration and review of these hospitals' Worksheet S-10 data was 
necessary (85 FR 58825).
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized the 
definition of ``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). 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). 
This is the same definition that we initially adopted in the FY 2018 
IPPS/LTCH PPS final rule. 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 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. The OMB control number for this information collection 
request is 0938-0050, which expired on March 31, 2022. A reinstatement 
of the information collection request is currently being developed. The 
public will have an opportunity to review and submit comments on the 
reinstatement through a public notice and comment period separate from 
this rulemaking.
(b) Background on the Methodology Used To Calculate Factor 3 for FY 
2022
    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

[[Page 28389]]

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 2022 IPPS/LTCH PPS final rule, we continued to apply 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; (3) the modified new hospital 
policy that was finalized in the FY 2020 IPPS/LTCH PPS final rule; (4) 
the new merger policy adopted in the FY 2021 IPPS/LTCH PPS final rule 
that accounts for the merger effective date; and (5) 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. We discuss these policies in 
greater detail in this section.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45244), 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 cost report for the applicable fiscal year. 
That is, for FY 2022, we will revise the numerator of Factor 3 for a 
newly merged hospital to reflect the uncompensated care costs reported 
on the newly merged hospital's FY 2022 cost report.
    In FY 2022 IPPS/LTCH PPS final rule, 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 
originally adopted in 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. We also applied the modified policy that was 
adopted in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58829) 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 2022 IPPS/LTCH PPS final rule (86 FR 25454), we continued 
the modified new hospital policy for new hospitals that do not have 
data for the cost reporting period(s) used in the Factor 3 calculation 
(that is, the most recent cost reporting year for which audits have 
been conducted). 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 during the fiscal year. However, because these 
hospitals do not have a cost report for the cost reporting period used 
in the Factor 3 calculation and the projection of eligibility for DSH 
payments is still preliminary, we are unable to calculate a prospective 
Factor 3 for these hospitals and they do not receive interim 
uncompensated care payments. The MAC will make a final determination 
concerning whether the hospital is eligible to receive Medicare DSH 
payments for the fiscal year at cost report settlement. Thus, for FY 
2022, if a new 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 same 
denominator that was used in the prospective Factor 3 calculation for 
FY 2022 (that is, the sum of the uncompensated care costs reported on 
Worksheet S-10 of the FY 2018 cost reports for all DSH-eligible 
hospitals).
    In the FY 2022 IPPS/LTCH PPS final rule, we continued the new 
merger policy that accounts for the merger effective date, that was 
originally adopted in FY 2021. To more accurately estimate 
uncompensated care costs (UCC) for the hospitals involved in a merger 
when the merger effective date occurs partway through the surviving 
hospital's cost reporting period, we apply 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 the UCC 
of the surviving hospital for purposes of determining Factor 3 for the 
merged hospital.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 25454 and 25455), 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

[[Page 28390]]

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 (86 FR 45245). However, because we audit the 
Worksheet S-10 data for a number of hospitals, we no longer believe it 
is necessary to apply the trim methodology for hospitals whose cost 
report has been audited. Accordingly, for FY 2022, we continued the 
policy adopted in FY 2021 under which we exclude hospitals that were 
part of the audits for the fiscal year used in the Factor 3 calculation 
from the trim methodology for potentially aberrant UCC. We also 
continued to apply a modified trim methodology for all-inclusive rate 
providers (AIRPs) with potentially aberrant UCC (86 FR 45235). 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 cost report for the most recent cost reporting year 
for which audits have been conducted, we 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 addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45245 
and 452456), we finalized an alternative trim specific to hospitals 
that are not projected to be DSH-eligible and that do not have audited 
FY 2018 Worksheet S-10 data for use in determining Factor 3. We 
explained that we believe this new alternative 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. Specifically, we finalized that, for the hospitals 
that would be subject to the 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 stated that we believe if a hospital subject to this 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 noted 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.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45242 and 45243), 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 2022 IPPS/LTCH PPS final rule (86 FR 
45236) for a discussion of the approach that we continued to apply in 
FY 2022 to determine Factor 3 for new Puerto Rico hospitals. In brief, 
Puerto Rico hospitals that do not have a FY 2013 cost report were 
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.
    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) for 
subsequent fiscal years, in the FY 2022 IPPS/LTCH PPS final rule we 
used a single year of Worksheet S-10 data from FY 2018 cost reports to 
calculate Factor 3 for FY 2022 for all eligible hospitals with the 
exception of IHS and Tribal hospitals and Puerto Rico hospitals that 
have a cost report for 2013.
    Therefore, for FY 2022, we applied the following methodology to 
compute Factor 3 for each hospital:
    Step 1: Select the provider's longest cost report from its Federal 
fiscal year (FFY) 2018 cost reports. (Alternatively, in the rare case 
when the provider has no FFY 2018 cost report because the cost report 
for the previous Federal fiscal year spanned the FFY 2018 time period, 
the previous Federal fiscal year cost report will be used in this 
step.)
    Step 2: Annualize the uncompensated care costs (UCC) from Worksheet 
S-10 Line 30, if the cost report is more than or less than 12 months. 
(If applicable, use the statewide average CCR (urban or rural) to 
calculate uncompensated care costs.)
    Step 3: Combine adjusted and/or annualized uncompensated care costs 
for hospitals that merged using the merger policy.
    Step 4: Calculate Factor 3 for IHS and Tribal hospitals and Puerto 
Rico hospitals that have a cost report for 2013 using the low-income 
insured days proxy based on FY 2013 cost report data and the most 
recent available SSI ratio (or, for Puerto Rico hospitals, 14 percent 
of the hospital's FY 2013 Medicaid days). The denominator is calculated 
using the low-income insured days proxy data from all DSH eligible 
hospitals.
    Step 5: Calculate Factor 3 for the remaining DSH eligible hospitals 
using annualized uncompensated care costs (Worksheet S-10 Line 30) 
based on FY 2018 cost report data (from Step 1, 2 or 3). New hospitals 
and the hospitals for which Factor 3 was calculated in Step 4 are 
excluded from this calculation.
    We amended 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 finalized a conforming 
change to limit the reference to Puerto Rico hospitals in Sec.  
412.106(g)(1)(iii)(C)(8) to those Puerto Rico hospitals that have a 
cost report for 2013.
(c) Proposed Changes to the Methodology for Calculating Factor 3 for FY 
2023 and Subsequent Fiscal Years
    As described in the FY 2022 IPPS/LTCH PPS final rule, commenters 
expressed concerns that the use of only one year of data to determine 
Factor 3 would lead to significant variations in year-to-year 
uncompensated care

[[Page 28391]]

payments. Some stakeholders recommended the use of two years of 
historical Worksheet S-10 data (86 FR 45237). In the FY 2022 IPPS/LTCH 
PPS final rule, we stated that we would consider using multiple years 
of data when the vast majority of providers have been audited for more 
than one fiscal year under the revised reporting instructions. The 
audits of FY 2019 cost reports began in 2021 and those audited reports 
are now available, in time for the development of this proposed rule. 
Feedback from previous audits and lessons learned were incorporated 
into the audit process for the FY 2019 reports.
    In consideration of the comments discussed in the FY 2022 IPPS/LTCH 
PPS final rule, for FY 2023, we are proposing to determine Factor 3 
using the average of the audited FY 2018 and audited FY 2019 reports. 
We believe this proposal addresses concerns from stakeholders regarding 
year-to-year fluctuations in uncompensated care payments. In addition, 
taking into consideration the comments recommending that CMS transition 
to the use of three years of audited data, we expect that FY 2024 will 
be the first year that three years of audited data will be available at 
the time of rulemaking. Accordingly, for FY 2024 and subsequent fiscal 
years, we propose to use a three-year average of the uncompensated care 
data from the three most recent fiscal years for which audited data are 
available to determine Factor 3. Specifically, for FY 2024, we would 
expect to use data from FY 2018, FY 2019, and FY 2020 reports to 
calculate uncompensated care payments. In other words, for each of the 
three most recent fiscal years for which audited data are available at 
the time of rulemaking for the applicable fiscal year, we would divide 
a hospital's uncompensated care costs for the fiscal year by the 
estimated total uncompensated care costs of all DSH hospitals for that 
fiscal year. We would then calculate an average of those proportions to 
determine the hospital's Factor 3 for the applicable Federal fiscal 
year. We believe this proposed approach is generally consistent with 
our past practice of using the most recent single year of audited data 
from the Worksheet S-10, while also addressing commenters' concerns 
regarding year-to-year fluctuations in uncompensated care payments. 
Consistent with past methodology when multiple years of data were used 
in the Factor 3 methodology, we propose that if a hospital does not 
have data for all three years, we would determine Factor 3 based on an 
average of the hospital's available data.
    As discussed in the earlier background section describing the 
methodology used to calculate Factor 3 for FY 2022, since the FY 2014 
final rule, we have determined Factor 3 for IHS and Tribal hospitals 
and Puerto Rico hospitals, based on the low-income insured days proxy 
for uncompensated care costs. In the FY 2022 IPPS/LTCH PPS final rule, 
we discussed comments we had received from IHS/Tribal hospitals and 
Puerto Rico hospitals about the significant challenges they face in 
relation to uncompensated care reporting (86 FR 45242 and45243). For 
example, a commenter stated that the information technology systems 
used by IHS and Tribal hospitals are not equipped to collect the 
necessary data for the Worksheet S-10, noting that while IHS recently 
received funding to upgrade its information technology system, it will 
take some time, potentially years, before it is fully functional (86 FR 
45242). Another commenter expressed concerns that Puerto Rico hospitals 
were understating the components of uncompensated care costs, and 
indicated that technical education is needed to address the challenges 
Puerto Rico hospitals have regarding charity care and bad debt 
reporting, which the commenter stated would take years to address (86 
FR 45243).
    To the extent the commenters have identified specific challenges 
for IHS/Tribal hospitals and Puerto Rico hospitals in reporting 
uncompensated care costs on Worksheet S-10, it is possible that after a 
sufficient number of years these reporting challenges could be 
addressed. However, despite the reporting challenges described by 
commenters, we are concerned that the historical 2013-based data on 
low-income insured days, which has been used as an alternative to data 
on uncompensated care costs from the Worksheet S-10 to determine Factor 
3 for IHS/Tribal hospitals and Puerto Rico hospitals, is no longer a 
good proxy for the costs of these hospitals in treating the uninsured, 
given the time that has elapsed since 2013. In 2023, this data will be 
ten years old and there is no obvious way to update the information 
given our stated concerns surrounding the differential impact of state 
Medicaid expansions after 2013. In light of these concerns, we can no 
longer conclude that alternative data to the data on uncompensated care 
costs reported on Worksheet S-10 are currently available for IHS/Tribal 
hospitals and Puerto Rico hospitals that are a better proxy for the 
costs of these hospitals in treating the uninsured. Accordingly, for FY 
2023 and subsequent fiscal years, we are proposing to discontinue the 
use of low-income insured days as a proxy for the uncompensated care 
costs of these hospitals and are proposing to use the same data to 
determine Factor 3 for IHS and Tribal hospitals and Puerto Rico 
hospitals as for other hospitals. Specifically, we would determine 
Factor 3 for IHS and Tribal hospitals and Puerto Rico hospitals based 
on the average of the uncompensated care data reported on Worksheet S-
10 of their FY 2018 and FY 2019 cost reports. However, we are seeking 
comments on alternatives both to our proposal to use data on 
uncompensated care costs from the Worksheet S-10 to determine Factor 3 
for IHS/Tribal hospitals and Puerto Rico hospitals and to the continued 
use of low-income insured days as a proxy for the uncompensated care 
costs of these hospitals. We are also seeking comments on how to best 
measure and define the uncompensated care costs associated with these 
hospitals that might not otherwise be captured in Factor 3 calculations 
based on Worksheet S-10 data. Because we recognize that our proposal to 
discontinue the use of the low-income insured days proxy and to rely 
solely on Worksheet S-10 data to calculate Factor 3 of the 
uncompensated care payment methodology for IHS/Tribal hospitals and 
Puerto Rico hospitals could result in a significant financial 
disruption for these hospitals, we are proposing to establish a new 
supplemental payment for IHS/Tribal hospitals and Puerto Rico 
hospitals, beginning in FY 2023. We refer readers to section IV.E of 
the preamble of this proposed rule for a complete discussion of the 
proposed new supplemental payment.
    Prior to the proposed rulemaking for FY 2023, CMS consulted with 
IHS and Tribes regarding our policies for determining uncompensated 
care payments. They expressed that uncompensated care payments are 
critical to the providers and should be maintained at their current 
levels, at a minimum. We have considered this recent input along with 
previous input from stakeholders in the development of our proposed 
policies. We also welcome additional input from stakeholders regarding 
the unique circumstances of IHS/Tribal hospitals and Puerto Rico 
hospitals and/or any mitigating factors, as this will inform our 
considerations about our proposal to determine Factor 3 for these 
hospitals using data from Worksheet S-10 and the related proposal to 
establish a new

[[Page 28392]]

supplemental payment for IHS/Tribal hospitals and Puerto Rico 
hospitals.
    For purposes of this FY 2023 proposed rule, we have used the 
December 2021 HCRIS extract to calculate Factor 3. We note that we 
intend to use the March 2022 update of HCRIS to calculate Factor 3 for 
the FY 2023 IPPS/LTCH PPS final rule. However, we may consider the use 
of more recent data that may become available after March 2022, but 
prior to the development of the final rule, if appropriate, for 
purposes of calculating the final Factor 3 for the FY 2023 IPPS/LTCH 
PPS final rule.
    For purposes of determining Factor 3 for FY 2023 and subsequent 
fiscal years, we will apply 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 
(85 FR 58828 and 58829) to incorporate the use of a multiplier to 
account for merger effective date; (2) the policy for hospitals with 
multiple cost reports, beginning in the same fiscal year, of using the 
longest cost report and annualizing 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 (85 FR 
58829) and as further modified as proposed in this section, 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 and as further modified as proposed in this section; (5) 
the newly merged hospital policy, as modified as proposed in this 
section; 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, as 
modified as proposed in this section.
    Because we are proposing to use multiple years of cost reports to 
determine Factor 3 starting in FY 2023, we have determined that it is 
also necessary to make a further modification to the policy regarding 
cost reports that start in one fiscal year and span the entirety of the 
following fiscal year. Specifically, in the rare cases when we use a 
cost report that starts in one fiscal year and spans the entirety of 
the subsequent Federal fiscal year to determine uncompensated care 
costs for the subsequent Federal fiscal year, we would not use the same 
cost report to determine the hospital's uncompensated care costs for 
the earlier fiscal year. Using the same cost report to determine 
uncompensated care costs for both fiscal years would not be consistent 
with our intent to smooth year-to-year variation in uncompensated care 
costs. As an alternative, we propose to use the hospital's most recent 
prior cost report, if that cost report spans the applicable period. In 
other words, in determining Factor 3 for FY 2023, we would not use the 
same cost report to determine the hospital's uncompensated care costs 
for both FY 2018 and FY 2019. Rather, we would use the cost report that 
spans the entirety of FY 2019 to determine uncompensated care costs for 
FY 2019 and we would use the hospital's most recent prior cost report 
to determine its uncompensated care costs for FY 2018, provided that 
cost report spans some portion of Federal fiscal year 2018.
 Proposed Scaling Factor
    To address the effects of the calculating Factor 3 using data from 
multiple fiscal years, we are proposing to apply a scaling factor to 
the Factor 3 values calculated for all DSH eligible hospitals so that 
total uncompensated care payments to hospitals that are projected to be 
eligible for DSH for a fiscal year will be consistent with the 
estimated amount available to make uncompensated care payments for that 
fiscal year. Specifically, we are proposing to adopt a policy under 
which we divide 1 (the expected sum of all DSH-eligible hospitals' 
Factor 3 values) by the actual sum of all DSH-eligible hospitals' 
Factor 3 values and then multiply the quotient by the uncompensated 
care payment determined for each DSH-eligible hospital to obtain a 
scaled uncompensated care payment amount for each hospital. This 
process is designed to ensure that the sum of the scaled uncompensated 
care payments for all hospitals that are projected to be DSH-eligible 
is consistent with the estimate of the total amount available to make 
uncompensated care payments for the applicable fiscal year. We note 
that a similar scaling factor methodology was previously used in both 
FY 2018 (82 FR 38214 and 38215) and FY 2019 (83 FR 41414), when the 
Factor 3 calculation also included multiple years of data.
 Proposed Modifications to New Hospital Policy for Purposes of 
Factor 3
    We are proposing to modify the new hospital policy that was 
initially adopted in the FY 2020 IPPS/LTCH PPS final rule to determine 
Factor 3 for new hospitals. Consistent with our proposal to use 
multiple years of cost reports to determine Factor 3, we are proposing 
to define new hospitals as hospitals that do not have cost report data 
for the most recent year of data being used in the Factor 3 
calculation. In other words, the cut-off date for the new hospital 
policy is the beginning of the Federal fiscal year after the most 
recent year for which audits of the Worksheet S-10 data have been 
conducted. For FY 2023, the FY 2019 cost reports are the most recent 
year of cost reports for which audits of Worksheet S-10 data have been 
conducted. Thus, hospitals with CCNs established on or after October 1, 
2019, would be subject to the new hospital policy in FY 2023.
    Under this proposed modification to the new hospital policy, we 
would continue the policy established in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42370) that 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 would not 
receive interim uncompensated care payments during FY 2023 because we 
would have no FY 2018 or FY 2019 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 
2023 cost report.
    We are also proposing to modify the methodology used to calculate 
Factor 3 for new hospitals. Specifically, we propose to determine 
Factor 3 for new hospitals using a denominator based solely on 
uncompensated care costs from cost reports for the most recent fiscal 
year for which audits have been conducted. For example, if a new 
hospital is ultimately determined to be eligible for Medicare DSH 
payments for FY 2023, 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 2023 cost report, and the denominator is the sum of the 
uncompensated care costs reported on Worksheet S-10 of the FY 2019 cost 
reports for all DSH-eligible hospitals. In addition, we are proposing 
to apply a scaling factor, as discussed previously, to the Factor 3 
calculation for a new hospital. We believe applying the scaling factor 
is appropriate for purposes of calculating Factor 3 for all hospitals, 
including new hospitals and hospitals that are treated as new

[[Page 28393]]

hospitals, in order to improve consistency and predictability across 
all hospitals.
 Proposed Modifications to the Newly Merged Hospital Policy
    We will continue 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 the proposed modification to the methodology used to 
determine Factor 3 for new hospitals described previously, we are 
proposing to determine Factor 3 for newly merged hospitals using a 
denominator that is the sum of the uncompensated care costs for all 
DSH-eligible hospitals, as reported on Worksheet S-10 of their cost 
reports for the most recent fiscal year for which audits have been 
conducted. In addition, we would apply a scaling factor, as discussed 
previously, to the Factor 3 calculation for a newly merged hospital. We 
believe applying the scaling factor is appropriate for purposes of 
calculating Factor 3 for all hospitals, including new hospitals and 
hospitals that are treated as new hospitals, in order to improve 
consistency and predictability across all hospitals.
    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 2023, 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 on the 
uncompensated care costs from the FY 2018 and FY 2019 cost reports 
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 2023 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 2023 cost report. The denominator would be the sum of the 
uncompensated care costs reported on Worksheet S-10 of the FY 2019 cost 
reports for all DSH-eligible hospitals, which is the most recent fiscal 
year for which audits have been conducted.
 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 for FY 2018 reports 
and FY 2019 reports separately:
    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: Calculate a CCR ``ceiling'' for the applicable fiscal year 
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 the applicable 
fiscal year for hospitals within each State (including non-DSH eligible 
hospitals), weighted by the sum of total hospital discharges from 
Worksheet S-3, Part I, Line 14, Column 15.
    Step 4: Assign the appropriate statewide average CCR (urban or 
rural) calculated in Step 3 to all hospitals, excluding all-inclusive 
rate providers, with a CCR for the applicable fiscal year 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 8 hospitals' FY 2018 reports, of 
which 3 hospitals had FY 2018 Worksheet S-10 data. The statewide 
average CCR was applied to 14 hospitals' FY 2019 reports, of which 6 
hospitals had FY 2019 Worksheet S-10 data.
    Step 5: For hospitals that did not report a CCR on Worksheet S-10, 
Line 1, we assign them the statewide average CCR for the applicable 
fiscal year as determined in step 3.
    After completing the previously described steps, we re-calculate 
the hospital's uncompensated care costs (Line 30) for the applicable 
fiscal year using the trimmed CCR (the statewide average CCR (urban or 
rural, as applicable)).
 Proposed Modifications to the Uncompensated Care Data Trim 
Methodology
    After applying the CCR trim methodology, there are rare situations 
where a hospital has potentially aberrant uncompensated care data for a 
fiscal year 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 
IPPS/LTCH PPS final rule (85 FR 58832), if the hospital's uncompensated 
care costs for FY 2018 or FY 2019 are an extremely high ratio (greater 
than 50 percent) of its total operating costs in the applicable fiscal 
year, 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 for the applicable fiscal year. Specifically, 
if a hospital's FY 2018 cost report is determined to include 
potentially

[[Page 28394]]

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 2023. Because we are proposing to use 
multiple years of cost reports in the Factor 3 calculation for FY 2023, 
we would apply this same approach to address potentially aberrant data 
in the FY 2019 cost report, by trimming based on the hospital's FY 2020 
cost report.
    We note that we have audited the FY 2018 and the FY 2019 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 a fiscal year 
for which a hospital's UCC data have been audited.
    In addition to the UCC trim methodology, we will continue to apply 
a trim specific to certain hospitals that do not have audited FY 2018 
Worksheet S-10 data and/or audited FY 2019 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). Similar to the approach initially adopted in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45245 and 45246), we are proposing 
to continue 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 that is the median total uncompensated care cost 
reported on most recent audited cost reports for hospitals that were 
projected to be DSH-eligible. We continue to believe these thresholds 
are appropriate, in order to address potentially aberrant data. 
However, we are proposing to modify the calculation to include 
Worksheet S-10 data from IHS/Tribal hospitals and Puerto Rico hospitals 
consistent with our proposal in this proposed rule to begin using 
Worksheet S-10 data to determine Factor 3 for these hospitals. We also 
propose to apply the same thresholds to identify potentially aberrant 
charity care costs data for all cost reporting years that are used in 
determining Factor 3. We note that based on calculations from the FY 
2019 reports, the threshold amounts were similar to FY 2018 reports; 
therefore, we believe it is reasonable to use the same thresholds to 
identify aberrant data for both years. Thus, under this proposal, in FY 
2023 we would use the same thresholds to identify potentially aberrant 
data for both FY 2018 and FY 2019 reports. In addition, we are 
proposing to apply the same threshold amounts originally calculated for 
the FY 2018 reports to identify potentially aberrant data for 
subsequent fiscal years, which we believe will facilitate transparency 
and predictability. Therefore, for FY 2023 and subsequent fiscal years, 
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, we would exclude the hospital from the prospective Factor 3 
calculation. This 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. 
Consistent with the approach adopted in the FY 2022 IPPS/LTCH PPS final 
rule, if a hospital would be trimmed under both the UCC trim 
methodology and this alternative trim, we would apply this trim in 
place of the existing UCC trim methodology. We continue to believe this 
alternative trim more appropriately addresses potentially aberrant 
insured patient charity care costs compared to the UCC trim 
methodology, because the UCC 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 propose to continue to apply the policy adopted in 
the FY 2022 IPPS/LTCH PPS final rule, for the hospitals that would be 
subject to this alternative trim and are ultimately determined to be 
DSH-eligible at cost report settlement. We believe if a hospital 
subject to this 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 2023 Worksheet S-10 has been reviewed. Accordingly, the 
MAC would calculate a Factor 3 for the hospital only after reviewing 
the uncompensated care information reported on Worksheet S-10 of the 
hospital's FY 2023 cost report. We would then calculate Factor 3 for a 
hospital subject to this alternative trim using the same methodology 
used to determine Factor 3 for new hospitals. Specifically, the 
numerator would reflect the uncompensated care costs reported on the 
hospital's FY 2023 cost report, while the denominator would reflect the 
sum of the uncompensated care costs reported on Worksheet S-10 of the 
FY 2019 costs reports of all DSH-eligible hospitals. In addition, 
consistent with our proposed approach for new hospitals, we would apply 
a scaling factor, as discussed previously, to the Factor 3 calculation 
for these hospitals. We believe applying the scaling factor is 
appropriate for purposes of calculating Factor 3 for all hospitals, 
including new hospitals and hospitals that are treated as new 
hospitals, in order to improve consistency and predictability across 
all hospitals.
 Summary of Methodology
    In summary, for FY 2023, we propose to compute Factor 3 for each 
hospital using the following steps:
    Step 1: Select the hospital's longest cost report from its Federal 
fiscal year (FY) 2018 cost reports and the longest cost report from its 
FY 2019 cost reports. (Alternatively, in the rare case when the 
hospital has no cost report for a particular year because the cost 
report for the previous Federal fiscal year spanned the more recent 
Federal fiscal yeartime period, the previous Federal fiscal year cost 
report would be used in this step. In the rare case, that using a 
previous Federal fiscal year cost report results in a period without a 
report, then we propose to use the prior year report, if that cost 
report spanned the applicable period. (For example, if a hospital does 
not have a FY 2019 cost report because the hospital's FY 2018 cost 
report spanned the FY 2019 time period, then we would use the FY 2018 
cost report that spanned the FY 2019 time period for this step. Using 
the same example, where the hospital's FY 2018 report is used for the 
FY 2019 time period, then we would use the hospital's FY 2017 report if 
it spans some of the FY 2018 time period. In other words, we would not 
use the same cost report for both the FY 2019 and the FY 2018 time 
periods.) In general, we note that, for purposes of the Factor 3 
methodology, references to a fiscal year cost report are to the cost 
report that

[[Page 28395]]

spans the relevant Federal fiscal year period.
    Step 2: Annualize the uncompensated care costs (UCC) from Worksheet 
S-10 Line 30, if a 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 the all DSH eligible hospitals using 
annualized uncompensated care costs (Worksheet S-10 Line 30) based on 
FY 2018 cost report data and FY 2019 cost report (from Step 1, 2 or 3). 
New hospitals and other hospitals that are treated as if they are new 
hospitals for purposes of Factor 3 are excluded from this calculation.
    Step 5: Average the Factor 3 values from Step 4; that is, add the 
Factor 3 values for FY 2018 and FY 2019 for each hospital, and divide 
that amount by the number of cost reporting periods with data to 
compute an average Factor 3 for the hospital. Multiply by a scaling 
factor.
    For FY 2024 and subsequent fiscal years, these steps would be 
calculated using the most recent three years of audited cost reports. 
(For example, in FY 2024, the FY 2018, FY 2019, and FY 2020 reports 
would be used.)
    We are proposing to make a conforming change to the existing 
regulation at Sec.  412.106(g)(1)(iii)(C)(8) and to add a new 
regulation at Sec.  412.106(g)(1)(iii)(C)(10) to reflect our proposal 
to calculate Factor 3 based on the most recent two years of audited 
data on uncompensated care costs in FY 2023. We are also proposing to 
add Sec.  412.106(g)(1)(iii)(C)(11) to reflect our proposal to 
calculate Factor 3 for FY 2024 and subsequent fiscal years based on a 
3-year average of the most recent available audited data on 
uncompensated care costs.
(d) 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.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45247 and 45248), we 
modified this calculation for FY 2022 to be based on an average of FY 
2018 and FY 2019 historical discharge data, rather than a 3-year 
average that included data from FY 2018, FY 2019, and FY 2020. We 
explained our belief that computing a 3-year average with the FY 2020 
discharge data would underestimate discharges, due to the decrease in 
discharges during the COVID-19 pandemic. For the same reason, we are 
now proposing to modify this calculation for FY 2023 to be based on the 
average of FY 2018, FY 2019, and FY 2021 historical discharge data, 
rather than a 3-year average of the most recent three years of 
discharge data from FY 2019, FY 2020, and FY 2021. We believe that 
computing a 3-year average using the most recent three years would 
potentially underestimate the number of discharges for FY 2023, due to 
the effects of the COVID-19 pandemic in FY 2020, which was the first 
year of the COVID-19 pandemic. Therefore, we believe the proposed 
modification may result in a better estimate of the number of 
discharges during FY 2023, for purposes of the interim uncompensated 
care payment calculation. In addition, we note that our proposal to 
include discharge data from FY 2021 to compute this 3-year average is 
consistent with the proposed use of FY 2021 Medicare claims in the IPPS 
ratesetting, as discussed in section I.F. of the preamble of this 
proposed rule. Under this proposal, the resulting 3-year average of the 
number of discharges would be used to calculate a per discharge payment 
amount that will be used to make interim uncompensated care payments to 
each projected DSH-eligible hospital during FY 2023. The interim 
uncompensated care payments made to a hospital during the fiscal year 
will be 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 FY 2023.
    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 the hospital's projected FY 2023 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.
(e) 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

[[Page 28396]]

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 2023 (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 an uncompensated care 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 new hospitals and hospitals 
that are subject to the alternative trim for hospitals with potentially 
aberrant data that are not projected to be DSH-eligible.
    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 11 hospitals that 
would be subject to the alternative trim for hospitals with potentially 
aberrant data that are not projected to be DSH-eligible, with a N/A in 
the Factor 3 column.
    Hospitals have 60 days from the date of public display of this FY 
2023 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 this 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 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). 
Stakeholders may submit issues or concerns that are specific to the 
information included in the table and supplemental data file by email 
to the CMS inbox at [email protected]. We will address issues 
related to mergers and/or reporting upload discrepancies submitted to 
the CMS DSH inbox as appropriate in the table and the supplemental data 
file that we publish on the CMS website in conjunction with the 
publication of the FY 2023 IPPS/LTCH PPS final rule. All other comments 
submitted in response to our proposed policies for determining 
uncompensated care payments for FY 2023 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.
    For FY 2023, we are again proposing that hospitals will have 15 
business days from the date of public display of the FY 2023 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, 
2022. 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 2022 HCRIS extract for the FY 2023 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, as previously 
indicated, we may consider using more recent data that may become 
available after March 2022, but before the final rule for the purpose 
of calculating the final Factor 3s for the FY 2023 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 2023 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 2023 and subsequent fiscal years, 
including, but not limited to, our proposal to use the most recent 
audited Worksheet S-10 data from FY 2018 and FY 2019 cost reports to 
determine Factor 3 for FY 2023, and our proposal to begin using the 
three most recent years of audited Worksheet S-10 data starting in FY 
2024.

E. Proposed Supplemental Payment for Indian Health Service and Tribal 
Hospitals and Puerto Rico Hospitals for FY 2023 and Subsequent Fiscal 
Years

    In the IPPS/LTCH PPS rulemaking for several previous fiscal years, 
Indian Health Service (IHS) and Tribal hospitals and hospitals located 
in Puerto Rico have commented about the unique challenges they face 
with respect to uncompensated care due to structural differences in 
health care delivery and financing in these areas compared to the rest 
of the country. We refer the readers to FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45242 and 45243) and the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58824 and 58825) for a discussion of these comments. We 
appreciate the concerns raised and the input offered by commenters 
regarding the methodology for calculating uncompensated care payments 
for IHS/Tribal hospitals and the Puerto Rico hospitals. As discussed in 
greater detail in this section, after taking into consideration 
stakeholders' longstanding concerns and their input on potential 
approaches to address these concerns, CMS is proposing to establish a 
new permanent supplemental payment under the IPPS for IHS/Tribal 
hospitals and hospitals located in Puerto Rico. As discussed in greater 
detail in this section, we believe this proposed new supplemental 
payment would mitigate the anticipated impact on IHS/Tribal hospitals 
and hospitals located in Puerto Rico from our proposal to discontinue 
the use of low-income insured days as a proxy for their uncompensated 
care costs for purposes of determining Factor 3 of the uncompensated 
care payment methodology by providing for an additional payment to 
these hospitals that would be determined based upon the difference 
between the amount of the uncompensated care payment determined for the 
hospital using Worksheet S-10 data and an approximation of the amount 
the hospital would have received if we had continued to use low-income 
days as a proxy for uncompensated care.
    As background, beginning in the FY 2018 IPPS/LTCH PPS final rule 
when we first included Worksheet S-10 data in the calculation of Factor 
3, and continuing through the FY 2022 IPPS/LTCH PPS final rule, we 
relied on the authority under section 1886(r)(2)(C)(i) of the Act to 
use alternative data that is a better proxy for the costs of hospitals 
for treating the uninsured in order to determine Factor 3 for IHS/
Tribal and Puerto Rico hospitals using low-income insured days as a 
proxy for uncompensated care costs. Since FY

[[Page 28397]]

2019, Factor 3 for these hospitals has been determined using FY 2013 
Medicaid days and the most recent available data on SSI days. We have 
explained our belief that this approach was appropriate as the FY 2013 
Medicaid days 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 low-income 
insured 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 
initially adopted in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56953 
through 56956). For FY 2023 and subsequent fiscal years, as discussed 
in the previous section, we are proposing to discontinue the use of 
low-income insured days as a proxy for uncompensated care costs. We 
recognize that this proposal would result in a significant financial 
disruption to the IHS/Tribal hospitals and hospitals located in Puerto 
Rico. For the vast majority of these hospitals, the proposal to use 
uncompensated care data reported on Worksheet S-10 to determine Factor 
3 of the uncompensated care payment methodology is expected to result 
in an approximately 90 to 100 percent reduction in uncompensated care 
payments for FY 2023 compared to FY 2022. For a discussion of the 
anticipated impact of the proposal to use uncompensated care costs from 
Worksheet S-10 to determine uncompensated care payments for IHS/Tribal 
hospitals and Puerto Rico hospitals and the proposal to establish a new 
supplemental payment for these hospitals, we refer the readers to 
section I.H. of the Appendix A of this proposed rule.
    In consideration of the unique circumstances faced by the hospitals 
and the comments received from IHS/Tribal hospitals and Puerto Rico 
hospitals in response to prior rulemaking, raising concerns regarding 
financial stability in the event of a change in the data used to 
determine Factor 3, we are proposing to use our exceptions and 
adjustments authority under section 1886(d)(5)(I) of the Act to 
establish a new permanent supplemental payment under the IPPS for IHS/
Tribal hospitals and hospitals located in Puerto Rico, beginning in FY 
2023. Section 1886(d)(5)(I) of the Act authorizes the Secretary to 
provide by regulation for such other exceptions and adjustments to the 
payment amounts under section 1886(d) of the Act as the Secretary deems 
appropriate. We have determined, after taking into consideration 
stakeholders' comments from prior rulemakings, that the supplemental 
payment is necessary so as not to cause undue long-term financial 
disruption to these hospitals as a result of our proposal to 
discontinue the use of low-income insured days as a proxy for 
uncompensated care in determining Factor 3 for IHS/Tribal hospitals and 
Puerto Rico hospitals beginning in FY 2023. We believe the proposed 
supplemental payment would help to mitigate the anticipated impact of 
the proposed changes to the uncompensated care payment methodology for 
these hospitals and therefore prevent undue long-term financial 
disruption for these providers.
    This proposed new supplemental payment would not change in any way 
the DSH payment methodology under section 1886(d)(5)(F) or the 
uncompensated care payment methodology under section 1886(r). 
Therefore, the total uncompensated care payment amount discussed in the 
previous section of the preamble of this proposed rule, would not be 
affected by this proposal to establish a supplemental payment for IHS/
Tribal and hospitals located in Puerto Rico nor would there be any 
impact on the amount of the uncompensated care payment determined for 
each DSH-eligible hospital under Sec.  412.106(g)(1) of the 
regulations.
    For IHS and Tribal hospitals and hospitals located in Puerto Rico 
for which Factor 3 of the uncompensated care payment methodology was 
determined using the low-income insured days proxy in FY 2022, we 
propose to calculate a supplemental payment as follows. We would use 
the hospital's FY 2022 uncompensated care payment as the starting point 
for this calculation. We believe using the FY 2022 uncompensated care 
payment is an appropriate starting point because FY 2022 is the most 
recent year for which we used low-income insured days data in the 
determination of uncompensated care payments for IHS/Tribal hospitals 
and Puerto Rico hospitals and the purpose of the supplemental payment 
is to avoid undue long-term financial disruption to these hospitals as 
a result of our proposal to discontinue the use of low-income insured 
days as a proxy for uncompensated care beginning in FY 2023. The base 
year amount would be calculated as the hospital's FY 2022 uncompensated 
care payment adjusted by one plus the percent change in the total 
uncompensated care amount between the applicable year (for example, FY 
2023 for purposes of this rulemaking) and FY 2022, where the total 
uncompensated care amount for a year is determined as the product of 
Factor 1 and Factor 2 for the applicable year. For the hospitals that 
were not projected to be DSH eligible in FY 2022, we propose to use the 
uncompensated care payment that the hospital would receive, if the 
hospital were to be determined to be DSH eligible in FY 2022 at cost 
report settlement. For purposes of this proposed rule, the percent 
change between the proposed FY 2023 uncompensated care amount and final 
FY 2022 uncompensated care amount is projected to be negative 9.1 
percent. (This negative 9.1 percent change is calculated based on the 
difference between the proposed FY 2023 uncompensated care amount of 
approximately $6.537 billion and the final FY 2022 uncompensated care 
amount of approximately $7.192 billion, divided by the final FY 2022 
uncompensated care amount). Therefore, we propose to calculate each 
hospital's base year amount for FY 2023 by multiplying its FY 2022 
uncompensated care amount by 0.909 (1-0.091). The hospital's 
supplemental payment for a fiscal year would then be determined as the 
difference between the hospital's base year amount and its 
uncompensated care payment for the applicable fiscal year as determined 
under Sec.  412.106(g). If the base year amount is equal to or lower 
than the hospital's uncompensated care payment for the current fiscal 
year, then the hospital would not receive a supplemental payment 
because the hospital would not be experiencing financial disruption in 
that year as a result of the use of uncompensated care data from the 
Worksheet S-10 in determining Factor 3 of the uncompensated care 
payment methodology.
    We propose to align the eligibility and payment processes for the 
new supplemental payment with the processes used to make uncompensated 
care payments. Consistent with the process for determining eligibility 
to receive interim uncompensated care payments adopted in the FY 2014 
IPPS/LTCH final rule, for the supplemental payment, we propose to base 
eligibility to receive interim supplemental payments on a projection of 
DSH eligibility for the applicable fiscal year. In addition, consistent 
with the approach that is used to calculate interim uncompensated care 
payments on a per discharge basis, for the supplemental payment, we 
propose to

[[Page 28398]]

use an average of historical discharges to calculate a per discharge 
amount for interim supplemental payments. We refer readers to the FY 
2014 IPPS/LTCH PPS final rule for additional background and discussion 
of uncompensated care payment processes (78 FR 50643 through 50647). 
Consistent with our proposal to use 3-years of historical discharges to 
determine interim uncompensated care payments for a fiscal year, the 
amount of a hospital's supplemental payment calculated for a fiscal 
year would be divided by the hospital's historical 3-year average of 
discharges computed using the most recent available data to determine 
an estimated per discharge payment amount.
    For FY 2023, we propose to use FY 2018, FY 2019, and FY 2021 
discharge data to determine a hospital's historical 3-year average of 
discharges, because we continue to believe the FY 2020 discharge data 
would underestimate discharges, due to the effects of the COVID-19 
pandemic in FY 2020. In addition, consistent with the policy of 
including per-discharge uncompensated care payment amounts in the 
outlier calculation, which was initially adopted in the FY 2014 IPPS/
LTCH PPS final rule, we are proposing to use our authority under 
section 1886(d)(5)(I) to include the per-discharge supplemental payment 
in the outlier payment determination under section 1886(d)(5)(A) of the 
Act. We refer readers to the Addendum for further discussion of the 
outlier payment calculation.
    Consistent with the process used to reconcile interim uncompensated 
care payments, we propose that the MAC would reconcile the interim 
supplemental payments at cost report settlement to ensure that the 
hospital receives the full amount of the supplemental payment that was 
determined prior to the start of the fiscal year. Consistent with the 
process used for cost reporting periods that span multiple Federal 
fiscal years, we propose that a pro rata supplemental payment 
calculation may be made if the hospital's cost reporting period differs 
from the Federal fiscal year. Thus, the final supplemental payment 
amounts that would be included on a cost report spanning two Federal 
fiscal years would be the pro rata share of the supplemental payment 
associated with each Federal fiscal year. This pro rata share would be 
determined based on the proportion of the applicable Federal fiscal 
year that is included in that cost reporting period. We refer readers 
to the FY 2014 interim final rule for additional background and 
discussion of the processes for determining pro rata uncompensated care 
payments (78 FR 61191 through 61196).
    We propose that the MAC would make a final determination with 
respect to a hospital's eligibility to receive the supplemental payment 
for a fiscal year, in conjunction with its final determination of the 
hospital's eligibility for DSH payments and uncompensated care payments 
for that fiscal year. We note that if a hospital is determined not to 
be DSH eligible for a fiscal year then the hospital would not be 
eligible to receive a supplemental payment for that fiscal year. We 
believe linking eligibility for the supplemental payment to eligibility 
for DSH payments and the uncompensated care payment is appropriate 
because a hospital that is not eligible to receive an uncompensated 
care payment for a fiscal year would not experience any financial 
disruption due to the discontinuation of the low-income insured days 
proxy and the use of Worksheet S-10 data in determining Factor 3 for 
that fiscal year.
    In addition, we propose that IHS/Tribal hospitals and Puerto Rico 
hospitals that do not have a FY 2022 Factor 3 amount determined under 
Sec.  412.106(g)(1)(iii)(C)(9) using the low-income insured days proxy 
or that are new hospitals that begin participating in the Medicare 
program on or after October 1, 2022, would not be eligible to receive 
the supplemental payment. These hospitals will not experience any 
reduction to their uncompensated care payments due to the proposed 
discontinuation of the low-income insured days proxy because they are 
not currently receiving uncompensated care payments determined using 
the proxy.
    We propose to redesignate the existing provision at Sec.  
412.106(h) as Sec.  412.106(i) and to add a new provision at Sec.  
412.106(h) to reflect the methodology for calculating the supplemental 
payment for FY 2023 and subsequent fiscal years.
    We are seeking comments on our proposal to establish a new 
supplemental payment for IHS/Tribal hospitals and Puerto Rico 
hospitals. As discussed in section IV.D.3. of the preamble of this 
proposed rule, which includes our proposed changes to the methodology 
for determining Factor 3 of the uncompensated care payment methodology 
for FY 2023 and subsequent fiscal years, we also are seeking comments 
on alternatives both to our proposal to use data on uncompensated care 
costs from the Worksheet S-10 to determine Factor 3 for IHS/Tribal 
hospitals and Puerto Rico hospitals and to the continued use of low-
income insured days as a proxy for the uncompensated care costs of 
these hospitals. In addition, we are also seeking comments on how to 
best measure and define the uncompensated care costs associated with 
these hospitals that might not otherwise be captured in Factor 3 
calculations based on Worksheet S-10 data.

F. Medicare Disproportionate Share Hospital (DSH) Payments: Counting 
Days Associated With Section 1115 Demonstrations in the Medicaid 
Fraction (Sec.  412.106)

    States use section 1115(a) demonstrations to test changes to their 
Medicaid programs that generally cannot be made using other Medicaid 
authorities, including to provide health insurance to groups that 
generally could not or have not been made eligible for ``medical 
assistance under a State plan approved under title XIX'' (Medicaid 
benefits). These groups, commonly referred to as expansion populations 
or expansion waiver groups, are specific, finite groups defined in the 
demonstration approval letter and special terms and conditions for each 
demonstration. (We note in the discussion that follows, we use the term 
``demonstration'' rather than ``project'' and/or ``waiver'' and the 
term ``groups'' instead of ``populations,'' as this terminology is 
generally more consistent with the implementation of the provisions of 
section 1115 of the Social Security Act.)
    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 certain patients that receive Medicaid benefits under a section 
1115 demonstration in calculating the Medicare DSH adjustment. 
Previously, hospitals could include only the days for those patients 
receiving Medicaid benefits under a section 1115 demonstration who 
were, or could have been made, eligible for Medicaid under the State 
plan. Patient days of those demonstration expansion groups that were 
not and could not be made eligible for Medicaid 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 policy adopted in the January 2000 interim final rule (65 
FR 3136), hospitals could include in the numerator of the Medicaid 
fraction all patient days of groups made eligible for Title XIX 
matching payments through a

[[Page 28399]]

section 1115 demonstration, whether or not those individuals were, or 
could be made, eligible for Medicaid under a State plan (assuming they 
were not also entitled to benefits under Medicare Part A). 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 
demonstration expansion groups 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 to limit the types of section 1115 
demonstrations 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 demonstration expansion groups, 
our intention was to include patient days of those groups who under a 
demonstration receive benefits, including inpatient benefits, that are 
similar to the benefits provided to Medicaid beneficiaries under a 
State plan. We had become aware, however, that certain section 1115 
demonstrations provide expansion groups with benefit packages so 
limited that the benefits are unlike the relatively expansive health 
insurance (including insurance for inpatient hospital services) 
provided under a Medicaid State plan. We explained that these limited 
section 1115 demonstrations extend benefits only for specific services 
and do not include similarly expansive benefits.
    In the FY 2004 IPPS final rule, we specifically discussed family 
planning benefits offered through a section 1115 demonstration as an 
example of the kind of demonstration days that should not be counted in 
the Medicaid fraction because the benefits granted to the expansion 
group are too limited. Our intention in discussing family planning 
benefits under a section 1115 demonstration 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 (set forth in the January 2000 
interim final rule (65 FR 3136)) to allow only the days of those 
demonstration expansion groups who are provided Medicaid benefits, and 
specifically inpatient hospital benefits, like the health care 
insurance that Medicaid beneficiaries receive under a State plan, to be 
included in the numerator of the Medicaid fraction of the Medicare DSH 
calculation. Moreover, this example was intended to illustrate the kind 
of benefits offered through a section 1115 demonstration that are so 
limited that the patients receiving them should not be considered 
eligible for Medicaid for purposes of the DSH calculation.
    Because of the limited nature of the Medicaid benefits provided to 
expansion groups under some demonstrations, as compared to the benefits 
provided to the Medicaid population under a State plan, we determined 
it was appropriate to exclude the patient days of patients provided 
limited benefits under a section 1115 demonstration from the 
determination of Medicaid days for purposes of the DSH calculation. 
Therefore, in the FY 2004 IPPS final rule (68 FR 45420 and 45421), 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 demonstration. 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 
made eligible for inpatient hospital services under either a State 
Medicaid plan or a section 1115 demonstration, who are not also 
entitled to benefits under Medicare Part A.
    In 2005, the Ninth Circuit held that demonstration expansion groups 
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.\603\ 
Subsequently, the District Court for the District of Columbia reached 
the same conclusion, reasoning that if our policy of counting the days 
of demonstration expansion groups after 2000 was correct, then patients 
in demonstration expansion groups were necessarily ``eligible for 
medical assistance under a State plan'' (that is, Medicaid) and the Act 
had always required inclusion of their days.\604\
---------------------------------------------------------------------------

    \603\ Portland Adventist Med. Ctr. v. Thompson, 399 F.3d 1091, 
1096 (9th Cir. 2005).
    \604\ Cookeville Reg'l Med. Ctr. v. Thompson, No. 04-1053, 2005 
WL 3276219, at *4-6 (D.D.C. Oct. 28, 2005).
---------------------------------------------------------------------------

    Shortly after these court decisions, Congress, in early 2006, 
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 days of expansion groups from the DSH 
calculation. First, section 5002(a) of the DRA clarified that groups 
that receive Medicaid benefits through a section 1115 demonstration are 
not ``eligible for medical assistance under a State plan'' by referring 
to them as ``not so eligible.'' This provision effectively overruled 
the earlier court decisions that held that expansion groups were, in 
fact, made eligible for Medicaid. Second, the statute made explicit 
that the Secretary nevertheless has the discretion to include in the 
Medicaid fraction days of patients who are not eligible for Medicaid if 
they ``are regarded as'' being eligible for Medicaid ``because they 
receive benefits under a demonstration project approved under title 
XI.'' This statutory language endorsed and codified the Secretary's 
view that it is appropriate to include in the DSH calculation days of 
patients who are treated as if they were eligible for Medicaid under 
the authority of section 1115(a)(2). Third, the DRA granted the 
Secretary the discretion to include or exclude the days of patients who 
are regarded as being eligible for Medicaid in the numerator of the 
Medicaid fraction ``to the extent and for the period the Secretary 
determines appropriate.'' Finally, section 5002(b) of the DRA expressly 
ratified our policy on counting demonstration days in the Medicaid 
fraction. Our pre-2000 policy was not to include days of section 1115 
demonstration expansion groups in the numerator of the Medicaid 
fraction unless they could have been made eligible for Medicaid under a 
State plan. As discussed previously, we changed our policy in 2000 to 
permit inclusion in the Medicaid fraction of all patient days of groups 
made eligible for matching payments under Title XIX through a section 
1115 demonstration. By the time the DRA was enacted, CMS had further 
refined this policy, and we included in the Medicaid fraction the days 
of only a small subset of demonstration expansion groups regarded as 
eligible for Medicaid: Those that were eligible to receive inpatient 
hospital insurance benefits under the terms of a section 1115 
demonstration.
    Considering this history, and the text of the DRA, we understand 
the Secretary's authority to include the days of patients who receive 
benefits through a section1115 demonstration in the numerator of the 
Medicaid fraction of the DSH calculation as requiring two 
determinations. First, we must determine whether the patients at issue 
``are regarded as'' being eligible for Medicaid. Second, if they are, 
the Secretary then has the discretion to determine whether to count 
those

[[Page 28400]]

patients in the DSH calculation and for what period.
    We do not believe that the DRA gave the Secretary blanket authority 
to count in the Medicaid fraction any patient who is in any way related 
to a section 1115 demonstration. Rather, our authority under section 
1886(d)(5)(F)(vi) of the Act remains limited to including the days of 
expansion groups--those for whom a state seeks Federal Medicaid 
matching funds in order to provide health insurance to individuals 
through a demonstration that is comparable to Medicaid state plan 
benefits--that is, patients who ``are regarded as'' ``eligible for 
medical assistance under a State plan approved under title XIX.'' 
Because the existing language of regulations already addressed the 
treatment of section 1115 days, we did not believe it was necessary to 
update our regulations after the DRA explicitly granted us the 
discretion to include or exclude section 1115 days.
    More recently, section 1115 demonstrations have been used to 
authorize the funding of uncompensated care pools that help to offset 
hospitals' costs for treating uninsured and underinsured individuals. 
These pools do not extend health insurance directly to such 
individuals. Rather, such funding pools benefit patients less directly 
by helping hospitals treat the uninsured and underinsured and stay 
financially viable to treat patients eligible for Medicaid under a 
state plan. Unlike demonstrations that expand the group of people who 
receive Medicaid benefits beyond those groups eligible under the State 
plan, uncompensated care pools do not provide inpatient health 
insurance to patients or, like insurance, make payments on behalf of 
specific, covered individuals. 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 and underinsured.
    We also note that demonstrations can simultaneously authorize 
different programs within a single demonstration, thereby creating a 
group regarded as Medicaid eligible because they receive health 
insurance through the demonstration while also creating a separate 
uncompensated/undercompensated care pool for providers that does not 
directly extend health insurance to individuals.
    Recently, courts have decided a series of cases (Bethesda Health, 
Inc. v. Azar, 980 F.3d 121 (D.C. Cir. 2020); Forrest General Hospital 
v. Azar, 926 F.3d 221 (5th Cir. 2019); HealthAlliance Hospitals, Inc. 
v. Azar, 346 F. Supp. 3d 43 (D.D.C. 2018)) interpreting the current 
language of the regulation at Sec.  412.106(b)(4) to require CMS to 
count in the numerator of the Medicaid fraction patient days for which 
hospitals have 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. 
Interpreting the regulatory language that was adopted before the DRA 
was enacted, 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, a court has 
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 in the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25459), we stated that we continued to believe 
that it is not appropriate to include patient days associated with 
funding pools and premium assistance authorized by section 1115 
demonstrations in the Medicaid fraction of the Medicare DSH calculation 
because the benefits offered under these demonstrations are not similar 
to Medicaid benefits under a State plan and may offset costs that 
hospitals incur when treating uninsured and underinsured individuals. 
In the FY 2022 IPPS/LTCH PPS proposed rule, we proposed a revision to 
our regulations to more clearly state that in order for an inpatient 
day to be counted in the Medicaid fraction of the Medicare DSH 
calculation, the section 1115 demonstration must provide inpatient 
hospital insurance benefits directly to the individual whose day is 
being considered for inclusion, and we proposed to revise our 
regulations to reflect this requirement. We specifically discussed 
that, under the proposed change, days of patients who receive premium 
assistance through a section 1115 demonstration and the days of 
patients for which hospitals receive payments from an uncompensated/
undercompensated care pool created by a section 1115 demonstration 
would not be included in the calculation of the Medicaid fraction of 
the Medicare DSH calculation because neither premium assistance nor 
uncompensated/undercompensated care pools are inpatient hospital 
insurance benefits directly provided to individuals, nor are they 
comparable to the level of benefits available under a Medicaid State 
plan such that the individuals should be ``regarded as'' ``eligible for 
medical assistance under a State plan.''
    Commenters generally disagreed with our proposal, arguing that both 
premium assistance programs and uncompensated/undercompensated care 
pools are used to provide individuals with inpatient hospital services, 
either by reimbursing hospitals for the same services as the Medicaid 
program in the case of uncompensated/undercompensated care pools or by 
allowing individuals to purchase insurance with benefits similar to 
Medicaid benefits offered under a State plan in the case of premium 
assistance, and thus should be included in calculating the Medicaid 
fraction. Following review of these comments, in the final rule with 
comment period published in the Federal Register on December 27, 2021, 
which finalized certain provisions of the FY 2022 IPPS/LTCH PPS 
proposed rule related to Medicare graduate medical education payments 
for teaching and Medicare organ acquisition payment, we stated that 
after further consideration of the issue, we had determined not to move 
forward with our proposal and planned to revisit the issue of section 
1115 demonstration days in future rulemaking (86 FR 73418).
    After considering the comments we received in response to the FY 
2022 IPPS/LTCH PPS proposed rule, we continue to believe that, in order 
for days associated with section 1115 demonstrations to be counted in 
the numerator of the Medicaid fraction, the statute requires those days 
to be of patients who can be ``regarded as'' eligible for Medicaid. 
Accordingly, we propose to modify our regulations to explicitly state 
our view that ``regarded as eligible'' for Medicaid only includes 
patients who receive health insurance through a section 1115 
demonstration where state expenditures to provide the insurance may be 
matched with funds from Title XIX. Furthermore, we believe that it is 
appropriate, and therefore propose, to use our discretion under the Act 
to include only the days of patients ``regarded as'' eligible for 
Medicaid who receive health insurance through a section 1115 
demonstration that provides essential health benefits (EHB) as set 
forth in 42 CFR part 440, subpart C, for an Alternative Benefit Plan, 
which is a uniform benchmark and a standard that is broadly used. This 
would be a change from the current regulation that

[[Page 28401]]

requires a demonstration only provide inpatient hospital benefits for 
days to be counted in the DSH calculation. We believe that by applying 
the standard of EHB to identify which section 1115 days may be included 
in the DSH calculation, both providers and CMS contractors will be able 
to distinguish between section 1115 demonstrations, or parts of 
demonstrations, that provide benefits to individuals whose patient days 
are properly counted in the Medicaid fraction from those demonstrations 
or parts of demonstrations (like uncompensated/undercompensated care 
pools) that are not properly included.
    Consistent with our interpretation of the Medicare DSH statute, the 
evolution of our policy on counting section 1115 demonstration days in 
the Medicaid fraction of the Medicare DSH calculation as set forth in 
our regulations, and considering the series of adverse cases 
interpreting the current regulation, we are proposing to amend the 
regulation to preclude counting days of patients associated with 
uncompensated/undercompensated care pools in the numerator of the 
Medicaid fraction. While these pools may result in hospitals receiving 
some payment for inpatient hospital services they provide to uninsured 
or underinsured individuals, such payments are not a form of health 
insurance and do not entitle any particular individual to any specific 
benefit. Rather, payments from uncompensated/undercompensated care 
pools essentially function as supplemental Medicaid DSH payments. As we 
have consistently stated, individuals eligible for benefits under Title 
XIX are eligible for specific benefits related to the provision of 
inpatient hospital services (in the form of inpatient hospital 
insurance). Because funding pool payments to hospitals do not inure to 
any specific individual, nor do uncompensated/undercompensated care 
pools provide any health insurance to any patient, it cannot reasonably 
be argued that patients associated with uncompensated care for which 
hospitals are reimbursed through section 1115 demonstration-authorized 
funding pools may be ``regarded as'' eligible for Medicaid. Individuals 
who receive health insurance through a section 1115 demonstration are 
being treated as if they were eligible for Medicaid. In contrast, 
uninsured or underinsured individuals, whether or not they benefit from 
uncompensated care pool payments to hospitals, do not have health 
insurance provided by the Medicaid program. Thus, we continue to 
believe that days associated with uncompensated/undercompensated care 
pools must be excluded from the Medicaid fraction of the Medicare DSH 
calculation.
    Even if the statute could be read to permit patient groups whose 
uncompensated care is paid for from a section 1115 demonstration-
authorized funding pool to be ``regarded as'' eligible for Medicaid 
(which the Secretary does not agree the statute permits), those groups 
may be quite distinct from the groups who are eligible for Medicaid 
under a State plan, and therefore we are proposing to use our 
discretion under section 1886(d)(5)(F)(vi) of the Act to exclude from 
the Medicaid fraction the days of patients whose care costs may be 
reimbursed to the hospitals through uncompensated/undercompensated care 
pools.
    However, in further considering the comments regarding the 
treatment of the days of patients provided premium assistance through a 
section 1115 demonstration, we have concluded that patients receiving 
premium assistance through a section 1115 demonstration to purchase 
health insurance can be ``regarded as'' eligible for Medicaid under 
section 1886(d)(5)(F)(vi). Indeed, it may be difficult to distinguish 
between a patient who receives 100 percent, or nearly 100 percent 
(``all or substantially all,'' as defined below), in premium assistance 
under a section 1115 demonstration to purchase health insurance from a 
patient who is eligible for medical assistance under the State plan and 
may be enrolled in a Medicaid managed care plan. Both patients receive 
health insurance funded through a program of cooperative federalism and 
paid for with Title XIX funds. Therefore, upon further review we 
propose, for purposes of the DSH calculation, to ``regard as'' eligible 
for Medicaid those patients who use premium assistance they obtain 
through a section 1115 demonstration to buy and pay for all or 
substantially all (as defined below) of the cost of the health 
insurance.
    Additionally, using the discretion granted to the Secretary under 
section 1886(d)(5)(F)(vi) of the Act to determine the extent to which 
patient days of patients ``regarded as'' eligible for Medicaid will be 
included in the Medicaid fraction, we further propose to include in the 
Medicaid fraction only those days of patients who have bought health 
insurance that provides EHB using premium assistance obtained through a 
section 1115 demonstration that is equal to at least 90 percent of the 
cost of the health insurance. As some commenters pointed out, some 
section 1115 demonstrations that provide premium assistance to 
enrollees require the insurance bought to be offered through the 
State's Health Insurance Exchange, and as a result the insurance that 
is available under these demonstrations is individual health insurance 
that is required to provide EHB, including inpatient hospital benefits. 
Further, we believe ``all or substantially all'' in the context of 
purchasing hospital insurance with premium assistance requires the 
premium assistance be equal to at least 90 percent of the cost of the 
insurance. We picked people who receive premium assistance of at least 
90 percent of the cost of the hospital insurance that provides EHB 
because this level of benefit is similar to the benefits received by 
individuals who are eligible for Title XIX programs, and as such, it 
would be appropriate to include the days of these individuals in the 
numerator of the Medicaid fraction, if the individual is also not 
entitled to benefits under Medicare Part A. Individuals who receive 
less premium assistance are not receiving benefits similar to the 
benefits received by individuals eligible for Medicaid under a State 
plan. Therefore, we believe it is appropriate to exclude from the 
Medicaid fraction days of individuals who use premium assistance to buy 
health insurance that does not provide EHB or for whom the premium 
assistance provided by the demonstration accounts for less than 90 
percent of the cost of the health insurance. Individual health 
insurance that is not grandfathered coverage, which is required to 
identify itself as grandfathered, is generally required to provide EHB. 
Additionally, depending on the state, information on health insurance 
that provides EHB may be available directly from individual states (for 
example, through a state's Insurance Commissioner).
    Accordingly, in this proposed rule, we are proposing to revise our 
regulations at Sec.  412.106(b)(4) to explicitly reflect our 
interpretation of the language ``regarded as'' ``eligible for medical 
assistance under a State plan approved under title XIX'' in section 
1886(d)(5)(F)(vi) of the Act, to mean patients who receive health 
insurance through a section 1115 demonstration itself or purchase such 
insurance with the use of premium assistance provided by a section 1115 
demonstration. Moreover, of the groups we ``regard'' as Medicaid 
eligible, we propose that only the days of those individuals that 
obtain health insurance that provides EHB (defined as meeting the EHB 
requirements set forth in 42 CFR part

[[Page 28402]]

440, subpart C, for an Alternative Benefit Plan), and if bought with 
premium assistance, for which the premium assistance is equal to or 
greater than 90 percent of the cost of the health insurance, are 
included in the Medicaid fraction of the DSH calculation, provided the 
patient is not also entitled to Medicare Part A.
    As discussed previously, uncompensated/undercompensated care pools 
serve essentially the same function as Medicaid DSH by indirectly 
subsidizing the cost of treating the uninsured and underinsured, while 
not extending health insurance to additional groups. Accordingly, we do 
not interpret the statute as authorizing the Secretary to ``regard as'' 
Medicaid eligible patients with uncompensated care costs for which a 
hospital is reimbursed by a section 1115 demonstration-authorized 
uncompensated care funding pool. Additionally, even if section 
1886(d)(5)(F)(vi) of the Act could be interpreted to permit patients 
with uncompensated care costs for which a hospital is reimbursed by a 
demonstration funding pool to be ``regarded as'' Medicaid eligible, we 
invoke our discretion to exclude such patient days from being counted 
in the Medicaid fraction of the DSH payment calculation because 
uncompensated/undercompensated care pools do not provide health 
insurance to individuals.
    We propose that these changes would be effective for discharges 
occurring on or after October 1, 2022.

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 2023 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 2023, we are setting the applicable percentage 
increase by applying the adjustments listed in this section in the same 
sequence as we did for FY 2022. (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 2023 is equal to the rate-of-increase in the hospital market 
basket for IPPS hospitals in all areas, subject to all of the 
following:
     A reduction of one-quarter of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals that fail to submit quality information 
under rules established by the Secretary in accordance with section 
1886(b)(3)(B)(viii) of the Act.
     A reduction of three-quarters of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals not considered to be meaningful EHR users 
in accordance with section 1886(b)(3)(B)(ix) of the Act.
     An adjustment based on changes in economy-wide multifactor 
productivity (MFP) (the productivity adjustment).
    Section 1886(b)(3)(B)(xi) of the Act, as added by section 3401(a) 
of the Affordable Care Act, states that application of the productivity 
adjustment may result in the applicable percentage increase being less 
than zero.
    We note, in compliance with section 404 of the MMA, in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45194 through 45204), we replaced the 
2014-based IPPS operating and capital market baskets with the rebased 
and revised 2018-based IPPS operating and capital market baskets 
beginning in FY 2022.
    We are proposing to base the FY 2023 market basket update used to 
determine the applicable percentage increase for the IPPS on IHS Global 
Inc.'s (IGI's) fourth quarter 2021 forecast of the 2018-based IPPS 
market basket rate-of-increase with historical data through third 
quarter 2021, which is estimated to be 3.1 percent. We also are 
proposing that if more recent data subsequently become available (for 
example, a more recent estimate of the market basket update), we would 
use such data, if appropriate, to determine the FY 2023 market basket 
update in 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 
productivity adjustment. As we explained in that rule, section 
1886(b)(3)(B)(xi)(II) of the Act, as added by section 3401(a) of the 
Affordable Care Act, defines this productivity adjustment as equal to 
the 10-year moving average of changes in annual economy-wide, private 
nonfarm business MFP (as projected by the Secretary for the 10-year 
period ending with the applicable fiscal year, calendar year, cost 
reporting period, or other annual period). The U.S. Department of 
Labor's Bureau of Labor Statistics (BLS) publishes the official 
measures of productivity for the U.S. economy. We note that previously 
the productivity measure referenced in section 1886(b)(3)(B)(xi)(II) 
was published by BLS as private nonfarm business multifactor 
productivity. Beginning with the November 18, 2021 release of 
productivity data, BLS replaced the term multifactor productivity (MFP) 
with total factor productivity (TFP). BLS noted that this is a change 
in terminology only and will not affect the data or methodology. As a 
result of the BLS name change, the productivity measure referenced in 
section 1886(b)(3)(B)(xi)(II) is now published by BLS as private 
nonfarm business total factor productivity. However, as mentioned, the 
data and methods are unchanged. Please see www.bls.gov for the BLS 
historical published TFP data. A complete description of IGI's TFP 
projection methodology is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch. In addition, we 
note that beginning with the FY 2022 final rule, we refer to this 
adjustment as the productivity adjustment rather than the MFP 
adjustment to more closely track the statutory language in section 
1886(b)(3)(B)(xi)(II) of the Act. We note that the adjustment continues 
to rely on the same underlying data and methodology.
    For FY 2023, we are proposing a productivity adjustment of 0.4 
percent. Similar to the market basket update, for this proposed rule, 
the estimate of the proposed FY 2023 productivity adjustment is based 
on IGI's fourth quarter 2021 forecast 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 2023 
productivity adjustment for the final rule.
    Based on these data, we have determined four proposed applicable 
percentage increases to the standardized amount for FY 2023, as 
specified in the following table:

[[Page 28403]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.159

    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42344), we revised 
our regulations at 42 CFR 412.64(d) to reflect the current law for the 
update for FY 2020 and subsequent fiscal years. Specifically, in 
accordance with section 1886(b)(3)(B) of the Act, we added paragraph 
(d)(1)(viii) to Sec.  412.64 to set forth the applicable percentage 
increase to the operating standardized amount for FY 2020 and 
subsequent fiscal years as the percentage increase in the market basket 
index, subject to the reductions specified under Sec.  412.64(d)(2) for 
a hospital that does not submit quality data and Sec.  412.64(d)(3) for 
a hospital that is not a meaningful EHR user, less a productivity 
adjustment. (As previously noted, section 1886(b)(3)(B)(xii) of the Act 
required an additional reduction each year only for FYs 2010 through 
2019.)
    Section 1886(b)(3)(B)(iv) of the Act provides that the applicable 
percentage increase to the hospital-specific rates for SCHs 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 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). Therefore, under current law, 
the MDH program will expire at the end of FY 2022. We refer readers to 
section V.D. of the preamble of this proposed rule for further 
discussion of the expiration of the MDH program.
    For FY 2023, we are proposing the following updates to the 
hospital-specific rates applicable to SCHs: A proposed update of 2.7 
percent for a hospital that submits quality data and is a meaningful 
EHR user; a proposed update of 0.375 percent for a hospital that 
submits quality data and is not a meaningful EHR user; a proposed 
update of 1.925 percent for a hospital that fails to submit quality 
data and is a meaningful EHR user; and a proposed update of -0.4 
percent for a hospital that fails to submit quality data and is not an 
meaningful EHR user. As noted previously, for this proposed rule, the 
FY 2023 market basket update is based on IGI's fourth quarter 2021 
forecast of the 2018-based IPPS market basket with historical data 
through third quarter 2021. Similarly, for this proposed rule, the FY 
2023 productivity adjustment is based on IGI's fourth quarter 2021 
forecast. We are proposing that if more recent data subsequently become 
available (for example, a more recent estimate of the market basket 
update and the productivity adjustment), we would use such data, if 
appropriate, to determine the update in the final rule.
2. Proposed FY 2023 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 2023, consistent with section 1886(b)(3)(B) of the Act, as 
amended by section 602 of Public Law 114-113, we

[[Page 28404]]

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 66\2/3\ percent reduction to three-fourths of the applicable 
percentage increase (prior to the application of other statutory 
adjustments; also referred to as the market basket update or rate-of-
increase (with no adjustments)) for Puerto Rico hospitals not 
considered to be meaningful EHR users in accordance with section 
1886(b)(3)(B)(ix) of the Act, and then subject to the productivity 
adjustment at section 1886(b)(3)(B)(xi) of the Act. As noted 
previously, section 1886(b)(3)(B)(xi) of the Act states that 
application of the productivity adjustment may result in the applicable 
percentage increase being less than zero.
    Based on IGI's fourth quarter 2021 forecast of the 2018-based IPPS 
market basket update with historical data through third quarter 2021, 
for this FY 2023 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 3.1 percent and a 
productivity adjustment of 0.4 percent. Therefore, for FY 2023, 
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 2023 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 2023 
operating standardized amount of 2.7 percent (that is, the FY 2023 
estimate of the proposed market basket rate-of-increase of 3.1 percent 
less an adjustment of 0.4 percentage point for the proposed 
productivity 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 1.15 percent (that is, the FY 2023 
estimate of the proposed market basket rate-of-increase of 3.1 percent, 
less an adjustment of 1.55 percentage point (the proposed market basket 
rate-of-increase of 3.1 percent x 0.75 x (\2/3\) for failure to be a 
meaningful EHR user), and less an adjustment of 0.4 percentage point 
for the proposed productivity 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 2023 market basket update and the productivity 
adjustment for the FY 2023 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
     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.
    In the FY 2022 final rule (86 FR 45217), in light of the COVID-19 
PHE, we amended the regulations at 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. We also 
amended the regulations at Sec.  412.96(c)(1) to indicate that the 
individual hospital's CMI value for discharges during the same Federal 
fiscal year used to compute the national and regional CMI values is 
used for purposes of determining whether a hospital qualifies for RRC 
classification. We also amended the regulations 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.
1. 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). The proposed national 
median CMI value for FY 2023 is based on the CMI values of all urban 
hospitals nationwide, and the proposed regional

[[Page 28405]]

median CMI values for FY 2023 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). 
These proposed values are based on discharges occurring during FY 2021 
(October 1, 2020 through September 30, 2021), and include bills posted 
to CMS' records through December 2021. We believe that this is the best 
available data for use in calculating the proposed national and 
regional median CMI values and is consistent with our proposal to use 
the FY 2021 MedPAR claims data for FY 2023 ratesetting. We refer the 
reader to section I.F. of the preamble of this proposed rule for a 
complete discussion regarding our proposal to use the latest available 
data (that is, the FY 2021 MedPAR data) as the best available data for 
purposes of this FY 2023 rulemaking.
    In this FY 2023 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, 2022, they must have a CMI 
value for FY 2021 that is at least--
     1.8251 (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 intend to update the proposed CMI 
values in the FY 2023 final rule to reflect the updated FY 2021 MedPAR 
file, which will contain data from additional bills received through 
March 2022.
[GRAPHIC] [TIFF OMITTED] TP10MY22.160

    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 2023, we are 
proposing to update the regional standards based on discharges for 
urban hospitals' cost reporting periods that began during FY 2020 (that 
is, October 1, 2019 through September 30, 2020), which are the latest 
cost report data available at the time this proposed rule was 
developed. We believe that this is the best available data for use in 
calculating the proposed median number of discharges by region and is 
consistent with our data proposal to use cost report data from cost 
reporting periods beginning during FY 2020 for FY 2023 ratesetting. We 
refer the reader to section I.F. of the preamble of this proposed rule 
for a complete discussion regarding our proposal to use the latest 
available data (that is, cost reports beginning during FY 2020) as the 
best available data for purposes of this FY 2023 rulemaking. 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, 2022, must have, as the number 
of discharges for its cost reporting period that began during FY 2020, 
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 as set forth in this 
table. We intend to update these numbers in the FY 2023 final rule 
based on the latest available cost report data.

[[Page 28406]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.161

    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. Expiration of Temporary Changes to Low-Volume Hospital Payment 
Policy
    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 under section 1886(d)(12) of the Act for FYs 2019 through 
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, and the preexisting 
low-volume hospital payment adjustment methodology and qualifying 
criteria, as implemented in FY 2005 and discussed later in this 
section, will resume. (For additional information on the temporary 
changes to the low-volume hospital payment policy, we refer readers to 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 through 41401). We 
also note, in that same final rule, we amended the regulations at 42 
CFR 412.101 to reflect the provisions of section 50204 of the 
Bipartisan Budget Act of 2018.) We discuss the proposed payment 
policies for FY 2023 in section V.C.3. of the preamble of this proposed 
rule.
2. Background
    Section 1886(d)(12) of the Act provides for an additional payment 
to each qualifying low-volume hospital under the IPPS beginning in FY 
2005. The additional payment adjustment to a low-volume hospital 
provided for under section 1886(d)(12) of the Act is in addition to any 
payment calculated under section 1886 of the Act. Therefore, the 
additional payment adjustment is based on the per discharge amount paid 
to the qualifying hospital under section 1886 of the Act. In other 
words, the low-volume hospital payment adjustment is based on total per 
discharge payments made under section 1886 of the Act, including 
capital, DSH, IME, and outlier payments. For SCHs and MDHs, the low-
volume hospital payment adjustment is based in part on either the 
Federal rate or the hospital-specific rate, whichever results in a 
greater operating IPPS payment.
    As discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45219 
through 45221), 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. 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 determines 
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).
    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. Section 1886(d)(12)(C)(i) of the Act 
defines a low-volume hospital, for FYs 2005 through 2010 and FY 2023 
and subsequent years, as a subsection (d) hospital that the Secretary 
determines is located more than 25 road miles from another subsection 
(d) hospital and that has less than 800 discharges during the fiscal 
year. Section 1886(d)(12)(C)(ii) of the Act further stipulates that the 
term ``discharge'' means an inpatient acute care discharge of an 
individual, regardless of whether the individual is entitled to 
benefits under Medicare Part A (except with respect to FYs 2011 through 
2018). Therefore, for FYs 2005 through 2010 and FY 2019 and subsequent 
years, the term ``discharge'' refers to total discharges, regardless of 
payer (that is, Medicare and non-Medicare discharges), and as such the 
term discharge continues to refer to total discharges for FY 2023 and 
subsequent years. Furthermore, section 1886(d)(12)(B) of the Act 
requires, for discharges occurring in FYs 2005 through 2010 and FY 2023 
and subsequent years, that the Secretary determine an applicable 
percentage increase for these low-volume hospitals based on the 
``empirical relationship'' between the standardized cost-per-case for 
such hospitals and the total number of discharges of such hospitals and 
the amount of the additional incremental costs (if any) that are 
associated with such number of discharges. The statute thus mandates 
that the Secretary develop an empirically justifiable adjustment based 
on the relationship

[[Page 28407]]

between costs and discharges for these low-volume hospitals. Section 
1886(d)(12)(B)(iii) of the Act limits the applicable percentage 
increase adjustment to no more than 25 percent.
    Based on an analysis we conducted for the FY 2005 IPPS final rule 
(69 FR 49099 through 49102), a 25-percent low-volume adjustment to all 
qualifying hospitals with less than 200 discharges was found to be most 
consistent with the statutory requirement to provide relief to low-
volume hospitals where there is empirical evidence that higher 
incremental costs are associated with low numbers of total discharges. 
In the FY 2006 IPPS final rule (70 FR 47432 through 47434), we stated 
that multivariate analyses supported the existing low-volume adjustment 
implemented in FY 2005. Accordingly, under the existing regulations, in 
order for a hospital to continue to qualify as a low-volume hospital on 
or after October 1, 2022, it must have fewer than 200 total discharges 
during the fiscal year and be located more than 25 road miles from the 
nearest ``subsection (d)'' hospital (see Sec.  412.101(b)(2)(i)). (For 
additional information on the low-volume hospital payment adjustment 
prior to FY 2018, we refer readers to the FY 2017 IPPS/LTCH PPS final 
rule (81 FR 56941 through 56943). For additional information on the 
low-volume hospital payment adjustment for FY 2018, we refer readers to 
the FY 2018 IPPS notice (CMS-1677-N) that appeared in the April 26, 
2018, Federal Register (83 FR 18301 through 18308). For additional 
information on the low-volume hospital payment adjustment for FY 2019 
through FY 2022, we refer readers to the FY 2019 IPPS/LTCH PPS final 
rule (83 FR 41398 through 41399).)
3. Proposed Payment Adjustment for FY 2023 and Subsequent Fiscal Years
    In accordance with section 1886(d)(12) of the Act, beginning with 
FY 2023, the low-volume hospital definition and payment adjustment 
methodology will revert back to the statutory requirements that were in 
effect prior to the amendments made by the Affordable Care Act and 
subsequent legislation. Therefore, effective for FY 2023 and subsequent 
years, under current policy at Sec.  412.101(b), in order to qualify as 
a low-volume hospital, a subsection (d) hospital must be more than 25 
road miles from another subsection (d) hospital and have less than 200 
discharges (that is, less than 200 discharges total, including both 
Medicare and non-Medicare discharges) during the fiscal year. For FY 
2023 and subsequent years, the statute specifies that a low-volume 
hospital must have less than 800 discharges during the fiscal year. 
However, as required by section 1886(d)(12)(B)(i) of the Act and as 
discussed earlier, the Secretary has developed an empirically 
justifiable payment adjustment based on the relationship, for IPPS 
hospitals with less than 800 discharges, between the additional 
incremental costs (if any) that are associated with a particular number 
of discharges. Based on an analysis we conducted for the FY 2005 IPPS 
final rule (69 FR 49099 through 49102), a 25-percent low-volume 
adjustment to all qualifying hospitals with less than 200 discharges 
was found to be most consistent with the statutory requirement to 
provide relief for low-volume hospitals where there is empirical 
evidence that higher incremental costs are associated with low numbers 
of total discharges. (Under the policy we established in that same 
final rule, hospitals with between 200 and 799 discharges do not 
receive a low-volume hospital adjustment.)
    For FYs 2005 through 2010 and FY 2018 and subsequent years, the 
discharge determination is made based on the hospital's number of total 
discharges, that is, Medicare and non-Medicare discharges. The 
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 (Sec.  412.101(b)(2)(i)). 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. We note that, 
for FYs 2011 through 2018, we used the most recently available MedPAR 
data to determine the hospital's Medicare discharges because only 
Medicare discharges were used to determine if a hospital met the 
discharge criterion for those years.
    In addition to the discharge criterion, a hospital must also meet 
the mileage criterion to qualify for the low-volume payment adjustment. 
As specified by section 1886(d)(12)(C)(i) of the Act, a low-volume 
hospital must be more than 25 road miles (or 15 road miles for FYs 2011 
through 2022) from another subsection (d) hospital. Accordingly, for FY 
2023 and for subsequent fiscal years, in addition to the discharge 
criterion, the eligibility for the low-volume payment adjustment is 
also dependent upon the hospital meeting the mileage criterion at Sec.  
412.101(b)(2)(i), which specifies that a hospital must be located more 
than 25 road miles from the nearest subsection (d) hospital, consistent 
with section 1886(d)(12)(C)(i) of the Act. We define, at Sec.  
412.101(a), the term ``road miles'' to mean ``miles'' as defined at 
Sec.  412.92(c)(1) (75 FR 50238 through 50275 and 50414).
4. 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, most recently in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45219 through 45221), 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, 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

[[Page 28408]]

discharges were not used to determine if a hospital met the discharge 
criterion for those years.) Therefore, a hospital must refer to its 
most recently submitted cost report for total discharges (Medicare and 
non-Medicare) 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 2023, a hospital must 
be located more than 25 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). 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.
    Consistent with this previously established process, for FY 2023, 
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). Specifically, 
for FY 2023, a hospital must make a written request for low-volume 
hospital status that is received by its MAC no later than September 1, 
2022, in order for the 25-percent, low-volume, add-on payment 
adjustment to be applied to payments for its discharges beginning on or 
after October 1, 2022. If a hospital's written request for low-volume 
hospital status for FY 2023 is received after September 1, 2022, 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 2023 
discharges, effective prospectively within 30 days of the date of the 
MAC's low-volume hospital status determination.
    Under this process, a hospital that qualified for the low-volume 
hospital payment adjustment for FY 2022 may continue to receive a low-
volume hospital payment adjustment for FY 2023 without reapplying if it 
meets both the discharge criterion and the mileage criterion applicable 
for FY 2023. As discussed previously, for FY 2023 the discharge and the 
mileage criteria are reverting to the statutory requirements that were 
in effect prior to FY 2011, and to the preexisting low-volume hospital 
qualifying criteria, as implemented in FY 2005 and specified in the 
existing regulations at Sec.  412.101(b)(2)(i). As in previous years, 
we are proposing that such a hospital must send written verification 
that is received by its MAC no later than September 1, 2022, stating 
that it meets the mileage criterion applicable for FY 2023 (that is, is 
located more than 25 road miles from the nearest ``subsection (d)'' 
hospital). For FY 2023, we are further proposing that this written 
verification must also state, based upon the most recently submitted 
cost report, that the hospital meets the discharge criterion applicable 
for FY 2023 (that is, less than 200 discharges total, including both 
Medicare and non-Medicare discharges). If a hospital's request for low-
volume hospital status for FY 2023 is received after September 1, 2022, 
and if the MAC determines the hospital meets the criteria to qualify as 
a low-volume hospital, the MAC will apply the 25-percent, low-volume, 
add-on payment adjustment to determine the payment for the hospital's 
FY 2023 discharges, effective prospectively within 30 days of the date 
of the MAC's low-volume hospital status determination.
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 through 41401 
and 41702), in accordance with the provisions of section 50204 of the 
Bipartisan Budget Act of 2018, for FY 2023 and subsequent fiscal years, 
we made conforming changes to the regulations at 42 CFR 412.101 to 
reflect that the low-volume payment adjustment policy in effect for 
these years is the same low-volume hospital payment adjustment policy 
in effect for FYs 2005 through 2010. Under these revisions, beginning 
with FY 2023, consistent with current law, the low-volume hospital 
qualifying criteria and payment adjustment methodology will return to 
the criteria and methodology that were in effect prior to the 
amendments made by the Affordable Care Act (that is, the low-volume 
hospital payment policy in effect for FYs 2005 through 2010). 
Therefore, no further revisions to the policy or to the regulations at 
Sec.  412.101 are required to conform them to the statutory requirement 
that the low-volume hospital policy in effect prior to the Affordable 
Care Act will again be in effect for FY 2023 and subsequent years.

D. Proposed Changes in the Medicare-Dependent, Small Rural Hospital 
(MDH) Program (Sec.  412.108)

1. Background for the MDH Program
    Section 1886(d)(5)(G) of the Act provides special payment 
protections, under the IPPS, to a Medicare-dependent, small rural 
hospital (MDH). (For additional information on the MDH program and the 
payment methodology, we refer readers to the FY 2012 IPPS/LTCH PPS 
final rule (76 FR 51683 through 51684).) As discussed in section VB of 
the preamble of this proposed rule, the MDH program provisions at 
section 1886(d)(5)(G) of the Act will expire at the end of FY 2022. 
Beginning with discharges occurring on or after October 1, 2022, all 
hospitals that previously qualified for MDH status will be paid based 
on the Federal rate.
    Since the extension of the MDH program through FY 2012 provided by 
section 3124 of the Affordable Care Act, the MDH program had been 
extended by subsequent legislation as follows: Section 606 of the ATRA 
(Pub. L. 112- 240) extended the MDH program through FY 2013 (that is, 
for discharges occurring before October 1, 2013). Section 1106 of the 
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67) extended the MDH 
program through the

[[Page 28409]]

first half of FY 2014 (that is, for discharges occurring before April 
1, 2014). Section 106 of the PAMA (Pub. L. 113-93) extended the MDH 
program through the first half of FY 2015 (that is, for discharges 
occurring before April 1, 2015). Section 205 of the MACRA (Pub. L. 114-
10) extended the MDH program through FY 2017 (that is, for discharges 
occurring before October 1, 2017). Section 50205 of the Bipartisan 
Budget Act (Pub. L. 115- 123) extended the MDH program through FY 2022 
(that is for discharges occurring before October 1, 2022). For 
additional information on the extensions of the MDH program after FY 
2012, we refer readers to the following Federal Register documents: The 
FY 2013 IPPS/LTCH PPS final rule (77 FR 53404 through 53405 and 53413 
through 53414); the FY 2013 IPPS notification (78 FR 14689); the FY 
2014 IPPS/LTCH PPS final rule (78 FR 50647 through 50649); the FY 2014 
interim final rule with comment period (79 FR 15025 through 15027); the 
FY 2014 notification (79 FR 34446 through 34449); the FY 2015 IPPS/LTCH 
PPS final rule (79 FR 50022 through 50024); the August 2015 interim 
final rule with comment period (80 FR 49596); the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57054 through 57057); the FY 2018 notice (83 FR 18303 
through 18305); and the FY 2019 IPPS/LTCH PPS final rule (83 FR 41429).
2. Expiration of the MDH Program
    Because section 50205 of the Bipartisan Budget Act extended the MDH 
program through FY 2022 only, beginning October 1, 2022, the MDH 
program will no longer be in effect. Because the MDH program is not 
authorized by statute beyond September 30, 2022, beginning October 1, 
2022, all hospitals that previously qualified for MDH status under 
section 1886(d)(5)(G) of the Act will no longer have MDH status and 
will be paid based on the IPPS Federal rate.
    When the MDH program was set to expire at the end of FY 2012, in 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53404 through 53405), we 
revised our sole community hospital (SCH) policies to allow MDHs to 
apply for SCH status in advance of the expiration of the MDH program 
and be paid as such under certain conditions. We codified these changes 
in the regulations at Sec.  412.92(b)(2)(i) and (v). Specifically, the 
existing regulations at Sec.  412.92(b)(2)(i) and (v) allow for an 
effective date of an approval of SCH status that is the day following 
the expiration date of the MDH program. We note that these same 
conditions apply to MDHs that intend to apply for SCH status with the 
expiration of the MDH program on September 30, 2022. Therefore, in 
order for an MDH to receive SCH status effective October 1, 2022, the 
MDH must apply for SCH status at least 30 days before the expiration of 
the MDH program; that is, the MDH must apply for SCH status by 
September 1, 2022. The MDH also must request that, if approved as an 
SCH, the SCH status be effective with the expiration of the MDH 
program; that is, the MDH must request that the SCH status, if 
approved, be effective October 1, 2022, immediately after its MDH 
status expires with the expiration of the MDH program on September 30, 
2022. We emphasize that an MDH that applies for SCH status in 
anticipation of the expiration of the MDH program would not qualify for 
the October 1, 2022, effective date for SCH status if it does not apply 
by the September 1, 2022, deadline. If the MDH does not apply by the 
September 1, 2022, deadline, the hospital would instead be subject to 
the usual effective date for SCH classification; that is, as of the 
date the MAC receives the complete application as specified at Sec.  
412.92(b)(2)(i).
    We note that the regulations governing the MDH program are found at 
Sec.  412.108 and the MDH program is also cited in the general payment 
rules in the regulations at Sec.  412.90. As stated earlier, under 
current law, the MDH program will expire at the end of FY 2022, which 
is already reflected in Sec. Sec.  412.108 and 412.90(j). As such, we 
are not proposing specific amendments to the regulations at Sec.  
412.108 or Sec.  412.90 to reflect the expiration of the MDH program. 
However, we are proposing that if the MDH program were to be extended 
by law, similar to how it was extended through FY 2013, by the ATRA 
(Pub. L. 112-240); through March 31, 2014, by the Pathway for SGR 
Reform Act of 2013 (Pub. L. 113-167); through March 31, 2015, by the 
PAMA (Pub. L. 113-93); through FY 2017, by the MACRA (Pub. L. 114-10); 
and most recently through FY 2022, by the Bipartisan Budget Act of 2018 
(Pub. L. 115-123), we would make conforming changes to the regulations 
governing the MDH program at Sec.  412.108(a)(1) and (c)(2)(iii) and 
the general payment rules at Sec.  412.90(j) to reflect such an 
extension of the MDH program. These conforming changes would only be 
made if the MDH program were to be extended by statute beyond September 
30, 2022.

E. 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 
2023, the formula multiplier is 1.35. We estimate that application of 
this formula multiplier for the FY 2023 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.

F. 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

[[Page 28410]]

hospital's Medicare share of total inpatient days.
    Section 1886(d)(5)(B) of the Act provides for a payment adjustment 
known as the indirect medical education (IME) adjustment under the IPPS 
for hospitals that have residents in an approved GME program, in order 
to account for the higher indirect patient care costs of teaching 
hospitals relative to nonteaching hospitals. The regulations regarding 
the calculation of this additional payment are located at 42 CFR 
412.105. The hospital's IME adjustment applied to the DRG payments is 
calculated based on the ratio of the hospital's number of FTE residents 
training in either the inpatient or outpatient departments of the IPPS 
hospital (and, for discharges occurring on or after October 1, 1997, at 
non-provider sites, when applicable) 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.
a. Direct GME Payment Formula
    As mentioned previously, 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(h)(4) of the Act 
specifies the methodology for determining the amount of FTE residents 
to be included in a hospital's direct GME payment formula. That is, the 
number of FTE residents training at a hospital (or in non-provider 
sites as applicable) would not necessarily equal the sum of those FTE 
residents used in the hospital's direct GME payment formula, since 
certain rules and factors are applied to adjust the count of FTE 
residents for direct GME payment purposes. First, section 1886(h)(4)(C) 
of the Act requires that a ``weighting factor'' of either 1.0 or 0.5 be 
applied to each FTE resident, as follows: In calculating the number of 
FTE residents in an approved residency program on or after July 1, 
1987, for a resident who is not in the resident's initial residency 
period, the weighting factor is 0.50. Section 1886(h)(5)(F) of the Act 
defines the term ``initial residency period'' as the ``period of board 
eligibility,'' with certain exceptions. Finally, section 1886(h)(4)(G) 
of the Act states that the term ``period of board eligibility'' means, 
for a resident, the minimum number of years of formal training 
necessary to satisfy the requirements for initial board eligibility in 
the particular specialty for which the resident is training. The direct 
GME calculation and our policy on applying the weighting factors to 
each FTE resident based on the FTE resident's status within or beyond 
the initial residency period (IRP) was established in the September 29, 
1989, Federal Register (54 FR 40287, 40292, 40305-6), and implemented 
in the regulations at 42 CFR 413.86(f) (now 42 CFR 413.79(a) and (b)).
    Thus, the FTE count used in the direct GME payment formula must be 
a weighted FTE count when a hospital is training residents beyond their 
IRPs. However, the direct GME FTE cap is an unweighted number. That is, 
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 (that is the 
hospital's unweighted 1996 FTE cap or FTE cap). Regulations regarding 
the FTE caps and unweighted FTE counts were first published in the 
August 29, 1997, Federal Register. To address situations where a 
hospital's weighted FTE count exceeds its unweighted 1996 FTE cap, we 
established a policy effective for cost reporting periods beginning on 
or after October 1, 1997, to bring the weighted FTE count within the 
unweighted FTE cap using the following ratio on the Medicare cost 
report: ((1996 unweighted FTE cap/current year unweighted FTE count) x 
(current year total weighted FTE count)) (see 62 FR 46005 and 63 FR 
26,330 (May 12, 1998)). In the August 1, 2001, Federal Register (66 FR 
39893 through 39896), we modified this ratio effective for cost 
reporting periods beginning on or after October 1, 2001, to separately 
account for a hospital's current year weighted primary care and 
obstetrics/gynecology (OB/GYN) FTE count and primary care and OB/GYN 
PRA, and current year weighted other FTE count and other PRA, as 
follows: (FTE cap/unweighted total FTEs in the cost reporting period) x 
(weighted primary care and OB/GYN FTEs in the cost reporting period) 
plus (FTE cap/unweighted total FTEs in the cost reporting period) x 
(weighted nonprimary care FTEs in the cost reporting period). The sum 
of the products is the current year allowable weighted FTE count. In 
addition, effective for cost reporting periods beginning on or after 
October 1, 2001, the direct GME payment is calculated using two 
separate rolling averages, one for primary care and OB/GYN FTE 
residents, and one for nonprimary care FTE residents. These 
calculations were implemented at 42 CFR 413.86(g)(4) and (5) 
respectively, currently 42 CFR 413.79(c)(2)(iii) and (d)(3).
2. Milton S. Hershey Medical Center, et al. v. Becerra Litigation
    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME payments 
to teaching hospitals when those hospitals' weighted FTE counts exceed 
their direct GME FTE cap. In Milton S. Hershey Medical Center, et al. 
v. Becerra (Slip. Op., 2021 WL 1966572, May 17, 2021), the court 
ordered CMS to recalculate reimbursement owed, holding that CMS's 
regulation impermissibly modified the statutory weighting factors 
discussed previously. The plaintiffs in these consolidated cases 
alleged that as far back as 2005, the proportional reduction that CMS 
applied to the weighted FTE count when the weighted FTE count exceeded 
the FTE cap conflicted with the Medicare statute, and it was an 
arbitrary and capricious exercise of agency discretion under the 
Administrative Procedure Act. The Court held that the proportional 
reduction methodology improperly modified the weighting factors 
statutorily assigned to residents and fellows. The court ordered CMS to 
pay

[[Page 28411]]

the plaintiffs according to a more favorable method.
    For example, a hospital has a direct GME cap of 100, trains 90 FTE 
residents weighted at 1.0 and 10 FTE fellows weighted at 0.5, for a 
total unweighted count of 100, and a total weighted FTE count of 95. 
Under current methodology, the proportional reduction is:

(100 cap/100 current year unweighted count) x 95 (current year weighted 
count) = 95.

    If that hospital adds 10 more fellows and exceeds the cap with an 
unweighted total of 110 (90 residents and 20 fellows), its weighted FTE 
count of 100 is reduced as follows:

(100 cap/110 current year unweighted count) x 100 (current year 
weighted count) = 90.91.

    The plaintiffs argued that CMS's proportional reduction method 
unlawfully reduced the weighting factor of 0.5 to an amount less than 
that, thereby reducing the capped unweighted FTE amount (100 reduced to 
90.91 in the example) to which they were entitled for direct GME 
payment purposes. The court granted the plaintiffs' motion for summary 
judgment, denied defendant's, and remanded to the Agency so that it 
could recalculate plaintiffs' reimbursement payments consistent with 
the court's opinion. The court held that CMS's proportional reduction 
methodology, enacted at 42 CFR 413.79(c)(2)(iii), was inconsistent with 
the statutory weighting factors. In response to the court's decision, 
we are proposing to implement a modified policy applicable to all 
teaching hospitals, effective as of October 1, 2001, which would 
replace the existing policy at 42 CFR 413.79(c)(2)(iii). While the 
proportional reduction method struck down in Hershey was first 
effective for cost reports beginning on or after October 1, 1997, we 
are unaware of any open or reopenable NPRs for the 1997-2001 period 
where the proportional reduction method caused a provider's payments to 
be lower than they would be under our proposed new policy, but we 
welcome comments alerting us of such NPRs. The proportional reduction 
method was amended to its present form effective for cost reporting 
periods beginning on or after October 2001. See current 42 CFR 
413.79(c)(2)(ii), (iii). We are therefore proposing to modify the 
policy embodied in 42 CFR 413.79(c)(2)(iii), which the Court found 
unlawful in Hershey.
    Because the Hershey court concluded that Sec.  413.79(c)(2)(iii) 
was inconsistent with the statute, and the Secretary did not appeal, 
the Secretary ``has no promulgated rule governing'' DGME payments to 
teaching hospitals over the cap for cost reporting periods beginning on 
or after October 1, 2001. (See Allina Health Servs. v. Price, 863 F.3d 
937, 939 (D.C. Cir. 2017).) The Secretary is required to ``establish 
rules consistent with this paragraph for the computation of the number 
of full-time-equivalent residents in an approved medical residency 
training program'' (42 U.S.C. 1395ww(h)(4)). We believe that, in order 
to comply with the statutory requirement to make rules governing the 
computation of FTEs, it is necessary to engage in a retroactive 
rulemaking to establish the statutorily-required rule effective for 
cost reporting periods beginning on or after October 1, 2001. Doing so 
via notice-and-comment rulemaking is in the public interest because it 
will permit interested stakeholders to comment on the proposed approach 
and allow the agency to have the benefit of those comments in the 
development of a final rule. This is particularly true in this 
situation, where the existing policy was promulgated via an interim 
final rule with comment period, and the agency received no comments on 
the policy the court held unlawful and finalized it as originally 
proposed.
    Because we are proposing to establish this policy retroactively, it 
would cover cost reporting periods for which many NPRs have already 
been final settled. Consistent with Sec.  405.1885(c)(2), any final 
rule retroactively adopting the proposed new policy would not be the 
basis for reopening final settled NPRs.
a. Change to Direct GME Calculation in Response to Decision in Milton 
S. Hershey Medical Center et al. v. Becerra
    After reviewing the statutory language regarding the direct GME FTE 
cap and the court's opinion, we have decided to propose a modified 
policy to be applied for cost reporting periods beginning on October 1, 
2001, as described previously. The proposed modified policy would 
address situations for applying the FTE cap when a hospital's weighted 
FTE count is greater than its FTE cap, but would not reduce the 
weighting factor of residents that are beyond their IRP to an amount 
less than 0.5. Section 1886(h)(4)(F) of the Act states that for 
purposes of a cost reporting period beginning on or after October 1, 
1997, the total number of FTE residents before application of weighting 
factors may not exceed the number of such FTEs for the hospital's most 
recent cost reporting period ending on or before December 31, 1996. 
Under current policy, we interpreted this to mean that only a 
hospital's unweighted (before application of weighting factors) 
allopathic and osteopathic FTE count was compared to its FTE cap, and 
if the unweighted allopathic and osteopathic FTE count exceeded the FTE 
cap, then the proportional reduction is made to the weighted FTE 
counts. Under this modified proposed policy, in the instance where a 
hospital's unweighted allopathic and osteopathic FTE count exceeds its 
FTE cap, we propose to add a step to also compare the total weighted 
allopathic and osteopathic FTE count to the FTE cap. If the total 
weighted allopathic and osteopathic FTE count is equal to or less than 
the FTE cap, then no adjustments would be made to the respective 
primary care & OB/GYN weighted FTE counts or the other weighted FTE 
counts. If the total weighted allopathic and osteopathic FTE count 
exceeds the FTE cap, then we would adjust the respective primary care & 
OB/GYN weighted FTE counts or the other weighted FTE counts to make the 
total weighted FTE count equal the FTE cap, as follows:

((primary care & OB/GYN weighted FTEs/total weighted FTEs) x FTE cap)) 
+ ((other weighted FTEs/total weighted FTEs) x FTE cap)).

    The sum would be the current year total allowable weighted FTE 
count, which would be reported on Worksheet E-4, line 9, column 3.
    More specific to the Medicare cost report, we propose to revise the 
instructions to Worksheet E-4, line 9 to state: If line 6 is less than 
or equal to line 5, enter the amounts from line 8, columns 1 and 2, in 
columns 1 and 2, of this line. Otherwise, if the total weighted FTE 
count from line 8, column 3 is greater than the amount on line 5, then 
enter in column 1 the result of ((primary care & OBGYN weighted FTEs/
total weighted FTEs) x FTE cap)). Enter in column 2 the result of 
((other weighted FTEs/total weighted FTEs) x FTE cap)). Enter in column 
3 the sum of

((primary care & OBGYN weighted FTEs/total weighted FTEs) x FTE cap)) + 
((other weighted FTEs/total weighted FTEs) x FTE cap)).

    Example 1: Hospital with a FTE cap of 100 trains 120 FTEs with a 
weight of 1.0, and 105 FTEs with a weight of 0.5, consisting of 70 
weighted primary care & OBGYN FTEs and 35 weighted other FTEs. Since 
the total weighted count of 105 (Worksheet E-4, line 8, column 3) 
exceeds the FTE cap of 100 (Worksheet E-4, line 5), the Hospital 
reports the following adjusted weighted FTE counts on Worksheet E-4:


[[Page 28412]]


Line 9, column 1: ((70 weighted primary care & OBGYN FTEs/105 total 
weighted FTEs) x 100 cap)) = 66.67.
Line 9, column 2: ((35 weighted other FTEs/105 total weighted FTEs) x 
100 cap)) = 33.33.
Line 9, column 3: 66.67 FTEs + 33.33 FTEs = 100.

    Example 2: Hospital with a FTE cap of 100 trains 102 unweighted 
FTEs, equating to 96 weighted FTEs. This 96-weighted count consists of 
30 weighted primary care & OBGYN FTEs, and 66 weighted other FTEs. 
Since the total weighted count of 96 (Worksheet E-4, line 8, column 3) 
is less than the FTE cap of 100 (Worksheet E-4, line 5), then no 
further adjustment is needed; enter the amounts from line 8, columns 1 
and 2, in columns 1 and 2, of line 9.
    Example 3: Hospital with a cap of 100 FTEs trains 90 FTEs with a 
weight of 1.0, and 20 FTEs with a weight of 0.5. Since the total 
weighted count is 100 (90 + (20 x 0.5)), then no further adjustment is 
needed. Enter the amounts from line 8, columns 1 and 2, in columns 1 
and 2 of line 9.
    Under section 1886(h)(4)(G)(i) and 42 CFR 413.79(d)(3), a 
hospital's weighted FTE count for payment purposes is the 3-year 
average of its current year weighted FTEs, prior year weighted FTEs, 
and penultimate year FTEs (for primary care & OBGYN FTEs and other FTEs 
respectively). Effective for cost reporting periods beginning on or 
after October 1, 2001, we are proposing to implement this modified 
methodology for the purpose of determining the prior year weighted FTE 
count on line 12 of Worksheet E-4, and for the purpose of determining 
the penultimate year's weighted FTE count on line 13 of Worksheet E-4, 
even though the prior and penultimate years' FTE counts would be from 
cost reporting periods prior to October 1, 2001. In this manner, the 
modified methodology would be fully applied to determining the direct 
GME payment for cost reporting periods beginning on or after October 1, 
2001. Therefore, we are proposing to modify the cost report 
instructions on Worksheet E-4, lines 12 and 13, respectively to state 
that effective for cost reporting periods beginning on or after October 
1, 2001, if subject to the cap in the prior year or penultimate year 
respectively, if the prior/penultimate year total weighted FTE count 
from line 8, column 3 is greater than the amount on line 5 from the 
prior/penultimate year, then enter in column 1 the result of ((primary 
care & OBGYN weighted FTEs/total weighted FTEs) x FTE cap)). Enter in 
column 2 the result of ((other weighted FTEs/total weighted FTEs) x FTE 
cap)) plus the amount on line 10, column 2. These instructions do not 
in any way modify or reopen final-settled prior and penultimate year 
NPRs.
    We are proposing to amend the regulations text at 42 CFR 
413.79(c)(2)(iii) to state that, effective for cost reporting periods 
beginning on or after October 1, 2001, if the hospital's unweighted 
number of FTE residents exceeds the limit described in this section, 
and the number of weighted FTE residents in accordance with Sec.  
413.79(b) also exceeds that limit, the respective primary care and 
obstetrics and gynecology weighted FTE counts and other weighted FTE 
counts are adjusted to make the total weighted FTE count equal the 
limit. If the number of FTE residents weighted in accordance with Sec.  
413.79(b) does not exceed that limit, then the allowable weighted FTE 
count is the actual weighted FTE count.
3. Reasonable Cost Payment for Nursing and Allied Health Education 
Programs
a. General
    Under section 1861(v) of the Act, Medicare has historically paid 
providers for Medicare's share of the costs that providers incur in 
connection with approved educational activities. Approved nursing and 
allied health (NAH) education programs are those that are, in part, 
operated by a provider, and meet State licensure requirements, or are 
recognized by a national accrediting body. The costs of these programs 
are excluded from the definition of inpatient hospital operating costs 
and are not included in the calculation of payment rates for hospitals 
or hospital units paid under the IPPS, IRF PPS, or IPF PPS, and are 
excluded from the rate-of-increase ceiling for certain facilities not 
paid on a PPS. These costs are separately identified and ``passed 
through'' (that is, paid separately on a reasonable cost basis). 
Existing regulations on NAH education program costs are located at 
Sec.  413.85. The most recent rulemakings on these regulations were in 
the January 12, 2001 final rule (66 FR 3358 through 3374), and in the 
August 1, 2003, final rule (68 FR 45423 and 45434).
b. Medicare+Choice Nursing and Allied Health Education Payments
    Section 541 of the Balanced Budget Refinement Act (BBRA) of 1999 
provides for additional payments to hospitals for costs of nursing and 
allied health education associated with services to Medicare+Choice 
(now called Medicare Advantage (MA)) enrollees. Hospitals that operate 
approved nursing or allied health education programs and receive 
Medicare reasonable cost reimbursement for these programs would receive 
additional payments from Medicare Advantage organizations. Section 541 
of the nBBRA limits total spending under the provision to no more than 
$60 million in any calendar year (CY). (In this document, we refer to 
the total amount of $60 million or less as the payment ``pool''.) 
Section 541 of the BBRA also provides that direct Graduate Medical 
Education (GME) payments for Medicare+Choice utilization are reduced to 
the extent that these additional payments are made for nursing and 
allied health education programs. This provision was effective for 
portions of cost reporting periods occurring in a CY, on or after 
January 1, 2000.
    Section 512 of the Benefits Improvement and Protection Act (BIPA) 
of 2000 changed the formula for determining the additional amounts to 
be paid to hospitals for MA nursing and allied health costs. Under 
section 541 of the BBRA, the additional payment amount was determined 
based on the proportion of each individual hospital's nursing and 
allied health education payment to total nursing and allied health 
education payments made to all hospitals. However, this formula did not 
account for a hospital's specific MA utilization. Section 512 of the 
BIPA revised this payment formula to specifically account for each 
hospital's MA utilization. This provision was effective for portions of 
cost reporting periods occurring in a CY, beginning with CY 2001, and 
was implemented in the August 1, 2001 IPPS final rule (66 FR 39909 and 
39910).
    The regulations at 42 CFR 413.87 codified both of these statutory 
provisions. We first implemented the BBRA NAH MA provision in the 
August 1, 2000 IPPS interim final rule with comment period (IFC) (65 FR 
47036 through 47039). In that IFC, we outlined the qualifying 
conditions for a hospital to receive the NAH MA payment, how we would 
calculate the NAH MA payment pool, and how a qualifying hospital would 
calculate its ``share'' of payment from that pool. Determining a 
hospital's NAH MA payment essentially involves applying a ratio of the 
hospital-specific NAH Part A payments, total inpatient days, and MA 
inpatient days, to national totals of those same amounts, from cost 
reporting periods ending in the fiscal year that is 2 years prior to 
the current calendar year. The formula is as follows:

(((Hospital NAH pass-through payment / Hospital Part A Inpatient Days) 
*

[[Page 28413]]

Hospital MA Inpatient Days) / ((National NAH pass-through payment / 
National Part A Inpatient Days) * National MA Inpatient Days)) * 
Current Year Payment Pool.

    With regard to determining the total national amounts for NAH pass-
through payment, Part A inpatient days, and MA inpatient days, we note 
that section 1886(l) of the Act, as added by section 541 of the BBRA, 
gives the Secretary the discretion to ``estimate'' the national 
components of the formula noted previously. For example, section 
1886(l)(2)(A) states that the Secretary would estimate the ratio of 
payments for all hospitals for portions of cost reporting periods 
occurring in the year under subsection (h)(3)(D) to total direct 
graduate medical education payments estimated for the same portions of 
periods under subsection (h)(3). Accordingly, we made the following 
statements in the August 1, 2000 IFC:
     Each year, we would determine and publish in a proposed 
rule and a final rule the total amount of nursing and allied health 
education payments made across all hospitals during the fiscal year 
that is 2 years prior to the current calendar year (65 FR 47038). We 
would use the best available cost reporting data for the applicable 
hospitals from the Hospital Cost Report Information System (HCRIS) for 
cost reporting periods in the fiscal year that is 2 years prior to the 
current calendar year (65 FR 47038).
     To calculate the pool, in accordance with section 1886(l) 
of the Act, we would ``estimate'' a total amount for each calendar 
year, not to exceed $60 million (65 FR 47038).
     To calculate the proportional reduction to Medicare+Choice 
(now MA) Direct GME payments, we stated that the percentage is 
estimated by calculating the ratio of the Medicare+Choice nursing and 
allied health payment ``pool'' for the current calendar year to the 
projected total Medicare+Choice direct GME payments made across all 
hospitals for the current calendar year. We stated that the projections 
of Medicare+Choice direct GME and Part A direct GME are based on the 
best available cost report data from the HCRIS (for example, for 
calendar year 2000, the projections are based on the best available 
cost report data from HCRIS 1998), and these payment amounts were 
increased using the increases allowed by section 1886(h) of the Act for 
these services (using the percentage applicable for the current 
calendar year for Medicare+Choice direct GME and the Consumer Price 
Index (CPI) increases for Part A direct GME). We also stated that we 
would publish the applicable percentage reduction each year in the IPPS 
proposed and final rules (65 FR 47038).
    Thus, in the August 1, 2000, IFC, we described our policy regarding 
the timing and source of the national data components for the NAH MA 
add-on payment and the percent reduction to the direct GME MA payments, 
and we stated that we would publish the rates for each calendar year in 
the IPPS proposed and final rules. While the rates for CY 2000 were 
published in the August 1, 2000, IFC (see 65 FR 47038 and 47039), the 
rates for subsequent CYs were only issued through Change Requests (CRs) 
(CR 2692, CR 11642, CR 12407). After recent issuance of the CY 2019 
rates in CR 12407 on August 19, 2021, we reviewed our update 
procedures, and were reminded that the August 1, 2000 IFC states that 
we would publish the NAH MA rates and direct GME percent reduction 
every year in the IPPS rules. Accordingly, for CY 2020 and forward, the 
NAH MA add-on rates will be proposed and included in the IPPS proposed 
and final rules, and we are also reiterating the data sources we would 
use.
    In this FY 2023 IPPS proposed rule, we are proposing the NAH MA 
add-on rates as well as the direct GME MA percent reductions for CYs 
2020 and 2021. In this proposed rule, we are proposing to issue the 
rates for CYs 2020 and 2021 because we believe we have sufficient HCRIS 
data to develop the rates for these years, and these rate years are 
most needed to ensure accurate and timely cost report settlements of 
cost reports with portions overlapping with CYs 2020 and 2021. We 
expect to propose to issue the rates for CY 2022 in the FY 2024 IPPS 
proposed rule, and the rates for CY 2023 in the FY 2025 IPPS proposed 
rule, and so forth.
    Consistent with the use of HCRIS data for past CYs, for CY 2020, we 
propose to use data from cost reports ending in FY 2018 HCRIS (the 
fiscal year that is 2 years prior to the calendar year of 2020) to 
compile these national amounts: NAH pass-through payment, Part A 
Inpatient Days, MA Inpatient Days. We propose to use data from cost 
reports ending in FY 2019 HCRIS (the fiscal year that is 2 years prior 
to the calendar year of 2021) to compile the same national amounts for 
CY 2021. However, to calculate the ``pool'' and the direct GME MA 
percent reduction, we ``project'' Part A direct GME payments and MA 
direct GME payments for the current calendar years, which in this 
proposed rule, are CYs 2020 and 2021, based on the ``best available 
cost report data from the HCRIS'' (65 FR 47038). Next, consistent with 
the method we described previously from the August 1, 2000 IFC, we 
increase these payment amounts from midpoint to midpoint of the 
appropriate calendar year using the increases allowed by section 
1886(h) of the Act for these services (using the percentage applicable 
for the current calendar year for MA direct GME, and the Consumer Price 
Index-Urban (CPI-U) increases for Part A direct GME. For CY 2020, the 
direct GME projections are based on FY 2019 HCRIS. For CY 2021, the 
direct GME projections are based on FY 2019 HCRIS. For calendar years 
2020 and 2021, the proposed national rates and percentages, and their 
data sources are set forth in this table. We intend to update these 
numbers in the FY 2023 final rule based on the latest available cost 
report data.

[[Page 28414]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.162

    We are not proposing any changes to the regulations text at 42 CFR 
413.87 at this time, as our proposal to include the nursing and allied 
health MA rates in the IPPS rulemaking is consistent with current 
regulations.
4. Proposal To Allow Medicare GME Affiliation Agreements Within Certain 
Rural Track FTE Limitations
    Sections 1886(h)(4)(F) and 1886(d)(5)(B)(v) of the Act established 
limits on the number of allopathic and osteopathic residents that 
hospitals may count for purposes of calculating direct GME payments and 
the IME adjustment, respectively, thereby establishing hospital-
specific direct GME and IME full-time equivalent (FTE) resident caps. 
However, under the authority granted by section 1886(h)(4)(H)(ii) of 
the Act, the Secretary may issue rules to allow institutions that are 
members of the same affiliated group to apply their direct GME and IME 
FTE resident caps on an aggregate basis through a Medicare GME 
affiliation agreement. The Secretary's regulations permit hospitals, 
through a Medicare GME affiliation agreement, to increase or decrease 
their IME and direct GME FTE resident caps to reflect the rotation of 
residents among affiliated hospitals for agreed-upon academic years. 
Consistent with the broad authority conferred by the statute, we 
established criteria for defining an ``affiliated group'' and an 
``affiliation agreement'' in both the August 29, 1997, final rule (62 
FR 45966, 46006) and the May 12, 1998, final rule (63 FR 26318). In the 
August 1, 2002, IPPS final rule (67 FR 49982, 50069), we amended our 
regulations to require that each Medicare GME affiliation agreement 
must have a shared rotational arrangement. The term ``Medicare GME 
affiliation agreement'' is defined at 42 CFR 413.75(b) as a written, 
signed, and dated agreement by responsible representatives of each 
respective hospital in a Medicare GME affiliated group, as defined in 
Sec.  413.75(b), that specifies--
     The term of the Medicare GME affiliation agreement (which, 
at a minimum is 1 year), beginning on July 1 of a year;
     Each participating hospital's direct and indirect GME FTE 
caps in effect prior to the Medicare GME affiliation;
     The total adjustment to each hospital's FTE caps in each 
year that the Medicare GME affiliation agreement is in effect, for both 
direct GME and IME, that reflects a positive adjustment to one 
hospital's direct and indirect FTE caps that is offset by a negative 
adjustment to the other hospital's (or hospitals') direct and indirect 
FTE caps of at least the same amount;
     The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
Medicare GME affiliated group for each year the Medicare GME 
affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's FTE caps (in accordance with criteria 3); 
and
     The names of the participating hospitals and their 
Medicare provider numbers.
    We also define the term ``Shared Rotational Arrangement'' in that 
section of our rules as a residency training program under which a 
resident(s) participates in training at two or more hospitals in that 
program.
    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 1886(h)(4)(F), in an appropriate manner in 
order to encourage training of physicians in rural areas. 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, and their second and 
third year experiences at another site, which may or may not be rural). 
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 47025, 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. 
(We note that additional legislative and regulatory changes were made 
to Rural Track Programs in the December 27, 2021 final rule, 86 FR 
73445.) When we first implemented the rural track regulations in the 
August 1, 2000 IFC, we specified that the caps associated with rural 
tracks are separate and distinct from a hospital's general FTE caps. 
Specifically, we defined Rural track FTE limitation at 42 CFR 413.75(b) 
as the maximum number of residents training

[[Page 28415]]

in a rural track residency program that an urban hospital may include 
in its FTE count and that is in addition to the number of FTE residents 
already included in the hospital's FTE cap (emphasis added). As a 
result, the rural track FTE limitations are not part of the regular FTE 
caps that hospitals may aggregate in Medicare GME affiliation 
agreements.
    The rural track FTE limitations are calculated in the same manner 
as the adjustments to any allowable new program, in accordance with 42 
CFR 413.79(e)(1). That is, at the end of the 5-year cap building window 
for the rural track program, the urban hospital's and rural hospital 
respective IME and direct GME rural track FTE limitations are 
calculated as the product of three factors (limited to the number of 
accredited slots for each program):
     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.
    Thus, while the calculated rural track FTE limitations calculated 
at the end of the 5-year window may reflect the division of the 
rotations between the urban and rural hospitals over the 5 initial 
years of the program, the future rotations amounts may change somewhat 
(albeit adhering to greater than 50 percent of the duration of the 
training occurring in the rural hospital/rural area). As rotations 
shift to meet patient care needs, the respective rural track FTE 
limitations may not quite match the amount of FTEs actually training in 
the urban and rural hospitals. We have been asked that the same 
flexibility with cap sharing afforded to teaching hospitals to share 
general FTE cap slots via Medicare GME affiliation agreements also be 
afforded to urban and rural teaching hospitals that together train 
residents in a rural track program. This flexibility would allow the 
urban and rural hospitals to share their rural track FTE limitations in 
a manner that best matches the rotations occurring in the urban and 
rural hospitals. Stakeholders representing urban-rural training 
partnerships specifically raised this request with regard to separately 
accredited 1-2 family medicine programs that have existed for a number 
of years, and either already have established their rural track FTE 
limitations, or have just recently reached or will reach the end of 
their 5-year cap building windows.
    We have considered this request and agree it would be equitable to 
allow an urban and rural hospital jointly training residents in a 1-2 
separately accredited family medicine program to aggregate their 
respective IME and direct GME rural track FTE limitations and enter 
into a ``Rural Track Medicare GME Affiliation Agreement'' to share 
those cap slots, and facilitate the cross-training of residents. We are 
proposing to allow urban and rural hospitals that participate in the 
same separately accredited 1-2 family medicine rural track program and 
have rural track FTE limitations to enter into ``Rural Track Medicare 
GME Affiliation Agreements.'' We propose that programs that are not 
separately accredited in the 1-2 format and are not in family medicine 
would not be permitted to enter into ``Rural Track Medicare GME 
Affiliation Agreements'' under this proposal. These Rural Track 
Medicare GME Affiliation Agreements, which we propose to define in this 
proposed rule, will be structured similarly to regular Medicare GME 
affiliation agreements, but we propose two distinct requirements.
    First, in an effort to ensure that regular FTE caps and FTE 
residents in non-rural track programs are not commingled with the rural 
track FTE residents, and that rural track FTE limitations are not being 
used to provide additional cap slots for non-rural track FTE residents, 
we propose that the responsible representatives of each urban and rural 
hospital entering into the Rural Track Medicare GME Affiliation 
Agreement must attest in that written agreement that each participating 
hospital's FTE counts and rural track FTE limitations in the agreement 
do not reflect FTE residents nor FTE caps associated with programs 
other than the rural track program. We note this attestation is 
important for both the urban and rural hospital, as both urban and 
rural hospitals may have regular FTE caps that could be part of regular 
Medicare GME affiliation agreements (see 42 CFR 413.79(e)(1)(iv) and 
(v) and 413.79(f)). Second, we propose to only allow urban and rural 
hospitals to participate in Rural Track Medicare GME Affiliated Groups 
if they are separately accredited 1-2 family medicine programs that 
have rural track FTE limitations in place prior to October 1, 2022. We 
are proposing to choose these criteria and this date of October 1, 
2022, as the date by which eligible hospitals must have rural track FTE 
limitations in place because the effective date of section 127 of the 
Consolidated Appropriations Act (CAA) is cost reporting periods 
beginning on or after October 1, 2022, and we are proposing to limit 
this proposal to only rural track FTE limitations established under the 
BBRA of 1999 that are unaffected by section 127 of the CAA. In this 
proposed rule, we are distinguishing between rural track programs with 
rural track FTE limitations associated with the BBRA of 1999 in effect 
prior to October 1, 2022, and Rural Track Programs (RTPs, defined at 42 
CFR 413.75(b)) started or expanded to new participating sites under the 
authority of section 127 of the CAA. We explain this distinction later 
in this section. First, we refer readers to the December 27, 2021, 
final rule (86 FR 73445) for details about section 127 of the CAA. 
Generally, that provision removes the requirement that rural track 
programs be separately accredited by the ACGME, places in statute 
(previously in regulation) the requirement that rural track residents 
must spend greater than 50 percent of their training time in a rural 
area, and allows urban and rural hospitals to receive adjustments to 
their rural track FTE limitations for adding new rural training sites 
to an existing rural track program. In that December 27, 2021, final 
rule, we addressed a comment (86 FR 73456) asking whether multiple 
rural hospital training sites added under the new section 127 authority 
may share their rural track FTE limitations via a Medicare GME 
affiliation agreement. We responded that effective October 1, 2022, we 
are not permitting the formation of Medicare GME affiliated groups for 
the purpose of aggregating and cross-training RTP FTE limitations. 
First, we explained that we believe Medicare GME affiliated groups for 
RTPs would be premature, as only starting October 1, 2022, would 
hospitals have the first opportunity to add additional participating 
sites. Subsequently, there would be the 5-year cap building period in 
which Medicare GME affiliations are not permitted, even under existing 
Medicare GME affiliation agreement rules (42 CFR 413.79(f)). Second, we 
stated that before we create Medicare GME affiliation agreements unique 
to RTPs, we believe it would be best to first modify the Medicare cost 
report form to add spaces for the hospitals to indicate the number of 
any additional RTP FTEs, and the caps applicable to those FTEs. We also 
stated that we wish to assess flexibility within

[[Page 28416]]

a hospital's own total RTP FTE limitation, before sharing those slots 
with other hospitals. We would need to be vigilant to ensure that the 
RTP FTE limitations are not comingled with regular FTE cap adjustments 
currently used in Medicare GME affiliation agreements. Therefore, we 
concluded with our belief that it is best to reassess allowing Medicare 
GME affiliation agreements for RTP FTE limitations at some point in the 
future. For these same reasons, at this time, we believe it is 
appropriate to only propose to allow rural track Medicare GME 
affiliation agreements with urban and rural hospitals that have a rural 
track FTE limitation in place prior to October 1, 2022. We will assess 
allowing these agreements with RTP FTE limitations established after 
October 1, 2022, in the future.
    We are proposing the following new definitions at 42 CFR 413.75(b) 
and requirements:
     Rural track Medicare GME affiliated group is an urban 
hospital and a rural hospital that participates in a rural track 
program defined in 42 CFR 413.75(b), and that have rural track FTE 
limitations in effect prior to October 1, 2022, and that comply with 42 
CFR 413.79(f)(1) through (6) for Medicare GME affiliated groups.
     Rural track Medicare GME affiliation agreement is a 
written, signed, and dated agreement by responsible representatives of 
each respective hospital in a rural track Medicare GME affiliated 
group, as defined in 42 CFR 413.75(b), that specifies--
    ++ A statement attesting that each participating hospital's FTE 
counts and rural track FTE limitations in the agreement do not reflect 
FTE residents nor FTE caps associated with programs other than the 
rural track program.
    ++ The term of the rural track Medicare GME affiliation agreement 
(which, at a minimum is 1 year), beginning on July 1 of a year;
    ++ Each participating hospital's direct and indirect GME rural 
track FTE limitations in effect prior to the rural track Medicare GME 
affiliation;
    ++ The total adjustment to each hospital's rural track FTE 
limitations in each year that the rural track Medicare GME affiliation 
agreement is in effect, for both direct GME and IME, that reflects a 
positive adjustment to one hospital's direct and indirect rural track 
FTE limitations that is offset by a negative adjustment to the other 
hospital's (or hospitals') direct and indirect rural track FTE 
limitations of at least the same amount;
    ++ The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
rural track Medicare GME affiliated group for each year the Medicare 
GME affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's rural track FTE limitations (in 
accordance with criteria 3); and
    ++ The names of the participating hospitals and their Medicare 
provider numbers.
    In addition, we are proposing to require that no later than July 1 
of the residency year during which the rural track Medicare GME 
affiliation agreement will be in effect, the urban and rural hospital 
must submit the signed agreement to the CMS contractor or MAC servicing 
the hospital and send a copy to the CMS Central Office. The hospitals 
may submit amendments to the adjustments to their respective rural 
track FTE limitations to the MAC with a copy to CMS by June 30 of the 
residency year that the agreement is in effect. We propose that 
eligible urban and rural hospitals may enter into rural track Medicare 
GME affiliation agreements effective with the July 1, 2023, academic 
year.
    With regard to how the rural track Medicare GME affiliation 
adjustments would be reported on the Medicare cost report, first, for 
background, we note that on the previous Medicare cost report CMS-Form-
2552-96, the rural track FTE limitation was combined, together with the 
``cap'' add-on for new (non-rural track) programs on Worksheet E, Part 
A, line 3.05, and on Worksheet E-3, Part IV, line 3.02. On the current 
cost report CMS-Form-2552-10, the rural track FTE limitation is, 
likewise, combined together with the ``cap'' add-on for new (non-rural 
track) programs on Worksheet E, Part A, line 6, and on Worksheet E-4, 
line 2. Going forward, we intend to add lines to the cost report to 
accommodate separate reporting of urban or rural hospital rural track 
FTE limitations, and the positive or negative adjustments made to the 
rural track FTE limitations, including those applicable to the 
affiliated agreements.
    In summary, we are proposing to allow urban and rural hospitals 
that participate in the same separately accredited 1-2 family medicine 
rural track program and have rural track FTE limitations to enter into 
``Rural Track Medicare GME Affiliation Agreements''. We propose that 
programs that are not separately accredited in the 1-2 format and are 
not in family medicine would not be permitted to enter into ``Rural 
Track Medicare GME Affiliation Agreements'' under this proposal. We are 
proposing to add new definitions at 42 CFR 413.75(b) of rural track 
Medicare GME affiliated group and rural track Medicare GME affiliation 
agreement. We are also proposing to require that the responsible 
representatives of each urban and rural hospital entering into the 
rural track Medicare GME affiliation agreement must attest in that 
agreement that each participating hospital's FTE counts and rural track 
FTE limitations in the agreement do not reflect FTE residents nor FTE 
caps associated with programs other than the rural track program. In 
addition, we propose to only allow urban and rural hospitals to 
participate in rural track Medicare GME affiliated groups if they have 
rural track FTE limitations in place prior to October 1, 2022. We 
propose that eligible urban and rural hospitals may enter into rural 
track Medicare GME affiliation agreements effective with the July 1, 
2023, academic year.

G. Proposed Payment Adjustment for Certain Clinical Trial and Expanded 
Access Use Immunotherapy Cases (Sec. Sec.  412.85 and 412.312)

    Effective for FY 2021, 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 (85 FR 58599 through 
58600). Effective for FY 2022, we revised MS-DRG 018 to include cases 
that report the procedure codes for CAR T-cell and non-CAR T-cell 
therapies and other immunotherapies (86 FR 44798 through 448106). We 
refer the reader to section II.D.17. of the preamble of this proposed 
rule for discussion of the agenda items for the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting relating to new 
procedure codes to describe the administration of a CAR T-cell or 
another type of gene or cellular therapy product, as well as our 
established process for determining the MS-DRG assignment for codes 
approved at the March meeting.
    Effective for FY 2021, 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, under our finalized policy we do not 
include claims determined to be clinical trial claims that group to MS-
DRG 018 when calculating the average cost for MS-DRG 018 that is

[[Page 28417]]

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 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 MS-DRG 018 to the extent such claims can be identified 
in the historical data (85 FR 58600). The term ``expanded access'' 
(sometimes called ``compassionate use'') is a potential pathway for a 
patient with an immediately life-threatening condition or serious 
disease or condition to gain access to an investigational medical 
product (drug, biologic, or medical device) for treatment outside of 
clinical trials when no comparable or satisfactory alternative therapy 
options are available.\605\
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    Effective FY 2021, we also finalized an adjustment to the payment 
amount for applicable clinical trial and expanded access immunotherapy 
cases that group to MS-DRG 018 using the same methodology that we used 
to adjust the case count for purposes of the relative weight 
calculations (85 FR 58842 through 58844). (As previously noted, 
effective beginning FY 2022, we revised MS-DRG 018 to include cases 
that report the procedure codes for CAR T-cell and non-CAR T-cell 
therapies and other immunotherapies (86 FR 44798 through 448106).) 
Specifically, under our finalized policy we apply a payment adjustment 
to claims that group to MS-DRG 018 and include ICD-10-CM diagnosis code 
Z00.6, with the modification that when the CAR T-cell, non-CAR T-cell, 
or other immunotherapy 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. This payment adjustment is codified 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, and reflects that the adjustment is also 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, non CAR 
T-cell, or other immunotherapy product is purchased in the usual 
manner, but the case involves a clinical trial of a different product. 
The regulations at 42 CFR 412.85(c) also specify 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).
    For FY 2023, we are proposing to continue to apply an adjustment to 
the payment amount for expanded access use of immunotherapy and 
applicable clinical trial cases that would group to MS-DRG 018 using 
the same methodology adopted in the FY 2021 IPPS/LTCH PPS final rule 
(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 all other cases to be 
assigned to MS-DRG 018.
     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 expanded 
access use of immunotherapy and applicable clinical trial cases that 
group to MS-DRG 018 by multiplying the relative weight for MS-DRG 018 
by the adjustor.
    Additionally, we are proposing to continue to use our finalized 
methodology for calculating this payment adjustment, such that: (a) 
When the CAR T-cell, non CAR T-cell, or other immunotherapy 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 2021 
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. We note that we are in the process of making modifications to 
the MedPAR files to include information for claims with the payer-only 
condition code ``ZC'' in the future. Payer-only condition code ``ZC'' 
is used by the IPPS Pricer to identify a case where the CAR T-cell, non 
CAR T-cell, or other immunotherapy product is purchased in the usual 
manner, but the case involves a clinical trial of a different product 
so that the payment adjustment is not applied in calculating the 
payment for the case (for example, see Change Request 11879, available 
at https://www.cms.gov/files/document/r10571cp.pdf).
    Consistent with our calculation of the proposed adjustor for the 
relative weight calculations, and our proposal to use the FY 2021 data 
for the FY 2023 ratesetting, for this proposed rule we are proposing to 
calculate this adjustor based on the December 2021 update of the FY 
2021 MedPAR file for purposes of establishing the FY 2023 payment 
amount. Specifically, in accordance with 42 CFR 412.85 (for operating 
IPPS payments) and 42 CFR 412.312 (for capital IPPS payments), we are 
proposing to multiply the FY 2023 relative weight for MS-DRG 018 by a 
proposed adjustor of 0.20 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 includes 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies. We 
are also proposing to update the value of the adjustor based on more 
recent data for the final rule.

H. 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

[[Page 28418]]

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 (also known as ``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).
     FY 2021 IPPS/LTCH PPS final rule (85 FR 58844 through 
58847.
     FY 2022 IPPS/LTCH PPS final rule (86 FR 45249 through 
45266).
    We have also codified certain requirements of the Hospital 
Readmissions Reduction Program at 42 CFR 412.152 through 412.154.
3. Current Measures
    The Hospital Readmissions Reduction Program currently includes six 
applicable conditions/procedures: Acute myocardial infarction (AMI); 
heart failure (HF); pneumonia (PN); 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. In the FY 
2022 IPPS/LTCH PPS final rule, we finalized suppression of the CMS 30-
Day Pneumonia Readmission Measure (NQF #0506) for the FY 2023 program 
year due to the impact of the COVID-19 PHE (86 FR 45254 through 45256). 
In this proposed rule, we propose to resume use of this measure in the 
Hospital Readmissions Reduction Program beginning with the FY 2024 
program year, with an exclusion of patients with principal or secondary 
COVID-19 diagnoses from both the cohort and the outcome. We are also 
providing information on technical specification updates for all of the 
condition/procedure-specific readmission measures in the Hospital 
Readmissions Reduction Program to include a covariate adjustment for 
patients with a clinical history of COVID-19 in the 12 months prior to 
the index admission.
    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.
4. Flexibility for Changes That Affect Quality Measures During a 
Performance Period in the Hospital Readmissions Reduction Program
    In the FY 2022 IPPS/LTCH PPS final rule, we adopted a policy for 
the duration of the COVID-19 PHE that has allowed us to suppress the 
use of quality measures via adjustment to the Hospital Readmissions 
Reduction Program's program calculations if we determine that 
circumstances caused by the COVID-19 PHE significantly affected those 
measures and the associated ``excess readmissions'' calculations (86 FR 
45250 through 45253). As described under that finalized policy, if we 
were to determine that the suppression of a Hospital Readmissions 
Reduction Program measure was warranted for an applicable period, we 
would calculate the measure's rates for that program year but then 
suppress the use of those rates to make changes to hospitals' Medicare 
payments. In the Hospital Readmissions Reduction Program, this policy 
would have the effect of temporarily weighting the affected measure at 
zero percent in the program's scoring methodology until adjustments 
were made, the affected portion of the performance period for the 
measure was made no longer applicable to program calculations, or the 
measure was removed entirely through rulemaking. We also explained that 
we would provide feedback reports to hospitals as part of program 
activities, including to inform their quality improvement activities, 
and to ensure that they were made aware of the changes in performance 
rates that we observed (86 FR 45251). We stated that we would publicly 
report a suppressed measure's data with appropriate caveats noting the 
limitations of the data due to the COVID-19 PHE (86 FR 45251). To 
provide stakeholders an opportunity to review this proposed rule prior 
to release of the Hospital Specific Reports (HSRs) that incorporate 
updates to the CMS 30-Day Pneumonia Readmission Measure (NQF #0506), we 
are postponing incorporation of the CMS 30-Day Pneumonia Readmission 
Measure (NQF #0506), which would typically be included in the July 
update of the Compare website hosted by HHS (https://www.medicare.gov/care-compare/).
    In the FY 2022 IPPS/LTCH PPS final rule, we also adopted Measure 
Suppression Factors to guide our determination of whether to suppress a 
Hospital Readmissions Reduction Program measure for one or more program 
years that include discharges during the COVID-19 PHE (86 FR 45251). We 
adopted these Measure Suppression Factors for use in the Hospital 
Readmissions Reduction Program, and for consistency, the following 
other value-based purchasing programs: Hospital Value-Based Purchasing, 
HAC Reduction Program, Skilled Nursing Facility Value-Based Purchasing 
Program, and End-Stage Renal Disease Quality Incentive Program. We 
stated our belief that these Measure Suppression Factors 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, would help ensure consistency in our measure 
evaluations across programs. The previously adopted Measure Suppression 
Factors are as follows:
     Significant deviation in national performance on the 
measure during the PHE for COVID-19, which could be significantly 
better or significantly worse compared to historical performance during 
the immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or

[[Page 28419]]

biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We stated our belief that we view this measure suppression policy 
as necessary to ensure that the Hospital Readmissions Reduction Program 
did not penalize hospitals based on factors that the program's measures 
were not designed to accommodate (86 FR 45252).
    In this proposed rule, we are not proposing any changes to this 
policy.
5. Provisions That Address the Impact of COVID-19 on Current Hospital 
Readmissions Reduction Program Measures
a. Background
    As described in V.H.4 of the preamble of this proposed rule, in the 
FY 2022 IPPS/LTCH PPS final rule, we adopted a measure suppression 
policy and Measure Suppression Factors to ensure that the Hospital 
Readmissions Reduction Program did not penalize hospitals based on 
factors that the program's measures were not designed to accommodate 
(86 FR 45252).
    Additionally, in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
suppression of the CMS 30-Day Pneumonia Readmissions Measure (NQF 
#0506) for the FY 2023 program year (86 FR 45254 through 45256). We 
expressed the belief that the second Measure Suppression Factor 
(clinical proximity of the measure's focus to the relevant disease, 
pathogen, or health impacts of the COVID-19 PHE) applied to the CMS 30-
Day Pneumonia Readmissions Measure (NQF #0506). In our analysis of the 
impacts of the COVID-19 PHE on the measures in the Hospital 
Readmissions Reduction Program, we observed that pneumonia has been 
identified as a typical characteristic of individuals infected with 
COVID-19 (86 FR 45254). Using data available during and subsequent to 
the preparation of the FY 2022 IPPS/LTCH PPS final rule, we found that 
a substantial portion of the CMS 30-Day Pneumonia Readmissions Measure 
(NQF #0506) cohort included admissions with a COVID-19 diagnosis, 
ranging from 13.3 percent in April 2020 to a high of 27.1 percent in 
December 2020.\606\ Furthermore, we noted that at the beginning of the 
pandemic, the 30-day observed readmission rate for pneumonia patients 
with a secondary diagnosis of COVID-19 present on admission was lower 
than the observed readmissions rate for pneumonia patients without a 
diagnosis of COVID-19 (12.4 percent versus 15.8 percent) because 
patients with a secondary diagnosis of COVID-19 present on admission 
had a higher risk of mortality than patients without a COVID-19 
diagnosis (86 FR 45254 through 45255).
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    \606\ While data prior to April 1, 2020 are available, these 
data used a different method to identify COVID-19 diagnoses. To 
improve consistency of analysis we began our analysis on April 1, 
2020 with the introduction of the COVID-19 ICD-10 codes.
---------------------------------------------------------------------------

    Additionally, we provided information on technical specification 
updates for the remaining five condition/procedure-specific readmission 
measures to exclude patients with a principal or secondary COVID-19 
diagnosis from the measures' numerators and denominators beginning in 
fiscal year (FY) 2023 (86 FR 45256 through 45258). In the FY 2015 IPPS/
LTCH PPS 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). In the FY 2022 IPPS/LTCH PPS final rule, we 
noted that to continue to account for readmissions as intended, we 
would use our subregulatory process to update the specifications to 
exclude patients with a principal or secondary diagnosis of COVID-19 
from the denominators (cohorts) and the numerators (outcomes) of the 
following five condition/procedure-specific readmission measures: (1) 
Hospital 30-Day All-Cause RSRR Following AMI Hospitalization (NQF 
#0505); (2) the Hospital 30-Day, All-Cause, Unplanned, RSRR Following 
CABG Surgery (NQF #2515); (3) the Hospital 30-Day, All-Cause, RSRR 
Following COPD Hospitalization (NQF #1891); (4) the Hospital 30-Day, 
All-Cause RSRR Following Heart Failure Hospitalization (NQF #0330); and 
(5) the Hospital-Level 30-Day, RSRR Following Elective Primary Total 
Hip Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (NQF #1551) 
beginning in FY 2023 (86 FR 45256).
b. Proposed Resumption of the CMS 30-Day Pneumonia Readmission Measure 
(NQF #0506) for the FY 2024 Program Year
    Our measure suppression policy, described in section V.H.4 of the 
preamble of this proposed rule, focuses on a short-term, equitable 
approach during this unprecedented PHE, and was not intended for 
indefinite application. While we recognize that performance on some 
measures may not immediately return to levels seen prior to the PHE, we 
want to emphasize the long-term importance of value-based care and 
incentivizing quality care tied to payment. The Hospital Readmissions 
Reduction Program is an example of our long-standing effort to link 
payments to healthcare quality in the inpatient hospital setting. Our 
goal has been to resume the use of measure data for scoring and payment 
adjustment purposes. We note that in the FY 2022 IPPS/LTCH PPS final 
rule, we finalized the suppression of the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) for the FY 2023 Program Year and stated 
that 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. Additionally, we recognized that it is important to continue 
tracking the impact of the COVID-19 PHE on the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506), as these data will inform our 
considerations regarding whether future measure suppression is 
necessary beyond FY 2023. We noted that the measure is important to 
improving patient safety and quality of care and stated that we would 
continue to monitor measure data to determine when it may be considered 
sufficiently reliable such that resuming full implementation of the CMS 
30-Day Pneumonia Readmission Measure (NQF #0506) is appropriate (86 FR 
45256).
    Following publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have continued to monitor the claims that form the basis for this 
measure's calculations. While pneumonia continues to be a typical 
characteristic of individuals infected with COVID-19, we believe that 
coding practices enhanced by the availability of COVID-19-related ICD-
10-CM and ICD-10-PCS codes, effective since January 1, 2021, have 
enabled us to differentiate patients with COVID-19 from pneumonia 
patients without COVID-19 within certain data periods.
    In this proposed rule, we are proposing that beginning in FY 2024, 
the Pneumonia Readmission Measure (NQF #0506) will no longer be 
suppressed under the Hospital Readmissions Reduction Program. We would 
resume the use of the pneumonia readmission measure for FY 2024 because 
of the following differences between the FY 2023 and FY 2024 
performance periods: (1) The improved coding practices; (2) decreased

[[Page 28420]]

proportion of COVID-19 admissions in the pneumonia readmission measure 
for this performance period; and (3) sufficient available data to make 
technical updates to the measure specifications in order to further 
account for how patients with a COVID-19 diagnosis might impact the 
quality of care assessed by this measure. These differences lead us to 
believe that the clinical proximity of the measure's focus is no longer 
sufficiently close to the health impacts of the COVID-19 PHE for the 
suppression factor to continue to apply. Specifically, effective 
January 2021, the ICD-10 code J12.82, pneumonia due to coronavirus 
disease 2019, was added for use as a secondary diagnosis, along with a 
principal diagnosis of COVID-19 (U07.1), to identify patients with 
COVID-19 pneumonia. J12.82 is not included within the cohort of the 
pneumonia readmission measure, therefore readmission rates for patients 
with an index admission of COVID pneumonia (J12.82) are not captured by 
this measure as of January 1, 2021. Whenever new codes are introduced, 
changes in coding practices are difficult to predict. At the time of 
the FY 2022 IPPS final rule, we did not have sufficient data to 
determine the effects of these coding changes on the proportion of 
COVID-19 patients and readmission rates with pneumonia due to COVID-19 
in the pneumonia readmission measure. As additional months of data have 
become available since early 2021, we have now seen increased use of 
these codes. Secondly, as these coding changes have occurred and as the 
COVID-19 PHE has evolved, more recent data show the proportion of 
COVID-19 admissions in the pneumonia readmission measure have decreased 
compared to 2020 data. Finally, with the availability of additional 
data and the decrease in the proportion of COVID-19 admissions in the 
pneumonia readmission measure, we are now able to make technical 
updates to the measure specifications in alignment with the technical 
updates we are making to the five other readmission measures. All of 
these factors have led us to conclude that the suppression factor no 
longer applies to the CMS 30-Day Pneumonia Readmissions Measure (NQF 
#0506) measure.
    As previously discussed, we observed that in 2020 following the 
declaration of the COVID-19 PHE for COVID-19 a substantial proportion 
of the CMS 30-Day Pneumonia Readmissions Measure (NQF #0506) cohort 
included admissions with a COVID-19 diagnosis, ranging from 13.3 
percent when the COVID-19 ICD-10 diagnosis code became available in 
April 2020 to a high of 27.1 percent in December 2020. After the J12.82 
code was implemented in January 2021, the proportion of patients with 
COVID-19 diagnosis present on admission in the pneumonia measure 
dropped to 9.8 percent. Data on the proportion of patients with COVID-
19 diagnosis present on admission from April 2020 through December 2020 
are detailed in Table V.H.-01. The most recently available data on the 
proportion of patients with COVID-19 diagnosis present on admission for 
January through September 2021, which do not include patients with 
pneumonia due to coronavirus disease 2019 per ICD-10 code J12.82, are 
detailed in Table V.H-02.
[GRAPHIC] [TIFF OMITTED] TP10MY22.163

[GRAPHIC] [TIFF OMITTED] TP10MY22.164

    We note that the surge of COVID-19-related hospitalizations had 
begun to subside with the rollout of the U.S. vaccination program in 
early 2021, although hospitalizations began increasing again during 
late summer 2021 with the COVID-19 Delta variant and increased over the 
fall and winter with the COVID-19 Omicron variant.

[[Page 28421]]

We also note that updated data show that the proportion of admissions 
with a COVID-19 diagnosis for the CMS 30-Day Pneumonia Readmission 
Measure (NQF #0506) between April 2020 and December 2020 was 13.1 
percent, whereas the proportion between January 2021 and September 2021 
is substantially lower, at 3.1 percent.
    Analyzing data available for the FY 2022 IPPS/LTCH PPS final rule 
(April 2020 through June 2020), we noted that the 30-day observed 
readmissions rate for patients with a secondary diagnosis of COVID-19 
present on admission at the index admission were lower than the 
observed readmissions rates for patients without a diagnosis of COVID-
19 (12.4 percent versus 15.8 percent). In more recent data, we have 
found that the observed readmission rate for admissions with a COVID-19 
diagnosis are similar to observed readmission rates for admissions 
without a COVID-19 diagnosis (17.3 percent vs. 17.2 percent, 
respectively) as depicted in Table V.H.-03.
[GRAPHIC] [TIFF OMITTED] TP10MY22.165

    Because updated data show that following the January 2021 coding 
update patients with a diagnosis of COVID-19 now make up a smaller 
proportion of the population of pneumonia admissions than in the 
analysis described in the FY 2022 IPPS/LTCH PPS final rule, and because 
observed 30-day readmission rates are similar between admissions with 
and without a COVID-19 diagnosis, we believe that resuming the CMS 30-
Day Pneumonia Readmission Measure (NQF #0506) with a modification to 
exclude patients with a primary or secondary diagnosis of COVID-19 
beginning with the FY 2024 program year would be appropriate. As 
described in more detail in section V.H.5.c of the preamble of this 
proposed rule, we will also add a covariate to adjust for a history of 
COVID-19 diagnosis in the 12 months prior to the admission as a 
technical update to the measure specifications.
    In our analysis, measure scores calculated with the cohort and 
denominator exclusions and addition of the covariate for a history of 
COVID-19 diagnosis in the 12 months prior resulted in mean measure 
scores that were closer to the prior non-COVID-19 affected period 
compared with the unchanged measure. We note that these measure-
specific modifications are in addition to application of the nationwide 
ECE granted in response to the COVID-19 PHE, which precludes the use of 
data from January 1, 2020 through June 30, 2020 from measure score 
calculations. Because these updates are to minimize the effect of 
COVID-19 on the pneumonia measure, which was not developed to account 
for COVID-19 diagnosed patients, we believe that these changes do not 
fundamentally change the measure such that it is no longer the same 
measure that we originally adopted, and therefore we believe that these 
are non-substantive updates. We note that in the FY 2015 IPPS/LTCH PPS 
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 PPS 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). We 
believe that excluding COVID-19 patients from the measure denominator 
(cohort) and numerator (outcome) and adding a covariate to adjust for a 
history of a COVID-19 diagnosis in the 12 months prior to an admission 
(discussed in section V.H.5.c. of the preamble of this proposed rule), 
will ensure that this condition-specific readmission measure continues 
to account for readmissions as intended and meets the goals of the 
Hospital Readmissions Reduction Program. We note that the readmission 
measure uses three years of data. The performance period for the FY 
2023 program year includes admissions from July 1, 2018 through June 
30, 2021, exclusive of January 1, 2020 through June 30, 2020 data 
excluded due to the ECE waiver. Therefore, we continue to believe it is 
appropriate to suppress the currently implemented measure for use in 
payment calculations for FY 2023 as finalized in the FY 2022 IPPS/LTCH 
PPS final rule.
    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 (when the readmission Measure Methodology 
reports for 2022 public reporting are available, they will be posted on 
the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/readmission/methodology). Hospital Readmissions Reduction 
Program resources are located at the Resources web page of the 
QualityNet website (available at https://qualitynet.cms.gov/inpatient/hrrp/resources).
    We welcome public comment on our proposal to resume use of the CMS 
30-Day Pneumonia Readmissions Measure

[[Page 28422]]

(NQF #0506) beginning with the FY 2024 program year.
c. Technical Measure Specification Update To Include Covariate 
Adjustment for COVID-19 Beginning With FY 2023
    As discussed in section V.H.5.b of the preamble of this proposed 
rule, we have previously 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) and reiterated this policy in the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42385) and the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45256). As we continue to evaluate the effects of the 
COVID-19 PHE on our programs, and the effects of COVID-19 on our 
measures, we have observed that for some patients COVID-19 continues to 
have lasting effects, including fatigue, cough, palpitations, and 
others potentially related to organ damage, post-viral syndrome, post-
critical care syndrome or other reasons.\607\ These clinical conditions 
could affect a patient's risk factors for being readmitted following an 
index admission for any of the six conditions/procedures included in 
the Hospital Readmissions Reduction Program. Therefore, we are 
modifying the technical measure specifications of each of our six 
condition/procedure specific risk-standardized readmission measures to 
include a covariate adjustment for patient history of COVID-19 in the 
12 months prior to the admission beginning with the FY 2023 program 
year. This inclusion of the covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission will be effective 
beginning with the FY 2023 program year and for subsequent years for 
the five non-pneumonia condition- and procedure-specific readmission 
measures. As described in V.H.5.b, the pneumonia readmission measure 
remains suppressed from scoring and payment adjustments for the FY 2023 
program year and will be resumed for the FY 2024 program year. However, 
this update will be reflected in the confidential and public reporting 
of the pneumonia readmission measure for FY 2023.\608\ For more 
information on the application of covariate adjustments, please see the 
Measure Methodology Reports (when the readmission Measure Methodology 
reports for 2022 public reporting are available, they will be posted on 
the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/readmission/methodology).
---------------------------------------------------------------------------

    \607\ Raveendran, A.V., Jayadevan, R. and Sashidharan, S., Long 
COVID: An overview. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056514/. Accessed on December 15, 2021.
    \608\ We note that the pneumonia readmission measure would 
typically be included in the July update of the Compare website. 
However, to provide stakeholders an opportunity to provide comment 
on these updates, we are postponing incorporation of the pneumonia 
readmission measure to the October refresh of the Compare website.
---------------------------------------------------------------------------

6. Definition of ``Applicable Period''
    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.'' The definition of ``applicable period'' is also specified at 
42 CFR 412.152. 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 PPS 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.
    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.'' \609\ 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.
---------------------------------------------------------------------------

    \609\ Although the FY 2023 applicable period would be July 1, 
2018 through June 30, 2021, we note that the first and second 
quarter data from CY 2020 is excluded from consideration for program 
calculation purposes due to nationwide ECE that was granted in 
response to the COVID-19 PHE.
---------------------------------------------------------------------------

    In this proposed rule, we are not proposing any updates to this 
policy.
7. Identification of Aggregate Payments for Each Condition/Procedure 
and All Discharges
    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 2023 applicable period, this includes the 
discharge diagnoses for each applicable condition/procedure based on a 
list of specific ICD-10-CM and ICD-10-PCS code sets, as applicable, for 
that condition/procedure.
    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 services covered by 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.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38232), we stated 
that we would determine the neutrality modifier using the most recently 
available full year of MedPAR data. For the purpose of modeling the 
estimated FY 2023 readmissions payment adjustment factors for this 
proposed rule, we would use the proportion of dually eligible 
beneficiaries, excess readmission ratios, and aggregate payments for 
each condition/procedure and all discharges for applicable hospitals 
from the FY 2023 Hospital Readmissions Reduction Program applicable 
period (July 1, 2018 through June 30, 2021).\610\
---------------------------------------------------------------------------

    \610\ Although the FY 2023 applicable period is July 1, 2018, 
through June 30, 2021, we note that first and second quarter data 
from CY 2020 is excluded from consideration for program calculation 
purposes due to the nationwide ECE that was granted in response to 
the COVID-19 PHE.

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[[Page 28423]]

    For the FY 2023 program year, applicable hospitals will have the 
opportunity to review and correct calculations based on the FY 2023 
applicable period of July 1, 2018 to June 30, 2021, 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).
    We are not proposing any changes to our policies for the 
identification of aggregate payments for each condition/procedure in 
this proposed rule.
8. Use of MedPAR Data Corresponding to the Applicable Period
    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 
2022 IPPS/LTCH PPS final rule (86 FR 45258), 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 2022 applicable period.
    In addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45259), 
we expressed our continued belief 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. 
Therefore, we finalized our proposal to automatically adopt the use of 
MedPAR data corresponding to the applicable period (the 3-year period 
beginning 1 year advanced from the previous program fiscal year's 
MedPAR data) \611\ for Hospital Readmissions Reduction Program 
calculations for FY 2023 and all subsequent program years.
---------------------------------------------------------------------------

    \611\ Although the FY 2023 applicable period is July 1, 2018, 
through June 30, 2021, 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. Taking into consideration the 30-day window to 
identify readmissions, the period for calculating DRG payments would 
be adjusted to July 1, 2018 through December 1, 2019 and July 1, 
2020 through June 30, 2021. Further information will be found in the 
FY 2023 Hospital Specific Report (HSR) User Guide located on 
QualityNet website at https://qualitynet.cms.gov/inpatient/hrrp/reports.
---------------------------------------------------------------------------

    In this proposed rule, we are not proposing any changes to this 
policy.
9. Calculation and Application of Payment Adjustment Factors
    As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226), section 1886(q)(3)(D) of the Act requires the Secretary to 
group hospitals and apply a methodology that allows for separate 
comparisons of hospitals within peer groups, based on the proportion of 
dually eligible beneficiaries served by each hospital, in determining a 
hospital's adjustment factor for payments applied to discharges 
beginning in FY 2019. Section 1886(q)(3)(D) of the Act 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.
    Additionally, 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)(l) 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, and codified in our 
regulations at 42 CFR 412.154(c)(2), for FY 2023, 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 2023, 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).
    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. For additional information on Hospital 
Readmissions Reduction Program payment calculations, 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 the proposed rule.
10. Extraordinary Circumstance Exception (ECE) Policy for the Hospital 
Readmissions Reduction Program
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49542 through 
49543), we adopted an ECE policy for the Hospital Readmissions 
Reduction Program, which recognized that there may be periods of time 
during which a hospital is not able to submit data (from which 
readmission measures data are derived) in an accurate or timely fashion 
due to an extraordinary circumstance beyond its control. When adopting 
this policy, we noted that we considered the feasibility and 
implications of excluding data for certain measures for a limited 
period of time from the calculations for a hospital's excess 
readmission ratios for the applicable performance period. By minimizing 
the data excluded from the program, the policy enabled affected 
hospitals to continue to participate in the Hospital Readmissions 
Reduction Program for a given fiscal year if they otherwise continued 
to meet applicable measure minimum threshold requirements. We expressed 
the belief that this approach would help alleviate the burden for a 
hospital that might be adversely impacted by a natural disaster or 
other extraordinary circumstance beyond its control, while enabling the 
hospital to continue to participate in the Hospital Readmissions 
Reduction Program. We further observed that section 1886(q)(5)(D) of 
the Act permits the Secretary to determine the applicable period for 
readmissions data collection, and we interpreted the statute to allow 
us to determine that the period not include times when hospitals may 
encounter extraordinary circumstances. In the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38239 through 38240), 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

[[Page 28424]]

circumstance not within a provider's control.
    In response to COVID-19, we announced relief for clinicians, 
providers, hospitals, and facilities participating in Medicare quality 
reporting and value-based purchasing programs. 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 COVID-19 PHE, for the Hospital Readmissions Reduction 
Program and several other quality reporting programs (85 FR 54827 
through 54837). 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.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45260 through 
45262), we clarified our ECE policy to highlight that an ECE granted 
under the Hospital Readmissions Reduction Program would exclude claims 
data during the corresponding ECE period. Although we have considered 
the feasibility and implications of excluding data under the ECE policy 
for the Hospital Readmissions Reduction Program, we have never 
specified the types of data that would be excluded under an ECE granted 
to an individual hospital. Considering that the Hospital Readmissions 
Reduction Program only uses claims data, we clarified 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. We further clarified that although an approved ECE 
for the Hospital Readmissions Reduction Program would exclude excepted 
data from Hospital Readmissions Reduction Program payment reduction 
calculations, we did not waive the data submission requirements of a 
hospital for claims data (86 FR 45261 through 45262). For example, for 
claims data, we require a hospital to submit claims to receive payments 
for the services they provided to patients. Although an individual ECE 
approval under the Hospital Readmissions Reduction Program would except 
data submitted by a hospital from Hospital Readmissions Reduction 
Program calculations, a hospital would still need to submit its claims 
in order to receive payment outside the scope of the Hospital 
Readmissions Reduction Program for services provided.
    Finally, in the FY 2022 IPPS/LTCH PPS final rule, we clarified 
that, although an approved ECE for the Hospital Readmissions Reduction 
Program would exclude excepted data from Hospital Readmissions 
Reduction Program payment reduction calculations, such an ECE does not 
exempt hospitals from payment reductions under the Hospital 
Readmissions Reduction Program (86 FR 45262).
    We are not proposing any changes to our previously finalized ECE 
Policy in this proposed rule.
11. Request for Public Comment on Possible Future Inclusion of Health 
Equity Performance in the Hospital Readmissions Reduction Program
    We are committed to achieving equity in healthcare outcomes for our 
beneficiaries by supporting providers' quality improvement activities 
to reduce health inequities, by enabling them to make more informed 
decisions, and by promoting provider accountability for healthcare 
disparities.\612\ As described in section IX.B. of the preamble of this 
proposed rule, we discuss and seek comment on overarching principles 
for measuring health care quality disparities to provide more 
actionable and comprehensive information on health care disparities 
across multiple social risk factors and demographic variables. As part 
of this request for information, we also discuss different approaches 
for identifying meaningful performance differences and guiding 
principles for reporting disparity measures.
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    \612\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Qualityinitiativesgeninfo/downloads/cms-quality-strategy.pdf.
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    As previously discussed in the FY 2018 IPPS/LTCH PPS final rule (82 
FR 38226), section 1886(q)(3)(D) of the Act requires the Secretary to 
group hospitals and apply a methodology that allows for separate 
comparisons of hospitals with differing proportions of dually eligible 
beneficiaries in determining a hospital's adjustment factor for 
payments applied to discharges beginning in FY 2019. To implement this 
provision, in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38226 through 
38237), we finalized a number of changes to the payment reduction 
methodology, including our policy to stratify hospitals into quintiles, 
or peer groups, based on their proportion of dually eligible 
beneficiaries (82 FR 38229 through 38231) and our policy to use the 
median excess readmission ratio for the hospital's peer group in place 
of 1.0 in the payment reduction formula (82 FR 38231 through 38237). In 
this peer grouping methodology, dual-eligibility status is used as it 
is an indicator of beneficiaries' social risk. The peer grouping 
methodology mitigates against disproportionate payment reductions for 
hospitals serving socially at-risk populations. However, this peer 
grouping methodology does not directly measure or account for 
disparities in health care quality between beneficiary groups with 
heightened social risk and groups with less social risk.
    In the FY 2018 IPPS/LTCH PPS final rule, we introduced confidential 
reporting of hospital quality measure data stratified by social risk 
factors (82 FR 38403 through 38409). 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 across beneficiary groups 
within a hospital while accounting for their clinical risk factors. 
This method also allows for 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) assesses 
hospitals' outcome rates for subgroups of beneficiaries across 
hospitals, allowing for a comparison across hospitals on their 
performance serving beneficiaries with social risk factors. We refer 
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 
38407) and the Disparity Methods technical report and Updates and 
Specifications Report posted on the QualityNet website for additional 
details. The CMS Disparity Methods more directly measure disparities in 
health care quality between dually eligible and non-dually eligible 
beneficiary groups than the Hospital Readmissions Reduction Program's 
peer grouping methodology. For example, when considering the CMS 
Disparity Methods results calculated using data for the FY 2022 
Hospital Readmissions Reduction Program performance period, measures 
showed not only a range between low and high disparity rates within 
hospitals, but also worse overall outcome rates for beneficiaries with

[[Page 28425]]

social risk using beneficiary dual eligibility status as the 
stratification variable. Of these measures, the most actionable for 
hospitals were measures that showed overall high readmission rates for 
dually eligible beneficiaries across hospitals, or a large difference 
in readmission rates between dually eligible and non-dually eligible 
beneficiaries. These gaps in care indicated that there is potential for 
improvement, or a reduction in disparity at poorly performing hospitals 
if they were able to emulate the performance of strongly performing 
hospitals.
    The Hospital Readmissions Reduction Program currently groups 
hospitals into one of five peer groups based on their proportion of 
beneficiaries who are dually eligible for Medicare and full Medicaid 
benefits. Beneficiaries' dual eligibility for Medicare and Medicaid is 
a widely used proxy for a beneficiary's financial risk. Medicaid 
enrollees have incomes and overall wealth below a certain threshold and 
thus, Medicaid eligibility may be used as a proxy for low socioeconomic 
status. The use of beneficiaries' dual eligibility in social risk 
factor analyses was supported by ASPE's First Report to Congress.\613\ 
This report found that in the context of value-based purchasing 
programs such as the Hospital Readmissions Reduction Program, 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. In alignment with the current 
program, we are considering the use of the beneficiary's dual 
eligibility status as a measure of beneficiaries' social risk that 
could be used to incorporate hospitals' performance for socially at-
risk populations in the Hospital Readmissions Reduction Program.
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    \613\ Office of the Assistant Secretary for Planning and 
Evaluation. (2016). Social risk factors and performance under 
Medicare's value-based purchasing programs. Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
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    As part of our broader goal of achieving equity in healthcare 
outcomes for our beneficiaries, we are interested in encouraging 
providers to improve health equity and reduce health care disparities 
through the Hospital Readmissions Reduction Program. We are seeking 
comment on approaches to updating the Hospital Readmissions Reduction 
Program to incorporate performance for socially at-risk populations. 
For example, we are considering approaches that would account for a 
hospital's performance on readmissions for socially at-risk 
beneficiaries compared to all other hospitals, or its performance in 
treating socially at-risk beneficiaries compared to other beneficiaries 
within the hospital, or combinations of these approaches. We 
acknowledge that updating the Hospital Readmissions Reduction Program 
to encourage improved performance for socially at-risk populations can 
take many forms, and we seek to explore different approaches so we can 
find an approach that satisfies our goals without unintended 
consequences.
    In exploring approaches to incorporate performance for socially at 
risk populations in the Hospital Readmissions Reduction Program, our 
objective is to encourage providers to improve health equity and reduce 
health care disparities without disincentivizing hospitals to treat 
socially at-risk beneficiaries or disproportionately penalizing 
hospitals that treat a large proportion of socially at-risk 
beneficiaries. We are seeking comment on approaches that would achieve 
this objective.
    As also discussed in our request for information on overarching 
principles for measuring health care quality disparities, as described 
in section IX.C of the preamble of this proposed rule, many non-
clinical drivers of health are known to impact beneficiary outcomes, 
including social risk factors such as socioeconomic status, housing 
security and adequacy, and food security. The Hospital Readmissions 
Reduction Program currently uses beneficiaries' dual eligibility for 
Medicare and Medicaid as a proxy for a beneficiary's social risk and 
uses dual eligibility, as required by the statute, to divide hospitals 
into peer groups for comparison under the program. We are seeking 
comment on variables associated with or measures of social risk and 
beneficiary demographics that are already collected, as well as broader 
definitions of dual eligibility, such as those who are enrolled in a 
Medicare Savings Program or the Medicare Part D Low Income Subsidy, 
that could be included in the Hospital Readmissions Reduction Program 
in addition to dual eligibility. We note initially we would use such 
variables to stratify results within Hospital Specific Reports (HSRs) 
as confidential feedback to hospitals.
    Measures of social risk could also include indices developed for 
the purpose of identifying socially at-risk populations and measuring 
the degree of risk. For example, as described in section IX.B, we are 
considering the University of Wisconsin School of Medicine and Public 
Health and Health Resources and Services Administration's Area 
Deprivation Index,\614\ Agency for Healthcare Research and Quality 
Socioeconomic Status Index,\615\ and the Centers for Disease Control 
and Prevention's Social Vulnerability Index.\616\ For example, the Area 
Deprivation Index allows for rankings of neighborhoods by socioeconomic 
disadvantage in a region of interest (such as at the state or national 
level), and includes factors for income, education, employment, and 
housing quality and is used in our Everyone with Diabetes Counts 
program in order to target seniors in the most disadvantaged 
neighborhoods for diabetes education.\617\ In addition to individual 
variables or sets of variables we are seeking comment on the addition 
of one or more of these indices or proposals for other indices or 
modified indices that capture multiple dimensions of social risk and 
that have demonstrated relations to health outcomes or access to health 
care resources, that can be added to the Program along with dual 
eligibility as factors for stratifying data. We ask commenters to 
include information on the availability of public data sources and 
documentation of the methods and testing that establish their 
applicability and provide supporting information about availability and 
methods when suggesting variables or indices to measure social risk. 
Support from a national-level assessment of the impact of social risk 
can be particularly useful to demonstrate the relevance of a proposed 
indicator.
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    \614\ Center for Health Disparities Research. About the 
Neighborhood Atlas. Available at: https://www.neighborhoodatlas.medicine.wisc.edu/.
    \615\ Bonito A., Bann C., Eicheldinger C., Carpenter L. (2008). 
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 & 
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.
    \616\ Flanagan, B.E., Gregory, E.W., Hallisey, E.J., Heitgerd, 
J.L., Lewis, B. (2011). A social vulnerability index for disaster 
management. Journal of Homeland Security and Emergency Management, 
8(1). Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/img/pdf/Flanagan_2011_SVIforDisasterManagement-508.pdf.
    \617\ https://www.neighborhoodatlas.medicine.wisc.edu/.
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    Before any changes to the Hospital Readmissions Reduction Program 
are implemented, we plan to assess the extent to which they address our 
objective as well as their financial impact on the Hospital 
Readmissions Reduction Program. Any proposals to update the Hospital 
Readmissions

[[Page 28426]]

Reduction Program to account for the extent to which a hospital is able 
to provide high quality and equitable care for beneficiaries with 
social risk factors, as previously described, would be made through 
future rulemaking.
    We invite public comment on the following: (1) The benefit and 
potential risks, unintended consequences, and costs of incorporating 
hospital performance for beneficiaries with social risk factors in the 
Hospital Readmissions Reduction Program; (2) the approach of linking 
performance in caring for socially at-risk populations and payment 
reductions by calculating the reductions based on readmission outcomes 
for socially at-risk beneficiaries compared to other hospitals or 
compared to performance for other beneficiaries within the hospital; 
and (3) measures or indices of social risk, in addition to dual 
eligibility, that should be used to measure hospitals' performance in 
achieving equity in the Hospital Readmissions Reduction Program.

I. 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 incentive payments are made in a fiscal year 
(FY) to hospitals that meet performance standards established for a 
performance period for such fiscal year. Both the performance standards 
and the performance period for a fiscal year are to be established by 
the Secretary.
    For more of the statutory background and descriptions of our 
current policies for the Hospital VBP Program, we refer readers to our 
codified requirements for the Hospital VBP Program at 42 CFR 412.160 
through 412.168.
1. Flexibilities for the Hospital VBP Program in Response to the Public 
Health Emergency (PHE) Due to COVID-19
a. Measure Suppression Policy for the Duration of the COVID-19 PHE
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized a measure 
suppression policy and several Measure Suppression Factors for the 
duration of the COVID-19 PHE (86 FR 45266 through 45269). We stated 
that we had previously 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, such as the COVID-19 
PHE.
    Specifically, we finalized a policy for the duration of the COVID-
19 PHE that enables 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 
(TPSs) significantly. We also finalized the adoption of Measure 
Suppression Factors which will guide our determination of whether 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 COVID-19 PHE. The finalized Measure Suppression Factors are as 
follows:
     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 compared to 
historical performance during the immediately preceding program years.
     Measure Suppression Factor 2: Clinical proximity of the 
measure's focus to the relevant disease, pathogen, or health impacts of 
the PHE for COVID-19.
     Measure Suppression Factor 3: Rapid or unprecedented 
changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Measure Suppression Factor 4: Significant national 
shortages or rapid or unprecedented changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We also note that, as part of this measure suppression policy, we 
stated that we would still provide confidential feedback reports to 
hospitals on their measure rates on all measures to ensure that they 
are made aware of the changes in performance rates that we have 
observed. We also stated that we would publicly report suppressed data 
with appropriate caveats noting the limitations of the data due to the 
COVID-19 PHE. We continue to strongly believe that publicly reporting 
these data will balance our responsibility to provide transparency to 
consumers and uphold safety while ensuring that hospitals are not 
unfairly scored or penalized through payment under the Hospital VBP 
Program. We also note that, due to operational complications associated 
with the proposed changes to the scoring methodology, 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 2023 until after August 1, 2022. We intend to provide 
hospitals with these feedback reports for FY 20223 as soon as possible 
and estimate that we will be able to provide reports before the end of 
2022.
    We are not proposing any changes to the measure suppression policy 
in this proposed rule.
b. Proposals To Suppress Specific Measures for the FY 2023 Program Year
(1) Background and Overview
    COVID-19 has had significant negative health effects--on 
individuals, communities, nations, and globally. Consequences for 
individuals who have COVID-19 include morbidity, hospitalization, 
mortality, and post-COVID-19 related conditions (also known as long 
COVID). As of early- March 2022, over 78 million COVID-19 cases, 4.5 
million new COVID-19 related hospitalizations, and 900,000 COVID-19 
deaths have been reported in the U.S.\618\ One analysis projected that 
COVID-19 would reduce life expectancy in 2020 by 1.13 years overall, 
with the estimated impact disproportionately affecting minority 
communities. According to this analysis, the estimated life expectancy 
reduction for Black and Latino populations is 3 to 4 times the estimate 
when comparing to the white population.\619\ With a death toll 
surpassing that of the 1918 influenza pandemic, COVID-19 is the 
deadliest disease in American history.\620\
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    \618\ https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/index.html.
    \619\ Andrasfay, T., & Goldman, N. (2021). Reductions in 2020 US 
life expectancy due to COVID-19 and the disproportionate impact on 
the Black and Latino populations. Proceedings of the National 
Academy of Sciences of the United States of America, 118(5), 
e2014746118. https://www.pnas.org/content/118/5/e2014746118.
    \620\ Covid overtakes 1918 Spanish flu as deadliest disease in 
U.S. history (statnews.com).
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    Additionally, impacts of the COVID-19 pandemic have continued to 
accelerate in 2021 as compared with 2020. The Delta variant of COVID-19 
(B.1.617.2) surfaced in the United States in early-to-mid 2021. Studies 
have shown that the Delta variant is up to 60 percent more 
transmissible than the previously dominant Alpha variant in

[[Page 28427]]

2020.\621\ Further, in November 2021, the number of COVID-19 deaths for 
2021 surpassed the total deaths for 2020. According to CDC data, the 
total number of deaths involving COVID-19 reached 385,453 in 2020 and 
451,475 in 2021.\622\ With this increased transmissibility and 
morbidity associated with the Delta variant as well as new variants 
like Omicron which have impacted 2021 623 624 and worsening 
staffing shortages in Q3 and Q4 2021 associated with the ongoing 
PHE,\625\ we remain concerned about using measure data that is 
significantly impacted by COVID-19 for scoring and payment purposes for 
the FY 2023 program year.
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    \621\ Allen H., Vusirikala A., Flannagan J., et al. Increased 
Household Transmission of COVID-19 cases associated with SARS-CoV-2 
Variant of Concern B.1.617.2: A national case-control study. Public 
Health England. 2021.
    \622\ https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm.
    \623\ https://www.cdc.gov/coronavirus/2019-ncov/science/forecasting/mathematical-modeling-outbreak.html.
    \624\ https://www.cdc.gov/coronavirus/2019-ncov/variants/omicron-variant.html?s_cid=11734:omicron%20variant:sem.ga:p:RG:GM:gen
: PTN:FY22.
    \625\ Bloomberg, U.S. Hospital Staff Shortages Hit Most in a 
Year on Covid Surge, https://www.bloomberg.com/news/articles/2022-01-05/one-in-five-u-s-hospitals-face-staffing-shortages-most-in-year 
(citing HHS data).
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    As noted in section V.H.1.a., in the FY 2022 IPPS/LTCH PPS final 
rule, we finalized a measure suppression policy and several Measure 
Suppression Factors for the duration of the COVID-19 PHE (86 FR 45266 
through 45269). In addition, under this policy, we suppressed the 
following measures for the FY 2022 program year:

 Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) (NQF #0166)
 Medicare Spending per Beneficiary--Hospital (MSPB) (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)

    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have conducted analyses on all Hospital VBP Program measures to 
determine whether and how COVID-19 has impacted the validity of the 
data used to calculate these measures for the FY 2023 program year. We 
discuss our findings from these analyses that follows. Based on those 
analyses, we are proposing to suppress the following measures for the 
FY 2023 program year:

 Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) (NQF #0166)
 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 Outcome Measure (NQF #1716)
 National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome 
Measure (NQF #1717)

    We also note that in the FY 2022 IPPS/LTCH PPS final rule, we 
finalized our proposal 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 (86 FR 
45274 through 45276).
(2) Proposal To Suppress the Hospital Consumer Assessment of Healthcare 
Providers and Systems (HCAHPS) Survey Measure (NQF #0166) for the FY 
2023 Hospital VBP Program Year
    As noted in section V.H.1.b. of the preamble of this proposed rule, 
in the FY 2022 IPPS/LTCH PPS final rule, we finalized the suppression 
of the HCAHPS measure for the FY 2022 program year under 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 refer readers to the FY 2022 IPPS/LTCH PPS 
final rule for additional details and a summary of public comments we 
received related to that finalized policy (86 FR 45270 through 45271).
    We are proposing to suppress the HCAHPS measure for the FY 2023 
program year under Measure Suppression Factor 1, significant deviation 
in national performance on the measure during the COVID-19 PHE, which 
could be significantly better or significantly worse as compared to 
historical performance during the immediately preceding program years, 
and Measure Suppression Factor 4, significant national shortages or 
rapid or unprecedented changes in healthcare personnel. We would 
calculate hospitals' HCAHPS measure rates, but we would not use these 
measure rates to generate achievement, improvement, or consistency 
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 2023 domain scores for the Person 
and Family Engagement domain. Participating hospitals would continue to 
report the measure data to CMS so that we can monitor the effect of the 
circumstances on quality measurement and consider appropriate policies 
in the future. We would 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 CY 2021 measure rate data where feasible and 
appropriately caveated. As noted in section V.I.1.a. of the preamble of 
this proposed rule, we believe that publicly reporting suppressed 
measure data is an important step in providing transparency and 
upholding the quality of care and safety for consumers.
    Based on our analysis of HCAHPS data from Q1 2019 to Q3 2021, we 
continue to observe a sustained decline in hospital-level HCAHPS scores 
beginning in Q2 2020. This decline is associated with the COVID-19 PHE 
in 2020 and 2021. 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.\626\
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    \626\ Summary Analyses (hcahpsonline.org): https://www.hcahpsonline.org/en/summary-analyses/.
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    In order to determine whether the COVID-19 PHE impacted the HCAHPS

[[Page 28428]]

measure for the FY 2023 program year and to what extent, we conducted 
an analysis that compared the Q1 2021, Q2 2021, and Q3 2021 HCAHPS data 
to the Q1 2019, Q2 2019, and Q3 2019 HCAHPS data.\627\ This analysis 
was similar to the analysis we conducted last year when we compared Q1 
2020 and Q2 2020 HCAHPS data to Q1 2019 and Q2 2019 HCAHPS data.\628\ 
As reflected in Table V.I.-01, this analysis showed that HCAHPS measure 
top-box scores in Q1, Q2, and Q3 2021 compared to the same quarter in 
pre-COVID-19 2019 were almost always lower. The relatively steady 
decline in HCAHPS top-box scores that began in Q2 2020 became sharper 
in Q3 2021. Compared to Q3 2019, HCAHPS scores in Q3 2021 were lower by 
1 to 4 top-box points. These changes were statistically significant for 
all HCAHPS measures in Q2 2021 and Q3 2021 at the p < 0.0001 level, 
meaning that changes were too large to occur by chance more than one 
time in 10,000.\629\ These changes stand in sharp contrast to the 
pattern of generally small improvements prior to Q2 2020.
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    \627\ We note that the COVID-19 PHE was declared on January 31, 
2020: https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \628\ As described further in the FY 2022 IPPS/LTCH PPS final 
rule, in order to detect the possible impact of the COVID-19 PHE on 
patients' experience of hospital care, we previously conducted an 
``apples-to-apples'' analysis in which we compared hospitals' HCAHPS 
measure top-box scores for each quarter between Q1 2019 and Q4 2020 
to their top-box scores for each of the same quarters one year 
earlier (86 FR 45270 through 45271). We refer readers to the FY 2022 
IPPS/LTCH PPS final rule for additional details on that analysis (86 
FR 45270 through 45271).
    \629\ Comparisons for this analysis are based on hospitals with 
at least 25 completed surveys in each of the two matched quarters.
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    We believe that the analysis of Q1, Q2, and Q3 2021 HCAHPS scores 
indicates a pattern of significant negative changes in hospital 
performance from the immediately preceding pre-COVID-19 quarters where 
HCAHPS scores generally changed by less than 1 top-box point, sometimes 
increasing and sometimes decreasing, compared to the same quarter one 
year earlier.
[GRAPHIC] [TIFF OMITTED] TP10MY22.166

    We are also proposing to suppress the HCAHPS measure for the FY 
2023 program year under Measure Suppression Factor 4, significant 
national shortage or rapid or unprecedented changes in healthcare 
personnel. During the course of the PHE, an unprecedented number of 
healthcare personnel have left the workforce or ended their employment 
in hospitals.\630\ This healthcare personnel shortage worsened in 2021, 
with hospitals across the United States reporting 296,466 days of 
critical staffing shortages, an increase of 86 percent from the 159,320 
days of critical staffing shortage hospitals reported in 2020.\631\ 
Healthcare workers, especially those in areas with higher infection 
rates, have reported serious psychological symptoms, including anxiety, 
depression, and burnout.632 633
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    \630\ Health Affairs, COVID-19's Impact on Nursing Shortages, 
The Rise of Travel Nurses, and Price Gouging (Jan. 28, 2022), 
https://www.healthaffairs.org/do/10.1377/forefront.20220125.695159/.
    \631\ https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh.
    \632\ Kriti Prasad, Colleen McLoughlin, Martin Stillman, Sara 
Poplau, Elizabeth Goelz, Sam Taylor, Nancy Nankivil, Roger Brown, 
Mark Linzer, Kyra Cappelucci, Michael Barbouche, Christine A. 
Sinsky. Prevalence and correlates of stress and burnout among U.S. 
healthcare workers during the COVID-19 pandemic: A national cross-
sectional survey study. EClinicalMedicine, Volume 35. 2021. 100879. 
ISSN 2589-5370. https://doi.org/10.1016/j.eclinm.2021.100879.
    \633\ Vizheh, M., Qorbani, M., Arzaghi, S.M. et al. The mental 
health of healthcare workers in the COVID-19 pandemic: A systematic 
review. J Diabetes Metab Disord 19, 1967-1978 (2020). https://doi.org/10.1007/s40200-020-00643-9.
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    Shortages in hospital healthcare personnel have been shown to 
affect quality of care and patient satisfaction. Studies have shown 
that hospitals with greater numbers of hospitalists treating general-
medicine patients and greater availability of nursing unit support 
services have been associated with higher levels of patient 
satisfaction.634 635
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    \634\ Chen L, Birkmeyer J, Saint S, Jha A. 2013. Hospitalist 
Staffing and Patient Satisfaction in the National Medicare 
Population. Journal of Hospital Medicine, https://doi.org/10.1002/jhm.2001.
    \635\ Bacon, C.T., & Mark, B. (2009). Organizational effects on 
patient satisfaction in hospital medical-surgical units. The Journal 
of nursing administration, 39(5), 220-227. https://doi.org/10.1097/NNA.0b013e3181a23d3f.

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[[Page 28429]]

Conversely, nurse burnout has been linked to lower nurse-assessed 
quality of care \636\ and lower patient satisfaction.\637\ Nursing 
shortages have also been linked with negative patient perceptions of 
care.\638\ Therefore, we believe this significant national change in 
healthcare personnel due to the COVID-19 PHE has significantly impacted 
hospitals' scores on the HCAHPS measure, which measures patient 
experience of hospital care, including staff responsiveness, 
communication with hospital staff, and cleanliness of the hospital 
environment.
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    \636\ Aiken L, Clarke S, Sloane D. Hospital staffing, 
organization, and quality of care: Cross-national findings. 
International Journal for Quality in Health Care. Int J Qual Health 
Care. 2002.10.1093/intqhc/14.1.5.
    \637\ Jeannie P. Cimiotti, et al., Nurse staffing, burnout, and 
health care-associated infection, American Journal of Infection 
Control, Volume 40, Issue 6, 2012, Pages 486-490, https://doi.org/10.1016/j.ajic.2012.02.029 (citing Vahey DC, et al., Nurse burnout 
and patient satisfaction. Med Care 2004;42:II-57-66 and Leiter MP, 
Harvie P, Frizzell C. The correspondence of patient satisfaction and 
nurse burnout. Soc Sci Med 1998;47:1611-7).
    \638\ Aiken LH, Sloane DM, Ball J, et al, Patient satisfaction 
with hospital care and nurses in England: an observational study, 
https://bmjopen.bmj.com/content/8/1/e019189.
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    Additionally, reports of hospital staff shortages have varied 
widely geographically. In January 2021, half of the hospitals in New 
Mexico and over 40 percent of the hospitals in Vermont, Rhode Island, 
West Virginia, and Arizona reported staffing shortages.\639\ 
Conversely, in that same week, less than 10 percent of hospitals in 
Washington, DC, Connecticut, Alaska, Illinois, New York, Maine, 
Montana, Idaho, Texas, South Dakota and Utah reported staffing 
shortages. Given the wide variance in reported staffing shortages, and 
the impact staffing shortages has had on HCAHPS scores, we believe our 
proposal to suppress the HCAHPS measure fairly addresses the geographic 
disparity in the impact of the COVID-19 PHE on participating hospitals.
---------------------------------------------------------------------------

    \639\ U.S. News, States With the Biggest Hospital Staffing 
Shortages (Jan. 13, 2022), https://www.usnews.com/news/health-news/articles/2022-01-13/states-with-the-biggest-hospital-staffing-shortages (citing data from the HHS, CDC, and Assistant Secretary 
for Preparedness and Response Community Profile Report, updated 
frequently and available here: https://healthdata.gov/Health/COVID-19-Community-Profile-Report/gqxm-d9w9).
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    Due to the emergence of COVID-19 variants, such as the Delta 
variant, which worsened staffing shortages in Q3 and Q4 2021,\640\ we 
anticipate that Q4 2021 data will 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. 
Additionally, we believe that suppressing the HCAHPS measure is 
appropriate because the impact of COVID-19 on the measure cannot be 
addressed through risk-adjustment for two reasons. First, we cannot 
risk adjust the measure to exclude patients whose admissions were 
related to COVID-19 because this measure does not capture patient-level 
diagnosis data. Second, even if we could exclude patients whose 
admissions were related to COVID-19 from the measure, we believe the 
HCAHPS calculations would still be impacted because hospital staffing 
and resource issues affect a hospital's entire patient population. 
Therefore, we believe that suppressing this measure for the FY 2023 
program year will address concerns about the potential unintended 
consequences of penalizing hospitals that treated COVID-19 diagnosed 
patients.
---------------------------------------------------------------------------

    \640\ Bloomberg, U.S. Hospital Staff Shortages Hit Most in a 
Year on Covid Surge, https://www.bloomberg.com/news/articles/2022-01-05/one-in-five-u-s-hospitals-face-staffing-shortages-most-in-year 
(citing HHS data).
---------------------------------------------------------------------------

    For these reasons, we are proposing to suppress the HCAHPS measure 
for the FY 2023 Hospital VBP program year under Measure Suppression 
Factors 1 and 4.
    We welcome public comment on this proposal.
(3) Proposal To Suppress the Five Healthcare-Associated Infection (HAI) 
Safety Measures for the FY 2023 Hospital VBP Program Year
    As noted in section V.H.1.b. of the preamble of this proposed rule, 
in the FY 2022 IPPS/LTCH PPS final rule, we finalized the suppression 
of the five HAI Safety measures (CAUTI, CLABSI, Colon and Hysterectomy 
SSI, MRSA, and CDI) for the FY 2022 program year under 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 refer readers to the FY 2022 IPPS/LTCH PPS 
final rule for additional details on that policy and a summary of 
public comments we received related to that finalized policy (86 FR 
45272 through 45274).
    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 2023 program year under 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, 
Measure Suppression Factor 3, rapid or unprecedented changes in 
clinical guidelines, care delivery or practice, treatments, drugs, or 
related protocols, or equipment or diagnostic tools or materials, and 
Measure Suppression Factor 4, significant national shortages or rapid 
or unprecedented changes in healthcare personnel and patient case 
volumes. We are concerned that the COVID-19 PHE affected measure 
performance on the HAI measures in 2021 such that we will not be able 
to score hospitals fairly or reliably for national comparison and 
payment adjustment purposes. As part of this proposal, 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 
2023 Safety domain score. Participating hospitals would continue to 
report the measure data to the CDC and CMS so that we can monitor the 
effect of the circumstances on quality measurement and consider 
appropriate policies for 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. Though we are concerned that the 
COVID-19 PHE has affected measure performance on the HAI measures in 
2021, patient safety remains a priority in our value-based purchasing 
programs. Therefore, we also intend to publicly report CY 2021 data 
where feasible and appropriately caveated. As noted in section V.I.1.a. 
of the preamble of this proposed rule, we believe that publicly 
reporting suppressed measure data is an important step in providing 
transparency and upholding quality of care and safety for consumers.
    We are proposing to suppress three of the five CDC NHSN HAI 
measures (CLABSI, CAUTI, and MSRA bacteremia) under 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 refer readers to the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45272 through 45274) for previous analysis on the HAI Safety 
measures that showed that measure rates for the CLABSI, CAUTI, and MRSA 
measures increased during the CY 2020 pandemic year as compared to the 
pre-COVID-19 CY 2019 year immediately preceding the COVID-

[[Page 28430]]

19 PHE. To determine whether the CLABSI, CAUTI, and MRSA measure rates 
would continue to show increases for CY 2021, the CDC analyzed changes 
in standardized infection ratios (SIRs) for Q1 and Q2 of CY 2021 as 
compared to the SIRs in Q1 and Q1 of CY 2019. This analysis found that 
the CLASBI, CAUTI, and MSRA measures had statistically significant 
measure rate increases during Q1 and Q2 of CY 2021 as compared to pre-
pandemic levels in Q1 and Q2 of CY 2019. For Q1 2021, the national SIR 
increased by approximately 45 percent for the CLABSI measure, 
approximately 12 percent for the CAUTI measure, and approximately 39 
percent for the MRSA measure as compared to Q1 2019. For Q2 2021, the 
national SIR increased by approximately 15 percent for the CLABSI 
measure and approximately 8 percent for the MRSA measure. The SIRs for 
the CAUTI measure showed no statistically significant difference for Q2 
2021 as compared to Q2 2019.
[GRAPHIC] [TIFF OMITTED] TP10MY22.167

    For the CDI measure, the national SIR decreased by approximately 16 
percent for Q1 2021 as compared to Q1 2019 and by approximately 14 
percent for Q2 2021 as compared to Q2 2019. The SSI measure showed no 
significant increase or decrease during Q1 2021 and Q2 2021 as compared 
to Q1 2019 and Q2 2019. Though the changes in the national SIRs for SSI 
and CDI were not as large as compared to the other Safety domain 
measures, we are proposing to suppress these measures under Measure 
Suppression Factor 4, significant national shortages or rapid or 
unprecedented changes in patient case volumes and Measure Suppression 
Factor 3, rapid or unprecedented changes in clinical guidelines, care 
delivery or practice, treatments, drugs, or related protocols, or 
equipment or diagnostic tools or materials, respectively. Specifically, 
for the SSI measure, we are proposing to suppress the measure for FY 
2023 under Measure Suppression Factor 4, rapid or unprecedented changes 
in patient case volumes. We note that the SSI measure has historically 
had a low procedure volume for many hospitals, which impacts our 
ability to produce SIRs for that measure. For CY 2019, 2,087 hospitals 
(61 percent) did not have sufficient procedure-level data needed to 
calculate SSI SIRs for abdominal hysterectomy, and 1,262 hospitals (37 
percent) did not have sufficient data to calculate SIRs for colon 
surgery. However, nationally, procedure volumes declined even further 
during the COVID-19 PHE in 2020, compared to 2019, with decreases of up 
to 23 percent for colon procedures and 39 percent for abdominal 
hysterectomy procedures.\641\ As of July 2021, abdominal hysterectomy 
procedures were still 6 percent below predicted levels.\642\ These 
changes in patient volumes for the SSI measure limit our ability to 
calculate SSI SIRs for hospitals that do not have sufficient data in FY 
2023, which may impact the accuracy and reliability of overall national 
comparison on performance for this measure.
---------------------------------------------------------------------------

    \641\ Weiner-Lastinger, L, et al,. The impact of coronavirus 
disease 2019 (COVID-19) on healthcare-associated infections in 2020: 
A summary of data reported to the National Healthcare Safety 
Network. Infection Control & Hospital Epidemiology (2022), 43, 12-
25. doi:10.1017/ice.2021.362.
    \642\ https://epicresearch.org/articles/elective-surgeries-approach-pre-pandemic-volumes.
---------------------------------------------------------------------------

    For the CDI measure, we are proposing to suppress the measure under 
Measure Suppression Factor 3, rapid or unprecedented changes in 
clinical guidelines, care delivery or practice, related protocols, or 
equipment or diagnostic tools or materials. Pandemic-related 
improvements to typical CDI prevention practices such as hand hygiene, 
PPE practices, and environmental cleaning could have contributed to the 
declines seen in the CDI SIR in 2021 compared to 2019.\643\ In 
addition, a decline in outpatient antibiotic prescribing was observed 
starting in 2020 as healthcare utilization decreased during the COVID-
19 pandemic.\644\ This, combined with the continued use of inpatient 
antibiotic stewardship programs in hospitals, may also have contributed 
to the decline in the national CDI SIRs, as reducing patient antibiotic 
exposure is a recommended strategy for CDI prevention. More information 
about CDI prevention strategies can be found at https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
---------------------------------------------------------------------------

    \643\ Weiner-Lastinger LM, et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \644\ The intersection of antibiotic resistance (AR), antibiotic 
use (AU), and COVID-19. Department of Health and Human Services 
website. https://www.hhs.gov/sites/default/files/antibiotic-resistance-antibiotic-use-covid-19-paccarb.pdf. Published February 
10, 2021. Accessed June 28, 2021.
---------------------------------------------------------------------------

    Additionally, because we cannot identify all potential elements 
that could be impacting the overall HAI experience at facilities during 
an unprecedented PHE as well as potential geographic disparities in the 
impact of the PHE that could cause uneven impact on facilities based on 
their location, and in order to reduce bias toward only those measures 
that are performing well at the national level, we believe all five CDC 
NHSN HAI measures should be suppressed. Therefore, we believe it is 
appropriate to suppress all five HAI measures in the Safety domain to 
ensure

[[Page 28431]]

an accurate and reliable national comparison of performance on hospital 
safety.
    We are also proposing to suppress the five CDC NHSN HAI measures 
for the FY 2023 program year under Measure Suppression Factor 4, 
significant national shortage or rapid or unprecedented changes in 
healthcare personnel. As discussed in section V.I.1.b.(2). of the 
preamble of this proposed rule, during the course of the COVID-19 PHE, 
an unprecedented number of healthcare personnel have left the workforce 
or ended their employment in hospitals.\645\ This healthcare personnel 
shortage worsened in 2021, with hospitals across the United States 
reporting 296,466 days of critical staffing shortages, an increase of 
86 percent from the 159,320 days of critical staffing shortage 
hospitals reported in 2020.\646\ Healthcare workers, especially those 
in areas with higher infection rates, have reported serious 
psychological symptoms, including anxiety, depression, and 
burnout.647 648
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    \645\ Health Affairs, COVID-19's Impact on Nursing Shortages, 
The Rise of Travel Nurses, and Price Gouging (Jan. 28, 2022), 
https://www.healthaffairs.org/do/10.1377/forefront.20220125.695159/.
    \646\ https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh.
    \647\ Kriti Prasad, Colleen McLoughlin, Martin Stillman, Sara 
Poplau, Elizabeth Goelz, Sam Taylor, Nancy Nankivil, Roger Brown, 
Mark Linzer, Kyra Cappelucci, Michael Barbouche, Christine A. 
Sinsky. Prevalence and correlates of stress and burnout among U.S. 
healthcare workers during the COVID-19 pandemic: A national cross-
sectional survey study. EClinicalMedicine, Volume 35. 2021. 100879. 
ISSN 2589-5370. https://doi.org/10.1016/j.eclinm.2021.100879.
    \648\ Vizheh, M., Qorbani, M., Arzaghi, S.M. et al. The mental 
health of healthcare workers in the COVID-19 pandemic: A systematic 
review. J Diabetes Metab Disord 19, 1967-1978 (2020). https://doi.org/10.1007/s40200-020-00643-9.
---------------------------------------------------------------------------

    Healthcare personnel staffing shortages and burnout has been shown 
to be significantly associated with hospital-associated infections, 
including urinary tract infections and surgical site 
infections.649 650 Along with being shown to impact quality 
of care,\651\ healthcare staffing shortages impact a hospital's ability 
to investigate infections and take corrective action.\652\ As discussed 
in section V.I.1.b.(2). of the preamble of this proposed rule, reports 
of hospital staff shortages have varied widely geographically, ranging 
from 10 to 50 percent of hospitals in any particular state reporting 
staffing shortages. Given the wide variance in reported staffing 
shortages, and the impact staffing shortages may have on CDC NHSN HAI 
scores, we believe our proposal to suppress the CDC NHSN HAI measures 
fairly addresses the geographic disparity in the impact of the COVID-19 
PHE on participating hospitals.
---------------------------------------------------------------------------

    \649\ Jeannie P. Cimiotti, et al., Nurse staffing, burnout, and 
health care-associated infection, American Journal of Infection 
Control, Volume 40, Issue 6, 2012, Pages 486-490, https://doi.org/10.1016/j.ajic.2012.02.029.
    \650\ Jinjin Shang, et al., Nurse staffing and Healthcare 
Associated Infection, Unit-level Analysis, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478399/.
    \651\ Aiken L, Clarke S, Sloane D. Hospital staffing, 
organization, and quality of care: Cross-national findings. 
International Journal for Quality in Health Care. Int J Qual Health 
Care. 2002.10.1093/intqhc/14.1.5.
    \652\ Healthcare-Associated Infections Increase Dramatically 
During Panemic, https://www.reliasmedia.com/articles/148560-healthcare-associated-infections-increase-dramatically-during-pandemic.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45272 through 
45274), we stated our belief that the 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. We believe that the continued 
distortion in measure performance is impacted by similar circumstances 
unique to the effects of the COVID-19 PHE as hospitals and researchers 
have investigated the impact of COVID-19 on HAIs and found that COVID-
19 is associated with increases in HAIs, with changes in the SIR 
varying geographically and over time.653 654 655 656 657 
Additionally, we believe that suppressing the HAI measures is 
appropriate because the impact of COVID-19 on the measure cannot be 
addressed through risk-adjustment. Under current collection 
requirements for the CDC NHSN HAI measures, the data used for risk-
adjustment are collected at the ward or facility level, meaning that 
the hospital submits infection data for a given ward or the entire 
facility rather than at the individual patient level. Accordingly, we 
are not able to identify the number of patients with HAIs who also had 
COVID-19 and therefore cannot risk-adjust for or otherwise account for 
COVID-19 diagnoses. In order to address the impact of the ongoing 
COVID-19 PHE on HAI incidence, we are proposing to suppress the CY 2021 
HAI measure data.
---------------------------------------------------------------------------

    \653\ Fakih MG, et al. (2021). Coronavirus disease 2019 (COVID-
19) pandemic, central-line-associated bloodstream infection 
(CLABSI), and catheter-associated urinary tract infection (CAUTI): 
The urgent need to refocus on hardwiring prevention efforts. 
Infection Control & Hospital Epidemiology, https://doi.org/10.1017/ice.2021.70.
    \654\ Palmore TN and Henderson DK. (2021). Healthcare-associated 
infections during the coronavirus disease 2019 (COVID-19) pandemic. 
Infection Control & Hospital Epidemiology, https://doi.org/10.1017/ice.2021.377.
    \655\ Weiner-Lastinger LM, et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \656\ Baker, Meghan A et al. ``The Impact of COVID-19 on 
Healthcare-Associated Infections.'' Clinical infectious diseases: An 
official publication of the Infectious Diseases Society of America, 
ciab688. 9 Aug. 2021, doi:10.1093/cid/ciab688.
    \657\ Advani, Sonali D et al. ``The impact of coronavirus 
disease 2019 (COVID-19) response on hospital infection prevention 
programs and practices in the southeastern United States.'' 
Infection control and hospital epidemiology, 1-4. 2 Nov. 2021, 
doi:10.1017/ice.2021.460.
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    We welcome public comment on our proposal to suppress the five HAI 
Safety domain measures for the FY 2023 program year.
c. Proposed Scoring and Payment Methodology for the FY 2023 Program 
Year Due to the COVID-19 PHE
    As described in section V.I.1.b. of the preamble of this proposed 
rule, we are proposing to suppress six measures in the Hospital VBP 
Program for FY 2023 and use a special rule for FY 2023 scoring, which 
we would codify in our regulations at 42 CFR 412.168. Specifically, we 
are proposing that we would calculate measure rates for all measures in 
the FY 2023 program year. For measures that we have proposed to 
suppress or measures for which we have finalized suppression, we would 
not use the measure rates to generate achievement and improvement 
points within the Hospital VBP Program'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 
remaining measures in the Clinical Outcomes domain and the Efficiency 
and Cost Reduction domain that have not been proposed for suppression 
and that, because no other domains receive scores for the FY 2023 
program year, we would not award TPSs to any hospital for FY 2023.
    Because no hospital would receive a TPS for FY 2023, we further 
propose that we would reduce each hospital's base-operating DRG payment 
amount by two 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 two 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

[[Page 28432]]

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. 
Unlike other hospital value-based purchasing programs that are 
intentionally designed to focus on specific aspects of quality, such as 
the HAC Reduction Program and the Hospital Readmissions Reduction 
Program, the Hospital VBP Program is uniquely designed to address a 
comprehensive set of quality and efficient metrics that evaluate 
multiple facets of quality. However, as discussed in the measure 
suppression proposals in section V.I.1.b. of the preamble of this 
proposed rule, the data from several measures has been 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 
hospitals' overall performance in providing quality of care during a 
pandemic. We believe that the current scoring methodology remains a 
balanced and comprehensive approach for tying payment to hospitals for 
their performance on a set of diverse measures that depict quality of 
care provided. However, we understand that the COVID-19 PHE has led to 
sudden and unexpected changes to healthcare systems. Our measure 
suppression policy was designed as a non-permanent approach to provide 
flexibility for changing conditions outside of participating hospitals' 
control and to avoid penalizing hospitals on measure scores that we 
believe are distorted by the COVID-19 PHE and are thus not truly 
reflective of quality of care. As we enter the third year of the 
pandemic, we believe that the updated knowledge of the virus and access 
to various treatment and mitigation efforts in place have provided 
hospitals with various tools to adapt to this virus. Therefore, as we 
discuss further in section V.I.2. of the preamble of this proposed 
rule, our goal is to continue resuming the use of measure data for 
scoring and payment adjustment purposes beginning with the FY 2024 
program year.
    In order to ensure that hospitals are aware of changes in their 
performance rates that we have observed, we are proposing to provide FY 
2023 confidential feedback reports that contain the measure rates we 
have calculated for the FY 2023 program year, along with achievement 
and improvement scores for all the measures in the Cost and Efficiency 
Reduction domain and the Clinical Outcomes domain that have not been 
finalized for suppression and a Cost and Efficiency Reduction domain 
and a Clinical Outcomes domain score. However, as previously discussed, 
we would not calculate TPSs for the purpose of adjusting hospital 
payments under the FY 2023 Hospital VBP Program. We note that the 
proposed special scoring methodology for FY 2023 generally aligns with 
the special scoring methodology finalized in for FY 2022 in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45295 through 45296).
    We invite public comment on these proposals.
    We also understand that, if finalized, the FY 2023 special scoring 
and payment policy proposal for the Hospital VBP Program has 
implications for the MIPS program. Under the facility-based measurement 
option within MIPS described at 42 CFR 414.1380(e), clinicians eligible 
for facility-based measurement may have their MIPS quality and cost 
performance category scores based on the Total Performance Score of the 
applicable hospital from the Hospital VBP Program as determined under 
42 CFR 414.1380(e)(5). As described at 42 CFR 414.1380(e)(1)(ii) and in 
the CY 2019 PFS final rule, the scoring methodology applicable for MIPS 
eligible clinicians scored with facility-based measurement is the Total 
Performance Score methodology adopted for the Hospital VBP Program, for 
the fiscal year for which payment begins during the applicable MIPS 
performance period. Thus, for the CY 2022 MIPS performance period/CY 
2024 MIPS payment year, the Total Performance Score under the Hospital 
VBP Program for the FY 2023 program year would be applied. If a 
hospital does not have a Total Performance Score under the Hospital VBP 
Program for FY 2023, facility-based measurement would not be available 
for the MIPS eligible clinicians to whom that hospital's Total 
Performance Score would be applicable. If our proposed special scoring 
policy for the Hospital VBP Program for FY 2023 is finalized, hospitals 
would not have a FY 2023 Total Performance Score, and the clinicians 
who would normally be assessed through facility-based measurement would 
need to identify another method of participating in MIPS for the CY 
2022 MIPS performance period/CY 2024 MIPS payment year or submit an 
application for reweighting a performance category or categories, if 
applicable.
2. FY 2023 Program Year Payment Details If Proposed Special Scoring and 
Payment Adjustment Policies Are Not Finalized
    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.I.1.b. of the preamble of this proposed rule, we are proposing to 
suppress several measures in the Hospital VBP Program for the FY 2023 
program year, and in section V.I.1.c. of the preamble of this proposed 
rule, we are proposing to apply special scoring and payment adjustment 
policies for the FY 2023 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.I.1. of the preamble of 
this proposed rule are not finalized, the FY 2023 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 2023 
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 2023 is approximately $1.7 billion, based on the 
December 2021 update of the FY 2021 MedPAR file. We would update this 
estimate for the FY 2023 IPPS/LTCH PPS final rule using the March 2022 
update of the FY 2021 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 2023, on a per-claim

[[Page 28433]]

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 because FY 2022 TPSs 
were not calculated due to the measure suppressions and special scoring 
policy finalized for the FY 2022 program year. We note that the FY 2021 
TPSs were calculated using measure data from before the COVID-19 PHE 
was declared. Actual TPSs for the FY 2023 program year may be more 
variable than the FY 2021 TPSs due to the impacts of the COVID-19 PHE 
on FY 2023 data. We refer readers to section V.I.1.b. 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 2.6279472273. This slope, 
along with the estimated amount 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 would 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 2022 update to the FY 2021 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 2023 in the FY 2023 IPPS/LTCH PPS final rule 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 2023 program year before the FY 2023 IPPS/LTCH PPS final 
rule is published. After hospitals have been given an opportunity to 
review and correct their actual TPSs for FY 2023, we would post Table 
16B (which would be available via the internet on the CMS website) to 
display the actual value-based incentive payment adjustment factors, 
exchange function slope, and estimated amount available for the FY 2023 
program year.
    If our proposals to suppress measures and award each hospital a 
value-based payment amount that matches the reduction to the base 
operating DRG payment amount are finalized, we would 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).
    We continue to be concerned about the impact of the COVID-19 PHE, 
but are encouraged by the rollout of COVID-19 vaccinations and 
treatment for those diagnosed with COVID-19 and we believe that 
hospitals are better prepared to treat patients with COVID-19. Our 
measure suppression policy focuses on a short-term, equitable approach 
during this unprecedented PHE, and was not intended for indefinite 
application. Additionally, we want to emphasize the long-term 
importance of value-based care and incentivizing quality care tied to 
payment. The Hospital VBP Program is an example of our long-standing 
effort to link payments to healthcare quality in the inpatient hospital 
setting.\658\
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    \658\ CMS has also partnered with the CDC in a joint Call to 
Action on safety, which is focused on our core goal to keep patients 
safe. Fleisher et al. (2022). New England Journal of Medicine. 
Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    We understand that the COVID-19 PHE is ongoing and unpredictable in 
nature, however, we believe that 2022 has a more promising outlook in 
the fight against COVID-19. As we enter the third year of the pandemic, 
healthcare providers have gained experience managing the disease, 
surges of COVID-19 infection, and adjusting to supply chain 
fluctuations.\659\ In 2022 and the upcoming years, we anticipate 
continued availability and increased uptake in the use of 
vaccinations,\660\ including the availability and use of vaccination 
for young children ages 5-11, who were not eligible for vaccination for 
the majority of 2021 and for whom only 32 percent had received at least 
one dose as of February 23, 2022 661 662 Additionally, the 
Food and Drug Administration (FDA) has expanded availability of at-home 
COVID-19 treatment, having issued the first emergency use 
authorizations (EUAs) for two oral antiviral drugs for the treatment of 
COVID-19 in December 2021. 663 664 Finally, the Biden-Harris 
Administration has mobilized efforts to distribute home test kits,\665\ 
N-95 masks,\666\ and increase COVID-19 testing in schools,\667\ 
providing more treatment and testing to the American people. Therefore, 
we note that our goal is to continue resuming the use of measure data 
for scoring and payment adjustment purposes beginning with the FY 2024 
program year. That is, for FY 2024, for each hospital, we would plan to 
calculate measure scores for the measures in the Hospital VBP Program 
for which the hospital reports the minimum measure requirements, as 
well as domain scores for the Hospital VBP Program domains for which 
the

[[Page 28434]]

hospital reports the minimum number of measures. We would then 
calculate a TPS for each eligible hospital and use the established 
methodology for converting the TPSs to value-based incentive payments 
for the given fiscal year.
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    \659\ McKinsey and Company. (2021). How COVID-19 is Reshaping 
Supply Chains. Available at: https://www.mckinsey.com/business-functions/operations/our-insights/how-covid-19-is-reshaping-supply-chains.
    \660\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \661\ KFF, Update on COVID-19 Vaccination of 5-11 Year Olds in 
the U.S., https://www.kff.org/coronavirus-covid-19/issue-brief/update-on-covid-19-vaccination-of-5-11-year-olds-in-the-u-s/.
    \662\ https://www.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-and-covid-19-vaccination-trends/.
    \663\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes First Oral Antiviral for Treatment 
of COVID-19. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-oral-antiviral-treatment-covid-19.
    \664\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes Additional Oral Antiviral for 
Treatment of COVID-19 in Certain Adults. Available at: https://
www.fda.gov/news-events/press-announcements/coronavirus-covid-19-
update-fda-authorizes-additional-oral-antiviral-treatment-covid-19-
certain#:~:text=Today%2C%20the%20U.S.%20Food%20and,progression%20to%2
0severe%20COVID%2D19%2C.
    \665\ The White House. (2022). Fact Sheet: The Biden 
Administration to Begin Distributing At-Home, Rapid COVID-19 Tests 
to Americans for Free. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/14/fact-sheet-the-biden-administration-to-begin-distributing-at-home-rapid-covid-19-tests-to-americans-for-free/.
    \666\ Miller, Z. 2021. The Washington Post. Biden to give away 
400 million N95 masks starting next week Available at: https://www.washingtonpost.com/politics/biden-to-give-away-400-million-n95-masks-starting-next-week/2022/01/19/5095c050-7915-11ec-9dce-7313579de434_story.html.
    \667\ The White House. (2022). FACT SHEET: Biden-Harris 
Administration Increases COVID-19 Testing in Schools to Keep 
Students Safe and Schools Open. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/12/fact-sheet-biden-harris-administration-increases-covid-19-testing-in-schools-to-keep-students-safe-and-schools-open/.
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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. Technical Measure Specification Updates To Include Covariate 
Adjustment for COVID-19 Beginning With the FY 2023 Program Year
    In the FY 2022 IPPS/LTCH PPS final rule, we stated that we were 
updating the Hospital 30-Day, All-Cause, Risk-Standardized Mortality 
Rate Following Acute Myocardial Infarction (AMI) Hospitalization (MORT-
30-AMI), Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Coronary Artery Bypass Graft (CABG) Surgery (MORT-30-CABG), 
Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate Following 
Chronic Obstructive Pulmonary Disease (COPD) Hospitalization (MORT-30 
COPD), Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Heart Failure (HF) Hospitalization (MORT-30-HF), and 
Hospital-Level Risk-Standardized Complication Rate Following Elective 
Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty 
(TKA) (COMP-HIP-KNEE) measures to exclude admissions with either a 
principal or secondary diagnosis of COVID-19 present on admission from 
the measure denominators beginning in FY 2023 (86 FR 45256 through 
45258). We stated that we were making these updates pursuant to the 
technical updates policy we finalized in the FY 2015 IPPS/LTCH PPS 
final rule. Under this policy, we use 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). As we stated in the FY 2022 IPPS/LTCH PPS final 
rule, we continue to believe that this 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).
    As we continue to evaluate the effects of COVID-19 on the Hospital 
VBP Program measure set, we have observed that for some patients COVID-
19 continues to have lasting effects, including fatigue, cough, 
palpitations, and others potentially related to organ damage, post 
viral syndrome, post-critical care syndrome or other reasons.\668\ 
These clinical conditions could affect a patient's risk of mortality or 
complications following an index admission and, as a result, impact a 
hospital's performance on one or more of the four condition-specific 
mortality measures or the procedure-specific complication measure 
included in the Hospital VBP Program. In order to account for case mix 
among hospitals, the current risk adjustment approach for these 
measures include covariates for clinical comorbidities present on 
admission (POA) and in the 12 months prior to the index admission that 
are relevant and have relationships with the outcome, for example 
patient history of coronary artery bypass (CABG) surgery or history of 
mechanical ventilation. In accordance with the principles used during 
measure development and to adequately account for patient case mix, we 
are further modifying the technical measure specifications for the 
MORT-30-AMI, MORT-30-CABG, MORT-30-COPD, MORT-30-HF, and COMP-HIP-KNEE 
measures to include a covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission.
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    \668\ Raveendran, A.V., Jayadevan, R. and Sashidharan, S., Long 
COVID: An overview. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056514/. Accessed on December 15, 2021.
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    This inclusion of the covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission will be effective 
beginning with the FY 2023 program year for the MORT-30-AMI, MORT-30-
CABG, MORT-30-COPD, MORT-30-HF, and COMP-HIP-KNEE measures. We will 
also include the covariate adjustment for patient history of COVID-19 
in the 12 months prior to the admission for the Hospital 30-Day, All-
Cause, Risk-Standardized Mortality Rate Following Pneumonia 
Hospitalization (MORT-30-PN) measure. We note that, even though we 
previously finalized that we would suppress the MORT-30-PN measure for 
the FY 2023 program year, we would still publicly report the measure, 
and therefore, the inclusion of the covariate adjustment for patient 
history of COVID-19 in the 12 months prior to the admission will still 
be effective beginning with the FY 2023 program year. We will delay 
sending MORT-30-PN confidential hospital feedback reports until October 
2022 and delay public reporting until January 2023 to allow time for 
hospitals to become informed about this measure update and their 
hospital-level results. We will resume including hospital performance 
on the MORT-30-PN measure in the payment adjustment calculations, using 
the updated MORT-30-PN measure, beginning in FY 2024. We believe that 
making these updates to the MORT-30-PN measure for FY 2023 in 
hospitals' confidential feedback reports will allow hospitals the 
opportunity to preview these updates to the measure specifications in 
FY 2023 before they are used as part of payment adjustments for the FY 
2024 program year.
    For more information on the application of covariate adjustments, 
including the technical updates we are announcing in this proposed 
rule, please see the Measure Updates and Specifications Reports 
(available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology).
d. Technical Updates to the Specifications for the MORT-30-PN Measure 
Beginning With the FY 2024 Program Year
    In the FY 2022 IPPS/LTCH PPS final rule, pursuant to the measure 
suppression policy finalized in that rule and described in section 
V.I.1. of the preamble this proposed rule, we finalized suppression of 
the MORT-30-PN measure (NQF #0468) for the FY 2023 program year (86 FR 
45274 through 45276), and we refer readers to

[[Page 28435]]

that final rule for additional information.
    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have continued to monitor the MORT-30-PN measure and have found that 
several factors, such as improved coding practices and decreased 
proportion of COVID-19 admissions for the MORT-30-PN cohort, have 
mitigated some of the impact of COVID-19 on this measure within certain 
data periods. Beginning in FY 2024 the MORT-30-PN measure will no 
longer be suppressed under the Hospital VBP Program. We are resuming 
the use of the MORT-30-PN measure for FY 2024 because of the following 
differences between the FY 2023 and FY 2024 performance periods: (1) 
The improved coding practices; (2) decreased proportion of COVID-19 
admissions in the MORT-30-PN measure for this performance period; and 
(3) sufficient available data to make technical updates to the measure 
specifications in order to further account for how patients with a 
COVID-19 diagnosis might impact the quality of care assessed by this 
measure. Specifically, effective January 2021 the ICD10 code J12.82, 
Pneumonia due to coronavirus disease 2019, was added for use as a 
secondary diagnosis, along with a principal diagnosis of COVID-19 
(U07.1), to identify patients with COVID-19 pneumonia. J12.82 is not 
included within the cohort of the MORT-30-PN measure, therefore 
mortality rates with pneumonia due to COVID-19 are not captured by this 
measure as of January 1, 2021. Whenever new codes are introduced, 
changes in coding practices are difficult to predict. At the time of 
the FY 2022 IPPS/LTCH PPS final rule, we did not have sufficient data 
to determine the effects of these coding changes on the proportion of 
COVID-19 patients and mortality rates with pneumonia due to COVID-19 in 
the MORT-30-PN measure. As additional months of data have become 
available since early 2021, we have now seen increased use of these 
codes. Secondly, as these coding changes have occurred and as the 
COVID-19 PHE has evolved, more recent data show the proportion of 
COVID-19 admissions in the MORT-30-PN measure have decreased compared 
to 2020 data. Finally, with the availability of additional data and the 
decrease in the proportion COVID-19 admissions in the MORT-30-PN 
measure, we are now able to make technical updates to the measure 
specifications in alignment with the technical updates we are making to 
four other mortality measures and one complication measure. 
Specifically, we are updating the technical specifications for the 
MORT-30-PN measure to exclude patients with either principal or 
secondary diagnoses of COVID-19 from the measure denominator beginning 
with the FY 2024 program year.
    We are also updating the technical specifications for the MORT-30-
PN measure to add a covariate that adjusts the measure outcome for a 
history of COVID-19 diagnosis in the 12 months prior to the admission 
(as discussed in section V.I.3.c. of the preamble of this proposed 
rule) and ensures alignment with the other four mortality and one 
complication measures. In our analysis, hospital-level MORT-30-PN 
measure scores calculated with the cohort and denominator exclusions 
and the addition of the covariate for a history of COVID-19 diagnosis 
in the 12 months prior (using data from July 1, 2018 through June 30, 
2021, excluding admissions from December 2, 2019 through June 30, 2020 
to apply the nationwide ECE granted due to the COVID-19 PHE (85 FR 
54833 through 54835)), resulted in mean measure scores that were closer 
to the prior pre-COVID-19 period (July 1, 2017 through December 2, 
2019) compared with the unchanged measure. We believe that excluding 
COVID-19 patients from the measure denominator, in addition to 
adjusting for a prior infection with COVID-19, will mitigate the impact 
of COVID-19 on this measure as much as is currently feasibly possible 
given the unpredictable nature of the pandemic, and ensure that this 
measure continues to reflect mortality rates as intended and meet the 
goals of the Hospital VBP Program beginning in FY 2024. We note that 
the MORT-30-PN measure uses three years of data. The performance period 
for the FY 2023 program year includes admissions from July 1, 2018 
through June 30, 2021, exclusive of January 1, 2020 through June 30, 
2020 data excluded due to the ECE waiver. Therefore, we continue to 
believe it is appropriate to suppress the currently implemented measure 
for use in payment calculations as finalized in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45274 through 45276). The MORT-30-PN measure is 
also included in confidential feedback reports and public reporting on 
CMS' Care Compare website separate from the Hospital VBP Program use of 
the measure. Technical specifications of the Hospital VBP Program 
measures are provided on our website under the Measure Methodology 
Reports section (available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html). Additional resources about the measure 
technical specifications and methodology for the Hospital VBP Program 
are on the QualityNet website (available at https://qualitynet.cms.gov/inpatient/hvbp).
e. Summary of Previously Adopted Measures for FY 2023 Through FY 2026 
Program Years
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45281 through 45284) for summaries of previously adopted measures for 
the FY 2024 and FY 2025 program years, and to Table V.I.-03 in this 
section showing summaries of previously adopted measures for the FY 
2024, FY 2025, and FY 2026 program years. We are proposing to suppress 
the HCAHPS and HAI measures for the FY 2023 program year. We are not 
proposing to add new measures at this time. If these measure 
suppression proposals are finalized as proposed, the Hospital VBP 
Program measure set for the FY 2023, FY 2024, FY 2025 and FY 2026 
program years would contain the following measures:
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4. Previously Adopted Baseline and Performance Periods
a. Background
    Section 1886(o)(4) of the Act requires the Secretary to establish a 
performance period for the Hospital VBP Program that begins and ends 
prior to the beginning of such fiscal year. We refer readers to the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56998 through 57003) for a 
previously finalized schedule for all future baseline and performance 
periods for previously adopted measures. We refer readers to the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38256 through 38261), the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41466 through 41469), the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42393 through 42395), the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58850 through 58854), and FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45284 through 45290) for additional previously 
adopted baseline and performance periods for the FY 2024 and subsequent 
program years.
b. Proposal To Update Baseline Periods for Certain Measures Due to the 
COVID-19 PHE
(1) Background
    We previously finalized baseline periods for the FY 2024, 2025, 
2026, 2027, and 2028 program years for all the measures included in the 
Hospital VBP Program, and we refer readers to Tables V.I.-04 through 
V.I.-08 for those

[[Page 28437]]

previously adopted baseline periods. However, subsequent to finalizing 
those baseline periods and, as described further in section V.I.1.b. of 
the preamble of this proposed rule, we are proposing to suppress the 
HCAHPS and five HAI measures for the purposes of scoring and payment 
for FY 2023. Because these baseline periods are used to determine 
achievement thresholds and are used in awarding improvement scores to 
hospitals, we are concerned with using COVID-19 impacted data for the 
FY 2025 baseline periods for scoring and payment purposes.
    Accordingly, to ensure that we have reliable data that are not 
unfairly affected by the COVID-19 PHE for baselining purposes, we are 
proposing several updates to the baseline periods in this proposed rule 
for the FY 2025 program year.
    We note that we are proposing to update the baseline periods for 
certain measures under the Hospital VBP Program that have a 1-year 
baseline period. However, for measures that have baseline periods that 
span across multiple years, we believe the previously established 
baseline periods provide enough data from before and after CY 2021 to 
still calculate baseline scores that would be reliable for scoring and 
payment purposes. Specifically, for the measures in the Clinical 
Outcomes domain (MORT-30-AMI, MORT-30-CABG, MORT-30-COPD, MORT-30-HF, 
MORT-30-PN, and COMP-HIP-KNEE), which have 36-month baseline periods, 
we are not proposing any changes to the previously established baseline 
periods for FY 2025.
(2) Proposal To Update the FY 2025 Baseline Period for the Person and 
Community Engagement Domain Measure (HCAHPS Survey)
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized that the 
baseline period for Person and Community Engagement Domain Measure 
(HCAHPS Survey) for the FY 2025 program year would be January 1, 2021 
through December 31, 2021 (81 FR 56998). However, as more fully 
described in section V.I.1.b. of the preamble of this proposed rule, we 
have determined that the top-box scores for hospitals are significantly 
lower in Q1 and Q2 of CY 2021 than they were in Q1 and Q2 of CY 2019 
(pre-pandemic), demonstrating the impact of COVID-19 on hospital 
performance for this measure. Therefore, in order to best mitigate the 
impact of using measure data affected by the COVID-19 PHE when 
determining achievement thresholds or awarding improvement points, we 
are proposing to use a baseline period of January 1, 2019 through 
December 31, 2019 for the FY 2025 program year. This baseline period 
would be paired with a performance period of January 1, 2023 through 
December 31, 2023. We believe using data from this period will provide 
sufficiently reliable data for evaluating hospital performance that can 
be used for FY 2025 scoring. We are selecting 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.
(3) Proposal To Update the FY 2025 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 2025, the baseline period for the Safety domain 
measures would be January 1, 2021 through December 31, 2021. However, 
as more fully described in section V.I.1.b. of the preamble of this 
proposed rule, we have determined that the national measure rates for 
the HAI measures have significantly deviated in national performance in 
CY 2021, indicating that the COVID-19 PHE has impacted performance on 
this measure. Therefore, in order to mitigate the impact of using 
measure data affected by the COVID-19 PHE when determining achievement 
thresholds or awarding improvement points, we are proposing to use a 
baseline period of January 1, 2019 through December 31, 2019 for the FY 
2025 program year. This baseline period would be paired with a 
performance period of January 1, 2023 through December 31, 2023. We 
believe using data from this period will provide sufficiently reliable 
data for evaluating hospital performance that can be used for FY 2025 
scoring. We are selecting 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.
c. Summary of Previously Adopted and Newly Proposed Baseline and 
Performance Periods for the FY 2024 Through FY 2028 Program Years
    Tables V.I.-04 through 08 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 statutory provisions governing performance standards 
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 IPPS/LTCH PPS 
final rule, FY 2014 IPPS/LTCH PPS final rule, and FY 2015 IPPS/LTCH PPS 
final rule (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 2022 IPPS/LTCH PPS final rule (86 FR 45290 
through 45292) for previously established performance standards for the 
FY 2024 program year. We note that the measure suppression proposals 
for the FY 2023 program year, discussed more fully in section V.I.1.b. 
of this proposed rule, will not affect the performance standards for 
the FY 2023 program year. However, as discussed in section V.I.1.c. of 
this proposed rule, we are proposing to not generate achievement or 
improvement points for any suppressed measures for FY 2023.
    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 2025 Program Year
    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

[[Page 28441]]

(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). 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.I.4.b. of this proposed rule, we 
are proposing to update the FY 2025 program year baseline periods for 
the measures included in the Safety domain and Person and Community 
Engagement domain. If these proposals are finalized, we would use data 
from January 1, 2019 through December 31, 2019 to calculate performance 
standards for the FY 2025 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 domain and Person and Community Engagement 
domain for the FY 2025 program year in Tables V.I.-09 and V.I.-10 were 
calculated using data from January 1, 2019 through December 31, 2019. 
Therefore, if our proposed updates to the baseline periods for these 
measures are finalized, we will not update the numerical values in the 
FY 2023 IPPS/LTCH PPS final rule.
    The previously established and estimated performance standards for 
the measures in the FY 2025 program year are set out in Tables V.I.-09 
and V.I.-10.
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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.I.4.b.(2). of 
this proposed rule, we are proposing to update the FY 2025 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 2025 program year for this measure.

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c. 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 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 
58859), 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 
Table V.I.-11.
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d. Previously Established Performance Standards for Certain Measures 
for the FY 2027 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 2022 IPPS/LTCH PPS final rule (86 FR 45294 through 
45295), we established performance standards for the FY 2027 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 
Table V.I.-12.

[[Page 28443]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.177

e. Newly Established Performance Standards for Certain Measures for the 
FY 2028 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 2028 
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 Table V.I.-13.
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[[Page 28444]]


6. Data Requirements
a. Domain Weighting 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.
b. Domain Weighting 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 
proposing any changes to these domain weights in this proposed rule.
c. Minimum Numbers of Measures for Hospital VBP Program Domains
    We refer readers to the FY 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.
d. 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); and the FY 2018 IPPS/LTCH 
PPS final rule (82 FR 38266 through 38267) . 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 Table V.I.-14.
[GRAPHIC] [TIFF OMITTED] TP10MY22.179

BILLING CODE 4120-01-C
e. 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
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45298 through 45299) for additional details related to the Hospital VBP 
Program ECE policy. We are not proposing any changes to the Hospital 
VBP Program ECE policy in this proposed rule.

[[Page 28445]]

8. References to Requests for Information
a. NHSN Digital Quality Measures
    We also refer readers to section IX.E.9.a. of this proposed rule, 
where we are requesting information on the potential future adoption of 
the National Healthcare Safety Network (NHSN) Healthcare-Associated 
Clostridioides difficile Infection Outcome Measure and the National 
Healthcare Safety Network (NHSN) Hospital-Onset Bacteremia & Fungemia 
Outcome Measure into the Hospital IQR Program. In addition, we are 
requesting information on the potential future inclusion of these 
digital CDC NHSN measures in the Hospital VBP Program. 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 Hospital VBP Program.
b. Reference to the Request for Information: Overarching Principles for 
Measuring Healthcare Quality Disparities Across CMS Quality Programs
    We refer readers to section IX.B. of this proposed rule where we 
are seeking input on overarching principles in measuring healthcare 
quality disparities in hospital quality and value-based purchasing 
programs.

J. Hospital-Acquired Condition (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);
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58860 through 
58865); and
     The FY 2022 IPPS/LTCH PPS final rule (86 FR 45300 through 
45310).
    We have also codified certain requirements of the HAC Reduction 
Program at 42 CFR 412.170 through 412.172.
2. Flexibility for Changes That Affect Quality Measures During a 
Performance or Measurement Period in the HAC Reduction Program
a. Measure Suppression Policy for the Duration of the COVID-19 PHE
    In the FY 2022 IPPS/LTCH PPS final rule, we adopted a policy for 
the duration of the COVID-19 PHE enabling us to suppress a number of 
measures from the Total HAC Score calculations for the HAC Reduction 
Program if we determine that circumstances caused by the COVID-19 PHE 
have affected these measures and the resulting Total HAC Scores 
significantly (86 FR 45301 through 45304). We refer readers to the FY 
2022 IPPS/LTCH PPS final rule for further details on our measure 
suppression policy (86 FR 45301 through 45304).
    In the FY 2022 IPPS/LTCH PPS final rule, we also adopted Measure 
Suppression Factors to 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 (86 FR 45302). We adopted these 
Measure Suppression Factors for use in the HAC Reduction Program, and, 
for consistency, in 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 
continue to 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 will help ensure 
consistency in our measure evaluations across programs. The previously 
adopted Measure Suppression Factors are as follows:
     Significant deviation in national performance on the 
measure during the COVID-19 PHE, which could be significantly better or 
significantly worse compared to historical performance during the 
immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the COVID-19 PHE.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We stated that we view this measure suppression policy as necessary 
to ensure that the HAC Reduction Program does not reward or penalize 
facilities based on factors that the Program's measures were not 
designed to accommodate (86 FR 45302).
    We are proposing changes to this measure suppression policy in 
section V.J.2.b.(2). below.
b. Proposals To Apply the Measure Suppression Policy to FY 2023 and FY 
2024 HAC Reduction Program Years
(1) Background
    Through memoranda released in March 2020 \669\ and an interim final 
rule with comment (IFC) published in September 2020 (85 FR 54827 
through 54828), in response to the COVID-19 PHE, we excluded, by 
application of our Extraordinary Circumstances Exception (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.
---------------------------------------------------------------------------

    \669\ Centers for Medicare and Medicaid Services. (2020). 
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 
Available at: https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------

    Additionally, in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
our policy suppressing the third and fourth quarters of CY 2020 \670\ 
CDC NHSN HAI

[[Page 28446]]

and CMS PSI 90 data from our performance calculations for FY 2022, FY 
2023, and FY 2024 under the proposed Measure Suppression Factor 1, 
``significant deviation in national performance on the measure, which 
could be significantly better or significantly worse compared to 
historical performance during the immediately preceding program 
years''; and the Measure Suppression Factor 4 subfactor, ``significant 
national or regional shortages or rapid or unprecedented changes in 
patient case volumes or case mix'' (86 FR 45304 through 45307). We 
explained that 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.
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    \670\ In the FY 2022 IPPS/LTCH PPS final rule, we finalized the 
suppression of the third and fourth quarters of CY 2020, which is 
July 1, 2020 through September 30, 2020 (Q3 2020) and October 1, 
2020 through December 31, 2020 (Q4 2020).
---------------------------------------------------------------------------

    These policies resulted in the following applicable periods for 
calculating Total HAC Scores for FY 2022, FY 2023, and FY 2024 HAC 
Reduction Programs:
[GRAPHIC] [TIFF OMITTED] TP10MY22.180

    In sections V.J.2.b.(2). and (3), of this proposed rule, we are 
proposing to further modify some of these applicable periods.
(2) Proposed Updates to the FY 2023 HAC Reduction Program
    In this proposed rule, we are proposing two updates for the FY 2023 
HAC Reduction Program's measure suppression policy: (1) We are 
proposing to suppress the CMS PSI 90 measure and the five CDC NHSN HAI 
measures from the calculation of measure scores and the Total HAC 
Score, thereby not penalizing any hospital under the HAC Reduction 
Program FY 2023 program year; and (2) For the CMS PSI 90 measure, we 
are proposing to not calculate or report measure results for the HAC 
Reduction Program FY 2023 program year.
    COVID-19 has had significant negative health effects--on 
individuals, communities, and the nation as a whole. Consequences for 
individuals who have COVID-19 include morbidity, hospitalization, 
mortality, and post-COVID conditions (also known as long COVID). As of 
mid-December 2021, over 50 million COVID-19 cases, 3 million new COVID-
19 related hospitalizations, and over 800,000 COVID-19 deaths have been 
reported in the U.S.\671\ One analysis projected that COVID-19 would 
reduce life expectancy in 2020 by 1.13 years overall, with the 
estimated impact disproportionately affecting members of historically 
underserved and under-resourced communities. According to this 
analysis, the estimated life expectancy reduction for Black and Latino 
populations is 3 to 4 times the estimate when comparing to the white 
population.\672\ Indeed, COVID-19 has overtaken the 1918 influenza 
pandemic as the deadliest disease event in American history.\673\ 
Impacts of the pandemic have continued to accelerate in 2021. The Delta 
variant of COVID-19 (B.1.617.2), which was first identified in India, 
surfaced in the United States in early-to-mid 2021. It was found that 
the Delta variant is 60 percent more transmissible compared to the 
previously dominant Alpha variant.\674\ Further, in November 2021, the 
number of COVID-19 deaths for 2021 surpassed the total deaths for 2020. 
According to CDC data, the total number of deaths involving COVID-19 
reached 385,453 in 2020 and 451,475 in 2021.\675\ We continue to 
monitor and evaluate the measures in the HAC Reduction Program for 
impacts due to COVID-19 and the emergence of COVID-19 variants, such as 
Delta and Omicron variants, and will elaborate further below.
---------------------------------------------------------------------------

    \671\ Centers for Disease Control and Prevention. (2021). COVID 
Data Tracker, https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
    \672\ Andrasfay, T., & Goldman, N. (2021). Reductions in 2020 US 
life expectancy due to COVID-19 and the disproportionate impact on 
the Black and Latino populations. Proceedings of the National 
Academy of Sciences of the United States of America, 118(5), 
e2014746118. https://www.pnas.org/content/118/5/e2014746118.
    \673\ STAT News. (2021). Covid-19 overtakes 1918 Spanish flu as 
deadliest disease in American history, https://www.statnews.com/2021/09/20/covid-19-set-to-overtake-1918-spanish-flu-as-deadliest-disease-in-american-history/.
    \674\ Allen H., Vusirikala A., Flannagan J., et al. Increased 
Household Transmission of COVID-19 cases associated with SARS-CoV-2 
Variant of Concern B.1.617.2: A national case-control study. Public 
Health England. 2021.
    \675\ Centers for Disease Control. (2022). COVID-19 Death Data 
and Resources. Available at: https://www.cdc.gov/nchs/nvss/covid-19.htm.
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    As described in section V.J.2.b.(1). of this proposed rule, we 
previously excluded or suppressed all quarters of CY 2020 data from the 
calculation of the Total HAC Score, in part, because of concerns about 
the national comparability of these data and significant deviation in 
national performance on the measure compared to historical performance. 
We acknowledge that the time needed to adapt to the strains of the PHE 
and national performance deviated from previous performance during CY 
2021 and therefore are proposing to suppress all HAC Reduction Program 
measures (CMS PSI 90, CAUTI, CLABSI, Colon and Hysterectomy SSI, MRSA, 
and CDI) from the calculation of the Total HAC Score for the FY 2023 
HAC Reduction Program under 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; Measure 
Suppression Factor 3, rapid or unprecedented changes in clinical 
guidelines, care delivery or practice, treatments, drugs, or related 
protocols, or equipment or diagnostic tools or materials; and the 
Measure Suppression Factor 4, significant national or regional

[[Page 28447]]

shortages or rapid or unprecedented changes in patient case volumes or 
case mix.
    We are concerned that the COVID19 PHE resulted in changes in HAC 
Reduction Program measure performance such that we will not be able to 
score hospitals fairly. We refer readers to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45304 through 45305) for previous analysis on the HAC 
Reduction Program measures that showed that measure rates for the 
CLABSI, CAUTI, and MRSA measures increased during the CY 2020 pandemic 
year as compared to the pre-COVID CY 2019 year immediately preceding 
the COVID-19 PHE.
    We are proposing to suppress three of the five CDC NSHN HAI 
measures (CLABSI, CAUTI, and MRSA) under 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. 
To determine whether the CLABSI, CAUTI, and MRSA measure rates would 
continue to show increases for CY 2021, the CDC analyzed changes in 
standardized infection ratios (SIRs) for Q1 and Q2 of CY 2021 as 
compared to the SIRs in Q1 and Q2 of CY 2019. This analysis found that 
the CLASBI, CAUTI, and MSRA measures had statistically significant 
measure rate increases during Q1 and Q2 of CY 2021 as compared to pre-
pandemic levels in Q1 and Q2 of CY 2019. For Q1 2021, the national SIR 
increased by approximately 45 percent for the CLABSI measure, 
approximately 12 percent for the CAUTI measure, and approximately 39 
percent for the MRSA measure as compared to Q1 2019. For Q2 2021, the 
national SIR increased by approximately 15 percent for the CLABSI 
measure and approximately 8 percent for the MRSA measure. The SIRs for 
the CAUTI measure showed no statistically significant difference for Q2 
2021 as compared to Q2 2019.
    For the CDI measure, the national SIR decreased by approximately 16 
percent for Q1 2021 as compared to Q1 2019 and by approximately 14 
percent for Q2 2021 as compared to Q2 2019. The SSI measure showed no 
significant increase or decrease in SIRs during Q1 2021 and Q2 2021 as 
compared to Q1 2019 and Q2 2019, however there has been an appreciable 
decrease in procedure volume for the measure. We are proposing to 
suppress the SSI and CDI measures under Measure Suppression Factor 4, 
significant national shortages or rapid or unprecedented changes in 
patient case volumes and Measure Suppression Factor 3, rapid or 
unprecedented changes in clinical guidelines, care delivery or 
practice, treatments, drugs, or related protocols, or equipment or 
diagnostic tools or materials, respectively. Specifically, for the SSI 
measure, we are proposing to suppress the measure for FY 2023 under 
Measure Suppression Factor 4, rapid or unprecedented changes in patient 
case volumes. We note that the SSI measure has had a low procedure 
volume for many hospitals during the PHE, which impacts our ability to 
produce SIRs for that measure. For CY 2019, 2,087 hospitals (61 
percent) did not have sufficient procedure-level data needed to 
calculate an SSI SIR for abdominal hysterectomy, and 1,262 hospitals 
(37 percent) did not have sufficient data to calculate an SIR for colon 
surgery. However, nationally, procedure volumes declined even further 
during the COVID-19 PHE in 2020, compared to 2019, with decreases of up 
to 23 percent for colon procedures and 39 percent for abdominal 
hysterectomy procedures.\676\ As of July 2021, abdominal hysterectomy 
procedures were still 6 percent below predicted levels.\677\ These 
changes in patient volumes for the SSI measure limit our ability to 
calculate SSI SIRs for hospitals that don't have sufficient data in FY 
2023, which may impact the accuracy and reliability of overall national 
comparison on performance for this measure.
---------------------------------------------------------------------------

    \676\ Weiner-Lastinger, L, et al. The impact of coronavirus 
disease 2019 (COVID-19) on healthcare-associated infections in 2020: 
A summary of data reported to the National Healthcare Safety 
Network. Infection Control & Hospital Epidemiology (2022), 43, 12-
25. doi:10.1017/ice.2021.362.
    \677\ Butler, S, et al. (2021). Epic Research. Elective 
Surgeries Approach Pre-Pandemic Volumes. Available at: https://epicresearch.org/articles/elective-surgeries-approach-pre-pandemic-volumes.
---------------------------------------------------------------------------

    For the CDI measure, we are proposing to suppress the measure under 
Measure Suppression Factor 3, rapid or unprecedented changes in 
clinical guidelines, care delivery or practice, related protocols, or 
equipment or diagnostic tools or materials. Pandemic-related 
improvements to typical CDI prevention practices such as hand hygiene, 
PPE practices, and environmental cleaning could have contributed to the 
declines seen in the CDI SIR in 2021 compared to 2019.\678\ In 
addition, a decline in outpatient antibiotic prescribing was observed 
starting in 2020 as healthcare utilization decreased during the COVID-
19 pandemic. \679\ This, combined with the continued use of inpatient 
antibiotic stewardship programs in hospitals, may also have contributed 
to the decline in the national CDI SIRs, as reducing patient antibiotic 
exposure is a recommended strategy for CDI prevention. More information 
about CDI prevention strategies can be found at https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
---------------------------------------------------------------------------

    \678\ Weiner-Lastinger LM, et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \679\ The intersection of antibiotic resistance (AR), antibiotic 
use (AU), and COVID-19. (2021). Department of Health and Human 
Services website. https://www.hhs.gov/sites/default/files/antibiotic-resistance-antibiotic-use-covid-19-paccarb.pdf. Published 
February 10, 2021. Accessed June 28, 2021.
[GRAPHIC] [TIFF OMITTED] TP10MY22.181


[[Page 28448]]


    Additionally, because we cannot identify all potential elements 
that could be impacting the overall HAI experience at hospitals during 
an unprecedented PHE as well as potential geographic disparities in the 
impact of the PHE that could cause uneven impact on facilities based on 
their location, like shortages of healthcare personnel, we believe all 
five CDC NHSN HAI measures should be suppressed. Therefore, we believe 
it is appropriate to suppress all five HAI measures from the HAC 
Reduction Program for the FY 2023 program year, to ensure an accurate 
and reliable national comparison of performance on hospital safety.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45304 through 
45305), we observed that the skewed measure performance may be due to 
circumstances unique to the effects of the pandemic such as staffing 
shortages and turnover, patients who are more susceptible to infections 
due to increased hospitalization stays, and longer indwelling catheters 
and central lines. We believe that the continued skewed measure 
performance is impacted by similar circumstances unique to the effects 
of the COVID-19 PHE. We further believe that our proposal to suppress 
the HAI measure data from CY 2021 is appropriate because the impact of 
the COVID-19 PHE on the measures cannot be addressed through risk-
adjustment. Under current data collection requirements for the CDC NHSN 
HAI measures the data are collected at each hospital's ward level, 
meaning that the hospital submits infection data for a given ward 
rather than at the individual patient level. Accordingly, we are not 
able to identify the number of patients with HAIs who also had COVID-19 
and therefore cannot risk-adjust for or otherwise account for COVID-19 
diagnoses. Modifying CDC's risk adjustment methodology is a multi-year 
process that requires substantial time to review, analyze, and 
implement updated methodology for the calculation of the SIR. In order 
to address the impact of the ongoing COVID-19 PHE on HAI incidence, as 
reported to CDC NHSN, we believe suppression of the CY 2021 measure 
data is the best path forward for participating hospitals. Therefore, 
we are proposing to suppress all five HAI measures in the HAC Reduction 
Program for the FY 2023 program year.
    In accordance with the previously adopted measure suppression 
policy (86 FR 45301 through 45304), we are proposing to suppress the 
CMS PSI 90 measure and the five CDC NHSN HAI measures for the HAC 
Reduction Program FY 2023 program year. We will continue to provide the 
measure results for the CDC NHSN HAI measures to hospitals via their 
hospital-specific reports (HSRs). We will also continue providing 
information regarding hospital performance to hospitals and other 
interested persons via the Care Compare tool hosted by Health and Human 
Services, currently available at https://www.medicare.gov/care-compare, 
and the Provider Data Catalog. As previously noted, under this policy, 
we would continue to use claims data for the CMS PSI 90 measure and 
participating hospitals would continue to report CDC NHSN HAI measure 
data to the CDC, so that we can monitor the effect of the circumstances 
on quality measurement and determine appropriate policies in the 
future.
    Similarly, our analysis of the CMS PSI 90 measure suggested that 
comparability of performance on the measure has also been impacted by 
the PHE. Additionally, after the nationwide ECE (85 FR 54827 through 
54828) and the FY 2022 IPPS/LTCH PPS final rule measure suppression 
policies (86 FR 45304 through 45307) the CMS PSI 90 reference period 
for the FY 2023 program year does not include data affected by the 
COVID-19 PHE. Conversely, the applicable period for the CMS PSI 90 
measure does include data affected by COVID-19 PHE. Due to the fact 
that the reference period for this measure does not include data 
affected by the COVID-19 PHE and the applicable period does include 
such data, this would result in risk adjustment parameters that do not 
account for the impact of COVID-19 on affected patients. We believe 
that this misalignment would produce distorted measure results and 
potentially yield biased CMS PSI 90 measure results among hospitals 
highly impacted by the COVID-19 PHE. Therefore, for the FY 2023 program 
year we propose to not calculate measure results for CMS PSI 90, to not 
provide the measure results for the CMS PSI 90 measure to hospitals via 
their hospital-specific reports (HSRs), and to not publicly report 
those measure results on the Care Compare tool hosted by Health and 
Human Services and the Provider Data Catalog. We refer readers to 
section V.J.3.c.(1). and (2) of this proposed rule where we discuss the 
impact of the COVID-19 PHE on the CMS PSI 90 measure and a technical 
update to the measure specifications to risk-adjust for COVID-19 
diagnoses.
    For the remaining measures, specifically the CDC NHSN HAI measures, 
we would use the previously finalized applicable periods \680\ to 
calculate measure results (that is, SIRs for each of the CDC NHSN HAI 
measures) the FY 2023 program year. We would use those measure results 
in feedback reports to hospitals and as part of program activities, 
fulfilling our obligation under section 1886(p)(5) of the Act to 
provide confidential reports to applicable hospitals with information 
on their performance on measures with respect to hospital-acquired 
conditions. Consumers may continue to access information on hospital 
performance with regards to hospital-acquired conditions through 
several channels, including the Care Compare tool hosted by Health and 
Human Services, currently available at https://www.medicare.gov/care-compare, the Provider Data Catalog, available at https://data.cms.gov/provider-data/.
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    \680\ In the FY 2022 IPPS/LTCH PPS final rule, we finalized that 
the applicable periods for the FY 2023 HAC Reduction Program are for 
the CDC NHSN HAI measures the 12-month period from January 1, 2021 
through December 31, 2021.
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    Ultimately, if we finalize our proposals, all hospitals would 
receive a Total HAC Score of zero, and no hospitals would receive a 
penalty for FY 2023. We would confidentially and publicly report the 
measure scores of ``N/A'', Total HAC Score of zero and payment 
reduction indicators of ``no penalty'' for all hospitals for the FY 
2023 program year. For the five CDC NHSN HAI measures, we would also 
report the measure results, both via HSRs and public reporting methods. 
For the CMS PSI 90 measure results, we would not calculate or report on 
the measure results and would indicate `N/A' in confidential and public 
reporting. We would resume calculating measure scores in the FY 2024 
program year, as discussed in section V.J.2.b.(3). of this proposed 
rule.
    In determining how to address the impact of the COVID-19 PHE on 
hospital performance and calculating Total HAC Scores for FY 2023, we 
also considered suppressing some CY 2021 quality measure data as an 
alternative to suppressing all measures. Under this alternative, we 
considered suppressing the CY 2021 data for the CLABSI, CAUTI, and MRSA 
measures on the basis that performance on those measures continued to 
be affected by the COVID-19 PHE. We considered scoring hospitals based 
solely on their performance on SSI, CDI, and CMS PSI 90; however, we 
had concerns about running the HAC Reduction Program on only half of 
the program's measures as this may result in measure scores that are 
significantly better or worse than in immediately preceding years. In

[[Page 28449]]

addition, a Total HAC score based on only three program measures would 
be less reliable, with more random noise in identification of bottom 
quartile hospitals, than a score based on six program measures. 
Therefore, we believe it is appropriate to suppress all five CDC NSHN 
HAI measures and the CMS PSI 90 measure from the calculation of measure 
scores and Total HAC Scores for the FY 2023 program year.
    We also considered making no modifications to the program and 
suppressing no additional measure data from the FY 2023 Total HAC 
Scores rather than extending the measure suppression policy. As 
discussed, when considering this approach in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45305), this alternative would be operationally 
easier to implement, but would mean assessing participating hospitals 
using quality measure data that have been distorted 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 CY 
2021 at a disadvantage compared to hospitals in regions that were more 
heavily affected in CY 2020. Ultimately, we believe that our proposal 
to suppress all measures from the FY 2023 HAC Reduction Program more 
fairly addresses the impact of the COVID-19 PHE for participating 
hospitals.
    Finally, we considered reusing a previous fiscal year's applicable 
period to serve as the applicable period for FY 2023. Although this 
option would enable us to continue operating the program, it has the 
disadvantage of double penalizing hospitals that were in a prior fiscal 
year's worst performing quartile even if the hospital had implemented 
policy and operational changes to improve their performance in future 
program years. Under this option, no new quality data would be used to 
inform hospitals or drive quality improvement.
    We continue to be concerned about the pandemic, but are encouraged 
by the development and rollout of prevention techniques like COVID-19 
vaccinations and treatment for those diagnosed with COVID-19. Our 
measure suppression policy focuses on a short-term, equitable approach 
during this unprecedented PHE, and was not intended for indefinite 
application. We also recognize that measure performance for some 
measures may not immediately return to levels seen prior to the PHE, 
particularly for the CDC NHSN HAI measures for which we do not receive 
patient-level data. Additionally, we wanted to emphasize the long-term 
importance of value-based care and incentivizing quality care tied to 
payment. The HAC Reduction Program is an example of our long-standing 
effort to link payments to healthcare quality in the inpatient hospital 
setting payment.\681\ Therefore, we note that our goal is to continue 
resuming the use of measure data for the purposes of scoring and 
payment adjustment beginning with the FY 2024 program year.
---------------------------------------------------------------------------

    \681\ CMS has also partnered with the CDC in a joint Call to 
Action on safety, which is focused on our core goal to keep patients 
safe. Fleisher et al. (2022). New England Journal of Medicine. 
Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
---------------------------------------------------------------------------

    We understand that the COVID-19 PHE is ongoing and unpredictable in 
nature, however, we believe that 2022 has a more promising outlook in 
the fight against COVID-19. As we enter the third year of the pandemic, 
healthcare providers and systems have gained experience managing the 
disease, surges of COVID-19 infection, and adjusting to supply chain 
fluctuations.\682\ In 2022 and the upcoming years, we anticipate 
continued availability and increased uptake in the use of vaccinations 
and the associated boosters,\683\ including vaccination for children 
which was not available for most of 2021.\684\ Additionally, the FDA 
issued emergency use authorizations (EUAs) for the first oral antiviral 
COVID-19 pill on December 22, 2021, and later approved a second the 
following day, expanding access to at-home COVID-19 treatment 
options.685 686 Finally, the Biden-Harris Administration has 
mobilized efforts to distribute home test kits,\687\ N-95 masks,\688\ 
and increase COVID-19 testing in schools,\689\ providing more treatment 
and testing to the American people. Given these developments, we will 
continue to assess the impact of the PHE on measure data used for the 
HAC Reduction Program.
---------------------------------------------------------------------------

    \682\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \683\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \684\ Centers for Disease Control and Prevention. (2022). CDC 
Expands booster Shot Eligibility and Strengthens Recommendations for 
12-17 Year Olds. Available at: https://cdc.gov/media/releases/2022/
s0105-Booster-
Shot.html#:~:text=Today%2C%20CDC%20is%20endorsing%20the,initial%20Pfi
zer-BioNTech%20vaccination%20series.
    \685\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes First Oral Antiviral for Treatment 
of COVID-19. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-oral-antiviral-treatment-covid-19.
    \686\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes Additional Oral Antiviral for 
Treatment of COVID-19 in Certain Adults. Available at: https://
www.fda.gov/news-events/press-announcements/coronavirus-covid-19-
update-fda-authorizes-additional-oral-antiviral-treatment-covid-19-
certain#:~:text=Today%2C%20the%20U.S.%20Food%20and,progression%20to%2
0severe%20COVID%2D19%2C.
    \687\ The White House. (2022). Fact Sheet: The Biden 
Administration to Begin Distributing At-Home, Rapid COVID-19 Tests 
to Americans for Free. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/14/fact-sheet-the-biden-administration-to-begin-distributing-at-home-rapid-covid-19-tests-to-americans-for-free/.
    \688\ Miller, Z. (2021). The Washington Post. Biden to give away 
400 million N95 masks starting next week Available at: https://www.washingtonpost.com/politics/biden-to-give-away-400-million-n95-masks-starting-next-week/2022/01/19/5095c050-7915-11ec-9dce-7313579de434_story.html.
    \689\ The White House. (2022). FACT SHEET: Biden-Harris 
Administration Increases COVID-19 Testing in Schools to Keep 
Students Safe and Schools Open. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/12/fact-sheet-biden-harris-administration-increases-covid-19-testing-in-schools-to-keep-students-safe-and-schools-open/.
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    We invite public comments on our proposals.
(3) Proposal To Suppress CY 2021 CDC NHSN HAI Measure Data From the FY 
2024 HAC Reduction Program Year
    As described in section V.J.2.b.(1). of this proposed rule, we 
previously excluded or suppressed all quarters of CY 2020 data for all 
the program measures from the calculation of the Total HAC Score, in 
part, because of concerns about the national comparability of these 
data and significant deviation in national performance on the measure 
compared to historical performance. The exclusion and suppression of 
those data resulted in a shortened applicable period for the CMS PSI 90 
measure for the FY 2024 HAC Reduction Program, specifically the 18-
month period of January 1, 2021 through June 30, 2022. The applicable 
period for the CDC NHSN HAI measures for the FY 2024 program year was 
unaffected and remained as the 24-month period of January 1, 2021, 
through December 31, 2022.
    As described previously, we continue to be concerned about measure 
performance and the national comparability of such performance during 
CY 2021. We therefore are proposing to suppress CY 2021 CDC

[[Page 28450]]

NHSN HAI data from the FY 2024 HAC Reduction Program under 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.'' Under 
current data collection processes for the CDC NHSN HAI measures, we are 
not able to risk-adjust for or otherwise account for COVID-19 diagnoses 
and therefore must suppress the CY 2021 data in order to account for 
COVID-19 diagnoses in the CDC NHSN HAI data. For the FY 2024 program 
year, the resulting applicable period for CDC NHSN HAI measures would 
be the 12-month period of January 1, 2022, to December 31, 2022.
    To account for the impact of the COVID-19 PHE on CY 2021 data in 
the CMS PSI 90 measure, we are updating the measure specifications to 
risk-adjust for COVID-19 diagnoses, as described in section 
V.J.3.c.(2). of this proposed rule, beginning with the FY 2024 program 
year. Our analysis of the COVID-19 PHE impacts on CY 2021 data found 
that the decrease in volume continued in CY 2021 across nearly all 
component Patient Safety Indicator (PSI) measures, especially those 
related to surgical procedures (for which the denominator volume was 8 
percent to 45 percent lower in the first two quarters of CY 2021 than 
in the corresponding quarters of CY 2019). Our analysis also found that 
unadjusted rates continued to be high in CY 2021 for patients with a 
COVID-19 diagnosis compared to patients without a COVID-19 diagnosis. 
We refer readers to section V.J.3.c.(2). for more information about 
COVID-19 impacts on the CMS PSI 90 measure.
    For the CMS PSI 90 measure, the applicable period remains unchanged 
from January 1, 2021, through June 30, 2022.\690\ If finalized, these 
policies would result in the following applicable periods for FY 2023, 
FY 2024, and FY 2025 HAC Reduction Programs:
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    \690\ For the FY 2025 HAC Reduction Program year, there is no CY 
2021 data included in the applicable period for the HAI measures so 
the applicable period remains unchanged and would be January 1, 
2022, to December 31, 2023. For the CMS PSI 90 measure, the 
applicable period is July 1, 2021, through June 30, 2023. As 
discussed, to account for the impact of the COVID-19 PHE on CY 2021 
CMS PSI 90 measure data, we are updating the measure specifications 
to risk-adjust for COVID-19 diagnoses.
[GRAPHIC] [TIFF OMITTED] TP10MY22.182

    We invite public comments on this proposal to suppress CY 2021 CDC 
NHSN HAI Measure data from the FY 2024 HAC Reduction Program year.
3. Measures for FY 2023 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 28451]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.183

    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 https://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. However, we discuss our proposal to suppress all of the 
measures for the FY 2023 program year, as discussed in section 
V.J.2.b.(2). of the preamble of this proposed rule, and our proposal to 
suppress CY 2021 CDC NHSN HAI data from the FY 2024 program year, as 
discussed in section V.J.2.b.(3). of the preamble of this proposed 
rule.
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. Technical Measure Specification Updates to the CMS PSI 90 Measure
(1) Technical Measure Specification Update to the Minimum Volume 
Threshold for the CMS PSI 90 Measure beginning With the FY 2023 Program 
Year
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100 through 
50101), we finalized a subregulatory process to incorporate technical 
measure specification updates into the measure specifications we have 
adopted for the HAC Reduction Program. We stated our belief that this 
policy adequately balances our need to incorporate updates to HAC 
Reduction Program measures in the most expeditious manner possible 
while preserving the public's ability to comment on updates that so 
fundamentally change an endorsed measure that it is no longer the same 
measure that we originally adopted.
    Currently, the minimum volume threshold for the CMS PSI 90 measure 
requires hospitals to have three or more eligible discharges for at 
least one component indicator in order to receive a CMS PSI 90 measure 
score for the HAC Reduction Program (81 FR 57012). Although the CMS PSI 
90 measure surpasses the accepted reliability standard, based on an 
Intracluster Correlation Coefficient (ICC) for hospital-level reporting 
of at least 0.60 (in a standard 24-month performance period, the CMS 
PSI 90 measure demonstrated median reliability of 0.74), a small subset 
of hospitals have a reliability close to zero for their CMS PSI 90 
composite score due to the current minimum volume threshold for the 
measure.
    To address this subset of hospitals with a CMS PSI 90 composite 
score with reliability close to zero, we are instituting a stricter 
minimum volume threshold for the measure, which would prevent those 
small hospitals from receiving a CMS PSI 90 composite score. Consistent 
with the current minimum volume threshold policy, hospitals that do not 
meet the threshold criteria would not receive a measure result or, 
subsequently, a measure score (that is, a Winsorized z-score) for the 
CMS PSI 90 measure and it would not factor into the calculation of 
their Total HAC Score. Accordingly, in this proposed rule, we are 
announcing an increased minimum volume threshold for the CMS PSI 90 
measure, under which hospitals would be required to meet both of the 
following criteria in order to receive a CMS PSI 90 composite score:
     One or more component PSI measure with at least 25 
eligible discharges; and
     Seven or more component PSI measures with at least three 
eligible discharges.
    We note that this change to the CMS PSI 90 minimum volume threshold 
criteria will be applied to both the version of the measure used in HAC 
Reduction Program scoring calculations as well as the version of the 
measure displayed on the main pages of the Care Compare tool hosted by 
the U.S. Department of Health and Human Services, currently available 
at https://www.medicare.gov/care-compare, via updates to the next 
version of the CMS PSI 90 software. Additional information regarding 
the technical specifications for the CMS PSI 90 measure can be found on 
the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/psi/resources.
    An analysis of the impact of this threshold change on HAC Reduction 
Program results indicates that it would impact the scoring of a small 
number of low-volume hospitals. As a result of this threshold change, 
approximately five percent of hospitals would no longer receive a CMS 
PSI 90 composite score (and, subsequently, a CMS PSI 90 measure score) 
and approximately half of those hospitals, or 2.5 percent of all 
hospitals, would no longer receive a Total HAC Score. Accordingly, 
there will be a decrease in the number of hospitals in the worst-
performing quartile. We anticipate that the majority of the hospitals 
no longer receiving a Total HAC Score will be small hospitals with 
fewer than 100 beds. Rural hospitals, which tend to have lower 
capacity, are also more impacted by the

[[Page 28452]]

change than urban hospitals. The threshold change only impacts a small 
number of hospitals in the HAC Reduction Program while improving 
overall measure reliability.
(2) Technical Measure Specification Update to Risk-Adjust for COVID-19 
Diagnoses in the CMS PSI 90 Measure Beginning With the FY 2024 HAC 
Reduction Program Year
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45305) for previous analysis on the impact of the COVID-19 PHE on the 
CMS PSI 90 measure. Our analysis found that the decrease in volume 
continued in CY 2021 across all component Patient Safety Indicator 
(PSI) measures, especially those related to surgical procedures for 
which the denominator volume was 8 percent to 45 percent lower in the 
first two quarters of CY 2021 than in the corresponding quarters of CY 
2019. Our analysis also found that unadjusted rates continued to be 
high in CY 2021 for patients with a COVID-19 diagnosis compared to 
patients without a COVID-19 diagnosis, across most of the 10 component 
measures in CMS PSI 90. However, PSI 90 component rates among patients 
without COVID-19 were virtually unchanged through the COVID-19 PHE. CMS 
has found that adjusting for COVID-19 at the patient level entirely 
removes the incremental risk associated with this diagnosis. After 
risk-adjustment for COVID-19, PSI component rates appear consistently 
flat across the first two quarters of 2021.
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100 through 
50101), we finalized a subregulatory process to make nonsubstantive 
updates to measures used for the HAC Reduction Program. To address the 
impact of the COVID-19 PHE on the CMS PSI 90 measure, we are announcing 
a technical update to the CMS PSI 90 software to include COVID-19 
diagnosis as a risk-adjustment parameter for the FY 2024 program year 
and subsequent years.
d. HAC Reduction Program Requests for Information
(1) Digital CDC NHSN Measures
    We refer readers to section IX.E.9.a. of this proposed rule, where 
we request information on the potential future adoption of two digital 
NHSN measures, the NHSN Healthcare-associated Clostridioides difficile 
Infection Outcome Measure and the NHSN Hospital-Onset Bacteremia & 
Fungemia Outcome Measure, into the Hospital IQR Program, PCHQR Program, 
and the LTCH QRP. In addition, we request information on the potential 
inclusion of these digital CDC NHSN measures in the HAC Reduction 
Program. 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.
(2) Overarching Principles for Measuring Healthcare Quality Disparities 
Across CMS Quality Programs
    We refer readers to section IX.B. of this proposed rule where we 
are seeking input on overarching principles in measuring healthcare 
quality disparities in hospital quality and value-based purchasing 
programs.
4. Proposal To Update the CDC NHSN HAI Data Submission Requirements for 
Newly Opened Hospitals Beginning in the FY 2023 HAC Reduction Program 
Year
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57013), we finalized 
CDC NHSN HAI data submission requirements for newly-opened hospitals 
under the HAC Reduction Program that referred to the date that a 
hospital filed a notice of participation (NOP) with the Hospital IQR 
Program. At the time, the HAC Reduction Program obtained measure 
results that hospitals submitted to the CDC NHSN from the Hospital IQR 
Program. However, in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41545 
through 41553), we transferred our collection of the CDC NHSN HAI 
measures from the Hospital IQR Program to the HAC Reduction Program 
beginning with CY 2020 data. Given the transition from the Hospital IQR 
Program, the NOP requirements noted in the FY 2017 IPPS/LTCH PPS final 
rule do not apply.
    In this proposed rule, we are proposing to update the definition of 
``newly-opened hospitals'' for the CDC NHSN HAI measures to include 
hospitals with a Medicare Accept Date within the last 12 months of the 
performance period.\691\ Under the HAC Reduction Program scoring 
methodology, hospitals that are defined as newly-opened hospitals for 
the CDC NHSN HAI measures do not receive a measure score for any of the 
CDC NHSN HAI measures.
---------------------------------------------------------------------------

    \691\ Because the CMS PSI 90 measure requires at least 12 months 
of measure data (81 FR 50712), hospitals that open during the final 
12 months of the performance period would also not receive a CMS PSI 
90 measure score.
---------------------------------------------------------------------------

    The number of hospitals impacted by this change in criteria is 
small, less than one-quarter percent of hospitals. Hospitals with a 
Medicare Accept Date between the 12th and the 6th month before the end 
of the HAI performance period (January 1, 2021 to June 30, 2021 for the 
FY 2023 program year) do not meet the current criteria for newly-opened 
hospitals for the CDC NHSN HAI measures, but would meet the updated 
criteria.\692\ In addition, all of these hospitals do not have 12 
months of CMS PSI 90 data and because of this already do not receive a 
measure score for that measure. Therefore, all impacted hospitals would 
not receive a Total HAC Score for the program year and could not be 
subject to the one percent payment reduction. As per the measure 
suppression policy discussed in section V.J.2.b.(2). above we are 
proposing to suppress all six measures in the program for the FY 2023 
program year, so no hospitals will be impacted by this change for the 
FY 2023 program year.
---------------------------------------------------------------------------

    \692\ There is a small subset of hospitals with a Medicare 
Accept Date between the 6th and 9th month before the end of the HAI 
performance period (April 1, 2021, to June 30, 2021 for the FY 2023 
program year) and a Hospital IQR Program Notice of Participation 
Date during the last quarter of the HAI performance period (before 
October 1, 2021 or after December 31, 2021 for the FY 2023 program 
year), that are also currently defined as newly-opened hospitals. 
These hospitals' newly-opened status would not be impacted by this 
criteria change.
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    An analysis of the number of hospitals not meeting the current 
definition of ``new hospitals'' that would meet the criteria under this 
new proposed definition indicate that 0.22 percent of hospitals would 
have been affected by this definition change in the FY 2021 program 
year and 0.09 percent in the FY 2020 program year.
    We invite public comments on this proposal to update the newly-
opened hospital definition for CDC NHSN HAI measures beginning in the 
FY 2023 program year.
5. HAC Reduction Program Scoring Methodology and Scoring Review and 
Corrections Period
    In the 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. In this proposed rule we are not 
proposing to make any changes to the Scoring Calculations Review and 
Correction Period process.
    We note that in section V.J.2.b.(2). of this proposed rule, we are 
proposing to temporarily suppress all measures from the FY 2023 HAC 
Reduction Program.

[[Page 28453]]

We are proposing to calculate the measure results for the five CDC NHSN 
HAI measures for the FY 2023 HAC Reduction Program, but to not use 
those measure results to calculate measure scores (that is, Winsorized 
z-scores) for any of the measures because of our concerns regarding the 
comparability of measure results. Additionally, we are proposing to not 
calculate measure results for CMS PSI 90 measure nor publicly report 
the measure on the Care Compare tool hosted by Health and Human 
Services and the Provider Data Catalog. We are also proposing that all 
hospitals would receive a Total HAC Score of zero, and no hospitals 
would receive a penalty for FY 2023. We intend to resume the previously 
adopted HAC Reduction Program scoring methodology in FY 2024 (with the 
proposed suppression of CY 2021 CDC NHSN HAI data as discussed in 
section V.J.2.b.(3).) and for subsequent years. In section 
V.J.2.b.(2)., we invite public comment on the proposal to temporarily 
suppress all measures from the FY 2023 HAC Reduction Program.
6. 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 CY 2021 data for the 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 validation schedule posted on the QualityNet Secure 
Portal (also referred to as the Hospital Quality Reporting (HQR) 
System.
    In section V.J.2.b.(2). and V.J.2.b.(3). of this proposed rule, we 
are proposing to suppress all measures from the FY 2023 program and CY 
2021 CDC NHSN HAI data from the FY 2024 HAC Reduction Program, 
respectively. As discussed in those sections, hospitals are still 
required to submit such data and such data will be used for validation 
purposes. If hospitals do not submit measure data for validation during 
the FY 2024 program year, then those hospitals will automatically 
receive the maximum Winsorized z-score for the measure in the FY 2024 
program year payment calculation. We are not proposing any changes to 
the policies regarding measure validation in this proposed rule.
7. Clarification of the Removal of the No Mapped Locations Policy 
Beginning With the FY 2023 Program Year
    Under the HAC Reduction Program, hospitals have historically been 
able to receive a ``no mapped locations (NML)'' exemption \693\ for the 
CLABSI and CAUTI measures.\694\ This exemption has been applied when 
hospitals do not map an applicable ward (that is, Intensive Care Units 
(ICUs), surgical, medical, and medical-surgical wards) in the NHSN 
system, do not submit data for the measures, and do not submit an IPPS 
Measure Exception Form.\695\
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    \693\ Prior to FY 2018, the program used the term No Facilities 
Waiver for this same situation. Centers for Medicare & Medicaid 
Services. (2017). HACRP HAI Webinar Slides Final. Available at: 
https://www.qualityreportingcenter.com/globalassets/migrated-pdf/vbp-iqr-hacrp_hai_webinar_slides_vfinal508.pdf.
    \694\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP HSR User Guide. Available at: https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf.
    \695\ The valid OMB control number for the IPPS Measure 
Exception Form is 0938-1022.
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    In this proposed rule we would like to clarify the removal of the 
No Mapped Locations (NML) policy. The CDC has confirmed that the NML 
exemption does not indicate that a hospital does not need to report 
data, and that hospitals requesting to be exempt from reporting for CMS 
quality programs including the HAC Reduction Program, should submit an 
IPPS Measure Exception Form on the QualityNet website at https://qualitynet.cms.gov/files/5e3459aa152a7d001f93d36c?filename=IPPS_MeasureExceptionForm_CY2020.pdf. 
Therefore, we want to clarify that beginning in FY 2023 and subsequent 
years, the NML designation will no longer apply, and hospitals will be 
required to appropriately submit data to the NHSN or, if hospitals do 
not have the applicable locations for the CLABSI and CAUTI measures, 
the hospital must submit an IPPS Measure Exception Form to be exempt 
from CLABSI and CAUTI reporting for CMS programs. If the hospitals do 
not submit an IPPS Measure Exception Form and continue to not submit 
data to the NHSN, these hospitals would receive the maximum measure 
score (that is, Winsorized z-score) under the HAC Reduction Program for 
not reporting data. In the FY 2020 IPPS/LTCH PPS final rule, we 
instructed hospitals that do not have adequate locations for CLABSI or 
CAUTI reporting to submit the IPPS Measure Exception Form to the HAC 
Reduction Program beginning on January 1, 2020 (84 FR 42406), and the 
removal of the NML policy has previously been communicated in the FY 
2022 HAC Reduction Program Frequently Asked Questions \696\ and the FY 
2022 HAC Reduction Program HSR User Guide.\697\ Additionally, because 
NML only applies to a small subset of hospitals, we plan to execute 
targeted outreach via email to those hospitals that had received the 
exception in the past two program years notifying them of the removal 
of the NML policy.
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    \696\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP FAQs. Available at: https://qualitynet.cms.gov/files/61152d1252b92f00229e9717?filename=FY_2022_HACRP_FAQ.pdf.
    \697\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP HSR User Guide. Available at: https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf.
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    For more details on the NML designation and policy, we refer 
readers to the FY 2022 Hospital Specific Report (HSR) User Guide 
located on QualityNet website at https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf and 
the FY 2022 HAC Reduction Program Frequently Asked Questions website at 
https://qualitynet.cms.gov/files/61152d1252b92f00229e9717?filename=FY_2022_HACRP_FAQ.pdf.
8. Extraordinary Circumstances Exception (ECE) Policy for 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 final rule (82 FR 
38276 through 38277) for discussion of our Extraordinary Circumstances 
Exception

[[Page 28454]]

(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 not able to submit data 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 measure results 
or Total HAC Score for the applicable performance period. By minimizing 
the data excluded from the program, the policy enabled affected 
hospitals to continue to participate in the HAC Reduction Program for a 
given fiscal year if they otherwise continued to meet applicable 
measure minimum threshold requirements. We expressed the belief that 
this approach would help alleviate the burden for a hospital that might 
be adversely impacted by a natural disaster or other extraordinary 
circumstance beyond its control, while enabling the hospital to 
continue to participate in the HAC Reduction Program. In developing 
this policy, we considered a policy and process similar to that for the 
Hospital IQR Program, as finalized in the FY 2012 IPPS/LTCH PPS final 
rule (76 FR 51651), modified by the FY 2014 IPPS/LTCH PPS final rule 
(78 FR 50836) (designation of a non-CEO hospital contact), and further 
modified in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277) (amended 
Sec.  412.40(c)(2)) to refer to ``extension or exemption'' instead of 
the former ``extension or waiver''). We also considered how best to 
align an extraordinary circumstance exception policy for the HAC 
Reduction Program with existing extraordinary circumstance exception 
policies for other IPPS quality reporting and payment programs, such as 
the Hospital Value-Based Purchasing (VBP) Program, to the extent 
feasible. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38276 through 
38277), we modified the requirements for the HAC Reduction Program ECE 
policy to further align with the processes 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.
    In response to the COVID-19 PHE, we announced relief for 
clinicians, providers, hospitals, and facilities participating in 
Medicare quality reporting and value-based purchasing programs. 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 COVID-19 PHE, 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 the first and second 
quarters of CY 2020 from our calculation of performance for FY 2022 and 
FY 2023.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45308 through 
45310), we clarified our ECE policy to highlight that an ECE granted 
under the HAC Reduction Program may allow an exception from quality 
data reporting requirements and 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.
    Finally, in the FY 2022 IPPS/LTCH PPS final rule we clarified that, 
although an approved ECE for the HAC Reduction Program would exclude 
excepted data and grant an exception with respect to data reporting 
requirements for the period during which performance or ability to 
submit data was impacted or both, a hospital would still be evaluated 
for the remainder of the applicable period during which performance and 
ability to submit data was not impacted (to the extent that enough data 
are available to ensure that the calculation is statistically sound) or 
both. We clarified that an approved ECE for the HAC Reduction Program 
does not exempt hospitals from payment reductions under the HAC 
Reduction Program (86 FR 45309 through 45310).
    We are not proposing any changes to our previously finalized ECE 
Policy in this proposed rule.

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), 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, 2021 (Pub. L. 116-
260). In this proposed rule, we summarize the status of the 
demonstration program, and the ongoing methodologies for implementation 
and budget neutrality.
    We are also proposing the amount to be applied to the national IPPS 
payment rates to account for the costs of the demonstration in FY 2023, 
and, in addition, the reconciled amount of demonstration costs for FY 
2017, the most recent year for which finalized cost reports have become 
available.
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) Public Law 108-
173, is a hospital that--
     Is located in a rural area (as defined in section 
1886(d)(2)(D) of the Act) or is treated as being located in a rural 
area under section 1886(d)(8)(E) of the Act;
     Has fewer than 51 beds (excluding beds in a distinct part 
psychiatric or rehabilitation unit) as reported in its most recent cost 
report;
     Provides 24-hour emergency care services; and
     Is not designated or eligible for designation as a CAH 
under section 1820 of the Act.
3. Policies for Implementing the 5-Year Extension Period Authorized by 
Public Law 116-260
    Our policy for implementing the 5-year extension period authorized 
by Public Law 116-260 (the Consolidated Appropriations Act, 2021) 
follows upon that for the previous extensions, under the Affordable 
Care Act (Pub. L. 111-

[[Page 28455]]

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 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 the Affordable Care Act. 
Specifically, section 15003 of the 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 the Cures Act 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 and payment for services provided under the cost-
based payment methodology under section 410A of the MMA (as amended by 
section 15003 of the Cures Act) 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 the Affordable 
Care Act elected to continue in the 5-year extension period authorized 
by the Cures Act. Therefore, for these hospitals, the period of 
participation under this second 5-year extension 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 
October 1, 2019--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.
    Section 128 of Public Law 116-260 requires a 15-year 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. Therefore, in FY 2022 IPPS final rule 
(86 FR 45314), we stated that we interpreted 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 finalized the policy from previous 
extensions, that is, to 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 is 
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 demonstration 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 would 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

[[Page 28456]]

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 have calculated 
this difference for FYs 2005 through 2016 between the actual costs of 
the demonstration as determined from finalized cost reports once 
available, and estimated costs of the demonstration as identified in 
the applicable IPPS final rules for these years.
c. Budget Neutrality Methodology for the Extension Period Authorized by 
Public Law 116-260
    For the newly enacted extension period, under the Consolidated 
Appropriations Act, 2021, we continue upon the general budget 
neutrality methodology used in previous years, and to specifically 
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. In the FY 2022 IPPS final rule (86 FR 45316), we included an 
estimate of the costs of the demonstration for FY 2022 for the 26 
hospitals expected to participate in that fiscal year.
    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. In the FY 2022 final rule, we included 
the difference between the amount determined for the cost of the 
demonstration in FY 2016 and the estimated amount included in the 
budget neutrality offset in the final rule for that fiscal year.
(2) Methodology for Estimating Demonstration Costs for FY 2023
    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 2023. We are conducting this estimate for FY 2023 based on 
the 26 hospitals that are continuing participation in the demonstration 
for fiscal year 2023. The methodology for calculating this amount

[[Page 28457]]

for FY 2023 proceeds according to the following steps:
    Step 1: For each of these 26 hospitals, we identify the reasonable 
cost amount calculated under the reasonable cost-based methodology for 
covered inpatient hospital services, including swing beds, as indicated 
on the ``as submitted'' cost report for the most recent cost reporting 
period available. For each of these hospitals, the ``as submitted'' 
cost report is defined as the submitted report with a cost report 
period end date in CY 2020. We sum these hospital-specific amounts 
(derived from the cost for each hospital for inpatient hospital 
services, including swing beds, based on the CY 2020 ``as submitted'' 
cost reports) to arrive at a total general amount representing the sum 
of the costs for covered inpatient hospital services applicable for 
2020 across the 26 hospitals eligible to participate during FY 2023. 
Then, we multiply the 2020 amount (for inpatient hospital services 
including swing beds) by the IPPS final market basket percentage 
increases for FY 2021 and FY 2022, and then again by the proposed FY 
2023 IPPS market basket increase. The proposed market basket percentage 
increase for FY 2023 is 3.1 percent, explained in more detail in 
section II.A of the Addendum to this proposed rule). The result for the 
26 hospitals is the general estimated reasonable cost amount for 
covered inpatient hospital services for FY 2023.
    Consistent with our methods in previous years for formulating this 
estimate, we are applying the IPPS market basket percentage increases 
for FYs 2021 through 2023 to the applicable estimated reasonable cost 
amount (previously described) in order to model the estimated FY 2023 
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 2023 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 2020 hospital-specific amounts, and, 
in turn, multiply this sum by the FYs 2021, 2022 and 2023 IPPS 
applicable percentage increases. (For FY 2023, 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 payments constitute the majority of 
payments that would otherwise be made without the demonstration and the 
applicable percentage increase is the factor used under the IPPS to 
update the inpatient hospital payment rates.
    Step 3: We subtract the amount derived in Step 2 from the amount 
derived in Step 1. According to our methodology, the resulting amount 
indicates the total difference for the 26 hospitals (for covered 
inpatient hospital services, including swing beds), which would be the 
general estimated amount of the costs of the demonstration for FY 2023.
    For this proposed rule, the resulting amount is $71,955,710, which 
we are incorporating into the budget neutrality offset adjustment for 
FY 2023. 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 projected update factors 
for cost and payment. We propose that if more recent data subsequently 
become available (for example, a more recent estimate of the market 
basket update), we would use such data, if appropriate to estimate the 
costs for the demonstration program for FY 2023 in accordance with our 
methodology for determining the budget neutrality estimate. We would 
also incorporate any statutory change that might affect the methodology 
for determining hospital costs either with or without the 
demonstration.
(3) Reconciling Actual and Estimated Costs of the Demonstration for 
Previous Years
    As described earlier, we have calculated the difference for FYs 
2005 through 2016 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.
    At this time, for the FY 2023 proposed rule, all of the finalized 
cost reports are available for the 17 hospitals that completed cost 
report periods beginning in FY 2017 under the demonstration payment 
methodology; these cost reports show the actual costs of the 
demonstration for this fiscal year to be $35,989,928. We note that the 
FY 2017 IPPS final rule included no budget neutrality offset amount for 
that fiscal year. The final rule for FY 2017 preceded the re-
authorization of the demonstration under the Cures Act. Anticipating 
that the demonstration would end in 2016, we projected no demonstration 
cost estimate for the upcoming fiscal year, FY 2017, while we stated 
that we would continue to reconcile actual costs when all finalized 
cost reports for previous fiscal years under the demonstration became 
available (81 FR 57037). Thus, keeping with past practice, for this 
proposed rule we are including the actual costs of the demonstration as 
determined from finalized cost reports for FY 2017 within the budget 
neutrality offset amount for this upcoming fiscal year.
    We observe that the cost amounts shown by finalized cost reports 
may change in the case of revised settlements by the MACs. We propose 
that if such a re-settlement of any of the FY 2017 finalized cost 
reports occurs ahead of the FY 2023 IPPS final rule, we would 
accordingly adjust the amount for the actual costs of the demonstration 
for FY 2017 when compiling the total budget neutrality offset amount 
for the FY 2023 final rule.
(4) Total Proposed Budget Neutrality Offset Amount for FY 2023
    Therefore, for this FY 2023 IPPS/LTCH PPS proposed rule, the 
proposed budget neutrality offset amount for FY 2023 is based on the 
sum of two amounts:
     The amount determined under section X.4.c.(2) of the 
preamble of this proposed rule, representing the difference applicable 
to FY 2023 between the sum of the estimated reasonable cost amounts 
that would be paid under the demonstration for covered inpatient 
services to the 26 hospitals participating in the fiscal year and the 
sum of the estimated amounts that would generally be paid if the 
demonstration had not been implemented. This estimated amount is 
$71,955,710.
     The amount determined under section X.4.c.(3) of the 
preamble of this proposed rule, indicating the amount by which the 
actual costs of the demonstration in FY 2017 (as shown by finalized 
cost reports from that fiscal year) differ from the amount determined 
for FY 2017. Since no budget neutrality offset was conducted in FY 
2017, the amount of this difference is the actual cost amount for FY 
2017 $35,989,928.

[[Page 28458]]

    We propose to subtract the sum of these amounts ($107,945,638) from 
the national IPPS rates for FY 2023.
    However, we note that the total amount of the adjustment may change 
if there are any revisions prior to the final rule to the data used to 
formulate this estimate. We would also revise the budget neutrality 
offset amount in case of any re-settlement to finalized cost reports or 
changes to statutory provisions that affect the methodology for 
determining the budget neutrality estimate for the upcoming year.

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 
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 2023

    The proposed annual update to the national capital Federal rate, as 
provided for in 42 CFR 412.308(c), for FY 2023 is discussed in section 
III. of the Addendum to this FY 2023 IPPS/LTCH PPS proposed rule.
    In section II.C. of the preamble of this FY 2023 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 
2023, 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).

VII. Proposed Changes for Hospitals Excluded From the IPPS

A. Proposed Rate-of-Increase in Payments to Excluded Hospitals for FY 
2023

    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,

[[Page 28459]]

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 nonmedical health care institutions (RNHCIs) 
also are subject to the rate-of-increase limits established under Sec.  
413.40 of the regulations discussed previously. Furthermore, in 
accordance with Sec.  412.526(c)(3) of the regulations, extended 
neoplastic disease care hospitals also are subject to the rate-of-
increase limits established under Sec.  413.40 of the regulations 
discussed previously.
    As explained in the FY 2006 IPPS final rule (70 FR 47396 through 
47398), beginning with FY 2006, we have used the percentage increase in 
the IPPS operating market basket to update the target amounts for 
children's hospitals, the 11 cancer hospitals, and RNHCIs. Consistent 
with the regulations at Sec. Sec.  412.23(g) and 413.40(a)(2)(ii)(A) 
and (c)(3)(viii), we also have used the percentage increase in the IPPS 
operating market basket to update target amounts for short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa. In the FY 2018 IPPS/LTCH PPS final 
rule, we rebased and revised the IPPS operating basket to a 2014 base 
year, effective for FY 2018 and subsequent fiscal years (82 FR 38158 
through 38175), and finalized the use of the percentage increase in the 
2014-based IPPS operating market basket to update the target amounts 
for children's hospitals, the 11 cancer hospitals, RNHCIs, and short-
term acute care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa for FY 2018 and subsequent 
fiscal years. As discussed in section IV. of the preamble of the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45194 through 45207), we rebased 
and revised the IPPS operating basket to a 2018 base year. Therefore, 
we used 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.
    For this FY 2023 IPPS/LTCH PPS proposed rule, based on IGI's 2021 
fourth quarter forecast, we estimate that the 2018-based IPPS operating 
market basket update for FY 2023 is 3.1 percent (that is, the estimate 
of the market basket rate-of-increase). Based on this estimate, the FY 
2023 rate-of-increase percentage that would be applied to the FY 2022 
target amounts in order to calculate the FY 2023 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 3.1 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 
2023 IPPS/LTCH PPS final rule, we would use such data, if appropriate, 
to calculate the final IPPS operating market basket update for FY 2023.
    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 2023, 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 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 2023 
is 3.1 percent, which is based on IGI's 2021 fourth quarter forecast. 
Furthermore, we are proposing that if more recent data become available 
for the FY 2023 IPPS/LTCH PPS final rule, we would use such data, if 
appropriate, to calculate the IPPS operating market basket update for 
FY 2023.

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 Demonstration
a. Introduction
    The Frontier Community Health Integration Project Demonstration was 
originally authorized by section 123 of the Medicare Improvements for 
Patients and Providers Act of 2008 (Pub. L. 110-275). The demonstration 
has been extended by section 129 of the Consolidated Appropriations 
Act, 2021 (Pub. L. 116-260) for an additional 5 years. In this proposed 
rule, we are summarizing the status of the demonstration program, and 
the ongoing methodologies for implementation and budget neutrality for 
the demonstration extension period.
b. Background and Overview
    As discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), section 123 of the Medicare Improvements for Patients 
and Providers Act of 2008, as amended by

[[Page 28460]]

section 3126 of the Affordable Care Act, authorized a demonstration 
project to allow eligible entities to develop and test new models for 
the delivery of health care services in eligible counties in order to 
improve access to and better integrate the delivery of acute care, 
extended care and other health care services to Medicare beneficiaries. 
The demonstration was titled ``Demonstration Project on Community 
Health Integration Models in Certain Rural Counties,'' and commonly 
known as the Frontier Community Health Integration Project (FCHIP) 
Demonstration.
    The authorizing statute stated the eligibility criteria for 
entities to be able to participate in the demonstration. An eligible 
entity, as defined in section 123(d)(1)(B) of Public Law 110-275, as 
amended, is a Medicare Rural Hospital Flexibility Program (MRHFP) 
grantee under section 1820(g) of the Act (that is, a CAH); and is 
located in a state in which at least 65 percent of the counties in the 
state are counties that have 6 or less residents per square mile.
    The authorizing statute stipulated several other requirements for 
the demonstration. 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. CMS selected 
CAHs to participate in 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.
    Section 123 of Public Law 110-275 initially required a 3-year 
period of performance. The FCHIP Demonstration began on August 1, 2016, 
and concluded on July 31, 2019 (referred to in this section as the 
``initial period''). Subsequently, section 129 of the Consolidated 
Appropriations Act, 2021 (Pub. L. 116-260) extended the demonstration 
by 5 years (referred to in this section as the ``extension period''). 
The Secretary is required to conduct the demonstration for an 
additional 5-year period. CAHs participating in the demonstration 
project during the extension period shall begin such participation in 
the cost reporting year that begins on or after January 1, 2022.
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), 10 CAHs were selected for participation in the 
demonstration initial period. The selected CAHs were located in three 
states--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) and the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45323 through 45328). 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.
    In the FY 2022 IPPS/LTCH PPS final rule, CMS concluded that the 
initial period of the FCHIP Demonstration (covering the performance 
period of August 1, 2016, to July 31, 2019) had satisfied the budget 
neutrality requirement described in section 123(g)(1)(B) of Public Law 
110-275. Therefore, CMS did not apply a budget neutrality payment 
offset policy for the initial period of the demonstration.
    Section 129 of Public Law 116-260, stipulates that only the 10 CAHs 
that participated in the initial period of the FCHIP Demonstration are 
eligible to participate during the extension period. Among the eligible 
CAHs, six have elected to participate in the extension period. The 
selected CAHs are located in two states--Montana and North Dakota--and 
are implementing three of the four interventions. The eligible CAH 
participants elected to change the number of interventions and payment 
waivers they would participate in during the extension period. CMS 
accepted and approved the CAHs intervention and payment waiver updates. 
For the extension period, five CAHs are participants in the telehealth 
intervention, four CAHs are participants in the skilled nursing 
facility/nursing facility bed intervention, and three CAHs are 
participants in the ambulance services intervention. As with the 
initial period, each CAH was allowed to participate in more than one of 
the interventions during the extension period. None of the selected 
CAHs are participants in the home health intervention, which was the 
fourth intervention.
c. Intervention Payment and Payment Waivers
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), CMS waived certain Medicare rules for CAHs 
participating in the demonstration initial period 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 apply if the CAH is a 
participant in the associated intervention. Given updates to Medicare 
payment rules and regulations, CMS has modified and/or updated the 
Intervention Payment and Payment Waivers for the extension period. The 
FCHIP payment waivers for the demonstration extension period consist of 
the following:
(1) Telehealth Services Intervention Payments
    CMS waives section 1834(m)(2)(B) of the Act, which specifies the 
facility fee to the originating site. CMS modifies the facility fee 
payment specified under section 1834(m)(2)(B) of the Act to make 
reasonable cost-based reimbursement to the participating CAH where the 
participating CAH serves as the originating site for a telehealth 
service furnished to an eligible telehealth individual, as defined in 
section 1834(m)(4)(B). CMS would reimburse the participating CAH 
serving as the originating site at 101 percent of its reasonable costs 
for overhead, salaries and fringe benefits associated with telehealth 
services at the participating CAH. CMS would not fund or provide 
reimbursement to the participating CAH for the purchase of new 
telehealth equipment.
    CMS waives section 1834(m)(2)(A) of the Act, which specifies the 
payment made for a telehealth service furnished by the distant site 
practitioner. CMS modifies the distant site payment specified under 
section 1834(m)(2)(A) of the Act to make reasonable cost-based 
reimbursement to the participating CAH for telehealth services 
furnished by a physician or practitioner located at distant site that 
is a participating CAH that is billing for the physician or

[[Page 28461]]

practitioner professional services. Whether the participating CAH has 
or has not elected Optional Payment Method II for outpatient services, 
CMS would pay the participating CAH 101 percent of reasonable costs for 
telehealth services when a physician or practitioner has reassigned 
their billing rights to the participating CAH and furnishes telehealth 
services from the participating CAH as a distant site practitioner. 
This means that participating CAHs that are billing under the Standard 
Method on behalf of employees who are physicians or practitioners (as 
defined in section 1834(m)(4)(D) and (E), respectively) would be 
eligible to bill for distant site telehealth services furnished by 
these physicians and practitioners. Additionally, CAHs billing under 
the Optional Method would be reimbursed based on 101 percent of 
reasonable costs, rather than paid based on the Medicare physician fee 
schedule, for the distant site telehealth services furnished by 
physicians and practitioners who have reassigned their billing rights 
to the CAH. For distant site telehealth services furnished by 
physicians or practitioners who have not reassigned billing rights to a 
participating CAH, payment to the distant site physician or 
practitioner would continue to be made as usual under the Medicare 
physician fee schedule. Currently these services are eligible to be 
furnished and paid in this way due to a waiver issued during the PHE. 
Except as described herein, CMS does not waive any other provisions of 
section 1834(m) of the Act for purposes of the telehealth services 
intervention payments, including the scope of Medicare telehealth 
services as established under section 1834(m)(4)(F).
(2) Ambulance Services Intervention Payments
    CMS waives 42 CFR 413.70(b)(5)(D) and section 1834(l)(8) of the 
Act, 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, but only if the CAH or the entity is the only provider or 
supplier of ambulance services located within a 35-mile drive of the 
CAH, excluding ambulance providers or suppliers that are not legally 
authorized to furnish ambulance services to transport individuals to or 
from the CAH. The participating CAH would be paid 101 percent of 
reasonable costs for its ambulance services regardless of whether there 
is any provider or supplier of ambulance services located within a 35-
mile drive of the participating CAH or participating CAH-owned and 
operated entity. CMS would not make cost-based payment to the 
participating CAH for any new capital (for example, vehicles) 
associated with ambulance services. This waiver does not modify any 
other Medicare rules regarding or affecting the provision of ambulance 
services.
(3) SNF/NF Beds Expansion Intervention Payments
    CMS waives 42 CFR 485.620(a), 42 CFR 485.645(a)(2), and section 
1820(c)(2)(B)(iii) of the Act which limit CAHs to maintaining no more 
than 25 inpatient beds, including beds available for acute inpatient or 
swing bed services. CMS waives 1820(f) of the Act permitting 
designating or certifying a facility as a critical access hospital for 
which the facility at any time is furnishing inpatient beds which 
exceed more than 25 beds. Under this waiver, if the participating CAH 
has received swing bed approval from CMS, the participating CAH may 
maintain up to ten additional beds (for a total of 35 beds) available 
for acute inpatient or swing bed services; however, the participating 
CAH may only use these 10 additional beds for nursing facility or 
skilled nursing facility level of care. CMS would pay the participating 
CAH 101 percent of reasonable costs for its SNF/NF services furnished 
in the 10 additional beds.
d. Budget Neutrality
(1) Budget Neutrality Requirement
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 through 
45328), we finalized a policy to address the budget neutrality 
requirement for the demonstration initial period. We also discussed 
this policy 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), 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). As explained in the FY 2022 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 finalized for the demonstration initial period of 
performance in the FY 2022 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.
    For the FY 2023 proposed rule, CMS is proposing to adopt the budget 
same neutrality policy contingency plan used during the demonstration 
initial period to ensure that the budget neutrality requirement in 
section 123 of Public Law 110 275 is met during the demonstration 
extension period. 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 5-year extension period are not sufficiently offset by 
reductions elsewhere, we would recoup the additional expenditures 
attributable to the demonstration through a reduction in payments to 
all CAHs nationwide.
    As explained in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), because of the small scale of the demonstration, we 
indicated that we did not believe it would be feasible to implement 
budget neutrality for the demonstration initial period by reducing 
payments to only the participating CAHs. Therefore, in the event that 
this demonstration extension period is found to result in aggregate 
payments in excess of the amount that would have been paid if this 
demonstration extension period were not implemented, CMS policy is to 
comply with the budget neutrality requirement finalized in the FY 2022 
IPPS/LTCH PPS final rule, by reducing payments to all CAHs, not just 
those participating in the demonstration extension period.
    In the FY 2022 IPPS/LTCH PPS final rule, 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

[[Page 28462]]

implemented, and does not identify the range across which aggregate 
payments must be held equal.
    Under the policy finalized in the FY 2022 IPPS/LTCH PPS final rule, 
we adopted the policy finalized in the FY 2017 IPPS/LTCH PPS final 
rule, in the event the demonstration initial period was found not to 
have been budget neutral, any excess costs would be recouped over a 
period of 3 cost reporting years. For the FY 2023 proposed rule, we 
seek public comment on this proposal, as we are revising an aspect of 
the policy finalized in the FY 2022 IPPS/LTCH PPS final rule. Our new 
proposed policy is in the event the demonstration extension period is 
found not to have been budget neutral, any excess costs would be 
recouped within one fiscal year. We believe our new proposed policy is 
a more efficient timeframe for the government to conclude the 
demonstration operational requirements (such as analyzing claims data, 
cost report data and/or other data sources) to adjudicate the budget 
neutrality payment recoupment process due to any excess cost that 
occurred as result of the demonstration extension period.
(2) FCHIP Budget Neutrality Methodology and Analytical Approach
    As explained in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
a policy to address the demonstration budget neutrality methodology and 
analytical approach for the initial period of the demonstration. For 
this FY 2023 proposed rule, CMS is proposing to adopt the budget 
neutrality methodology and analytical approach used during the 
demonstration initial period to ensure budget neutrality for the 
extension period. The analysis of budget neutrality during the initial 
period of the demonstration 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 for the demonstration 
initial period incorporated two major data components: (1) Medicare 
cost reports; and (2) Medicare administrative claims. As described in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 through 45328), CMS 
computed the cost of the demonstration for each fiscal year of the 
demonstration initial period using Medicare cost reports for the 
participating CAHs, and Medicare administrative claims and enrollment 
data for beneficiaries who received demonstration intervention 
services.
    In addition, in order to capture the full impact of the 
interventions, CMS developed a statistical modeling, Difference-in-
Difference (DiD) regression analysis to estimate demonstration 
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 
demonstration period of performance under the initial period of the 
demonstration. The DiD regression analysis would compare the direct 
cost and potential downstream effects of intervention services, 
including any savings that may have accrued, during the baseline and 
performance period for both the demonstration and comparison groups.
    Second, the Medicare administrative claims analysis would be 
reconciled using data obtained from auditing the participating CAHs' 
Medicare cost reports. We would estimate the costs of the demonstration 
using ``as submitted'' cost reports for each hospital's financial 
fiscal year participation within each of the demonstration extension 
period performance years. Each CAH has its own Medicare cost report end 
date applicable to the five-year period of performance for the 
demonstration extension period. The cost report is structured to gather 
costs, revenues and statistical data on the provider's financial fiscal 
period. As a result, we would determine the final budget neutrality 
results for the demonstration extension once complete data is available 
for each CAH for the demonstration extension period.
d. Proposed Policies for Implementing the 5-Year Extension and 
Provisions Authorized by Section 129 of the Consolidated Appropriations 
Act, 2021 (Pub. L. 116-260)
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), our policy for implementing the 5-year extension period 
for section 129 of Public Law 116-260 follows same budget neutrality 
methodology and analytical approach as the demonstration initial period 
methodology. 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, 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. For the FY 2023 
proposed rule, CMS is proposing to adopt the same budget neutrality 
methodology and analytical approach used during the demonstration 
initial period to be used for the demonstration extension period.
e. Total Proposed Budget Neutrality Offset Amount for FY 2023
    At this time, for the FY 2023 proposed rule, while this discussion 
represents our anticipated approach to assessing the financial impact 
of the demonstration extension period based on upon receiving data for 
the full demonstration extension period, we may update and/or modify 
the FCHIP Demonstration budget neutrality methodology and analytical 
approach to ensure that the full impact of the demonstration is 
appropriately captured.
    Therefore, we do not propose to apply a budget neutrality payment 
offset to payments to CAHs in FY 2023. This policy would have no impact 
for any national payment system for FY 2023.

VIII. Proposed Changes to the Long-Term Care Hospital Prospective 
Payment System (LTCH PPS) for FY 2023

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

[[Page 28463]]

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 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 
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, which was a payment adjustment that was applied to 
payments for Medicare patient LTCH discharges when the number of such 
patients originating from any single referring hospital was in excess 
of the applicable threshold for given cost reporting period.
    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

[[Page 28464]]

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
    We refer readers to section I.F. of the preamble of this proposed 
rule for our discussion on our proposal to use the most recent data 
available for the FY 2023 LTCH PPS ratesetting, including the FY 2021 
MedPAR claims and FY 2020 cost report data. In section I.F. of the 
preamble of this proposed rule we also discuss our proposal to modify 
our ratesetting methodology for FY 2023 to account for the ongoing 
COVID-19 PHE.

B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-LTC-
DRG) Classifications and Relative Weights for FY 2023

1. Background
    Section 123 of the BBRA required that the Secretary implement a PPS 
for LTCHs to replace the cost-based payment system under TEFRA. Section 
307(b)(1) of the BIPA modified the requirements of section 123 of the 
BBRA by requiring that the Secretary examine the feasibility and the 
impact of basing payment under the LTCH PPS on the use of existing (or 
refined) hospital DRGs that have been modified to account for different 
resource use of LTCH patients.
    Under both the IPPS and the LTCH PPS, the DRG-based classification 
system uses information on the claims for inpatient discharges to 
classify patients into distinct groups (for example, DRGs) based on 
clinical characteristics and expected resource needs. 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. We referred to this patient 
classification system as the ``long-term care diagnosis-related groups 
(LTC-DRGs).'' 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), we adopted the MS-DRGs and the Medicare severity 
long-term care diagnosis-related groups (MS-LTC-DRGs) 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.)
    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. As noted previously, we adopted the same 
DRG patient classification system utilized at that time under the IPPS. 
The MS-DRG classifications are updated annually, which has resulted in 
the number of MS-DRGs changing over time. For FY 2023, there would be 
767 MS-DRG, and by extension, MS-LTC-DRG, groupings based on the 
proposed changes, as discussed in section II.E. of the preamble of this 
proposed rule.
    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. That is, we assign an appropriate weight 
to the MS-LTC-DRGs to account for the differences in resource use by 
patients exhibiting the case complexity and multiple medical problems 
characteristic of LTCH patients.
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

[[Page 28465]]

structure. As noted previously in this section, we refer to the DRGs 
under the LTCH PPS as MS-LTC-DRGs although they are structurally 
identical to the MS-DRGs used under the IPPS.
    The MS-DRGs are organized into 25 major diagnostic categories 
(MDCs), most of which are based on a particular organ system of the 
body; the remainder involve multiple organ systems (such as MDC 22, 
Burns). Within most MDCs, cases are then divided into surgical DRGs and 
medical DRGs. Surgical DRGs are assigned based on a surgical hierarchy 
that orders operating room (O.R.) procedures or groups of O.R. 
procedures by resource intensity. The GROUPER software program does not 
recognize all ICD-10-PCS procedure codes as procedures affecting DRG 
assignment. That is, procedures that are not surgical (for example, 
EKGs) or are 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 the 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 types of 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 2023
    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, 2022 through September 30, 2023 
(FY 2023) 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 2023 
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 
2023. In addition, because the proposed MS-LTC-DRGs for FY 2023 are the 
same as the proposed MS-DRGs for FY 2023, the other proposed changes 
that affect MS-DRG (and by extension MS-LTC-DRG) assignments under 
proposed GROUPER Version 40, as discussed in section II.E. of the 
preamble of this

[[Page 28466]]

proposed rule, including the proposed changes to the MCE software and 
the ICD-10-CM/PCS coding system, are also applicable under the LTCH PPS 
for FY 2023.
3. General Summary of the FY 2023 MS-LTC-DRG Relative Weights 
Methodology
    In this section of this proposed rule, we provide a general summary 
of our proposed modifications to the methodology for determining the FY 
2023 MS-LTC-DRG relative weights under the LTCH PPS.
a. Proposed Averaging of Relative Weights for FY 2023
    In section I.F. of the preamble to this proposed rule, we discuss 
our proposal to use FY 2021 claims data for the FY 2023 LTCH PPS 
ratesetting. We recognize the impact COVID-19 cases in the FY 2021 
claims data have on the relative weight calculations for a few COVID-
19-related MS-LTC-DRGs. Specifically, we have determined that the 
COVID-19 cases grouped to a few MS-LTC-DRGs have, on average, 
meaningfully different costs than the non-COVID-19 cases grouped to 
these MS-LTC-DRGs. As a result, for these MS-LTC-DRGs, the relative 
weights calculated using all cases will be meaningfully different than 
the relative weights calculated excluding COVID-19 cases. For example, 
using the FY 2021 MedPAR data, the relative weight for MS-LTC-DRG 870 
(Septicemia or severe sepsis with MV >96 hours) is approximately 3.1 
percent higher when the relative weights are calculated including 
COVID-19 cases compared to when the relative weights are calculated 
excluding COVID-19 cases. In section I.F. of the preamble to this 
proposed rule, we also discuss that we believe it is reasonable to 
assume there will be fewer COVID-19 hospitalizations among Medicare 
beneficiaries in LTCHs in FY 2023 than there were in FY 2021, although 
we cannot know the actual number of COVID-19 hospitalizations among 
Medicare beneficiaries in LTCHs in FY 2023. We are proposing to modify 
our relative weight methodology for FY 2023 to align with an assumption 
that there will be fewer, but not zero, COVID-19 cases in FY 2023 
compared to FY 2021. To account for this assumption, we are proposing 
an averaging approach to determine the MS-LTC-DRG relative weights for 
FY 2023. Specifically, we are proposing to calculate the relative 
weights both including and excluding COVID-19 cases, and then average 
the two sets of relative weights together. We believe this proposal is 
appropriate as it will reduce, but not remove entirely, the effect of 
COVID-19 cases on the relative weight calculations. Given the 
uncertainty in the number of COVID-19 cases in FY 2023, we believe this 
proposal is appropriate. By averaging the relative weights in this 
manner, we believe the result would reflect a reasonable estimation of 
the mix of cases for FY 2023 based on the information available at this 
time on the trajectory of the COVID-19 PHE (as discussed in section 
I.F. of the preamble to this proposed rule), and a more accurate 
estimate of the relative resource use for cases treated in FY 2023. We 
believe the relative weights calculated using our proposed modified 
methodology would be more accurate than if we applied our standard 
methodology, that is, with relative weights calculated based on 100 
percent of the relative weights calculated using all applicable LTCH 
cases. The technical details of this proposal are discussed in section 
VIII.B.4. of the preamble to this proposed rule. As discussed in 
section I.O of Appendix A of this proposed rule, as an alternative to 
our proposed approach, we considered following our historical approach 
for calculating the relative weights and not proposing this 
modification. That is, we considered proposing to determine the FY 2023 
MS-LTC-DRG weights using all applicable LTCH cases without any 
modifications to account for COVID-19 cases. We note, this proposed 
averaging approach and alternative considered for the calculation of 
the FY 2023 MS-LTC-DRG relative weights are consistent with the 
proposed approach and alternative considered under the IPPS for FY 2023 
as discussed in section II.E.c. of the preamble and section I.O of 
Appendix A, respectively, to this proposed rule.
b. Proposed Cap on Relative Weight Decreases
    In recent years, we have received comments about significant 
fluctuations in the relative weights for some MS-LTC-DRGs. Some 
commenters requested that CMS establish a transition policy to mitigate 
the negative effects of significant year-to-year reductions to relative 
weights. In addition, we acknowledge long-standing concerns of 
commenters about fluctuations in low-volume MS-LTC-DRGs, which 
consistently fluctuate more significantly than higher volume MS-LTC-
DRGs. In general, typical year-to-year fluctuations in case mix and the 
presence of some very high-cost or very low-cost cases (that are not 
statistical outliers) do not have a significant impact on the relative 
weights for most MS-LTC-DRGs with at least 25 cases (that is, MS-LTC-
DRGs that are not low-volume or no-volume as discussed later in section 
VIII.B.4. of this preamble). However, for some MS-LTC-DRGs, 
particularly those with low volume, these fluctuations in the volume or 
mix of cases and the presence of a few high-cost or low-cost cases can 
have a disproportionate impact on both, thus resulting in greater 
instability in the relative weights for these MS-LTC-DRGs, which can 
reduce the predictability and stability of an individual LTCH's 
Medicare payments from year to year.
    Predictability and stability of rates is one of the fundamental 
principles of a prospective payment system. We have reconsidered 
requests made by commenters that we mitigate the financial impacts of 
significant year-to-year fluctuations in relative weights. We note that 
in section V.B.5. of the addendum to this proposed rule, we are 
proposing a permanent 5 percent cap on yearly decreases to an LTCH's 
wage index to mitigate the financial impacts of wage index decreases to 
increase predictability and stability in LTCH PPS payments. Given the 
concerns commenters have raised about the financial impacts of 
significant year-to-year fluctuations in MS-LTC-DRGs relative weights, 
we are revisiting the appropriateness of establishing a policy to 
address these concerns.
    Consistent with the broad authority conferred upon the Secretary by 
section 123 of the BBRA, as amended by section 307(b) of the BIPA, to 
determine appropriate payment adjustments under the LTCH PPS, including 
adjustments to DRG weights, we are proposing a permanent 10-percent cap 
on the reduction to a MS-LTC-DRG's relative weight in a given year, 
beginning in FY 2023. (The details on the application of this proposed 
adjustment are discussed in section VIII.B.4. of the preamble to this 
proposed rule.) For example, if the relative weight for MS-LTC-DRG XYZ 
in FY 2022 is 1.100 and the relative weight for FY 2023 would otherwise 
be 0.9350, which would represent a decrease of 15 percent from FY 2022, 
the reduction would be limited to 10 percent such that the proposed 
relative weight for FY 2023 would be 0.9900 (that is, 0.90 x FY 2022 
weight of 1.100). We are proposing that this 10-percent cap would be 
applied to the relative weights for MS-LTC-DRGs with applicable LTCH 
cases. Under this proposal, the 10-percent cap would not apply to no-
volume MS-LTC-DRGs (that is an MS-LTC-DRG with no applicable LTCH 
cases) whose relative

[[Page 28467]]

weight was determined by a cross-walk to another MS-LTC-DRG's relative 
weight. We believe it is not necessary to apply the 10-percent cap to 
no-volume MS-LTC-DRGs because the financial impact of fluctuations in 
the relative weights for these no-volume MS-LTC-DRGs is extremely small 
as evident by there being zero applicable LTCH cases grouped to these 
MS-LTC-DRGs in the MedPAR claims data.
    We are also proposing that the 10-percent cap on the reduction in a 
MS-LTC-DRG's relative weight in a given year be budget neutral. This 
means we would apply a budget neutrality adjustment to the MS-LTC-DRG 
relative weights, after application of the 10-percent cap, to ensure 
that our proposed 10-percent cap on relative weight reductions policy 
results in no change in aggregate LTCH PPS standard Federal rate 
payments. Our proposal to apply the proposed 10-percent cap on the 
reduction in a MS-LTC-DRG's relative weight in a given year in a budget 
neutral manner is consistent with the existing budget neutrality 
requirement for annual MS-LTC-DRG reclassification and recalibration, 
which we adopted to mitigate estimated fluctuations in estimated 
aggregate LTCH PPS payments (72 FR 26881-26882).
    We believe the impact of the application of a cap on relative 
weight reductions on an LTCH's total LTCH PPS payments in a given year 
would be relatively small because a change in the relative weight would 
be applied to a single MS-LTC-DRG, unlike the impact of the wage index 
adjustment, which adjusts the payment for each discharge and impacts 
approximately two-thirds of an LTCH's total LTCH PPS payments in a 
given year. In considering the amount of the cap we should propose, we 
balanced the number of MS-LTC-DRGs that would receive the cap with the 
magnitude of the budget neutrality factor that would be applied to all 
MS-LTC-DRGs, while also maintaining an accurate reflection of the 
relative resource use across the MS-LTC-DRG weights overall. We 
considered that a higher cap, such as twenty percent cap, would limit 
declines in the relative weights for fewer MS-LTC-DRGs while a lower 
cap, such as a five percent cap, would limit declines in the relative 
weights for more MS-LTC-DRGs, but would also result in a larger budget 
neutrality adjustment. On balance, we believe that a 10-percent cap 
would mitigate financial impacts resulting from fluctuations in the 
relative weights, particularly for low-volume MS-LTC-DRGs, without the 
larger budget neutrality adjustment associated with a smaller cap, and 
without distorting the integrity of the MS-LTC-DRG relative weights 
overall as a reflection of relative resource use. We note that this 
proposed 10-percent cap on reductions to a MS-LTC-DRG's relative weight 
would apply only to a given MS-LTC-DRG with its current MS-LTC-DRG 
number. In cases where CMS creates new MS-LTC-DRGs or modifies the MS-
LTC-DRGs as part of its annual reclassifications resulting in 
renumbering of one or more MS-LTC-DRGs, we are proposing that this 
limit on the reduction in the relative weight would not apply to any 
MS-LTC-DRGs affected by the renumbering (that is, the proposed 10-
percent cap would not apply to the relative weight for any new or 
renumbered MS-LTC-DRGs for the fiscal year). The technical details of 
this proposal are discussed in section VIII.B.4. of the preamble to 
this proposed rule. This proposal is consistent with the proposed 
permanent 10-percent cap on decreases to a MS-DRG relative weight under 
the IPPS as discussed in section II.E.d. of the preamble of this 
proposed rule.
    We are proposing to amend our regulations at 42 CFR 412.515 to 
reflect this proposed permanent cap on MS-LTC-DRG relative weight 
reductions. We are seeking comments on our proposal to establish a 
permanent 10-percent cap on decreases to a MS-LTC-DRG relative weight 
each year.
c. Proposed Conforming Changes to Other Components of the Proposed FY 
2023 MS-LTC-DRG Relative Weights Methodology
    In general, for FY 2023, we are proposing to continue applying the 
other components of our existing methodology for determining the MS-
LTC-DRG relative weights (as discussed in greater detail in section 
VIII.B.4. of the preamble of this proposed rule) that are not impacted 
by our previously described proposed modifications to our methodology. 
We note that in conjunction with our proposal to establish the MS-LTC-
DRG relative weights using an average of the relative weights 
calculated both including and excluding the COVID-19 claims, as 
described in greater detail later in this section, to align with an 
assumption that there will be fewer, but not zero, COVID-19 cases in FY 
2023 compared to FY 2021 (as discussed previously), under our proposed 
modification to our relative weight methodology for FY 2023, we would 
calculate the MS-LTC-DRG relative weights methodology, described later 
in this section, twice--once to determine the relative weights based on 
claims data that include COVID-19 cases and again to determine the 
relative weights based on claims data that exclude COVID-19 cases. 
Specifically, in determining the relative weights based on both sets of 
claims, we are proposing to apply our 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, and adjustments for nonmonotonicity, 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). We discuss all components of our MS-LTC-DRG relative 
weight methodology in greater detail in section VIII.B.4.g. of the 
preamble of this proposed rule.
4. Proposed Development of the FY 2023 MS-LTC-DRG Relative Weights
a. General Overview 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 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. 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.
    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

[[Page 28468]]

relative weights in cases of zero volume and nonmonotonicity or both 
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 nonmonotonicity or both, 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).
    For purposes of determining the MS-LTC-DRG relative weights, under 
our historical methodology, there are three different categories of MS-
LTC-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 in Step 3 of our proposed 
methodology) 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 later in this section in Step 8 
of our proposed methodology). For FY 2023, we are proposing to continue 
to use applicable LTCH cases to establish the same volume-based 
categories to calculate the FY 2023 MS-LTC-DRG relative weights.
    As discussed in section VIII.B.3.a. of the preamble to this 
proposed rule, for FY 2023, we are proposing to establish the MS-LTC-
DRG relative weights as an average of the relative weights calculated 
both including and excluding the COVID-19 claims. As discussed in 
section VIII.B.3.b. of the preamble to this proposed rule, we also are 
proposing a 10-percent cap on the reduction in a MS-LTC-DRG's relative 
weight in a given year, beginning in FY 2023.
b. Proposed Development of the MS-LTC-DRG Relative Weights for FY 2023
    In this section, we present our proposed methodology for 
determining the MS-LTC-DRG relative weights for FY 2023. In general, we 
are proposing to continue to apply the components of our existing 
methodology that are not impacted by our proposed modifications to use 
an average of the relative weights calculated both including and 
excluding the COVID-19 claims and the application of a 10-percent cap 
on the reduction in a MS-LTC-DRG's relative weight, discussed in 
section VIII.B.3 of the preamble to this proposed rule. For example, we 
are proposing to continue with the 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, 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). We note that under our proposal to establish the 
MS-LTC-DRG relative weights using an average of the relative weights 
calculated both including and excluding the COVID-19 claims, particular 
components of our existing relative weight methodology would be 
performed twice (once when determining relative weights based on claims 
data that include COVID-19 cases and again when determining relative 
weights based on claims data that exclude COVID-19 cases). Later in 
this section we list and provide a brief description of our proposed 
steps for determining the FY 2023 MS-LTC-DRG relative weights. Each 
proposed step is discussed in greater detail later in this section.
     Step 1--Prepare data for MS-LTC-DRG relative weight 
calculation. In this step, we select and group the applicable claims 
data used in the development of the proposed MS-LTC-DRG relative 
weights. For FY 2023, we are proposing to prepare two sets of claims: A 
claims dataset that includes COVID-19 cases and a claims dataset that 
excludes COVID-19 cases.
     Step 2--Remove cases with a length of stay of 7 days or 
less. In this step, we trim the applicable claims data to remove cases 
with a length of stay 7 days or less. For FY 2023, we are proposing to 
perform this step on each set of claims data (claims dataset that 
includes COVID-19 cases and claims dataset that excludes COVID-19 
cases).
     Step 3--Establish low-volume MS-LTC-DRG quintiles. In this 
step, we employ our established quintile methodology for low-volume MS-
LTC-DRGs (that is, MS-LTC-DRGs with less than 25 cases). For FY 2023, 
we are proposing to perform this step on each set of claims data 
(claims dataset that includes COVID-19 cases and claims dataset that 
excludes COVID-19 cases).
     Step 4--Remove statistical outliers. In this step, we trim 
the applicable claims data to remove statistical outlier cases. For FY 
2023, we are proposing to perform this step on each set of claims data 
(claims dataset that includes COVID-19 cases and claims dataset that 
excludes COVID-19 cases).
     Step 5--Adjust charges for the effects of Short Stay 
Outliers (SSOs). In this step, we adjust the number of applicable cases 
in each MS-LTC-DRG (or low-volume quintile) for the effect of SSO 
cases. For FY 2023, we are proposing to perform this step on each set 
of claims data (claims dataset that includes COVID-19 cases and claims 
dataset that excludes COVID-19 cases).
     Step 6--Calculate the relative weights on an iterative 
basis using the hospital-specific relative weights methodology. In this 
step, we use our established hospital-specific relative value (HSRV) 
methodology, which is an iterative process, to calculate the relative 
weights. For FY 2023, we are proposing to use the HSRV methodology to 
calculate relative weights using the claims that include COVID-19 cases 
and again using the claims that exclude the COVID-19 cases.
     Step 7--Adjust the relative weights to account for 
nonmonotonically increasing relative weights. In this step, we make 
adjustments that ensure that within each base MS-LTC-DRG, the relative 
weights increase by MS-LTC-DRG severity. For FY 2023, we are proposing 
to adjust each set of relative weights (that is, the relative weights 
calculated including COVID-19 cases and the relative weights calculated 
excluding COVID-19 cases).
     Step 8--Determine a relative weight for MS-LTC-DRGs with 
no applicable LTCH cases. In this step, we cross-walk each no-volume 
MS-LTC-DRG to another MS-LTC-DRG for which we calculated a relative 
weight. For FY 2023, we are proposing to cross-walk no-volume MS-LTC-
DRGs in each set of relative weights (that is, the set of relative 
weights calculated including COVID-19 cases and the set of relative

[[Page 28469]]

weights calculated excluding COVID-19 cases).
     Step 9--Normalize each set of relative weights. In this 
step, we make a normalization adjustment so that the recalibration of 
the MS-LTC-DRG relative weights (that is, the process itself) neither 
increases nor decreases the average case-mix index. For FY 2023, we are 
proposing to normalize the set of relative weights calculated including 
COVID-19 cases and the set relative weights calculated excluding COVID-
19 cases.
     Step 10--Average the two sets of normalized relative 
weights. In this step, we average the set of normalized relative 
weights calculated including COVID-19 cases and the set of normalized 
relative weights calculated excluding COVID-19 cases. In addition to 
the relative weights, we also average the geometric mean length of 
stays and arithmetic mean length of stays.
     Step 11--Budget neutrality the averaged relative weights. 
In this step, to ensure budget neutrality in the proposed annual update 
to the MS-LTC-DRG classifications and relative weights, we adjust the 
relative weights by a normalization factor and budget neutrality factor 
that ensures estimated aggregate LTCH PPS payments would be unaffected 
by the proposed updates to the MS-LTC-DRG classifications and relative 
weights. This step is performed prior to applying the proposed 10-
percent cap.
     Step 12--Apply the 10-percent cap to decreases in MS-LTC-
DRG relative weights. In this step we limit the reduction of the 
relative weight for a MS-LTC-DRG to 10 percent of its prior year value. 
This 10-percent cap does not apply to zero-volume MS-LTC-DRGs.
     Step 13--Calculate the MS-LTC-DRG cap budget neutrality 
factor. In this step, to ensure budget neutrality in the application of 
the proposed MS-LTC-DRG cap policy, we adjust the relative weights by a 
budget neutrality factor that ensures estimated aggregate LTCH PPS 
payments would be unaffected by our application of the cap to the MS-
LTC-DRG relative weights.
    Later in this section we describe each of the 13 proposed steps for 
calculating the proposed FY 2023 MS-LTC-DRG relative weights in greater 
detail. In this discussion, we note when the proposed step was 
performed twice under our proposal for averaging relative weights 
calculated including COVID-19 cases and relative weights calculated 
excluding COVID-19 cases.
    Step 1--Prepare data for MS-LTC-DRG relative weight calculation.
    For this FY 2023 IPPS/LTCH PPS proposed rule, consistent with our 
proposal in section I.F. of the preamble of this proposed rule to use 
FY 2021 data in the FY 2023 LTCH PPS ratesetting, we obtained total 
charges from FY 2021 Medicare LTCH claims data from the December 2021 
update of the FY 2021 MedPAR file and used proposed Version 40 of the 
GROUPER to classify LTCH cases. Consistent with our historical 
practice, we are proposing that if better data become available, we 
would use those data and the finalized Version 40 of the GROUPER in 
establishing the FY 2023 MS-LTC-DRG relative weights in the final rule.
    To calculate the FY 2023 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 FR 49624). Specifically, we began by first 
evaluating the LTCH claims data in the December 2021 update of the FY 
2021 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 2021 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 2021 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 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. These statutory provisions were not in effect for any 
discharges occurring in FY 2021 (or beyond), so it is no longer 
necessary to address their treatment for purposes of developing the MS 
LTC DRG relative weights. We also note that section 3711(b)(2) of the 
CARES Act, which provided a waiver of the application of the site 
neutral payment rate for LTCH cases admitted during the COVID-19 PHE 
period, was in effect for the entirety of FY 2021. Therefore, all LTCH 
PPS cases in FY 2021 were paid the LTCH PPS standard Federal rate 
regardless of whether the discharge met the statutory patient criteria. 
However, for purposes of setting rates for LTCH PPS standard Federal 
rate cases for FY 2023 (including MS-LTC-DRG relative weights), we used 
FY 2021 cases that meet the statutory patient criteria without 
consideration to how those cases were paid in FY 2021.)
    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.
    In addition, as discussed in section VIII.B.3.a. of this proposed 
rule, for FY 2023, we are proposing to establish the MS-LTC-DRG 
relative weights as an average of the relative weights calculated both 
including and excluding the COVID-19 claims. To calculate the set of 
relative weights based on claims that excluded COVID-19 cases, we 
performed an additional trim to remove COVID-19 cases. We identified 
COVID-19 cases as any claim in the FY 2021 MedPAR file with a principal 
or secondary diagnosis of COVID-19 (ICD-10-CM diagnosis code U07.1).
    In summary, in general, we identified the claims data used in the 
development of the FY 2023 MS-LTC-DRG relative weights in this proposed 
rule by trimming claims data that would have been paid the site neutral 
payment rate had the provisions of the CARES Act not been in effect. We 
trimmed the

[[Page 28470]]

claims data of all-inclusive rate providers reported in the December 
2021 update of the FY 2021 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 December 2021 
update of the FY 2021 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 used the remaining data (that is, the applicable LTCH data) in 
the subsequent proposed steps to calculate the set of relative weights 
based on claims that include COVID-19 cases. In addition, we performed 
a trim to remove COVID-19 cases based on a principal or secondary 
diagnosis of COVID-19. We used these data in the subsequent proposed 
steps to calculate the set of relative weights based on claims that 
exclude COVID-19 cases.
    Step 2--Remove cases with a length of stay of 7 days or less.
    The next step in our proposed calculation of the proposed FY 2023 
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 2023 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 2023 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 both sets of claims (that is the 
applicable LTCH claims that include COVID-19 cases and the applicable 
LTCH claims that exclude COVID-19 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 3--Establish low-volume MS-LTC-DRG quintiles.
    To account for 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)). Under our proposal in section VIII.B.3.a. of 
the preamble to this proposed rule to establish the FY 2023 MS-LTC-DRG 
relative weights as an average of the relative weights calculated both 
including and excluding the COVID-19 claims, we are proposing to employ 
our quintile methodology when calculating the relative weights for each 
set of claims (that is the claims that include COVID-19 cases and the 
claims that exclude COVID-19 cases).
    In this proposed rule, based on the best available data (that is, 
the December 2021 update of the FY 2021 MedPAR files), we identified 
233 MS-LTC-DRGs that contained between 1 and 24 applicable LTCH cases 
in the claims data that included COVID-19 cases, and 232 MS LTC-DRGs 
that contained between 1 and 24 applicable LTCH cases in the claims 
data that excluded COVID-19 cases. These lists of MS-LTC-DRGs were then 
divided into 1 of the 5 low-volume quintiles. 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 MS-LTC-DRGs with less than 25 applicable 
LTCH cases in each set of claims was not evenly divisible by 5. The 
quintiles based on the claims data that included COVID-19 cases each 
contained at least 46 MS-LTC-DRGs (233/5 = 46 with a remainder of 3). 
Meanwhile, the quintiles based on the claims data that excluded COVID-
cases also each contained at least 46 MS-LTC-DRGs (232/5 = 46 with a 
remainder of 2). We are proposing to employ our historical methodology 
of assigning each remainder low-volume MS-LTC-DRG to the low-volume 
quintile that contains an MS-LTC-DRG with an average charge closest to 
that of the remainder low-volume MS-LTC-DRG.
    For the claims that include COVID-19 cases, the application of our 
quintile methodology resulted in 2 low-volume quintiles containing 46 
MS-LTC DRGs (Quintiles 1 and 5) and 3 low-volume quintiles containing 
47 MS-LTC-DRGs (Quintiles 2, 3, and 4). For the claims that excluded 
COVID-19 cases, the application of our quintile methodology resulted in 
3 low-volume quintiles containing 46 MS-LTC DRGs (Quintiles 1, 4, and 
5) and 2 low-volume quintiles containing 47 MS-LTC-DRGs (Quintiles 2 
and 3). In cases where these initial assignments of low-volume MS-LTC-
DRGs to quintiles results in nonmonotonicity within a base-DRG, we are 
proposing to make adjustments to the resulting low-volume MS-LTC-DRGs 
to preserve monotonicity, as discussed in Step 7 of our proposed 
methodology.
    To determine the FY 2023 relative weights for the low-volume MS-
LTC-DRGs, consistent with our historical practice, we are proposing to 
use the five low-volume quintiles from each set of claims described 
previously. We determined a relative weight and (geometric) average 
length of stay for each of the five low-volume quintiles using the 
methodology described in Step 6 of our proposed methodology. We 
assigned the same relative weight and average length of stay to each of 
the low-volume MS-LTC-DRGs that make up an individual low-volume 
quintile. These calculations were performed separately for the relative 
weight set based on claims that include COVID-19 cases and the relative 
weight set based on claims that exclude COVID-19 cases. 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 would 
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. We note our description in 
previous rules did not specify the point in our methodology when the 
low-volume MS-LTC-DRG quintiles are established. Although we are now 
including this step explicitly, this is not a change to our historical 
methodology for determining the MS-LTC-DRG relative weights.
    For this proposed rule, we are providing the lists of the 
composition of the proposed low-volume quintiles for low-volume MS-LTC-
DRGs in a

[[Page 28471]]

supplemental data file for public use posted via the internet on the 
CMS website for this proposed rule at https://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 Table 11. This supplemental data file 
includes the composition of the proposed low-volume quintiles for low-
volume MS-LTC-DRGs based on the claims that include COVID-19 cases and 
the composition of the proposed low-volume quintiles for low-volume MS-
LTC-DRGs based on the claims that exclude COVID-19 cases.
    Step 4--Remove statistical outliers.
    The next step in our proposed calculation of the proposed FY 2023 
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 relative 
weights because we believe that they may represent aberrations in the 
data that distort the measure of average resource use. Including those 
LTCH cases in the calculation of the relative weights could result in 
an inaccurate relative weight that does not truly reflect relative 
resource use among those MS-LTC-DRGs. (For additional information on 
what is removed in this step of the relative weight methodology, we 
refer readers to 67 FR 55989 and 74 FR 43959.) This step was performed 
on both sets of claims (that is the applicable LTCH claims that include 
COVID-19 cases and the applicable LTCH claims that exclude COVID-19 
cases). After removing cases with a length of stay of 7 days or less 
and statistical outliers, in each set of claims, 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 5--Adjust charges for the effects of Short Stay Outliers 
(SSOs).
    As the next step in the proposed calculation of the proposed FY 
2023 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 in each set of claims (that is, trimmed 
applicable LTCH cases that include COVID-19 cases and the trimmed 
applicable LTCH cases that exclude COVID-19 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 2023 MS-LTC-DRG relative weights would 
lower the 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 propose 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 6--Calculate the relative weights on an iterative basis using 
the 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 2023 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 2023. We believe that this method removes this hospital-
specific source of bias in measuring LTCH average charges (67 FR 
55985). Specifically, under this methodology, we reduced the impact of 
the variation in charges across providers on any particular MS-LTC-DRG 
relative weight by converting each LTCH's charge for an applicable LTCH 
case to a relative value based on that LTCH's average charge for such 
cases.
    Under the HSRV methodology, we standardize charges for each LTCH by 
converting its charges for each applicable LTCH case to hospital-
specific relative charge values and then adjusting those values for the 
LTCH's case-mix. The adjustment for case-mix is needed to rescale the 
hospital-specific relative charge values (which, by definition, average 
1.0 for each LTCH). The average relative weight for an LTCH is its 
case-mix; therefore, it is reasonable to scale each LTCH's average 
relative charge value by its case-mix. In this way, each LTCH's 
relative charge value is adjusted by its case-mix to an average that 
reflects the complexity of the applicable LTCH cases it treats relative 
to the complexity of the applicable LTCH cases treated by all other 
LTCHs (the average LTCH PPS case-mix of all applicable LTCH cases 
across all LTCHs). In other words, by multiplying an LTCH's relative 
charge values by the LTCH's case-mix index, we account for the fact 
that the same relative charges are given greater weight at an LTCH with 
higher average costs than they would at an LTCH with low average costs, 
which is needed to adjust each LTCH's relative charge value to reflect 
its case-mix relative to the average case-mix for all LTCHs. By 
standardizing charges in this manner, we count charges for a Medicare 
patient at an LTCH with high average charges as less resource-intensive 
than they would be at an LTCH with low average charges. For example, a 
$10,000 charge for a case at an LTCH with an average adjusted charge of 
$17,500 reflects a higher level of relative resource use than a $10,000 
charge for a case at an LTCH with the same case-mix, but an average 
adjusted charge of $35,000. We believe that the adjusted charge of an 
individual case more accurately reflects actual resource use for an 
individual LTCH because the variation in charges due to systematic 
differences in the markup of charges among LTCHs is taken into account.
    Consistent with our historical relative weight methodology, we 
propose to calculate the proposed FY 2023 MS-LTC-DRG relative weights 
using the HSRV methodology, which is an iterative process. Under our 
proposal in section VIII.B.3.a. of the preamble to this proposed rule 
to establish the FY

[[Page 28472]]

2023 MS-LTC-DRG relative weights as an average of the relative weights 
calculated both including and excluding the COVID-19 claims, we are 
proposing to apply the HSRV methodology when calculating the relative 
weights for each sets of claims (that is the claims that include COVID-
19 cases and the claims that exclude COVID-19 cases).
    Therefore, in accordance with our established methodology, for FY 
2023, 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 Step 5 of our 
proposed methodology) by the average adjusted charge for all applicable 
LTCH cases at the LTCH in which the case was treated. 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 average adjusted charge 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 FY 2023 relative 
weight by dividing the SSO-adjusted average of the hospital-specific 
relative charge values for applicable LTCH cases for the MS-LTC-DRG 
(that is, the sum of the hospital-specific relative charge value, as 
previously stated, divided by the sum of equivalent cases from Step 5 
for each MS-LTC-DRG) by the overall SSO-adjusted average hospital-
specific relative charge value across all applicable LTCH cases for all 
LTCHs (that is, the sum of the hospital-specific relative charge value, 
as previously stated, divided by the sum of equivalent applicable LTCH 
cases from Step 5 for each MS-LTC-DRG). Using these recalculated MS-
LTC-DRG relative weights, each LTCH's average relative weight for all 
of its SSO-adjusted trimmed applicable LTCH cases (that is, its case-
mix) was calculated by dividing the sum of all the LTCH's MS-LTC-DRG 
relative weights by its total number of SSO-adjusted trimmed applicable 
LTCH cases. The LTCHs' hospital-specific relative charge values (from 
previous) are then multiplied by the hospital-specific case-mix 
indexes. The hospital-specific case-mix adjusted relative charge values 
are then used to calculate a new set of MS-LTC-DRG relative weights 
across all LTCHs. This iterative process continued until there was 
convergence between the relative weights produced at adjacent steps, 
for example, when the maximum difference was less than 0.0001.
    Step 7--Adjust the 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 FY 2023 proposed MS-LTC-DRG 
relative weights based on each set of claims (that is claims that 
include COVID-19 cases and the claims that exclude COVID-19 cases), 
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). For both sets of weights, the one based on claims that include 
COVID-19 cases and the one based on claims that exclude COVID-19 cases, 
any adjustments for nonmonotonicity that were made in determining the 
proposed FY 2023 MS-LTC-DRG relative weights 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 8--Determine a relative weight for MS-LTC-DRGs with no 
applicable LTCH cases.
    Using the trimmed applicable LTCH cases, consistent with our 
historical methodology, we identified the MS-LTC-DRGs for which there 
were no claims in the December 2021 update of the FY 2021 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 relative weight (determined in 
accordance with the methodology as previously described). Then, the 
``no-volume'' proposed MS-LTC-DRG is assigned the same 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).
    For this proposed rule, there was only one claim grouped to MS-LTC-
DRG 273

[[Page 28473]]

(Percutaneous and other intracardiac procedures with MCC) in the 
December 2021 update of the FY 2021 MedPAR file. This claim had a 
COVID-19 diagnosis code. Therefore, when determining relative weights 
based on all applicable LTCH claims, a relative weight was computed for 
MS-LTC-DRG 273. However, when determining relative weights based on the 
set of claims that excluded COVID-19 cases, a relative was not computed 
for MS-LTC-DRG 273. When establishing the relative weights based on 
claims that exclude COVID-19 cases, instead of assigning a cross-walked 
relative weight for MS-LTC-DRG 273, we are proposing to assign MS-LTC-
DRG 273 the relative weight calculated using all applicable LTCH cases. 
In the absence of a non-COVID-19 claim for this MS-LTC-DRG, we believe 
the relative weight based on a COVID-19 claim grouped to this same MS-
LTC-DRG would more accurately reflect the relative resource use of this 
MS-LTC-DRG than a relative weight based on a proposed cross-walked MS-
LTC-DRG.
    Of the 767 proposed MS-LTC-DRGs for FY 2023, we identified 427 MS-
LTC-DRGs for which there were no trimmed applicable LTCH cases. We do 
not include MS-LTC-DRG 273, discussed previously, in this count. The 
427 MS LTC DRGs for which there were no trimmed applicable LTCH cases 
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 399 
MS-LTC-DRGs that for which, we are proposing to assign a relative 
weight using our existing ``no-volume'' MS-LTC-DRG methodology (that 
is, 427-11-2-15 = 399). We are proposing to assign relative weights to 
each of the 399 no-volume MS-LTC-DRGs based on clinical similarity and 
relative costliness to 1 of the remaining 340 (767-427 = 340) MS-LTC-
DRGs for which we calculated relative weights based on the trimmed 
applicable LTCH cases in the FY 2021 MedPAR file data using the steps 
described previously. (For the remainder of this discussion, we refer 
to the ``cross-walked'' MS-LTC-DRGs as one of the 340 MS-LTC-DRGs to 
which we cross-walked each of the 399 ``no-volume'' MS-LTC-DRGs.) Then, 
in general, we are proposing to assign the 399 no-volume MS-LTC-DRGs 
the relative weight of the cross-walked MS-LTC-DRG (when necessary, we 
made adjustments to account for nonmonotonicity).
    We cross-walked the no-volume MS-LTC-DRG to a MS-LTC-DRG for which 
we calculated relative weights based on the December 2021 update of the 
FY 2021 MedPAR file, and to which it is similar clinically in intensity 
of use of resources and relative costliness as determined by criteria 
such as care provided during the period of time surrounding surgery, 
surgical approach (if applicable), length of time of surgical 
procedure, postoperative care, and length of stay. (For more details on 
our process for evaluating relative costliness, we refer readers to the 
FY 2010 IPPS/RY 2010 LTCH PPS final rule (73 FR 48543).) We believe in 
the rare event that there would be a few LTCH cases grouped to one of 
the no-volume MS-LTC-DRGs in FY 2023, the relative weights assigned 
based on the cross-walked MS-LTC-DRGs would result in an appropriate 
LTCH PPS payment because the crosswalks, which are based on clinical 
similarity and relative costliness, would be expected to generally 
require equivalent relative resource use.
    Then we assigned the proposed relative weight of the cross-walked 
MS-LTC-DRG as the relative weight for the no-volume MS-LTC-DRG such 
that both of these MS-LTC-DRGs (that is, the no-volume MS-LTC-DRG and 
the cross-walked MS-LTC-DRG) have the same relative weight (and average 
length of stay) for FY 2023. We note that, if the cross-walked MS-LTC-
DRG had 25 applicable LTCH cases or more, its relative weight 
(calculated using the methodology as previously described in Steps 1 
through 4) is assigned to the no-volume MS-LTC-DRG as well. Similarly, 
if the MS-LTC-DRG to which the no-volume MS-LTC-DRG was cross-walked 
had 24 or less cases and, therefore, was designated to 1 of the low-
volume quintiles for purposes of determining the relative weights, we 
assigned the relative weight of the applicable low-volume quintile to 
the no-volume MS-LTC-DRG such that both of these MS-LTC-DRGs (that is, 
the no-volume MS-LTC-DRG and the cross-walked MS-LTC-DRG) have the same 
relative weight for FY 2023. (As we noted previously, in the infrequent 
case where nonmonotonicity involving a no-volume MS-LTC-DRG resulted, 
additional adjustments are required to maintain monotonically 
increasing relative weights.)
    For this proposed rule, we are providing the list of the no-volume 
MS-LTC-DRGs and the MS-LTC-DRGs to which each was cross-walked (that 
is, the cross-walked MS-LTC-DRGs) for FY 2023 in a supplemental data 
file for public use posted via the internet on the CMS website for this 
proposed rule at https://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 Table 
11.
    To illustrate this methodology for determining the proposed 
relative weights for the FY 2023 MS-LTC-DRGs with no applicable LTCH 
cases, we are providing the following example.
    Example: There were no trimmed applicable LTCH cases in the FY 2021 
MedPAR file that we are using for this proposed rule for proposed MS-
LTC-DRG 061 (Ischemic stroke, precerebral occlusion or transient 
ischemia with thrombolytic agent with MCC). We determined that proposed 
MS-LTC-DRG 070 (Nonspecific cerebrovascular disorders with MCC) is 
similar clinically and based on resource use to proposed MS-LTC-DRG 
061. Therefore, we are proposing to assign the same relative weight 
(and average length of stay) of proposed MS-LTC-DRG 70 of 0.837 for FY 
2023 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 would vary in 
the future. Consistent with our historical practice, we are proposing 
to use the best available claims data to identify the trimmed 
applicable LTCH cases from which we determined the relative weights in 
the final rule.
    For FY 2023, 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.

[[Page 28474]]

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 established 
a relative weight of 0.0000 for the 2 ``error'' MS-LTC-DRGs (that is, 
MS-LTC-DRG 998 (Principal Diagnosis Invalid as Discharge Diagnosis) and 
MS-LTC-DRG 999 (Ungroupable)) because applicable LTCH cases grouped to 
these MS-LTC-DRGs cannot be properly assigned to an MS-LTC-DRG 
according to the grouping logic.
    Additionally, 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 are proposing 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 would not be applicable for any LTCH 
discharges occurring in FY 2023, and as such payment under the LTCH PPS 
would be no longer be made in part based on the LTCH PPS standard 
Federal payment rate for any discharges assigned to those MS-LTC-DRGs.
    Step 9--Normalize the two sets of relative weights.
    The next step in our proposed calculation of the proposed FY 2023 
MS-LTC-DRG relative weights is to normalize the set of relative weights 
that were calculated using claims that include COVID-19 cases and to 
normalize the set of relative weights that were calculated using claims 
that excluded COVID-19 cases. The normalization adjustment is intended 
to ensure that the recalibration of the MS-LTC-DRG relative weights 
(that is, the process itself) neither increases nor decreases the 
average case-mix index. To calculate the normalization factors, we 
grouped applicable LTCH cases from each set of claims using the 
proposed FY 2023 Version 40 GROUPER, and used the proposed FY 2023 MS-
LTC-DRG relative weights associated with each set to calculate the 
average case-mix index (CMI) for each set; we grouped the same 
applicable LTCH cases from each set of claims using the FY 2022 GROUPER 
Version 39 and MS-LTC-DRG relative weights and calculated the average 
CMI for each set; and computed the ratio by dividing the average CMI 
for each set for FY 2022 by the average CMI for each set for FY 2023. 
These ratios are the normalization factors that were applied to each 
respective set of unnormalized weights. Because the calculation of the 
normalization factor involves the relative weights for the MS-LTC-DRGs 
that contained applicable LTCH cases to calculate the average CMIs, any 
low-volume MS-LTC-DRGs are included in the calculation (and the MS-LTC-
DRGs with no applicable LTCH cases are not included in the 
calculation). The table displays the normalization factors that were 
calculated and applied for each set of relative weights.
[GRAPHIC] [TIFF OMITTED] TP10MY22.184

    Step 10--Average the two sets of normalized relative weights.
    After each set of relative weights was normalized, we computed a 
simple average of the normalized relative weights and geometric mean 
length of stays from each set, by using 50 percent of the relative 
weights calculated using applicable LTCH cases that include COVID-19 
cases and 50 percent of the relative weights calculated using 
applicable LTCH cases that exclude COVID-19 cases.
    Step 11--Budget neutralize the averaged relative weights.
    In accordance with the regulations at Sec.  412.517(b) (in 
conjunction with Sec.  412.503), the annual update to the MS-LTC-DRG 
classifications and relative weights is done in a budget neutral manner 
such that estimated aggregate LTCH PPS payments would be unaffected, 
that is, would be neither greater than nor less than the estimated 
aggregate LTCH PPS payments that would have been made without the MS-
LTC-DRG classification and relative weight changes. (For a detailed 
discussion on the establishment of the budget neutrality requirement 
for the annual update of the MS-LTC-DRG classifications and relative 
weights, we refer readers to the RY 2008 LTCH PPS final rule (72 FR 
26881 and 26882).
    To achieve budget neutrality under the 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 continue to apply budget neutrality adjustments in 
determining the proposed FY 2023 MS-LTC-DRG relative weights so that 
our proposed update the MS-LTC-DRG classifications and relative weights 
for FY 2023 are made in a budget neutral manner. In addition, as 
discussed in section VIII.B.3.b. of the preamble to this proposed rule, 
we are proposing that the proposed 10-percent cap on the reduction in a 
MS-LTC-DRG's relative weight in a given year be budget neutral. 
Therefore, for FY 2023, we are proposing to apply two budget neutrality 
factors to determine the MS-LTC-DRG relative weights. In this step, we 
describe the determination of the budget neutrality adjustment that 
accounts for the proposed update of the MS-LTC-DRG classifications and 
relative weights prior to the application of the ten-percent cap. In 
steps 12 and

[[Page 28475]]

13, we describe the application of the proposed 10-percent cap policy 
(step 12) and the determination of the proposed budget neutrality 
factor that accounts for the application of the proposed 10-percent cap 
policy (step 13).
    As described previously, the relative weights constructed up to 
this point in our methodology were calculated based on two different 
set of claims (the applicable LTCH cases that included COVID-19 cases 
and the applicable LTCH cases that excluded COVID-19 cases) and then 
averaged together. However, when modeling payments for determining the 
budget neutrality factors, we are proposing to use the set of LTCH 
cases that include COVID-19 cases. In the absence of a set of MedPAR 
claims that reflect our expectation that there will be fewer (but not 
zero) COVID-19 cases in FY 2023 as compared to the COVID-19 cases in 
the FY 2021 claims data, we believe this is the best data available for 
determining the budget neutrality factors. We note this is consistent 
with the approach being proposed under the IPPS as discussed in section 
II.A.4. of the Addendum of this proposed rule. We are also soliciting 
feedback from commenters on alternative ways to use the FY 2021 claims 
data for purposes of calculating the FY 2023 budget neutrality factors.
    In this proposed rule, to ensure budget neutrality for the proposed 
update to the MS-LTC-DRG classifications and relative weights prior to 
the application of the 10-percent cap (that is, uncapped relative 
weights), under Sec.  412.517(b), we are proposing to continue to use 
our established two-step budget neutrality methodology. Therefore, in 
the first step of our MS-LTC-DRG update budget neutrality methodology, 
for FY 2023, we propose to calculate and apply a proposed normalization 
factor to the recalibrated relative weights (the result of Steps 1 
through 10 discussed previously) to ensure that estimated payments are 
not affected by changes in the composition of case types or the changes 
to the classification system. That is, the normalization adjustment is 
intended to ensure that the recalibration of the MS-LTC-DRG relative 
weights (that is, the process itself) neither increases nor decreases 
the average case-mix index.
    To calculate the proposed normalization factor for FY 2023, we 
propose to use the following three steps: (1.a.) Use the applicable 
LTCH cases from the best available data (that is, LTCH discharges from 
the FY 2021 MedPAR file, including the COVID-19 cases as discussed 
previously) and group them using the proposed FY 2023 GROUPER (that is, 
Version 40 for FY 2023) and the proposed recalibrated FY 2023 MS-LTC-
DRG uncapped relative weights (determined in Steps 1 through 10 
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 2022 GROUPER (Version 39) and FY 2022 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 
case-mix index for FY 2022 (determined in Step 1.b.) by the average 
case-mix index for FY 2023 (determined in Step 1.a.). As a result, in 
determining the proposed MS-LTC-DRG relative weights for FY 2023, each 
recalibrated MS-LTC-DRG uncapped relative weight is multiplied by the 
proposed normalization factor of 0.99885 (determined in Step 1.c.) in 
the first step of the budget neutrality methodology, which produces 
``normalized relative weights.''
    In the second step of our MS-LTC-DRG update budget neutrality 
methodology, we calculated a proposed budget neutrality adjustment 
factor consisting of the ratio of estimated aggregate FY 2023 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 2023 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 2023, we propose to 
determine the budget neutrality adjustment factor using the following 
three steps: (2.a.) Simulate estimated total FY 2023 LTCH PPS standard 
Federal payment rate payments for applicable LTCH cases using the 
uncapped normalized relative weights for FY 2023 and proposed GROUPER 
Version 40 (as described previously); (2.b.) simulate estimated total 
FY 2023 LTCH PPS standard Federal payment rate payments for applicable 
LTCH cases using the FY 2022 GROUPER (Version 39) and the FY 2022 MS-
LTC-DRG relative weights in Table 11 of the FY 2022 IPPS/LTCH PPS final 
rule; and (2.c.) calculate the ratio of these estimated total payments 
by dividing the value determined in Step 2.b. by the value determined 
in Step 2.a. In determining the proposed FY 2023 MS-LTC-DRG relative 
weights, each uncapped normalized relative weight is then multiplied by 
a proposed budget neutrality factor of 0.9932185 (the value determined 
in Step 2.c.) in the second step of the budget neutrality methodology.
    Step 12--Apply the 10-percent cap to decreases in MS-LTC-DRG 
relative weights.
    As discussed in section VIII.B.3.b. of the preamble to this 
proposed rule, we are proposing a 10-percent cap on the reduction in a 
MS-LTC-DRG's relative weight in a given year, beginning in FY 2023. 
Specifically, in cases where the relative weight for a MS-LTC-DRG would 
decrease by more than 10-percent in a given year, we propose to limit 
the reduction to 10-percent for that year. Under this proposal, this 
10-percent cap would only be applied to the relative weights for MS-
LTC-DRGs with applicable LTCH cases and would not be applied to the no-
volume MS-LTC-DRGs identified in Step 8. Therefore, in this step, for 
each proposed FY 2023 MS-LTC-DRG with applicable LTCH cases (excludes 
zero-volume MS-LTC-DRGs) we compared its FY 2023 relative weight (after 
application of the proposed normalization and proposed budget 
neutrality factors determined in Step 11), to its FY 2022 MS-LTC-DRG 
relative weight. For any MS-LTC-DRG where the FY 2023 relative weight 
would otherwise have declined more than 10 percent, we established a 
proposed capped FY 2023 MS-LTC-DRG relative weight that would be equal 
to 90 percent of that MS-LTC-DRG's FY 2022 relative weight (that is, we 
set the proposed FY 2023 relative weight equal to the FY 2022 weight x 
0.90).
    Step 13--Calculate the MS-LTC-DRG cap budget neutrality factor.
    As discussed in section VIII.B.3.b. of the preamble to this 
proposed rule, we also are proposing to apply a budget neutrality 
adjustment to the MS-LTC-DRG relative weights so that the proposed 10-
percent cap on relative weight reductions is implemented in a budget 
neutral manner. Therefore, we are proposing to determine the budget 
neutrality adjustment factor for our proposed 10-percent cap on 
relative weight reductions using the following three steps: (a) 
Simulate estimated total FY 2023 LTCH PPS standard Federal payment rate 
payments for applicable LTCH cases using the proposed capped relative 
weights for FY 2023 (determined in Step 12) and proposed GROUPER 
Version 40; (b) simulate estimated total FY 2023 LTCH PPS standard 
Federal payment rate payments for applicable LTCH cases using the 
proposed uncapped relative weights for FY 2023 (determined in Step 11) 
and proposed GROUPER Version 40; and (c) calculate the ratio of these

[[Page 28476]]

estimated total payments by dividing the value determined in step (b) 
by the value determined in step (a). In determining the proposed FY 
2023 MS-LTC-DRG relative weights, each capped relative weight is then 
multiplied by a proposed budget neutrality factor of 0.9966694 (the 
value determined in step (c)) to achieve the proposed budget neutrality 
requirement.
    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, proposed geometric mean length of stay, and proposed five-
sixths of the geometric mean length of stay (used to identify SSO cases 
under Sec.  412.529(a)) for FY 2023. We also are making available on 
our website the two sets of relative weights that were averaged 
together in determining the proposed FY 2023 MS-LTC-DRG relative 
weights. That is, the set of relative weights based on applicable LTCH 
cases that included COVID-19 cases and the set of relative weights 
based on applicable LTCH cases that excluded COVID-19 cases. We also 
are making available on the website the proposed MS-LTC-DRG relative 
weights prior to the application of the proposed 10 percent cap on MS-
LTC-DRG relative weight reductions and corresponding proposed cap 
budget neutrality factor.

C. Proposed Changes to the LTCH PPS Payment Rates and Other Proposed 
Changes to the LTCH PPS for FY 2023

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 2023, that is, effective for LTCH discharges occurring on or 
after October 1, 2022 through September 30, 2023. 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 2023 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 2023.
    The proposed update to the LTCH PPS standard Federal payment rate 
for FY 2023 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 2023 are discussed in this 
section, including the statutory reduction to the annual update for 
LTCHs that fail to submit quality reporting data for FY 2023 as 
required by the statute (as discussed in section VIII.C.2.c. of the 
preamble of this proposed rule). We are 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 2023 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).
2. Proposed FY 2023 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 2023
    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).) 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 
2023.

[[Page 28477]]

    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. 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 2023.
    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 points 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 2023
    Consistent with our historical practice, we estimate the market 
basket increase and the productivity adjustment based on IGI's forecast 
using the most recent available data. Based on IGI's fourth quarter 
2021 forecast, the FY 2023 market basket update for the LTCH PPS using 
the 2017-based LTCH market basket is 3.1 percent. The current estimate 
of the productivity adjustment for FY 2023 based on IGI's fourth 
quarter 2021 forecast is 0.4 percent.
    For FY 2023, section 1886(m)(3)(A)(i) of the Act requires that any 
annual update to the LTCH PPS standard Federal payment rate be reduced 
by the productivity adjustment, described in section 
1886(b)(3)(B)(xi)(II) of the Act. Consistent with the statute, we are 
proposing to reduce the FY 2023 market basket increase by the FY 2023 
productivity adjustment. To determine the proposed market basket 
increase for LTCHs for FY 2023, as reduced by the proposed productivity 
adjustment, consistent with our established methodology, we are 
subtracting the proposed FY 2023 productivity adjustment from the 
proposed FY 2023 market basket increase. (For additional details on our 
established methodology for adjusting the market basket increase by the 
productivity adjustment, we refer readers to the FY 2012 IPPS/LTCH PPS 
final rule (76 FR 51771).)
    For FY 2023, 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 3.1 percent market basket update to the LTCH PPS 
standard Federal payment rate for FY 2023 would be reduced by the 0.4 
percentage point productivity adjustment as required under section 
1886(m)(3)(A)(i) of the Act and by the additional 2.0 percentage points 
reduction required by section 1886(m)(5) of the Act.
    In this FY 2023 IPPS/LTCH PPS proposed rule, in accordance with the 
statute, we are proposing to reduce the proposed FY 2023 market basket 
update of 3.1 percent (based on IGI's fourth quarter 2021 forecast of 
the 2017-based LTCH market basket) by the proposed FY 2023 productivity 
adjustment of 0.4 percentage point (based on IGI's fourth quarter 2021 
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 2023 
of 2.7 percent (that is, the most recent estimate of the LTCH PPS 
market basket increase of 3.1 percent less the productivity adjustment 
of 0.4 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 0.7 percent (that is, 2.7 
percent minus 2.0 percentage points) for FY 2023 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 productivity adjustment, 
if appropriate, in the final rule to establish an annual update to the 
LTCH PPS standard Federal payment rate for FY 2023. We note that, 
consistent with historical practice, we are also proposing to adjust 
the FY 2023 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 section IX. of the preamble of this proposed rule, we seek 
public comment on the following focus areas and proposed changes to the 
Medicare quality reporting programs:
     In section IX.A., assessment of the impact of climate 
change and health equity.
     In section IX.B., overarching principles in measuring 
healthcare quality disparities in hospital quality programs.

[[Page 28478]]

     In section IX.C., advancement of digital quality 
measurement and use of Fast Healthcare Interoperability Resources 
(FHIR) in hospital quality programs.
     In section IX.D., advancing the Trusted Exchange Framework 
and Common Agreement (TEFCA).
     In section IX.E., the Hospital IQR.
     In section IX.F., the PCHQR Program.
     In section IX.G., the LTCH QRP.
     In section IX.H., the Medicare Promoting Interoperability 
Program for Eligible Hospitals and Critical Access Hospitals (CAHs) 
(previously known as the Medicare EHR Incentive Program).

A. Current Assessment of Climate Change Impacts on Outcomes, Care, and 
Health Equity--Request for Information

1. Background
    A recent consensus statement signed by more than 200 medical 
journals noted climate change represents the greatest threat to global 
public health of the coming century.\698\ Pollution associated with the 
burning of fossil fuels is known to cause serious harm and loss in 
productivity, and resultant climate instability introduces a 
combination of catastrophic weather events and chronic disease impacts 
that create serious burdens on organizations providing health 
care.\699\ There is also evidence that climate change 
disproportionately harms underserved populations (for example, racial 
and ethnic minority groups, indigenous people, members of religious 
minorities, people with disabilities, sexual and gender minorities, 
individuals with limited English proficiency, older adults, and rural 
populations).\700\ Long-term discrimination and disparities based on 
social determinants of health mean that these groups are often less 
equipped to withstand climate threats and are more susceptible to 
associated harm.\701\ For example, Black Americans are much likelier to 
experience premature mortality as a result of extreme heat, and 
childhood asthma rates related to warming temperatures will be much 
higher in minority communities, as well.\702\ Out of concern for the 
health of individuals, and to maintain uninterrupted operations in 
service of patients, we believe the healthcare sector should more fully 
explore how to effectively prepare for climate threats. Because 
healthcare facilities also emit greenhouse gases (GHGs) that contribute 
to climate change and its impacts, we believe that they should study 
how best to reduce those emissions, as well.
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    \698\ Atwoli, L, Banqui A, Benfield T, et al. (2021). Call for 
emergency action to limit global temperature increases, restore 
biodiversity, and protect health. Lancet, 398(10304):939-41.
    \699\ Eckelman, M, Huang K, et al. (2020). Health Care Pollution 
and Public Health Damage in the United States: An Update. Health 
Affairs, 39:12.
    \700\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
    \701\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
    \702\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
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2. Solicitation of Comments on the Current State of Health System 
Climate Change Efforts
    In this Request for Information (RFI), we are seeking comment on 
how hospitals, nursing homes, hospices, home health agencies, and other 
providers can better prepare for the harmful impacts of climate change 
on their patients, and how we can support them in doing so. Because 
research has shown that climate change causes harm to individuals 
(through both catastrophic events and chronic disease) \703\ and 
because there is evidence to show that climate change will 
disproportionately harm underserved populations,\704\ we believe that 
it is critical to study and prepare for these impacts.
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    \703\ Eckelman, M, Huang K, et al. (2020). Health Care Pollution 
and Public Health Damage in the United States: An Update. Health 
Affairs,39:12.
    \704\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
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    Generally, we are seeking stakeholder input on what the U.S. 
Department of Health and Human Services (HHS) and CMS can do to support 
hospitals, nursing homes, hospices, home health agencies, and other 
providers in more effectively: (a) Determining likely climate impacts 
(that is, both immediate impacts associated with climate-related 
disasters and long-term chronic disease implications of climate change) 
on their patients, residents and consumers so that they can develop 
plans to mitigate those impacts; (b) understanding exceptional threats 
that climate-related emergencies (for example, storms, floods, extreme 
heat, wildfires) present to continuous facility operations (including 
potential disruptions in patient services associated with catastrophic 
events as a result of power loss, limited transportation, evacuation 
challenges, etc.) so they can better address those; and (c) 
understanding how to take action on reducing their emissions and 
tracking their progress in this regard. We believe this will inform the 
development and updating of policies that can assist providers in 
responding to climate-related challenges (for example, policies related 
to emergency preparedness) as well as the updating of HHS climate-
health tools and resources.
    We also invite public comments on the following topics 
(understanding that some provider types might have done more work in 
this area than others):
     The availability of information, such as analyses of 
climate change impacts (whether developed internally or collected from 
outside sources), that hospitals, nursing homes, hospices, home health 
agencies, and other providers can access to better understand climate 
threats to their patients, community, and staff.
     The degree to which different provider types currently 
complete comprehensive climate change risk assessments to better 
understand risks to their patient populations and the costs incurred 
due to catastrophic climate events and climate-related chronic disease.
     The degree to which facility efforts to prepare for 
climate impacts overlap with the work they already complete to meet 
CMS's Emergency Preparedness Requirements for Medicare and Medicaid 
Participating Providers and Suppliers, and the degree to which related 
CMS requirements sufficiently (or insufficiently) prepare them for the 
threats created by climate change and help or hinder these efforts.
     The degree to which hospitals, nursing homes, hospices, 
home health agencies, and other providers measure and share performance 
associated with their response to climate-related catastrophes (for 
example, measuring harm to vulnerable populations as a result of such 
events, or extent of disruption in service).
     The nature of facility plans for assisting the community 
and patients to prepare for and recover from climate-related events, as 
well as the nature of plans for evacuating patients with differing 
needs, including those with disabilities.
     The degree to which climate change, and climate change 
linked to health equity, is publicly addressed in strategic plans and 
objectives in your facility or system, and the degree to which hospital 
leadership regularly reviews progress on goals related to climate 
preparedness and mitigation

[[Page 28479]]

and invests in health professional training on this topic.
     Whether health systems and facilities have time-bound, 
public aims for GHG emissions reduction, and, if yes, whether those 
aims relate to direct facility emissions, emissions associated with 
purchased energy, emissions associated with supply chain or some 
combination of these.
     The measures that health systems and facilities use to 
track their progress on GHG emissions reduction and use of renewable 
energy, as well as the data collection tools that they may use support 
this tracking.
     The tools and supports that health systems and facilities 
most heavily rely on to support their efforts to reduce GHG emissions.
     How HHS and CMS can support hospitals, nursing homes, 
hospices, home health agencies, and other providers in their efforts to 
more fully prepare for climate change's catastrophic and chronic 
impacts on their operations and the people they serve, as well as what 
incentives (for example, recognition, payment, reporting) might assist 
them in taking more action on climate readiness and emissions 
reduction.
     Whether accrediting organizations assess facilities' 
readiness for climate-related threats and their efforts to reduce GHG 
emissions.

B. Overarching Principles for Measuring Healthcare Quality Disparities 
Across CMS Quality Programs--Request for Information

1. Background
    Significant and persistent inequities in healthcare outcomes exist 
in the United States (U.S.). Belonging to a racial or ethnic minority 
group; being a member of a religious minority; 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, are often associated with worse health 
outcomes.705 706 707 708 709 710 711 712 713 We are 
committed to achieving equity in healthcare outcomes for our 
beneficiaries by supporting healthcare providers' quality improvement 
activities to reduce health disparities, enabling beneficiaries to make 
more informed decisions, and promoting healthcare provider 
accountability for healthcare disparities.\714\
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    \705\ Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission 
rates for Medicare beneficiaries by race and site of care. JAMA, 
305(7):675-681.
    \706\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; S.B. Nadimpalli, et al., The Association between 
Discrimination and the Health of Sikh Asian Indians.
    \707\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and thirty-day outcomes after acute myocardial 
infarction, heart failure, and pneumonia: Retrospective cohort 
study. British Medical Journal, 346.
    \708\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and equity of care in U.S. hospitals. New England Journal of 
Medicine, 371(24):2298-2308.
    \709\ Polyakova, M., et al. (2021). Racial disparities in excess 
all-cause mortality during the early COVID-19 pandemic varied 
substantially across states. Health Affairs, 40(2): 307-316.
    \710\ Rural Health Research Gateway. (2018). Rural communities: 
Age, income, and health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \711\ HHS Office of Minority Health. (2020). Progress Report to 
Congress: 2020 Update on the Action Plan to Reduce Racial and Ethnic 
Health Disparities. Available at: https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=2&lvlid=57.
    \712\ Heslin, KC, Hall, JE. (2021). Sexual Orientation 
Disparities in Risk Factors for Adverse COVID-19-Related Outcomes, 
by Race/Ethnicity--Behavioral Risk Factor Surveillance System, 
United States, 2017-2019. MMWR Morb Mortal Wkly Rep 2021;70:149-154. 
Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \713\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). 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. doi:10.1101/2020.07.21.20159327. Available at: https://pubmed.ncbi.nlm.nih.gov/32743608/.
    \714\ Centers for Medicare and Medicaid Services. (2016). CMS 
Quality Strategy. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Qualityinitiativesgeninfo/downloads/cms-quality-strategy.pdf.
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    Health equity is an important component of an equitable society. 
Equity, as defined in Executive Order 13985, is ``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; LGBTQ+ 
persons; persons with disabilities; persons who live in rural areas; 
and persons otherwise adversely affected by persistent poverty or 
inequality.'' \715\ We define health equity as the attainment of the 
highest level of health for all people, where everyone has a fair and 
just opportunity to attain their optimal health regardless of race, 
ethnicity, disability, sexual orientation, gender identity, religion, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes. We are working to 
advance health equity by designing, implementing, and operationalizing 
policies and programs that support health for all the people served by 
our programs, eliminating avoidable differences in health outcomes 
experienced by people who are disadvantaged or underserved, and 
providing the care and support that our beneficiaries need to 
thrive.\716\
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    \715\ 86 FR 7009 (January 25, 2021). Advancing Racial Equity and 
Support for Underserved Communities Through the Federal Government. 
Available at: https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
    \716\ Centers for Medicare & Medicaid Services. (2022). Health 
Equity. Available at: https://www.cms.gov/pillar/health-equity.
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    Advancing health equity will require a variety of efforts across 
the healthcare system. The reduction in healthcare disparities is one 
aspect of improving equity that we have prioritized. In a RFI that we 
included in the FY 2022 IPPS/LTCH PPS final rule, titled ``Closing the 
Health Equity Gap in CMS Hospital Quality Programs'' (86 FR 45349 
through 45360), we described programs and policies we have implemented 
over the past decade with the aim of identifying and reducing 
healthcare disparities, including: The CMS Mapping Medicare Disparities 
Tool \717\ and the CMS Disparity Methods stratified reporting.\718\ CMS 
has also supported HHS efforts to implement of the National Standards 
for Culturally and Linguistically Appropriate Services (CLAS) in Health 
and Health Care (78 FR 58539); \719\ as well as improvement of the 
collection of social determinants of health in standardized patient 
assessment data in four post-acute care settings and the collection of 
health-related social need data by model participants in the 
Accountable Health Communities Model.720 721 722
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    \717\ Centers for Medicare and Medicaid Services. (2021). CMS 
Office of Minority Health. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
    \718\ Centers for Medicare and Medicaid Services. Disparity 
Methods Confidential Reporting. Available at: https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \719\ 78 FR 58539 (September 24, 2013). National Standards for 
Culturally and Linguistically Appropriate Services (CLAS) in Health 
and Health Care. Available at: https://www.federalregister.gov/documents/2013/09/24/2013-23164/national-standards-for-culturally-and-linguistically-appropriate-services-clas-in-health-and-health.
    \720\ Centers for Medicare and Medicaid Services. (2021). 
Accountable Health Communities Model. Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \721\ Centers for Medicare and Medicaid Services. The 
Accountable Health Communities Health-Related Social Needs Screening 
Tool. Available at: https://innovation.cms.gov/files/worksheets/ahcm-screeningtool.pdf.
    \722\ Centers for Medicare and Medicaid Services. (2021). IMPACT 
Act Standardized Patient Assessment Data Elements. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/-IMPACT-Act-Standardized-Patient-Assessment-Data-Elements.

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[[Page 28480]]

    Measuring healthcare disparities and reporting these results to 
healthcare providers is a cornerstone of our approach to advancing 
healthcare equity. It is important to consistently measure differences 
in care received by different groups of our beneficiaries, and this can 
be achieved by methods to stratify quality measures. Measure 
stratification is defined for this purpose as calculating measure 
results for specific groups or subpopulations of patients. Assessing 
healthcare disparities through stratification is only one method for 
using healthcare quality measurement to address health equity, but it 
is an important approach that allows healthcare providers to tailor 
quality improvement initiatives, decrease disparity, track improvement 
over time, and identify opportunities to evaluate upstream drivers of 
health. The use of measure stratification to assess disparities has 
been identified by our Office of Minority Health as a critical 
component of an organized response to health disparities.\723\ To date, 
we have performed analyses of disparities in our quality programs by 
using a series of stratification methodologies identifying quality of 
care for patients with heightened social risk or with demographic 
characteristics with associations to poorer outcomes. In 2015, we began 
providing entity-level quality and member experience data to all 
Medicare Part C/D health plans stratified by race and ethnicity. In 
2018, we introduced confidential reporting of hospital quality measure 
data stratified by dual eligibility in the Hospital IQR Program (81 FR 
25199; 82 FR 38403 through 38409).\724\
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    \723\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
    \724\ Centers for Medicare & Medicaid Services, Office of 
Minority Health. Racial, Ethnic, & Gender Disparities in Health Care 
in Medicare Advantage. (2021). Available at: https://www.cms.gov/files/document/racial-ethnic-gender-disparities-health-care-medicare-advantage.pdf.
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    We are continuing to evaluate opportunities to expand our measure 
stratification reporting initiatives using existing sources of data. 
Our goal is to provide comprehensive and actionable information on 
health disparities to healthcare providers participating in our quality 
programs to support quality improvement efforts. We are doing this, in 
part, by starting with confidential reporting of stratified measure 
results that highlight potential gaps in care between groups of 
patients. This includes examining the possibility of reporting 
disparities in care based on additional social risk factors and 
demographic variables associated with historic disadvantage in the 
healthcare system, and examining disparities through the use of 
stratified healthcare quality measures across a variety of care 
settings. As we consider expanding our disparity measurement 
initiatives through the use of measure stratification, we believe that 
we should model these efforts on existing best practices, such as 
considering stakeholder feedback and making use of lessons learned 
through the development of our existing disparity reporting efforts.
    There are several key elements that we intend to take into account 
as we consider advancing the use of measurement and stratification as 
tools to address healthcare disparities and advance healthcare equity. 
We seek input on key considerations in five specific areas that could 
inform our approach. Each is described in more detail later in this 
section:
     Identification of Goals and Approaches for Measuring 
Healthcare Disparities and Using Measure Stratification Across CMS 
Quality Programs--This section identifies potential approaches for 
measuring healthcare disparities through measure stratification in CMS 
quality reporting programs.
     Guiding Principles for Selecting and Prioritizing Measures 
for Disparity Reporting Across CMS Quality Reporting Programs--This 
section describes considerations that could inform the selection of 
healthcare quality measures to prioritize for stratification.
     Principles for Social Risk Factor and Demographic Data 
Selection and Use--This section describes several types of social risk 
factor and demographic data that could be used in stratifying measures 
for healthcare disparity measurement.
     Identification of Meaningful Performance Differences--This 
section reviews several strategies for identifying meaningful 
differences in performance when measure results are stratified.
     Guiding Principles for Reporting Disparity Results--This 
section reviews considerations we could take into account in 
determining how quality programs will report measure results stratified 
by social risk factors and demographic variables to healthcare 
providers, as well as the ways different reporting strategies could 
hold healthcare providers accountable for identified disparities.
2. Identification of Goals and Approaches for Measuring Healthcare 
Disparities and Using Measure Stratification Across CMS Quality 
Programs
    One of our goals in developing methods to measure disparities in 
care for beneficiaries is to provide actionable and useful results to 
healthcare providers. By quantifying healthcare disparities (for 
example, through quality measure stratification), we aim to provide 
useful tools for healthcare providers to drive improvements. We hope 
that these results support healthcare provider efforts to examine the 
underlying drivers of disparities in their patients' care and to 
develop their own innovative and targeted quality improvement 
interventions. With stratified disparity information available, it may 
be possible to drive system-wide advancement through incremental, 
provider-level improvement.
    There are multiple conceptual approaches to stratifying measures. 
Since 2018, we have focused on illuminating healthcare disparities by 
reporting stratified results of existing quality measures by dual 
eligible status in two complementary ways.\725\ First, after 
stratification by dual eligible status, measure results for subgroups 
of patients served by an individual healthcare provider can be directly 
compared. This type of comparison identifies such disparities, or gaps 
in care or outcomes between groups at a hospital. This approach is 
sometimes referred to as ``within-provider'' disparity and can be done 
for most measures that include patient-level data for most care 
settings. ``Within-provider'' disparities are a helpful means by which 
to quantitatively express disparities in care at the provider 
level.\726\ Second, a healthcare provider's performance on a measure 
for only dual eligible patients is compared to other healthcare 
providers' performance for that same subgroup of patients (sometimes 
referred to as ``across-provider'' disparities measurement). This type 
of comparison illuminates the healthcare provider's

[[Page 28481]]

performance for only the dual eligible subgroup, allowing comparisons 
for specific performance to be better understood and compared to peers, 
or against state and national benchmarks.
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    \725\ QualityNet. Disparity Methods Confidential Reporting 
Overview. Available at: https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \726\ Centers for Medicare & Medicaid Services. (2015). Risk 
Adjustment Fact Sheet. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/PhysicianFeedbackProgram/Downloads/Risk-Adjustment-Fact-Sheet.pdf.
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    Taken separately, each approach may provide an incomplete picture 
of disparities in care for a particular measure, but when reported 
together with overall quality performance, these results can give 
detailed information about where differences in care exist. Using dual 
eligibility as an example, a healthcare provider may underperform when 
compared to national averages for their dual eligible population 
(``across-provider'' disparity), but if they also underperform for 
patients who are not dual eligible, the measured difference, or 
``within-provider'' disparity, could be negligible even though 
performance for the group that has been historically marginalized 
remains poor. In this case, simply providing stratified within-provider 
results could show little difference in care between patient groups 
seen by the provider but the combined results show the provider is 
underperforming on care for some patients compared to other providers.
    Similar approaches have been recommended by the Assistant Secretary 
of Planning and Evaluation (ASPE) as ways to measure health equity in 
their 2020 Report to Congress.\727\ In their report, ASPE suggested 
measuring and reporting quality specifically for beneficiaries with 
social risk factors, stratifying measures by social risk factors, and 
encouraging the development of health equity measures such as these for 
incorporation into quality reporting programs.
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    \727\ ASPE. (2020). Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program: The Second of Two Reports 
Required by the Improving Medicare Post-Acute Care Transformation 
(IMPACT) Act of 2014. Available at: https://aspe.hhs.gov/sites/default/files/migrated_legacy_files//195191/Second-IMPACT-SES-Report-to-Congress.pdf.
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    We are especially sensitive to the need to ensure all disparity 
reporting avoids measurement bias. Stratified results must be carefully 
examined for potential measurement or algorithmic bias \728\ that is 
introduced through stratified reporting. Furthermore, results of 
stratified reporting must be evaluated for any type of selection bias 
that fails to capture disparity due to inadequate representation of 
subgroups of patients in measure cohorts. As part of the implementation 
of any type of measure stratification, we would carefully examine 
stratified results and methods to mitigate the potential for drawing 
incorrect conclusion from results.
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    \728\ Obermeyer Z, Powers B, Vogeli C, Mullainathan S. 
Dissecting racial bias in an algorithm used to manage the health of 
populations. Science. 2019;366(6464):447-53.
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3. Guiding Principles for Selecting and Prioritizing Measures for 
Disparity Reporting Across CMS Quality Reporting Programs
    We are considering expanding our efforts to provide stratified 
reporting for additional clinical quality measures, provided they offer 
meaningful and valid feedback to healthcare providers on their care for 
populations that may face social disadvantage or other forms of 
discrimination or bias. Further development of stratified reporting of 
healthcare quality measures can provide healthcare providers with more 
granular results that support targeting resources and initiatives to 
improve health equity as a means to improving the overall quality of 
care. We are mindful that it may not be possible to calculate 
stratified results for all quality measures, or that there may be 
situations where stratified reporting may not be desired. To help 
inform prioritization of the next generation of candidate measures for 
stratified reporting, we are soliciting feedback on several systematic 
principles under consideration that we believe will help us prioritize 
measures for disparity reporting across quality programs.
    These considerations would help guide the use of stratified measure 
results to provide information on healthcare disparities broadly across 
our quality programs. While we aim to standardize approaches where 
possible, disparity identification requires an understanding of the 
specific context and measures used by each program. To ensure that 
results provide the most actionable data possible, and to limit the 
potential for the introduction of bias, we believe decisions about how 
to identify and prioritize measures for possible stratification should 
be made at the program level.
     Prioritize Existing Clinical Quality Measures--When 
considering disparity reporting of stratified quality measures, there 
are several advantages to focusing on measures that we have already, 
through notice and comment rulemaking, adopted for one or more CMS 
quality programs. These measures assess the quality of care on agreed 
upon topics for quality measurement specific to a quality program 
setting. These measures have gone through an extensive development 
process and validation testing with significant opportunity for public 
input. Adapting these existing quality measures to measure disparity 
through stratification maintains adherence to the measurement 
priorities identified through expert review and validation completed 
through measure development and testing. The application of measure 
stratification to these measures would also minimize any new reporting 
burden on healthcare providers.
     Prioritize Measures with Identified Disparity in Treatment 
or Outcomes for the Selected Social or Demographic Factor--Candidate 
measures for stratification should be supported by evidence of 
underlying healthcare disparities in the procedure, condition, or 
outcome being measured. A review of peer-reviewed research studies 
should be conducted to identify disparities related to treatment, 
procedure, or outcome associated with the measure, and should carefully 
consider both social risk factors and patient demographics. In 
addition, analysis of Medicare-specific data should be done to 
demonstrate evidence of disparity in care among the Medicare 
population. In addition, consideration should also be given to 
conditions that have highly disproportionate prevalence in certain 
populations.
     Prioritize Measures with Sufficient Sample Size to Allow 
for Reliable and Representative Comparisons--Sample size holds specific 
significance for statistical calculations; however, it holds additional 
importance in the context of disparity reporting. Candidate measures 
for stratification will need to have sufficient cohort sample size to 
ensure that reported results of the disparity calculation are reliable 
and representative of the healthcare provider's patient population. 
This may be challenging if cohorts with a given social risk factor are 
small.
    Carefully establishing reliability and representation standards for 
measure reporting is important for considering measures to stratify. 
Reliability, in this case, refers to the minimum case count needed to 
achieve reliable results. Metrics for reliability are used in non-
stratified quality measure reporting, such as when measures require a 
certain number of procedures for their rates to be considered reliable. 
The use of a reliability standard for disparity reporting will ensure 
consistently reliable results are calculated.
    Representation standards are also important and may involve 
requiring a minimum number or percent of healthcare providers or 
patients to be eligible to receive stratified results with reliable 
estimates before a measure is considered for disparity reporting. This 
requirement aims to ensure that meaningful comparisons can be made. As 
we noted previously, when only a

[[Page 28482]]

small proportion of healthcare providers can receive statistically 
significant results, it may not be prudent for quality programs to 
pursue stratified reporting for that particular measure. Doing so can 
create challenges when generalizing rates of disparity for conditions 
or procedures when only a small proportion of a healthcare provider's 
results are considered. If, for example, only 10 percent of healthcare 
providers can report results, results must be clearly presented to 
ensure they are not understood to represent disparity in care for the 
measurement taking place in all care settings, as shown in this 
example, where 90 percent of them would not be included in reporting.
    Quality programs may further consider measures for disparity 
reporting based on the size of the calculated disparity by prioritizing 
measures for stratification that show large differences in care between 
patient groups. Large differences in care for patients along social or 
demographic lines may indicate high potential that targeted initiatives 
could be effective. However, measures with disparities of smaller 
magnitude but with large cohorts affect many patients because they may 
have very large aggregate impacts on the national scale.
     Prioritize Outcome Measures and Measures of Access and 
Appropriateness of Care--Quality measurement in CMS programs often 
focus on outcomes of care, such as mortality or readmission. Outcomes 
measures remain a priority in the context of disparities measurement. 
However, measures that focus on access to care, when available, are 
also critical tools for addressing healthcare disparities. Measures 
that address healthcare access can counterbalance the risk of creating 
perverse incentives. If only differences in care between groups are 
measured, performance on a measure of disparity could be improved by 
limiting access to care for high-risk patients in the populations that 
are historically underserved or marginalized.
    To complement stratification of measures focused on clinical 
outcomes, quality programs may consider prioritizing measures with a 
focus on access to or the appropriateness of care. These measures, when 
reported in tandem with clinical outcomes, would provide a broader 
picture of care provided by a healthcare provider, illuminate potential 
drivers of performance, and highlight organizations that fail to 
address barriers in access to care for groups that have been 
historically marginalized. We acknowledge that the measurement of 
access and appropriateness of care is a growing field, and that there 
are currently a limited number of developed quality measures on these 
topics. However, as our ability to measure these facets of healthcare 
improves, we expect that they will be high priority for measure 
stratification.
4. Principles for Social Risk Factor and Demographic Data Selection and 
Use
    There are a wide array of non-clinical drivers of health known to 
impact patient outcomes, including social risk factors such as 
socioeconomic status, housing availability, and nutrition, as well as 
marked inequity in outcomes based on patient demographics such as race 
and ethnicity, being a member of a minority religious group, geographic 
location, sexual orientation and gender identity, religion, and 
disability status.729 730 731 732 733 734 735 736 The World 
Health Organization (WHO) defines social risk factors as ``non-medical 
factors that influence health outcomes. They are the conditions in 
which people are born, grow, work, live, and age, and the wider set of 
forces and systems shaping the conditions of daily life.'' \737\ These 
include factors such as income, education, job security, food security, 
housing, social inclusion and non-discrimination, access to affordable 
health services, and any others. Research has indicated that these 
social factors may have as much or more impact on health outcomes as 
clinical care itself.738 739 Additionally, differences in 
outcomes based on patient race and ethnicity have been identified as 
significant, persistent, and of high priority for CMS and other Federal 
agencies.\740\
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    \729\ Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission 
rates for Medicare beneficiaries by race and site of care. JAMA, 
305(7):675-681.
    \730\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and thirty-day outcomes after acute myocardial 
infarction, heart failure, and pneumonia: Retrospective cohort 
study. British Medical Journal, 346.
    \731\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and equity of care in U.S. hospitals. New England Journal of 
Medicine, 371(24):2298-2308.
    \732\ Polyakova, M., et al. (2021). Racial disparities in excess 
all-cause mortality during the early COVID-19 pandemic varied 
substantially across states. Health Affairs, 40(2): 307-316.
    \733\ Rural Health Research Gateway. (2018). Rural communities: 
Age, income, and health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \734\ HHS Office of Minority Health (2020). 2020 Update on the 
Action Plan to Reduce Racial and Ethnic Health Disparities. 
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \735\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-
19 vulnerability of transgender women with and without HIV infection 
in the Eastern and Southern U.S. medRxiv [Preprint]. 
2020.07.21.20159327. doi: 10.1101/2020.07.21.20159327. PMID: 
32743608; PMCID: PMC7386532.
    \736\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; S.B. Nadimpalli, et al., The Association between 
Discrimination and the Health of Sikh Asian Indians.
    \737\ World Health Organization. Social Determinants of Health. 
Available at: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1.
    \738\ Hood, C., Gennuso K., Swain G., Catlin B. (2016). County 
Health Rankings: Relationships Between Determinant Factors and 
Health Outcomes. Am J Prev Med. 50(2):129-135. doi:10.1016/
j.amepre.2015.08.024.
    \739\ Chepaitis, A.E., Bernacet, A., Kordomenos, C., Greene, 
A.M., Walsh, E.G. (2020). Addressing social determinants of health 
in demonstrations under the financial alignment initiative. RTI 
International. Available at: https://innovation.cms.gov/data-and-reports/2021/fai-sdoh-issue-brief.
    \740\ 86 FR 7009 (January 25, 2021). Executive Order on 
Advancing Racial Equity and Support for Underserved Communities 
Through the Federal Government. Available at: 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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    Identifying and prioritizing specific indicators of social risk or 
demographic variables to consider for stratified analyses and measure 
reporting can be challenging due to the large number of variables 
identified in the literature as potential risk factors for disparities 
in health care and poorer health outcomes. And yet, the limited 
availability of data for many self-reported social risk factors and 
demographic factors across the healthcare sector further complicates 
our ability to choose effective metrics to evaluate disparity.
    Disparity reporting in the Hospital IQR Program has focused on 
stratification by dual eligibility for Medicare and Medicaid. Dual 
eligibility has been used in this and other CMS quality programs as an 
indicator of financial risk, as the majority of Medicaid beneficiaries 
are eligible based on meeting thresholds for low patient income and/or 
assets. The use of dual eligibility 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).\741\ 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

[[Page 28483]]

predictors of poor health outcomes among those social risk factors that 
ASPE examined and tested.
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    \741\ Office of the Assistant Secretary for Planning and 
Evaluation. (2016). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
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    Financial risk is only one metric of social risk, and 
stratification of quality measures by additional social risk factors 
and demographics (such as race, ethnicity, language, religion, sexual 
orientation, and gender identity) or disability, is important to 
provide more granular information for healthcare providers to act upon. 
As we consider prioritizing and expanding the variables used for 
measure stratification, we will carefully consider both social risk 
factors and patient demographics as well as other variables associated 
with historic disadvantage in healthcare, such as disability status.
    As noted previously, a growing body of literature identifies the 
association between social risk factors and demographic variables with 
poorer health outcomes.742 743 744 While social risk factors 
and demographic variables are both associated with worse healthcare 
outcomes and experiences, they are distinct constructs, and should be 
identified, measured, and reported as such. Patient demographic 
variables such as race and ethnicity are often identified as indicators 
of social risk driven by the differences in care received by persons 
who belong to minority racial and ethnic groups. The disparity in 
outcomes can be attributed to many factors, including discrimination in 
the healthcare system, challenges accessing quality healthcare, and 
societal inequity in other factors connected to social risk. 
Attributing differences in outcomes to race may inappropriately place 
the driver of poorer health outcomes on the patient, rather than on 
structural factors, such as racism in society and the healthcare system 
that drive the provision of lower quality care.\745\ It is important, 
in identification of non-clinical drivers of health, to identify that 
race and ethnicity are not the social risk factor, but markers of 
exposure to other factors.
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    \742\ 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. Available at: 
https://www.nap.edu/catalog/21858/accounting-for-social-risk-factors-in-medicare-payment-identifying-social.
    \743\ Office of the Assistant Secretary For Planning and 
Evaluation. (2016). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
    \744\ Office of the Assistant Secretary For Planning and 
Evaluation. (2020). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
    \745\ Gee G.C., Ford C.L. (2011). Structural Racism and health 
inequities: Old Issues, New Directions. Du Bois Review: Social 
science research on race, 8(1), 115-132. Available at: https://doi.org/10.1017/S1742058X11000130.
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    In prioritizing among social risk factors and demographic 
variables, disability, and other markers of disadvantage for stratified 
reporting, we anticipate that each individual quality program would 
design an approach appropriate to their care setting. We strive to 
operationalize our programs consistently where possible to decrease the 
burden on healthcare providers, however, the deeply contextual nature 
of this type of reporting may require the development of an approach 
specific to the quality programs based on care setting, patient 
population, and data availability.
    The availability of data is a crucial consideration when examining 
data sources for use in stratified quality reporting. In many cases, 
the lack of available patient-reported data on patient social risk or 
demographic variables limits the ability to conduct disparity analyses. 
While improving the collection of patient-reported demographic 
information and information on social risk is an ongoing goal, other 
methods and data sources for estimating social risk (as described 
further in this section) could potentially fill in gaps in existing 
data sets, and could include area-based indicators or imputation 
techniques that use existing information about patient populations to 
estimate approximations about related population information. Each of 
these types of data sources have advantages and disadvantages.
    Patient-reported data are considered to be the gold standard for 
evaluating care for patients with social risk factors or who belong to 
certain demographic groups as this is an accurate and preferred way to 
attribute social risk.\746\ Currently, there are many efforts underway 
to further develop data standards for collection for self-reported 
patient social risk and demographic variables. Yet, given that national 
data sources of reliable, self-reported data are not yet available, we 
also intend to consider other options for social risk factor data. We 
note efforts to standardize the collection of demographic and social 
risk factor data include prior work done by both CMS and the Office of 
the National Coordinator for Health Information Technology (ONC) with 
Federal and private partners to better collect and leverage data on 
social risk. This work includes: (1) The development of an Inventory of 
Resources for Standardized Demographic and Language Data Collection; 
747 748 (2) CMS work to support specialized International 
Classification of Diseases, (ICD) 10th Revision, Clinical Modification 
(ICD-10-CM) codes for describing the socioeconomic, cultural, and 
environmental determinants of health; \749\ and (3) the CMS sponsorship 
of several initiatives to statistically estimate race and ethnicity 
information when it is absent.750 751
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    \746\ Jarr[iacute]n OF, Nyandege AN, Grafova IB, Dong X, Lin H. 
(2020). Validity of race and ethnicity codes in Medicare 
administrative data compared with gold-standard self-reported race 
collected during routine home health care visits. Med Care, 
58(1):e1-e8. doi: 10.1097/MLR.0000000000001216. PMID: 31688554; 
PMCID: PMC6904433.
    \747\ Centers for Medicare & Medicaid Services. (2020). Building 
an Organizational Response to Health Disparities Inventory of 
Resources for Standardized Demographic and Language Data Collection. 
Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
    \748\ The Office of the National Coordinator for Health 
Information Technology (ONC). Health IT Standards Bulletin. 
HealthIT.gov: 2021. URL: https://www.healthit.gov/sites/default/files/page/2021-05/Standards_Bulletin_2021-2.pdf.
    \749\ Centers for Medicare & Medicaid Services (2019). 
Utilization of Z Codes for Social Determinants of Health among 
Medicare Fee-for-Service Beneficiaries, 2019. Available at: https://www.cms.gov/files/document/z-codes-data-highlight.pdf.
    \750\ Centers for Medicare & Medicaid Services (2021). A New 
Method to Improve measurement of Race-and-Ethnicity in CMS Data and 
Applications to Inequities in Quality of Care. Available at: https://www.cms.gov/files/document/new-method-improve-measurement-race-and-ethnicity-cms-data-and-applications-inequalities-quality.pptx.
    \751\ Eicheldinger, C., & Bonito, A. (2008). More accurate 
racial and ethnic codes for Medicare administrative data. Health 
Care Financing Review, 29(3), 27-42.
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    One example of improving sources of data come from the certified 
health IT utilized by hospitals to meet the requirements of the 
Promoting Interoperability program. This includes health IT certified 
to the ``demographics'' certification criterion (45 CFR 170.315(a)(5)), 
which provides for the capability to record race and ethnicity at a 
detailed level of granularity consistent with the Centers for Disease 
Control and Prevention's (CDC) Race & Ethnicity--CDC code system. This 
code system includes more than 900 concepts for race and ethnicity, 
which gives patients very specific options for self-identifying their 
demographic information. The 900 concepts are organized in a way to 
eventually ``roll up'' to the Office of Management and Budget's (OMB) 
minimum categories for race and

[[Page 28484]]

ethnicity,\752\ which can support aggregation and reporting needs when 
the OMB standard is necessary. It also includes social, psychological, 
and behavioral standards in health IT certification criteria (80 FR 
62601), 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. The Agency for 
Healthcare Research and Quality (AHRQ) has also worked with the Gravity 
Project which is a multistakeholder effort to expand capabilities to 
capture additional social determinants of health data elements, to 
identify and harmonize social risk factor data for interoperable 
electronic health information exchange for electronic health record 
(EHR) fields,\753\ and make recommendations on the expansion of the 
ICD-10 (International Classification of Diseases, 10th Revision) Z-
codes, the alphanumeric codes used worldwide to represent diagnoses, to 
include additional social risk diagnoses.\754\
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    \752\ 62 FR 58782 (October 30, 1997). Revisions to the Standards 
for the Classification of Federal Data on Race and Ethnicity. 
Available at: https://www.federalregister.gov/documents/1997/10/30/97-28653/revisions-to-the-standards-for-the-classification-of-federal-data-on-race-and-ethnicity.
    \753\ Gravity Project. Available at: https://thegravityproject.net/.
    \754\ Centers for Medicare and Medicaid Services. (2020). Z 
Codes Utilization among Medicare Fee-for-Service (FFS) Beneficiaries 
in 2017. Available at: https://www.cms.gov/files/document/cms-omh-january2020-zcode-data-highlightpdf.pdf.
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    We expect to continue evaluating patient-reported sources of social 
risk and demographic information. We are also considering three sources 
of social risk and demographic data that would allow us to report 
stratified measure results:
     Billing and Administrative Data--The majority of quality 
measurement tools used in our quality programs focus on utilizing 
existing claims and administrative data for Medicare beneficiaries. 
Using these existing data to assess disparity, for example by the use 
of dual enrollment for Medicare and Medicaid, allows for high impact 
analyses with negligible healthcare provider burden. There are, 
however, limitations in these data's usability for stratification 
analysis. CMS's current administrative race and ethnicity data have 
been shown to have historical inaccuracies due to limited collection 
classifications and attribution techniques, and are generally 
considered not to be accurate enough for stratification and disparity 
analyses.\755\ International Classification of Diseases,10th Revision 
(ICD-10) codes for socioeconomic and psychosocial circumstances (``Z 
codes'' Z55 to Z65) represent an important opportunity to document 
patient-level social risk factors in Medicare beneficiaries, however, 
they are rarely used in clinical practice, limiting their usability in 
disparities measurement.\756\ If the collection of social risk factor 
data improves in administrative data, we will continue to evaluate its 
applicability for stratified reporting in the future.
---------------------------------------------------------------------------

    \755\ Jarr[iacute]n OF, Nyandege AN, Grafova IB, Dong X, Lin H. 
(2020). Validity of race and ethnicity codes in Medicare 
administrative data compared with gold-standard self-reported race 
collected during routine home health care visits. Med Care, 
58(1):e1-e8. doi: 10.1097/MLR.0000000000001216. PMID: 31688554; 
PMCID: PMC6904433.
    \756\ Centers for Medicare & Medicaid Services, Office of 
Minority Health. (2021). Utilization of Z codes for social 
determinants of health among Medicare fee-for-service beneficiaries, 
2019. Available at: https://www.cms.gov/files/document/z-codes-data-highlight.pdf.
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    Dual eligibility is a widely used proxy for low socioeconomic 
status and is an exception to the previously discussed limitations, 
making it an effective indicator for worse outcomes due to low 
socioeconomic status. The use of dual eligibility in social risk factor 
analyses was supported by ASPE's First and Second Reports to 
Congress.757 758 These reports found that in the context of 
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.
---------------------------------------------------------------------------

    \757\ Office of the Assistant Secretary for Planning and 
Evaluation. (2016). Social risk factors and performance under 
Medicare's value-based purchasing programs. Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
    \758\ Office of the Assistant Secretary For Planning and 
Evaluation. (2020). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
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     Area-based Indicators of Social Risk Information and 
Patient Demographics--Area-based indicators pool area-level information 
to create approximations of patient risk or describe the neighborhood 
or context that a patient resides in. Popular among them are the use of 
the American Community Survey (ACS), which is commonly used to 
attribute social risk to populations at the ZIP code or Federal 
Information Processing Standards (FIPS) county level. Several indices, 
such as the Agency for Healthcare Research and Quality (AHRQ) 
Socioeconomic Status (SES) Index,\759\ Centers for Disease Control and 
Prevention/Agency for Toxic Substances and Disease Registry Social 
Vulnerability Index (CDC/ATSDR SVI),\760\ and Health Resources and 
Services Administration Area Deprivation Index,\761\ combine multiple 
indicators of social risk into a single score which can be used to 
provide multifaceted contextual information about an area and may be 
considered as an efficient way to stratify measures that include many 
social risk factors.
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    \759\ Bonito A., Bann C., Eicheldinger C., Carpenter L. (2008). 
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 & 
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.
    \760\ Flanagan, B.E., Gregory, E.W., Hallisey, E.J., Heitgerd, 
J.L., Lewis, B. (2011). A social vulnerability index for disaster 
management. Journal of Homeland Security and Emergency Management, 
8(1). Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/img/pdf/Flanagan_2011_SVIforDisasterManagement-508.pdf.
    \761\ Center for Health Disparities Research. About the 
Neighborhood Atlas. Available at: https://www.neighborhoodatlas.medicine.wisc.edu/.
---------------------------------------------------------------------------

     Imputed Sources of Social Risk Information and Patient 
Demographics--Imputed data sources use statistical techniques to 
estimate patient-reported factors, including race and ethnicity. In the 
case of race and ethnicity, indirect estimation improves upon imperfect 
and incomplete data by drawing on information about a person's name and 
address and the linkage of those variables to race and ethnicity. One 
such tool is the Medicare Bayesian Improved Surname Geocoding (MBISG) 
method (currently in version 2.1), which combines information from 
administrative data, surname, and residential location to estimate 
patient race and ethnicity.\762\ We have customized this tool for the 
Medicare population to improve our existing administrative data on race 
and ethnicity.
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    \762\ Haas A., Elliott M.N., Dembosky J.W., Adams J.L., Wilson-
Frederick S.M., Mallett J.S. et al. (2019). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Serv Res, 54(1):13-23. doi: 10.1111/1475-
6773.13099. Epub 2018 Dec 3. PMID: 30506674; PMCID: PMC6338295. 
Available at: https://pubmed.ncbi.nlm.nih.gov/30506674/.
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    The MBISG 2.1 method does not assign a single race and ethnicity to 
an individual; instead, it generates a set of six probabilities, each 
estimating how the individual would self-identify if provided with a 
set of racial and ethnic groups to choose from including: American 
Indian or Alaska Native, Asian or Pacific Islander, Black,

[[Page 28485]]

Hispanic, Multiracial, and White. In no case would the estimated 
probability be used for making inferences about a specific beneficiary; 
only self-reported data on race and ethnicity should be used for that 
purpose. However, in aggregate, these results can provide insight and 
accurate information at the population level, such as the patients of a 
given hospital, or the members of a given plan. MBISG 2.1 is currently 
used by our Office of Minority Health (OMH) to undertake various 
analyses, such as comparing scores on clinical quality of care measures 
from the Healthcare Effectiveness Database and Information Set (HEDIS) 
by race and ethnicity for Medicare Part C/D health plans, and in 
developing a Health Equity Summary Score (HESS) for Medicare Advantage 
(MA) health plans.\763\
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    \763\ Agniel D., Martino S.C., Burkhart Q., Hambarsoomian K., 
Orr N., Beckett M.K, et al. (2021). Incentivizing excellent care to 
at-risk groups with a health equity summary score. J Gen Intern Med, 
36(7):1847-1857. doi: 10.1007/s11606-019-05473-x. Epub 2019 Nov 11. 
PMID: 31713030; PMCID: PMC8298664. Available at: https://pubmed.ncbi.nlm.nih.gov/31713030/.
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    While the use of area-based indicators and imputed data sources are 
not meant to replace efforts to improve patient-level data collection, 
we are considering how they might be used to begin population-level 
disparity reporting of stratified measure results while being 
conscientious about data limitations.
    Imputed data sources, particularly when used to identify patient 
populations for measurement, must be carefully evaluated for their 
potential to negatively affect the populations being studied. For this 
reason, imputed data sources should only be considered after a 
significant validation study has been completed, including evaluation 
by key stakeholders for face validity, and any calculations that 
incorporate these methods should be continuously evaluated for the 
accuracy of their results and the necessity of their use. While neither 
imputed nor area-level geographic data should be considered a 
replacement for improved data collection, researchers have found their 
use to be a simple and cost-efficient way to make general estimations 
of social risk at a community level.\764\ In place of patient-level 
information when it is not available, the combination of several 
sources of imputed or area-level data can provide actionable 
estimations of social risk of a population.
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    \764\ Bi, Q., He, F., Konty, K., Gould, L. H., Immerwahr, S., & 
Levanon Seligson, A. (2020). ZIP code-level estimates from a local 
health survey: Added value and limitations. Journal of Urban Health: 
Bulletin of the New York Academy of Medicine, 97(4), 561-567.
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5. Identification of Meaningful Performance Differences
    In examining potential ways to report healthcare disparity data, 
that is, the results of quality measure stratification, we expect to 
consider different approaches to identifying meaningful differences in 
performance. Stratified results can be presented in several ways to 
describe to providers how well or poorly they are performing, or how 
they perform when compared to other care facilities. For this reason, 
it is important to identify how best to present meaningful differences 
in performance for measures of disparity reporting. While we aim to use 
standardized approaches where possible, we also expect that decisions 
about how to identify meaningful differences in performance would 
ultimately be tailored to each individual program. We welcome feedback 
on the benefits and limitations of the possible disparity reporting 
approaches we have described in this RFI.
     Statistical Differences--When aiming to examine 
differences in disparities results among healthcare providers, the use 
of statistical testing can be helpful. There are many statistical 
approaches that can be used to reliably group results, such as using 
confidence intervals, creating cut points based on standard deviations, 
or using a clustering algorithm. Importantly, these approaches may 
result in groupings that are statistically different, but not 
meaningfully different depending on the distribution of results.
     Rank Ordering and Percentiles--Ordering healthcare 
providers in a ranked system is another option for reporting disparity 
results in a meaningful way. In this system, healthcare providers could 
be ranked based on their performance on disparity measures to quickly 
allow them to compare their performance to other similar healthcare 
providers. We may consider using an ordered system to report healthcare 
provider results by categorizing healthcare providers into groups, for 
example, into quintile or decile groups. This approach works well as a 
way for healthcare providers to easily compare their own performance 
against others; however, a potential drawback is that it does not 
identify the overall magnitude of disparity. For example, if a measure 
shows large disparity in care for patients based on a given factor, and 
that degree of disparity has very little variation between healthcare 
providers, the difference between the top and bottom ranked healthcare 
providers would be very small even if the overall disparity is large.
     Threshold Approach--A categorization system could also be 
considered for reporting disparity results. In this system, healthcare 
providers could be grouped based on their performance using defined 
metrics, such as fixed intervals of results of disparity measures, 
indicating different levels of performance. Using a categorized system 
may be more easily understood by stakeholders by giving a clear 
indication that outcomes are not considered equal. However, this method 
does not convey the degree of disparity between healthcare providers or 
the potential for improvement based on the performance of other 
healthcare providers. Furthermore, it requires a determination of what 
is deemed `acceptable disparity' when developing categories.
     Benchmarking--Benchmarking, or comparing individual 
results to, for example, state or national averages, is another 
potential reporting strategy. This type of approach could be done, 
especially in combination with a ranked or threshold approach, to give 
healthcare providers more information about how they compare to the 
average care for a patient group.
    Another consideration for each of these approaches is grouping 
similar care settings together for comparison through a peer grouping 
step, especially if a ranked system is used to compare healthcare 
providers. Some stakeholders have argued that comparisons between 
healthcare providers have limited meaning if the healthcare providers 
are not similar, and that peer grouping would improve their ability to 
interpret results. Overall, the value of peer grouping must be weighed 
against the potential to set different standards of meaningful 
disparity among different care settings.
6. Guiding Principles for Reporting Disparity Results
    Confidential reporting for a short period that is not followed by 
public reporting of the same measure data is one approach we have used 
for newly adopted measures in a CMS quality program to give healthcare 
providers an opportunity to become more familiar with calculation 
methods and to begin improvement activities before their measure 
results are publicly reported. Providing early results to healthcare 
providers is an important way to provide healthcare providers the 
information they need to design impactful strategies to reduce 
disparity. Public reporting is a statutory requirement in all of our 
quality

[[Page 28486]]

programs. Public reporting provides all stakeholders with important 
information on healthcare provider quality, and in turn, relies on 
market forces to incentivize healthcare providers to improve and become 
more competitive in their markets.
    Payment accountability for performance is also statutorily required 
in some of our quality programs. Payment accountability refers to tying 
payment to the results of quality measure performance, and in general 
rewards better performance with higher payment rates. Payment 
accountability allows us to reward healthcare providers for having low 
disparity rates and performing well for vulnerable patient groups.
    We are exploring whether it would be prudent to first 
confidentially report all stratified measure results, where adopted 
into a quality reporting program, to give healthcare providers an 
opportunity to understand those results so they can begin to implement 
programs to reduce disparities before we report the results publicly.
    We also believe it is important to report stratified measure data 
alongside overall measure results. Review of both overall measure 
results along with stratified results can illuminate greater levels of 
detail about quality of care for subgroups of patients, providing 
important information to drive quality improvement. Unstratified 
quality measure results address general differences in quality of care 
between healthcare providers and promote improvement for all patients, 
but unless stratified results are available, it may be unclear whether 
there are subgroups of patients that would benefit most from targeted 
quality improvement initiatives. Notably, even if overall quality 
measure scores were to improve, without identifying and measuring 
differences in outcomes between groups of patients, it could be 
impossible to track progress in reducing disparity between patients 
with and without heightened risk of poor outcomes due to social 
factors.
7. Solicitation of Comments
    The goal of this RFI is to describe key considerations in 
determining how to develop future policies around the use of measure 
stratification as one quality measurement tool to address healthcare 
disparities and advance health equity across our quality programs. This 
is important as a means of setting priorities and expectations for the 
use of stratified measure results.
    We invite general comments on the principles and approaches listed 
previously, as well as additional thoughts about disparity measurement 
or stratification guidelines suitable for overarching consideration 
across our quality programs. Specifically, we invite comment on:
     Overarching goals for measuring disparity that should be 
considered across CMS quality programs, including the importance of 
pairing stratified results with overall measure results to evaluate 
gaps in care among groups of patients attributed to a given healthcare 
provider and comparison of care for a subgroup of patients across 
healthcare providers.
     Principles to consider for prioritization of measures for 
disparity reporting, including prioritizing stratification for: Valid 
clinical quality measures; measures with established disparities in 
care; measures that have adequate sample size and representation among 
healthcare providers; and, measures that consider access and 
appropriateness of care.
     Principles to be considered for the selection of social 
risk factors and demographic data for use measuring disparities, 
include the importance of identifying new social risk factor and 
demographic variables to use to stratify measures. We also seek comment 
on the use of imputed and area-based social risk and demographic 
indicators for measure stratification when patient reported data are 
unavailable.
     Preferred ways that meaningful differences in disparity 
results can be identified or should be considered.
     Guiding principles for the use and application of the 
results of disparity measurement such as providing confidential 
reporting initially

C. Continuing To Advance to Digital Quality Measurement and the Use of 
Fast Healthcare Interoperability Resources (FHIR) in Hospital Quality 
Programs--Request for Information

    In the FY 2022 IPPS/LTCH PPS final rule, we stated the aim to move 
fully to digital quality measurement in CMS quality reporting and 
value-based purchasing programs (86 FR 45342). As part of this 
modernization of our quality measurement enterprise, we are issuing 
this RFI to gather broad public input on the 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 notice-and-comment 
rulemaking. This RFI contains five parts:
     Background. This part provides an overview of our goals 
and strategies to achieve digital quality measurement, and notes input 
and learnings relevant to these goals and strategies.
     Refined definition of Digital Quality Measures (dQMs). 
This part outlines potential revisions for a future definition for 
dQMs.
     Data Standardization Activities to Leverage and Advance 
Standards for Digital Data. This part discusses data standardization 
strategies and potential venues for advancing data standardization.
     Approaches to Achieve FHIR[supreg] eCQM Reporting. This 
part describes activities we are undertaking and considering to achieve 
FHIR-based electronic clinical quality measure (eCQM) reporting (for 
example, via FHIR APIs) as our initial implementation of dQMs.
     Solicitation of Comments. This part lists all requests for 
input included in the sections of this RFI.
1. Background
    In the FY 2022 IPPS/LTCH PPS final rule, we noted the continued 
focus on use of digital data and advancements in technology and 
technical standards to improve interoperability of healthcare data 
which creates opportunity to significantly improve our quality 
measurement systems (86 FR 45342). In a learning health system, 
standardized and interoperable digital data from a single point of 
collection can support multiple use cases, including quality 
measurement, quality improvement efforts, clinical decision support, 
research, and public health. We believe data used for quality 
measurement, as well as these other use cases, should be a seamless 
outgrowth of data generation from routine workflows. Data sharing 
should be standards-based to maximize interoperability, minimize 
burden, and facilitate the development and use of common tooling across 
use cases. This approach supports data analysis, rapid-cycle feedback, 
and quality measurement that are aligned for continuous improvement in 
patient-centered care.
    We are continuing to define how we can leverage existing policy to 
transform all CMS quality measurement to digital reporting, such as 
policy finalized in the ONC 21st Century Cures Act final rule (85 FR 
25642). In that rule, ONC finalized a ``Standardized API for Patient 
and Population Services'' certification criterion (45 CFR 
170.315(g)(10)) for certified health information technology (IT) 
requiring the use of FHIR Release 4 and several other implementation 
specifications. Health IT certified to this criterion will offer single 
patient and multiple patient services that can be accessed by third

[[Page 28487]]

party applications (85 FR 25742). The ONC 21st Century Cures Act final 
rule (85 FR 25642) also required health IT developers to update their 
certified health IT to support the United States Core Data for 
Interoperability (USCDI) standard, Version 1.\765\ By aligning 
technology requirements for payers, healthcare providers, and health IT 
developers, HHS can advance an interoperable health IT infrastructure 
that ensures providers and patients have access to health data when and 
where it is needed.
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    \765\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
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    In the FY 2022 IPPS/LTCH PPS final rule, we outlined actions in 
four areas to transition to digital quality measures: (1) Leverage and 
advance standards for digital data and obtain all electronic health 
record (EHR) data required for quality measures via provider FHIR-based 
application programming interfaces (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 (86 FR 45342). The actions are further 
described in CMS' Digital Quality Measurement Strategic Roadmap 
available at https://ecqi.healthit.gov/dQM. In this RFI, we focus on 
data standardization activities related to leveraging and advancing 
standards for digital data and approaches to transition to FHIR eCQM 
reporting in the future, as initial steps in our transition to digital 
quality measurement.
    In the FY 2022 IPPS/LTCH PPS final rule, we also stated our goal of 
moving to digital quality measurement for all CMS quality reporting and 
value-based purchasing programs (86 FR 45342). We further clarify that 
we plan to transition incrementally, beginning with the uptake of FHIR 
API technology and shifting to eCQM reporting using FHIR standards as 
described subsequently in section IX.C.4. of the preamble of this 
proposed rule. We aim to achieve a quality measurement system fully 
based on digital measures. The goals of a fully digital measurement 
system include: Reduced burden of reporting; provision of multi-
dimensional data in a timely fashion, rapid feedback, and transparent 
reporting of quality measures; digital measures leveraged for advanced 
analytics to define, measure, and predict key quality issues; and 
quality measures that support development of a learning health system, 
which uses key data that are also used for care, quality improvement, 
public health, research, etc.
2. Refined Definition of Digital Quality Measures (dQMs)
    In the FY 2022 IPPS/LTCH PPS final rule, we sought to define a dQM 
as software that processes digital data to produce a measure score or 
measure scores (86 FR 45342). Based on feedback regarding confusion by 
the term ``software,'' we further clarify that dQMs are quality 
measures, organized as self-contained measure specifications and code 
packages, that use one or more sources of health information that is 
captured and can be transmitted electronically via interoperable 
systems. We continue to note data sources for dQMs may include 
administrative systems, electronically submitted clinical assessment 
data, case management systems, EHRs, laboratory systems, prescription 
drug monitoring programs (PDMPs), instruments (for example, medical 
devices and wearable devices), patient portals or applications (for 
example, for collection of patient-generated data such as a home blood 
pressure monitor, or patient-reported health data), health information 
exchanges (HIEs) or registries, and other sources. We are currently 
considering how eCQMs, which use EHR data, can be refined or repackaged 
to fit within the dQM umbrella. While eCQMs meet the definition for 
dQMs in many respects, limitations in data standards, requirements, and 
technology have limited their interoperability. In the current state, 
there are multiple standards that must be supported (for example, 
Health Quality Measurement Format (HQMF) \766\ and Quality Reporting 
Document Architecture (QRDA) \767\) for eCQM data collection and 
reporting. Mapping EHR data can be challenging and burdensome for 
providers as there is often novel data collection occurring to support 
quality measurement. For example, eCQMs require steps to map data 
elements from the EHR to the appropriate format. Future dQMs would 
leverage interoperability standards to decrease mapping burden and 
align standards for quality measurement with interoperability standards 
used in other healthcare exchange methods.
---------------------------------------------------------------------------

    \766\ https://www.hl7.org/implement/standards/product_brief.cfm?product_id=97.
    \767\ https://ecqi.healthit.gov/qrda.
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    We seek comment on this refined definition of dQMs and feedback on 
potential considerations or challenges related to non-EHR data sources.
3. Data Standardization Activities To Leverage and Advance Standards 
for Digital Data
    As noted in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45342), we 
are considering implementing eCQM quality reporting via FHIR-based APIs 
based on standardized, interoperable data. Advancing data 
standardization is a critical step for this implementation, and for 
long-term digital measurement strategies. Utilizing standardized data 
for EHR-based measurement (based on the FHIR standard) and aligning 
where possible with other interoperability requirements can reduce the 
data collection burden incurred by providers for the purpose of 
reporting quality measures and supports achieving the goals of 
transitioning to a fully digital quality measurement system identified 
in section IX.C.1. of the preamble of this proposed rule, including 
provision of timely feedback, leveraging the same data for multiple use 
cases, and contributing to a learning health system.
    We intend to utilize standardized data for quality measurement as 
one-use case of digital data in a learning health system. In a learning 
health system, standardized digital data can support multiple use 
cases, including quality measurement, quality improvement efforts, 
clinical decision support, research, and public health. We believe that 
standardization across data elements and data models is necessary to 
ensure data are accessible across use cases and enable the transmission 
of data through each stage of the health system's learning process. 
Standardized data and FHIR APIs are important for advancing 
interoperability; the goal is for data to be sent and received via 
trusted exchanges, and for patients to have access to their data. 
Operations activities (for example, prior authorization) are also 
dependent on standardized, interoperable data. Additionally, 
standardization is necessary across implementation guides, or rules for 
how a particular interoperability standard should be used,\768\ and 
across value sets that organize the specific terminologies and codes 
that define clinical concepts.\769\
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    \768\ Resource Implementation Guide--Content. Available at: 
https://www.hl7.org/fhir/implementationguide.html.
    \769\ National Library of Medicine, Value Set Authority Center. 
Available at: https://vsac.nlm.nih.gov/.
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    Commenters on the RFI in the FY 2022 IPPS/LTCH PPS proposed rule 
encouraged the use of data elements for quality measurement that are 
consistent

[[Page 28488]]

with ONC's USCDI standard,\770\ where possible. We agree with this 
approach. To advance the use of standardized data, models, 
implementation guides, and value sets in quality measurement, we 
continue to focus on leveraging the interoperability data requirements 
for standardized APIs in certified health IT, set by the ONC 21st 
Century Cures Act final rule and any future updates made in rulemaking, 
as a vehicle to support modernization of CMS quality measure reporting. 
These API requirements are being implemented as part of a series of 
updates to certified health IT (85 FR 84825), and include availability 
of data included in the USCDI via standards-based APIs. In the CY 2021 
Physician Fee Schedule final rule, we finalized that eligible 
clinicians and eligible hospitals and CAHs participating in the Merit-
based Incentives Payment System (MIPS) and the Medicare Promoting 
Interoperability Program, respectively, must transition to use of 
certified technology updated consistent with the 2015 Edition Cures 
Update by 2023 (85 FR 84825). We aim to align with these standardized 
data requirements as the basis for data used in quality measurement.
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    \770\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
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    We are collaborating with Federal agencies to define and prioritize 
additional data standardization needs and develop consensus with 
Federal partners on recommendations for future versions of the USCDI. 
We are also directly collaborating with ONC to build requirements to 
support data standardization and alignment with requirements for 
quality measurement. ONC recently launched the USCDI+ initiative 
focused on supporting identification and establishment of domain 
specific datasets that build on the core USCDI foundation.\771\ A 
USCDI+ quality measurement domain currently being explored would 
support defining additional data specifications for quality measurement 
that harmonize, where possible, with other Federal agency data needs 
and inform supplemental standards necessary to support quality 
measurement.
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    \771\ USCDI+. Available at: https://www.healthit.gov/topic/interoperability/uscdi-plus.
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    We also received feedback on the RFI in the FY 2022 IPPS/LTCH PPS 
proposed rule that the use of Health Level Seven (HL7[supreg]) 
Implementation Guides should be foundational to FHIR measure reporting. 
To advance implementation of standardized data, we continue to 
collaborate with consensus standards-setting bodies such as HL7. We are 
considering how best to leverage existing implementation guides that 
are routinely updated and maintained by HL7 to define data standards 
and exchange mechanisms for FHIR-based dQMs, in a fashion that supports 
the learning health system and alignment across use cases, including 
the following existing HL7 Implementation Guides:
     US Core Implementation Guide; \772\
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    \772\ HL7 FHIR US Core Implementation Guide. Available at: 
http://hl7.org/fhir/us/core/.
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     Quality Improvement Core (QI Core) Implementation Guide; 
\773\
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    \773\ HL7 FHIR QI Core Implementation Guide. Available at: 
http://hl7.org/fhir/us/qicore/.
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     Data Exchange for Quality Measures (DEQM) Implementation 
Guide; \774\ and
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    \774\ HL7 Data Exchange For Quality Measures. Available at: 
http://hl7.org/fhir/us/davinci-deqm/.
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     Quality Measure (QM) Implementation Guide.\775\
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    \775\ HL7 Quality Measure Implementation Guide. Available at: 
http://hl7.org/fhir/us/cqfmeasures/.
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    We are also considering what, if any, additional CMS-specific 
implementation guides may be necessary to support future digital 
quality measurement such as guidance on aggregation mechanisms for 
reporting.
    We recognize the importance of considering how implementation 
guides used across quality measurement and other use cases (for 
example, public health reporting, clinical decision support) work 
together to support a learning health system. For example, the Clinical 
Guidelines (CPG) Implementation Guide \776\ connects computable 
guidelines, clinical decision support, quality reporting, and case 
reporting. The mechanisms for reporting across use cases are also 
critical to consider, as each time a different mechanism for reporting 
is needed across different use cases, it creates more burden. We are 
collaborating closely with Federal partners, such as the Centers for 
Disease Control and Prevention (CDC), to align where possible.
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    \776\ HL7 FHIR Clinical Guidelines Implementation Guide. 
Available at: http://hl7.org/fhir/uv/cpg/.
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    We believe developing appropriately defined implementation guides 
will be a key component of supporting standardized FHIR APIs that 
enable access to standardized data elements for particular use cases, 
such as quality measurement.
    We seek comment on the specific Implementation Guides noted 
previously, additional Implementation Guides we should consider, and 
other data and reporting components (for example, data vocabulary/
terminology, alignment with other types of reporting) where 
standardization should be considered to advance data standardization 
for a learning health system.
4. Approaches To Achieve FHIR eCQM Reporting
    We previously noted in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45342) activities we are conducting to begin structuring and reporting 
eCQMs using FHIR. eCQMs are a subset of dQMs. We consider the 
transition to FHIR-based eCQM reporting the first step to dQM 
reporting, and a potential model for how future digital reporting can 
occur.
    To support the transition, we continue to undertake and consider 
activities necessary for reporting of FHIR-based eCQMs and future dQMs:
     In the near term, we plan to continue to convert current 
Quality Data Model (QDM)-based eCQMs to the FHIR standard and test the 
implementation of measures respecified to FHIR and submission of data 
elements represented in FHIR through ongoing HL7 Connectathons.
     In the near term, we also plan to develop a unified CMS 
FHIR receiving system. This system would allow for a singular point of 
data receipt to be used for quality reporting requirements, and 
modernization of programmatic data receiving systems to leverage 
opportunities related to digital data.
     We are committed to working with implementers and partners 
to optimize interoperable data exchange to support FHIR-based eCQM 
reporting (for example, via FHIR APIs) and eventually other digital 
quality measures, while ensuring solutions and implementation that 
require patients to engage with technology also support health equity.
     In the near term, we plan to identify opportunities for 
the public to provide feedback on FHIR-based measure specifications 
prior to implementation, such as during measure development/conversion 
activities.
     We also plan to identify opportunities for collaboration 
with vendors and implementers via systems testing of FHIR-based eCQM 
reporting to ensure involvement in systems development.
     Finally, we are exploring venues for continued feedback on 
CMS future measurement direction and data aggregation approaches in 
anticipation of FHIR-based API reporting of eCQMs.
     To support both near term FHIR-based eCQMs and other 
future dQMs, as noted in section IX.C.3., we intend to continue 
engaging with standards development organizations to advance and 
maintain implementation guides to support the FHIR standard and API 
reporting of quality measures.

[[Page 28489]]

     We also anticipate that prior to the implementation of any 
mandatory FHIR-based eCQM reporting requirements within our quality 
programs, it would be necessary to undertake voluntary reporting of 
FHIR-based eCQMs to allow time to learn and enhance systems and 
processes, both internally and among providers and vendors.
    We also continue to consider how best to leverage the FHIR API 
technology implemented to meet ONC's interoperability requirements to 
access and electronically transmit interoperable data for quality 
measurement. Based on feedback on the FY 2022 IPPS/LTCH PPS proposed 
rule RFI, many supported the use of FHIR APIs, while others expressed 
concern around infrastructure readiness. We continue to explore how to 
leverage FHIR APIs to decrease reporting burden and support implementor 
readiness. We seek comment on approaches to optimize data flows for 
quality measurement to retrieve data from EHRs via FHIR APIs, and to 
combine data needed for measure score calculation for measures that 
require aggregating data across multiple providers (for example, risk-
adjusted outcome measures) and multiple data sources (for example, 
hybrid claims-EHR measures). We are interested in data flows that 
support using the same data for measurement and to provide feedback to 
providers at multiple levels of accountability, such as at the 
individual clinician, group, accountable care organization and health 
plan levels, as are used for patient care and other use cases (for 
example public health reporting).
    We seek comment on additional venues to engage with implementors 
during the transition to digital quality measurement, and other 
critical considerations during the transition. We also seek comment on 
data flow options to support FHIR-based eCQM reporting.
5. Solicitation of Comments
    As noted previously, we seek input on the following:
     Refined potential future Definition of dQMs. We are 
seeking feedback on the following as described in section IX.C.2. of 
the preamble of this proposed rule:
    ++ Do you have feedback on the potential refined definition of 
digital quality measures (dQMs)?
    ++ Do you have feedback on potential considerations or challenges 
related to non-EHR data sources?
     Data Standardization Activities to Leverage and Advance 
Standards for Digital Data. We are seeking feedback on the following as 
described in section IX.C.3 of the preamble of this proposed rule:
    ++ Do you have feedback on the specific implementation guides we 
are considering, additional FHIR implementation guides we should 
consider, or other data and reporting components where standardization 
should be considered to advance data standardization for a learning 
health system?
     Approaches to Achieve FHIR eCQM Reporting. We are seeking 
feedback on the following as described in section IX.C.4. of the 
preamble of this proposed rule:
    ++ Are there additional venues to engage with implementors during 
the transition to digital quality measurement?
    ++ What data flow options should we consider for FHIR-based eCQM 
reporting, including retrieving data from EHRs via FHIR APIs and other 
mechanisms?
    ++ Are there other critical considerations during the transition?

D. Advancing the Trusted Exchange Framework and Common Agreement--
Request for Information

    Section 4003(b) of the 21st Century Cures Act (Pub. L. 114-255), 
enacted in 2016, amended section 3001(c) of the Public Health Service 
Act (42 U.S.C. 300jj-11(c)), and required HHS to take steps to advance 
interoperability for the purposes of ensuring full network-to-network 
exchange of health information. Specifically, Congress directed the 
National Coordinator to ``develop or support a trusted exchange 
framework, including a common agreement among health information 
networks nationally.'' Since the enactment of the 21st Century Cures 
Act, HHS has pursued development of a Trusted Exchange Framework and 
Common Agreement (TEFCA). ONC's goals for TEFCA are as follows:
    Goal 1: Establish a universal policy and technical floor for 
nationwide interoperability.
    Goal 2: Simplify connectivity for organizations to securely 
exchange information to improve patient care, enhance the welfare of 
populations, and generate health care value.
    Goal 3: Enable individuals to gather their health care 
information.\777\
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    \777\ See https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
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    On January 18, 2022, ONC announced a significant TEFCA milestone by 
releasing the Trusted Exchange Framework \778\ and Common Agreement 
Version 1.\779\ The Trusted Exchange Framework is a set of non-binding 
principles for health information exchange, and the Common Agreement 
for Nationwide Health Information Interoperability Version 1 (also 
referred to as Common Agreement) is a contract that advances those 
principles. The Common Agreement and the incorporated by reference 
Qualified Health Information Network (QHIN) Technical Framework Version 
1 (QTF) \780\ establish the technical infrastructure model and 
governing approach for different health information networks and their 
users to securely share clinical information with each other, all under 
commonly agreed to terms. The Common Agreement is a legal contract that 
QHINs \781\ sign with the ONC Recognized Coordinating Entity 
(RCE),\782\ a private-sector entity that implements the Common 
Agreement and ensures QHINs comply with its terms.
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    \778\ Trusted Exchange Framework (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \779\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \780\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \781\ The Common Agreement defines a QHIN as ``to the extent 
permitted by applicable SOP(s), a Health Information Network that is 
a U.S. Entity that has been Designated by the RCE and is a party to 
the Common Agreement countersigned by the RCE.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-.
    \782\ In August 2019, ONC awarded a cooperative agreement to The 
Sequoia Project to serve as the initial RCE. The RCE will 
operationalize and enforce the Common Agreement, oversee QHIN-
facilitated network operations, and ensure compliance by 
participating QHINs. The RCE will also engage stakeholders to create 
a roadmap for expanding interoperability over time. See ONC Awards 
The Sequoia Project a Cooperative Agreement for the Trusted Exchange 
Framework and Common Agreement to Support Advancing Nationwide 
Interoperability of Electronic Health Information (September 3, 
2019), https://sequoiaproject.org/onc-awards-the-sequoia-project-a-cooperative-agreement-for-the-trusted-exchange-framework-and-common-agreement-to-support-advancing-nationwide-interoperability-of-electronic-health-information.
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    The technical and policy architecture of how exchange occurs under 
TEFCA follows a network-of-networks structure, which allows for 
connections at different levels and is inclusive of many different 
types of entities at those different levels, such as health information 
networks, care practices, hospitals, public health agencies, and 
Individual Access Services (IAS) \783\

[[Page 28490]]

Providers.\784\ QHINs connect directly to each other to facilitate 
nationwide interoperability, and each QHIN can connect Participants, 
which can connect Subparticipants.\785\ Compared to most nationwide 
exchange today, the Common Agreement includes an expanded set of 
Exchange Purposes beyond Treatment to include Individual Access 
Services, Payment, Health Care Operations, Public Health, and 
Government Benefits Determination \786\--all built upon common 
technical and policy requirements to meet key needs of the U.S. health 
care system. This flexible structure allows stakeholders to participate 
in the way that makes most sense for them, while supporting simplified, 
seamless exchange.
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    \783\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' See Common Agreement 
for Nationwide Health Information Interoperability Version 1, at 7 
(Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \784\ The Common Agreement defines ``IAS Provider'' as: ``Each 
QHIN, Participant, and Subparticipant that offers Individual Access 
Services.'' See Common Agreement for Nationwide Health Information 
Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \785\ For the Common Agreement definitions of QHIN, Participant, 
and Subparticipant, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 8-12 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \786\ For the Common Agreement definitions of Payment, Health 
Care Operations, Public Health, and Government Benefits 
Determination, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6-10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    The QTF,\787\ which was developed and released by the RCE, 
describes the functional and technical requirements that a Health 
Information Network (HIN) \788\ must fulfill to serve as a QHIN under 
the Common Agreement. The QTF specifies the technical underpinnings for 
QHIN-to-QHIN exchange and certain other responsibilities described in 
the Common Agreement. The technical and functional requirements 
described in the QTF enable different types of information exchange, 
including querying and message delivery across participating entities.
---------------------------------------------------------------------------

    \787\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \788\ ``Health Information Network'' under TEFCA has the meaning 
assigned to the term ``Health Information Network or Health 
Information Exchange'' in the information blocking regulations at 45 
CFR 171.102.
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    In 2022, prospective QHINs are anticipated to begin signing the 
Common Agreement and applying for designation. The RCE will then begin 
onboarding and designating QHINs to share information. In 2023, HHS 
expects stakeholders across the care continuum to have increasing 
opportunities to enable exchange under TEFCA. Specifically, this would 
mean such stakeholders would be: (1) Signatories to either the Common 
Agreement or an agreement that meets the flow-down requirements of the 
Common Agreement (called a Framework Agreement \789\ under the Common 
Agreement), (2) in good standing (that is, not suspended) under that 
agreement, and (3) enabling secure, bi-directional exchange of 
information to occur, in production. TEFCA is expected to give 
individuals and entities easier, more efficient, access to more health 
information while requiring strong privacy and security protections.
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    \789\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    We believe that exchange of health information enabled by the 
Common Agreement can advance CMS policy and program objectives related 
to care coordination, cost efficiency, and patient-centeredness in a 
variety of ways. We also believe that CMS policy and programs can help 
to accelerate nationwide connectivity through TEFCA by health care 
providers as well as other stakeholders.
    As discussed in section IX.D. of the preamble of this proposed 
rule, we are proposing to add a new Enabling Exchange Under TEFCA 
measure in the Medicare Promoting Interoperability Program. This 
proposed measure would provide eligible hospitals and CAHs with the 
opportunity to earn credit for the Health Information Exchange 
objective if They: Are a signatory to a ``Framework Agreement'' as that 
term is defined in the Common Agreement; 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; and use the functions of certified EHR 
technology (CEHRT) to support bi-directional exchange.
    In addition to this proposal, we are considering other ways that 
available CMS policy and program levers can advance information 
exchange under TEFCA. For instance, similar to the proposal in the 
current rule, there may be opportunities for CMS to incentivize 
exchange under TEFCA through other programs that incentivize high 
quality care, or through program features in value-based payment models 
that encourage certain activities that can improve care delivery.
    In addition to programs focused on providers, we are interested in 
opportunities to encourage exchange under TEFCA through CMS regulations 
for certain health care payers, including Medicare Advantage, Medicaid 
Managed Care, and CHIP issuers. For instance, we believe there may be 
opportunities to encourage information exchange under TEFCA to support 
recently finalized requirements for these payers to make information 
available to patients and to make patient information available to 
other payers as beneficiaries transition between plans in the 
``Medicare and Medicaid Programs; Patient Protection and Affordable 
Care Act; Interoperability and Patient Access for Medicare Advantage 
Organization and Medicaid Managed Care Plans, State Medicaid Agencies, 
CHIP Agencies and CHIP Managed Care Entities, Issuers of Qualified 
Health Plans on the Federally-Facilitated Exchanges, and Health Care 
Providers'' final rule (85 FR 25510). Finally, we are considering 
future opportunities to encourage information exchange under TEFCA for 
payment and operations activities such as submission of clinical 
documentation to support claims adjudication and prior authorization 
processes.
    We are requesting input from the public on the ideas described 
previously and related concepts for future exploration, as well as the 
following questions:
     What are the most important use cases for different 
stakeholder groups that could be enabled through widespread information 
exchange under TEFCA? What key benefits would be associated with 
effectively implementing these use cases, such as improved care 
coordination, reduced burden, or greater efficiency in care delivery?
     What are key ways that the capabilities of TEFCA can help 
to

[[Page 28491]]

advance the goals of CMS programs? Should CMS explore policy and 
program mechanisms to encourage exchange between different 
stakeholders, including those in rural areas, under TEFCA? In addition 
to the ideas discussed previously, are there other programs CMS should 
consider in order to advance exchange under TEFCA?
     How should CMS approach incentivizing or encouraging 
information exchange under TEFCA through CMS programs? Under what 
conditions would it be appropriate to require information exchange 
under TEFCA by stakeholders for specific use cases?
     What concerns do commenters have about enabling exchange 
under TEFCA? Could enabling exchange under TEFCA increase burden for 
some stakeholders? Are there other financial or technical barriers to 
enabling exchange under TEFCA? If so, what could CMS do to reduce these 
barriers?

E. Hospital Inpatient Quality Reporting (IQR) Program

1. Background and History of the Hospital IQR Program
    Through the Hospital IQR Program, we strive 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 
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).
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58926 through 
58959).
     The FY 2022 IPPS/LTCH PPS final rule (86 FR 45360 through 
45426).
    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 
proposed and finalized. Measures are also 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 these policies 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 and providers. In 2021, we launched Meaningful Measures 2.0 to 
promote innovation and modernization of all aspects of quality, and to 
address a wide variety of settings, stakeholders, and measure 
requirements (we note that Meaningful Measures 2.0 is still under 
development).\790\ We are not proposing any changes to these policies 
in this proposed rule.
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    \790\ Centers for Medicare and Medicaid Services. (2021). 
Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that 
Meaningful Measures 2.0 is still under development.
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    We also note that the Hospital IQR Program must first adopt 
measures and publicly report them on the Compare tool hosted by HHS, 
currently available at https://www.medicare.gov/care-compare, or its 
successor website, for at least one year before the Hospital Value-
Based Purchasing (VBP) Program is able to adopt them. We view the 
value-based purchasing programs, including the Hospital VBP Program, as 
the next step in promoting higher quality care for Medicare 
beneficiaries by transforming Medicare from a passive payer of claims 
into an active purchaser of quality healthcare for its beneficiaries.
5. New Measures Being Proposed for the Hospital IQR Program Measure Set
    In this proposed rule, we are proposing to adopt 10 new measures, 
including four electronic clinical quality measures (eCQMs): (1) 
Hospital Commitment to Health Equity measure, beginning with the CY 
2023 reporting period/FY 2025 payment determination;

[[Page 28492]]

(2) Screening for Social Drivers of Health measure, beginning with 
voluntary reporting in the CY 2023 reporting period and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (3) Screen Positive Rate for Social Drivers of Health 
measure, beginning with voluntary reporting in the CY 2023 reporting 
period and mandatory reporting beginning with the CY 2024 reporting 
period/FY 2026 payment determination; (4) Cesarean Birth eCQM, 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination; (5) Severe Obstetric 
Complications eCQM, beginning with the CY 2023 reporting period/FY 2025 
payment determination and mandatory reporting beginning with the CY 
2024 reporting period/FY 2026 payment determination; (6) Hospital-
Harm--Opioid-Related Adverse Events eCQM, beginning with the CY 2024 
reporting period/FY 2026 payment determination; (7) Global Malnutrition 
Composite Score eCQM, beginning with the CY 2024 reporting period/FY 
2026 payment determination; (8) Hospital-Level, Risk Standardized 
Patient-Reported Outcomes Performance Measure (PRO-PM) Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA), beginning with two voluntary reporting periods 
followed by mandatory reporting for the reporting period which runs 
from July 1, 2025, through June 30, 2026, impacting the FY 2028 payment 
determination; (9) Medicare Spending Per Beneficiary (MSPB) Hospital 
measure beginning with the FY 2024 payment determination; and (10) 
Hospital-Level Risk-Standardized Complication Rate (RSCR) Following 
Elective Primary Total THA/TKA measure beginning with the FY 2024 
payment determination.
    We provide more details on each of these proposals in the 
subsequent sections.
a. Proposed Hospital Commitment to Health Equity Measure Beginning With 
the CY 2023 Reporting Period/FY 2025 Payment Determination and for 
Subsequent Years
(1) Background
    Significant and persistent disparities in healthcare outcomes exist 
in the U.S. For example, 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, being a member of 
a religious minority, living in a rural area, or being near or below 
the poverty level, is often associated with worse health 
outcomes.791 792 793 794 795 796 797 798 799 800 Numerous 
studies have shown that among Medicare beneficiaries, racial and ethnic 
minority individuals often receive lower quality of hospital care, 
report lower experiences of care, and experience more frequent hospital 
readmissions and procedural 
complications.801 802 803 804 805 806 Readmission rates in 
the Hospital Readmission Reduction Program have shown to be higher 
among Black and Hispanic Medicare beneficiaries with common conditions, 
including congestive heart failure and acute myocardial 
infarction.807 808 809 810 811 Data indicate that, even 
after accounting for factors such as socioeconomic conditions, members 
of racial and ethnic minority groups reported experiencing lower 
quality of healthcare.\812\ Evidence of differences in quality of care 
received among racial and ethnic minority groups show worse health 
outcomes including diabetes complications such as retinopathy.\813\ 
Additionally, inequities in the social determinants of health affecting 
these groups, such as poverty and healthcare

[[Page 28493]]

access, are interrelated and influence a wide range of health and 
quality-of-life outcomes and risks.\814\
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    \791\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \792\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
Inequality and thirty-Day Outcomes After Acute Myocardial 
Infarction, Heart Failure, and Pneumonia: Retrospective Cohort 
Study. BMJ, 346. Available at: https://doi.org/10.1136/bmj.f521.
    \793\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and Equity of Care in U.S. Hospitals. N Engl J Med, 371(24), 2298-
2308. Available at: doi: 10.1056/NEJMsa1405003.
    \794\ Polyakova, M, Udalova V, Kocks, G, Genadek K, Finlay K, 
Finkelstein AN. (2021). Racial Disparities In Excess All-Cause 
Mortality During The Early COVID-19 Pandemic Varied Substantially 
Across States. Health Affairs, 40(2), 307-316. Available at: https://doi.org/10.1377/hlthaff.2020.02142.
    \795\ Rural Health Research Gateway. (2018). Rural Communities: 
Age, Income, and Health Status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \796\ HHS Office of Minority Health. (2020). Progress Report to 
Congress, 2020 Update on the Action Plan to Reduce Racial and Ethnic 
Health Disparities. Department of Health and Human Services. 
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \797\ Heslin KC, Hall JE. (2021). Sexual Orientation Disparities 
in Risk Factors for Adverse COVID-19-Related Outcomes, by Race/
Ethnicity--Behavioral Risk Factor Surveillance System, United 
States, 2017-2019. MMWR Morb Mortal Wkly Rep, 70(5), 149. doi: 
10.15585/mmwr.mm7005a1.
    \798\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-
19 Vulnerability of Transgender Women With and Without HIV Infection 
in the Eastern and Southern U.S. medRxiv. doi: 10.1101/
2020.07.21.20159327.
    \799\ Vu M, Azmat A, Radejko T, Padela AI. (2016). Predictors of 
Delayed Healthcare Seeking Among American Muslim Women. Journal of 
Women's Health, 25(6), 586-593. doi: 10.1089/jwh.2015.5517.
    \800\ Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes 
LL, Van Devanter N. (2016). The Association Between Discrimination 
and the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-
355. https://doi.org/10.1037/hea0000268.
    \801\ CMS Office of Minority Health. (2020). Racial, Ethnic, and 
Gender Disparities in Healthcare in Medicare Advantage. Baltimore, 
MD: Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/files/document/2020-national-level-results-race-ethnicity-and-gender-pdf.pdf.
    \802\ CMS Office of Minority Health. (Updated August 2018). 
Guide to Reducing Disparities in Readmissions. Baltimore, MD: 
Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \803\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. (2014). 
Racial Disparities in Knee and Hip Total Joint Arthroplasty: An 18-
year analysis of national Medicare data. Ann Rheum Dis., 73(12), 
2107-15. Available at: doi:10.1136/annrheumdis-2013-203494.
    \804\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. (2019). 
Racial Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc., 67(8), 1672-1679. 
Available at: https://doi.org/10.1111/jgs.15960.
    \805\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \806\ Tsai TC, Orav EJ, Joynt KE. (2014). Disparities in 
Surgical 30-day Readmission Rates for Medicare Beneficiaries by Race 
and Site of Care. Ann Surg., 259(6), 1086-1090. Available at: doi: 
10.1097/SLA.0000000000000326.
    \807\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. (2011). 
Readmission Rates for Hispanic Medicare Beneficiaries with Heart 
Failure and Acute Myocardial Infarction. Am Heart J., 162(2), 254-
261 e253. Available at: https://doi.org/10.1016/j.ahj.2011.05.009.
    \808\ Centers for Medicare & Medicaid Services. (2014). Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures. 
Available at: https://www.hhs.gov/guidance/document/medicare-hospital-quality-chartbook-performance-report-outcome-measures.
    \809\ CMS Office of Minority Health. (Updated August 2018). 
Guide to Reducing Disparities in Readmissions. Baltimore, MD: 
Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \810\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
(2013). Chronic Obstructive Pulmonary Disease Readmissions at 
Minority-Serving Institutions. Ann Am Thorac Soc., 10(6), 680-684. 
Available at: https://doi.org/10.1513/AnnalsATS.201307-223OT.
    \811\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \812\ Nelson AR. (2003). Unequal Treatment: Report of the 
Institute of Medicine on Racial and Ethnic Disparities in 
Healthcare. The Annals of thoracic surgery, 76(4), S1377-S1381. doi: 
10.1016/s0003-4975(03)01205-0.
    \813\ Peek, ME, Odoms-Young, A, Quinn, MT, Gorawara-Bhat, R, 
Wilson, SC, & Chin, MH. (2010). Race and Shared Decision-Making: 
Perspectives of African-Americans with diabetes. Social science & 
medicine, 71(1), 1-9. Available at: doi:10.1016/
j.socscimed.2010.03.014.
    \814\ Department of Health and Human Services. (2021). Healthy 
People 2020: Disparities. Available at: www.healthypeople.gov/2020/about/foundation-health-measures/Disparities.
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    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25592), we 
identified potential opportunities specific to the Hospital IQR Program 
by which we could leverage current measures or develop new measures to 
address the gap in healthcare disparities. In that rule, we sought 
public comment on addressing this gap, specifically requesting input on 
the inclusion of a structural measure to assess the degree of hospital 
leadership commitment to collecting and monitoring health equity 
performance data. We sought feedback on conceptual and measurement 
priorities to better illuminate organizational efforts to improve 
health equity, and on an appropriate measure regarding organizational 
commitment to health equity and accessibility for individuals with 
intellectual and developmental disabilities (86 FR 25593). In the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45414 through 45416), we 
summarized the public comments we received, including support for the 
development and implementation of a health equity structural measure. 
We refer readers to the ``Closing the Health Equity Gap in CMS Quality 
Programs--Request for Information'' (86 FR 45349) and ``Potential 
Future Efforts to Address Health Equity in the Hospital IQR Program'' 
(86 FR 45414) in the FY 2022 IPPS/LTCH PPS final rule for more details.
    We note that the Agency for Healthcare Research and Quality (AHRQ) 
and The Joint Commission identified that hospital leadership plays an 
important role in promoting a culture of quality and 
safety.815 816 AHRQ research shows that hospital boards can 
influence quality and safety in a variety of ways; not only through 
strategic initiatives, but also through more direct interactions with 
frontline workers.\817\ Because we are working toward the goal of all 
patients receiving high quality healthcare when hospitalized, 
regardless of individual characteristics, we are committed to 
supporting healthcare organizations in building a culture of equity 
that focuses on educating and empowering their workforce to recognize 
and eliminate health disparities. This includes patients receiving the 
right care, at the right time, in the right setting for their 
condition(s), regardless of those characteristics.
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    \815\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Patient Safety. Patient Safety Primer, September 
2019. Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
    \816\ Joint Commission on Accreditation of Healthcare 
Organizations, USA. Leadership Committed to Safety. Sentinel Event 
Alert. 2009 Aug 27;(43):1-3. PMID: 19757544.
    \817\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Patient Safety. Patient Safety Primer, September 
2019: Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
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    We believe that strong and committed leadership from hospital 
executives and board members is essential and can play a role in 
shifting organizational culture and advancing equity goals. 
Additionally, studies demonstrate that hospital leadership can 
positively influence culture for better quality, patient outcomes, and 
experience of care.818 819 820 A systematic review of 122 
published studies showed that strong leadership that prioritized 
safety, quality, and the setting of clear guidance with measurable 
goals for improvement resulted in a high-performing hospital with 
better patient outcomes.\821\ We believe leadership commitment to 
health equity will have a parallel effect in contributing to a 
reduction in health disparities.
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    \818\ Bradley EH, Brewster AL, McNatt Z, et al. (2018) How 
Guiding Coalitions Promote Positive Culture Change in Hospitals: A 
Longitudinal Mixed Methods Interventional Study. BMJ Qual Saf., 
27(3), 218-225. doi:10.1136/bmjqs-2017-006574.
    \819\ Smith SA, Yount N, Sorra J. (2017). Exploring 
Relationships Between Hospital Patient Safety Culture and Consumer 
Reports Safety Scores. BMC Health Services Research, 17(1), 143. 
doi:10.1186/s12913-017-2078-6.
    \820\ Keroack MA, Youngberg BJ, Cerese JL, Krsek C, Prellwitz 
LW, Trevelyan EW. (2007). Organizational Factors Associated with 
High Performance in Quality and Safety in Academic Medical Centers. 
Acad Med., 82(12), 1178-86. doi: 10.1097/ACM.0b013e318159e1ff.
    \821\ Millar R, Mannion R, Freeman T, et al. (2013). Hospital 
Board Oversight of Quality and Patient Safety: A Narrative Review 
and Synthesis of Recent Empirical Research. The Milbank quarterly, 
91(4), 738-70. doi:10.1111/1468-0009.12032.
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    The Institute of Healthcare Improvement's (IHI's) research of 23 
health systems throughout the U.S. and Canada also shows that health 
equity must be a priority championed by leadership teams to improve 
both patient access to needed healthcare services and outcomes among 
disadvantaged populations.\822\ This IHI study specifically identified 
concrete actions to make health equity a core strategy, including 
making health equity a leader-driven priority alongside organizational 
development structures and processes that support equity.\823\ Based 
upon these findings, we believe that hospital leadership can be 
instrumental in setting specific, measurable, attainable, realistic, 
and time-based (SMART) goals to assess progress towards achieving 
equity priorities and ensuring high-quality care is equally accessible 
to all individuals. Therefore, we are proposing to adopt an 
attestation-based structural measure, Hospital Commitment to Health 
Equity, beginning with the CY 2023 reporting period/FY 2025 payment 
determination and for subsequent years.
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    \822\ Mate KS and Wyatt R. (2017). Health Equity Must Be a 
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556.
    \823\ Mate KS and Wyatt R. (2017). Health Equity Must Be a 
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556.
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    The first pillar of our strategic priorities \824\ reflects our 
deep commitment to improvements in healthcare equity by addressing the 
health disparities that underly our health system. We developed this 
structural measure to assess hospital commitment to health equity 
across five domains (see Table IX.E-01. in the subsequent section) 
using a suite of organizational competencies aimed at achieving health 
equity for racial and ethnic minority groups, people with disabilities, 
members of the LGBTQ+ community, individuals with limited English 
proficiency, rural populations, religious minorities, and people facing 
socioeconomic challenges. We believe these elements are actionable 
focus areas, and assessment of hospital leadership commitment to them 
is foundational. We also believe this measure will incentivize 
providers to collect and utilize data to identify critical equity gaps, 
implement plans to address said gaps, and ensure that resources are 
dedicated toward addressing healthcare equity initiatives. While many 
factors contribute to health equity, we believe this measure is an 
important step toward assessing hospital leadership commitment, and a 
fundamental step toward closing the gap in equitable care for all 
populations. We note that this measure is not intended to encourage 
hospitals to take action on any one given element of collected data, 
but instead encourages hospitals to analyze their own data to 
understand many factors, including race, ethnicity, and various social 
drivers of health, such as housing status and food security, in order 
to deliver more equitable care.
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    \824\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.

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[[Page 28494]]

    We believe this measure builds on current health disparities 
reporting, supports hospitals in quality improvement, promotes 
efficient and effective use of resources, and leverages available data. 
The five questions of the proposed structural measure are adapted from 
the CMS Office of Minority Health's Building an Organizational Response 
to Health Disparities framework, which focuses on data collection, data 
analysis, culture of equity, and quality improvement.\825\
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    \825\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
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    This measure also aligns with our efforts under the Meaningful 
Measures Framework, which identifies high-priority areas for quality 
measurement and improvement to assess core issues most critical to 
high-quality healthcare and improving patient outcomes.\826\ In 2021, 
we launched Meaningful Measures 2.0 to promote innovation and 
modernization of all aspects of quality, and to address a wide variety 
of settings, stakeholders, and measure requirements.\827\ We plan to 
address healthcare priorities and gaps with Meaningful Measures 2.0 by 
leveraging quality measures to promote equity and close gaps in care. 
The Hospital Commitment to Health Equity measure supports these efforts 
and is aligned with the Meaningful Measures Area of ``Equity of Care'' 
and the Meaningful Measures 2.0 goal to ``Leverage Quality Measures to 
Promote Equity and Close Gaps in Care.'' This measure also supports the 
Meaningful Measures 2.0 objective to ``Commit to a patient-centered 
approach in quality measure and value-based incentives programs to 
ensure that quality and safety measures address healthcare equity.''
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    \826\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \827\ Centers for Medicare & Medicaid Services. (2021). 
Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that 
Meaningful Measures 2.0 is still under development.
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(2) Overview of Measure
    The Hospital Commitment to Health Equity measure assesses hospital 
commitment to health equity using a suite of equity-focused 
organizational competencies aimed at achieving health equity for racial 
and ethnic minority groups, people with disabilities, members of the 
LGBTQ+ community, individuals with limited English proficiency, rural 
populations, religious minorities, and people facing socioeconomic 
challenges. Table IX.E-01 includes the five attestation domains and the 
elements within each of those domains that a hospital must 
affirmatively attest to for the hospital to receive credit for that 
domain.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TP10MY22.185

BILLING CODE 4120-01-C
    The Hospital Commitment to Health Equity measure was included in 
the publicly available ``List of Measures Under Consideration for 
December 1, 2021'' (MUC List), a list of measures under consideration 
for use in various Medicare programs.\828\ The National Quality Forum 
(NQF) Measure Applications Partnership (MAP) Rural Health Advisory 
Group reviewed the MUC List and the Hospital Commitment to Health 
Equity measure (MUC 2021-106) in detail on December 8, 2021.\829\ The 
MAP Rural Health Workgroup initially raised concerns that this measure 
may cause undue burden to

[[Page 28496]]

rural hospitals that may not yet be directing resources or have 
available resources to dedicate toward implementing the measure. We 
acknowledge that for some hospitals, the implementation of this 
structural measure may impose additional data collection efforts. 
However, we believe this measure builds on hospitals' current quality 
improvement activities through participation in the Hospital IQR 
Program. Additionally, we believe the activities outlined in the 
previous table are foundational best practices for advancing health 
equity for patients and communities. The Rural Health Workgroup agreed 
that this is an important measure and for that reason should be added 
to the Hospital IQR Program measure set as the intent of the measure is 
to identify these gaps and make the needed investments in workforce 
training, leadership development, and other related areas to improve 
equity.\830\ The MAP Rural Health Workgroup's recommendation was 
majority support for the Hospital Commitment to Health Equity 
measure.\831\
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    \828\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \829\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \830\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \831\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
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    In addition, on December 9, 2021, the MAP Health Equity Advisory 
Group reviewed the 2021 MUC List.\832\ The MAP Health Equity Advisory 
Group was convened at the request of CMS to provide input on the MUC 
List with the goal of reducing health disparities closely linked with 
social, economic, or environmental disadvantages.\833\ The MAP Health 
Equity Advisory Group is charged with providing feedback related to the 
relative priority of each measure in advancing health equity, and input 
on potential data, reporting, and/or methodological concerns on 
reporting measures adjusting for healthcare disparities.\834\ The MAP 
Health Equity Advisory Group provided input on potential unintended 
consequences or measurement gap areas related to health 
disparities.\835\ After discussion of each measure under consideration, 
the Workgroup was polled on the potential impact on health disparities 
if the measure were to be included in a specific program. Like the MAP 
Rural Health Advisory Group, the MAP Health Equity Advisory Group 
agreed this is an important measure for advancing healthcare equity in 
the Hospital IQR Program and a fundamental first step toward future 
measure development and innovation.\836\ The MAP Health Equity Advisory 
Group's feedback was supportive of this measure and its potential to 
decrease health disparities.\837\
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    \832\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \833\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \834\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \835\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \836\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \837\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
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    The MUC List, including this measure (MUC2021-106), was also 
reviewed by the MAP Hospital Workgroup on December 15, 2021.\838\ MAP 
stakeholders expressed concerns about whether measure data will be 
actionable and how improvements in clinical healthcare equity outcomes 
will be measured.\839\ The MAP Hospital Workgroup had concerns about 
how this measure would be publicly reported, specifically, how it would 
be and interpreted by patients/consumers.\840\ For these reasons, the 
MAP Hospital Workgroup recommended that the MAP not support the measure 
for rulemaking.\841\ In response to this feedback, we wish to explain 
that we would publicly report the numerator indicating how many of the 
competencies hospitals attest to, and we refer readers to section 
IX.E.5.a.(3). for our proposed measure calculation methodology and 
section IX.E.5.a.(4). for the proposed public reporting. Thereafter, 
the MAP Coordinating Committee deliberated and ultimately voted to 
conditionally support this measure for rulemaking given its importance 
in being a first step towards the future development of outcome-based 
measures.\842\ We agree that this measure is an important foundation of 
a comprehensive quality reporting program. Our approach to developing 
health equity measures is incremental and will evolve over time to 
capture healthcare equity outcomes in the Hospital IQR Program. We 
additionally believe this measure to be a building block that lays the 
groundwork for a future meaningful suite of measures that would assess 
progress in providing high-quality healthcare for all patients 
regardless of social risk factors or demographic characteristics.
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    \838\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \839\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \840\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \841\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \842\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
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    We have not submitted this measure for NQF endorsement at this 
time. We note that under section 1866(b)(3)(B)(viii)(IX)(aa) of the 
Act, each measure specified by the Secretary shall be endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 a measure that has 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 on 
this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.

[[Page 28497]]

(3) Measure Calculation
    The proposed Hospital Commitment to Health Equity measure consists 
of five domains, and a hospital would need to evaluate and determine 
whether it can affirmatively attest to each domain. Some of these 
domains have multiple elements to which a hospital must attest. For a 
hospital to affirmatively attest to a domain, and receive credit for 
that domain, the hospital would evaluate and determine whether it 
engages in each of the elements that comprise the domain. We are 
proposing that each of the domains would be represented in the 
denominator as a point, for a total of 5 points (one per domain).
    For example, for Domain 1 (``Hospital commitment to reducing 
healthcare disparities is strengthened when equity is a key 
organizational priority''), a hospital would evaluate and determine 
whether its strategic plan meets each of the elements described in (A) 
through (D) (see Table IX.E-01.). If the hospital's plan meets all four 
of these elements, the hospital would affirmatively attest to Domain 1 
and would receive a point for that attestation. A hospital would not be 
able to receive partial credit for a domain. In other words, if a 
hospital's strategic plan meets elements (A) and (B) but not (C) and 
(D), the hospital would not be able to affirmatively attest to Domain 1 
and would not receive a point for that attestation.
    The numerator would capture the total number of domain attestations 
that the hospital is able to affirm. For example, a hospital that 
affirmatively attests each element of the 5 domains would receive the 
maximum 5 points.
(4) Data Submission and Reporting
    Specifications for the proposed measure are available on the CMS 
Measure Methodology page with the file name ``Hospital Commitment to 
Health Equity Structural Measure Specifications'' at https://qualitynet.cms.gov/inpatient/iqr/resources. Hospitals are required to 
submit information for structural measures once annually using a CMS-
approved web-based data collection tool available within the Hospital 
Quality Reporting (HQR) System. We propose that hospitals would follow 
established submission and reporting requirements as previously 
finalized for structural measures and refer readers to section 
IX.E.10.i. of the preamble of this proposed rule for more details on 
our previously finalized data submission and deadline requirements for 
structural measures.
    We are proposing this measure for the CY 2023 reporting period/FY 
2025 payment determination and for subsequent years. In developing this 
proposal, we considered proposing an incremental approach to the 
implementation of this measure. However, we ultimately decided to 
propose mandatory reporting given the importance of this measure and 
how it aligns with our healthcare quality goal of closing the racial 
and ethnic disparity gaps.
    We invite public comment on this proposal.
b. Proposed Adoption of Two Social Drivers of Health Measures Beginning 
With Voluntary Reporting in the CY 2023 Reporting Period and Mandatory 
Reporting Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
    Health-related social needs (HRSNs), which we have previously 
defined as individual-level, adverse social conditions that negatively 
impact a person's health or healthcare, are significant risk factors 
associated with worse health outcomes as well as increased healthcare 
utilization.\843\ We believe that consistently pursuing identification 
of HRSNs will have two significant benefits. First, because social risk 
factors disproportionately impact underserved communities, promoting 
screening for these factors could serve as evidence-based building 
blocks for supporting hospitals and health systems in actualizing 
commitment to address disparities, improve health equity through 
addressing the social needs with community partners, and implement 
associated equity measures to track progress.\844\ Second, these 
measures could support ongoing hospital quality improvement initiatives 
by providing data with which to stratify patient risk and 
organizational performance.
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    \843\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights. June 
2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed: November 23, 2021.
    \844\ American Hospital Association. (2020). Health Equity, 
Diversity & Inclusion Measures for Hospitals and Health System 
Dashboards. December 2020. Accessed: January 18, 2022. Available at: 
https://ifdhe.aha.org/system/files/media/file/2020/12/ifdhe_inclusion_dashboard.pdf.
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    Further, we believe collecting patient-level HRSN data through 
screening is essential in the long-term in encouraging meaningful 
collaboration between healthcare providers and community-based 
organizations and in implementing and evaluating related innovations in 
health and social care delivery. We note that advancing health equity 
by addressing the health disparities that underlie the country's health 
system is one of our strategic pillars \845\ and a Biden-Harris 
Administration priority.
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    \845\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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    As a first step towards addressing the role of HRSNs in closing the 
health equity gap, we have developed two evidence-based measures--
Screening for Social Drivers of Health and Screen Positive Rate for 
Social Drivers of Health. These two proposed Social Drivers of Health 
measures will support identification of specific risk factors for 
inadequate healthcare access and adverse health outcomes among 
patients. We note that these measures would enable systematic 
collection of HRSN data which aligns with our other efforts, including 
the CY 2023 Medicare Advantage and Part D proposed rule in which we are 
proposing that all Special Needs Plans (SNPs) complete health risk 
assessments (HRAs) of enrollees that include specific standardized 
questions on housing stability, food security, and access to 
transportation (87 FR 1858).
    These standardized measures would identify patients with HRSNs, who 
are known to experience the greatest risk of poor health outcomes, 
thereby improving the accuracy of high-risk prediction calculations. 
Improvement in risk prediction has the potential to reduce healthcare 
access barriers, address the disproportionate expenditures attributed 
to high-risk population groups, and improve the hospital's quality of 
care.846 847 848 849 Further, these data could guide future

[[Page 28498]]

public and private resource allocation to promote targeted 
collaboration between hospitals and health systems and appropriate 
community-based organizations and ultimately contribute to improved 
patient outcomes following inpatient hospitalization.
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    \846\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \847\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
    \848\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://care.diabetesjournals.org/lookup/doi/10.2337/dci20-0053.
    \849\ Jaffrey, J.B., Safran, G.B., Addressing Social Risk 
Factors in Value-Based Payment: Adjusting Payment Not Performance to 
Optimize Outcomes and Fairness. Health Affairs Blog, April 19, 2021. 
Available at: https://www.healthaffairs.org/do/10.1377/forefront.20210414.379479/full/.
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    In this proposed rule, we are proposing voluntary reporting of 
these two measures beginning with the CY 2023 reporting period and 
mandatory reporting beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years. We believe incremental 
implementation of these measures beginning with one year of voluntary 
reporting would allow hospitals who are not yet screening patients for 
HRSNs to get experience with the measure and equally allow hospitals 
who already undertake screening efforts to report data already being 
collected.
    We provide further details on both proposed measures in the 
subsequent discussion. Additionally, consistent with our strategy to 
incorporate social drivers of health factors into Medicare quality 
reporting and payment, we refer readers to section II.D.13.(d). where 
we are seeking comment on how the reporting of diagnosis codes may 
improve our ability to advance health equity.
(1) Proposed Screening for Social Drivers of Health Measure
(a) Background
    In the FY 2022 IPPS/LTCH PPS final rule, we sought feedback on the 
development of new measures that could address the gap in existing 
health disparities, focusing on social risk factors for which providers 
should screen (85 FR 45414). As a result, we identified the Screening 
for Social Drivers of Health measure, which assesses the percent of 
patients admitted to the hospital who are 18 years or older at time of 
admission and are screened for food insecurity, housing instability, 
transportation problems, utility difficulties, and interpersonal 
safety.
    Health disparities manifest primarily as worse health outcomes in 
population groups where access to care is 
inequitable.850 851 852 853 854 Such differences persist 
across geography and healthcare settings irrespective of improvements 
in quality of care over time.855 856 857 Assessment of HRSNs 
is an essential mechanism for capturing the interaction between social, 
community, and environmental factors associated with health status and 
health outcomes.858 859 860 While widespread interest in 
addressing HRSNs exists, action is inconsistent, with 92 percent of 
hospitals screening for one or more of the five HRSNs--food insecurity, 
housing instability, transportation needs, utility difficulties, and 
interpersonal safety--specified in the proposed measures, but only 24 
percent of hospitals screening for all five HRSNs.\861\
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    \850\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning 
Programs and Policies to Support Food Security and Public Health 
Goals in the United States. Annual Review of Public Health, 40(1), 
319-337. Available at: https://doi.org/10.1146/annurev-publhealth-040218-044132.
    \851\ The Physicians Foundation. (2020). Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \852\ 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.
    \853\ 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.
    \854\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \855\ 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.
    \856\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://care.diabetesjournals.org/lookup/doi/10.2337/dci20-0053.
    \857\ Khullar, D., MD. (2020, September 8). Association Between 
Patient Social Risk and Physician Performance American academy of 
Family Physicians. Addressing Social Determinants of Health in 
Primary Care team-based approach for advancing health equity. 
Available at: https://www.aafp.org/dam/AAFP/documents/patient_care/everyone_project/team-based-approach.pdf.
    \858\ Institute of Medicine. (2014). Capturing Social and 
Behavioral Domains and Measures in Electronic Health Records: Phase 
2. Washington, DC: The National Academies Press. Available at: 
https://doi.org/10.17226/18951.
    \859\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. (2016). Accountable Health Communities--Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \860\ Centers for Disease Control and Prevention. CDC COVID-19 
Response Health Equity Strategy: Accelerating Progress Towards 
Reducing COVID-19 Disparities and Achieving Health Equity. July 
2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \861\ TK Fraze, AL Brewster, VA Lewis, LB Beidler, GF Murray, CH 
Colla. Prevalence of screening for food insecurity, housing 
instability, utility needs, transportation needs, and interpersonal 
violence by U.S. physician practices and hospitals. JAMA Network 
Open 2019; 2:e1911514.10.1001/jamanetworkopen.2019.11514.31532515.
    \862\ Zhang Y, Li J, Yu J, Braun RT, Casalino LP. (2021). Social 
Determinants of Health and Geographic Variation in Medicare per 
Beneficiary Spending. JAMA Network Open. 2021;4(6):e2113212. 
doi:10.1001/jamanetworkopen.2021.13212.
    \863\ Khullar, D., Schpero, W.L., Bond, A.M., Qian, Y., & 
Casalino, L.P. (2020). Association Between Patient Social Risk and 
Physician Performance Scores in the First Year of the Merit-based 
Incentive Payment System. JAMA, 324(10), 975-983. https://doi.org/10.1001/jama.2020.13129.
    \864\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights. June 
2021. Accessed: November 23, 2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
    \865\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. 2016. Accountable Health Communities-Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \866\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \867\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [bond] CMS Innovation Center. Accessed November 23, 2021. 
Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \868\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \869\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
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    Growing evidence demonstrates that specific social risk factors are 
directly associated with patient health outcomes as well as healthcare 
utilization, costs, and performance in quality-based payment 
programs862 863 In 2017, CMS' Center for Medicare and 
Medicaid Innovation (CMMI) launched the Accountable Health Communities 
(AHC) Model to test the impact of systematically identifying and 
addressing the HRSNs of Medicare and Medicaid beneficiaries (through 
screening, referral, and community navigation on their health outcomes 
and related healthcare utilization and 
costs).864 865 866 867 Although there are models that 
address HRSNs, the AHC Model is one of the first Federal pilots to 
systematically test whether identifying and addressing core HRSNs 
improves healthcare costs, utilization, and outcomes.\868\ It also 
tested the ability of hospitals and health systems to implement HRSN 
screening, referral, and community navigation in over 600 clinical 
sites in 21 states.\869\ The AHC Model has a 5-year period of 
performance that began in May 2017

[[Page 28499]]

and will end in April 2022, with beneficiary screening beginning in the 
summer of 2018 following an implementation period.\870\
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    \870\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
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    While social risk factors account for 50 to 70 percent of health 
outcomes, the mechanisms by which this connection emerges are complex 
and multifaceted.871 872 873 874 The persistent interactions 
between individuals' HRSNs, medical providers' practices/behaviors, and 
community resources significantly impact healthcare access, quality, 
and ultimately costs, as described in the CMS Equity Plan for Improving 
Quality in Medicare.875 876 In their 2018 survey of 8,500 
physicians, The Physicians Foundation found almost 90 percent of 
physician respondents reported their patients had a serious health 
problem linked to poverty or other social conditions.\877\ 
Additionally, associations between disproportionate health risk, 
hospitalization, and adverse health outcomes have been highlighted and 
magnified by the COVID-19 pandemic.878 879
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    \871\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \872\ Khullar, D., MD. (2020, September 8). Association Between 
Patient Social Risk and Physician Performance American academy of 
Family Physicians. (2020). Addressing Social Determinants of Health 
in Primary Care team-based approach for advancing health equity.
    \873\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
    \874\ The Physicians Foundation. (2021). Viewpoints: Social 
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed December 8, 2021.
    \875\ Centers for Medicare & Medicaid Services. (2021). Paving 
the Way to Equity: A Progress Report. Accessed January 18, 2022. 
Available at: https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf.
    \876\ Centers for Medicare & Medicaid Services Office of 
Minority Health. (2021). 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#:~:text=The%20Centers%20for%20Me
dicare%20%26%20Medicaid%20Services%20%28CMS%29,evidence%20base%2C%20i
dentifying%20opportunities%2C%20and%20gathering%20stakeholder%20input
.
    \877\ The Physicians Foundation. (2019). Viewpoints: Social 
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed December 8, 2021.
    \878\ Centers for Disease Control and Prevention. (2020). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \879\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
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    In developing this measure, we identified core HRSN domains based 
on the following criteria: (1) The availability of high-quality 
scientific evidence linking a given HRSN to adverse health outcomes and 
increased healthcare utilization, including hospitalizations, and 
associated costs; (2) the HRSNs can be screened and identified in the 
inpatient setting prior to hospital discharge, addressed by community-
based services, and potentially improve healthcare outcomes, including 
reduced hospital re-admission; and (3) the HRSNs are not systematically 
addressed by healthcare providers.\880\ Based on those criteria, the 
following five domains were selected to screen for social risk factors 
in Medicare and Medicaid beneficiaries under the AHC Model: (1) Food 
insecurity; (2) housing instability; (3) transportation needs; (4) 
utility difficulties; and (5) interpersonal safety. In addition to 
established evidence of their association with health status, risk, and 
outcomes, these five domains were selected because they can be assessed 
across the broadest spectrum of individuals in a variety of 
settings.881 882 883 The five core HRSN domains are 
described in Table IX.E-02.
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    \880\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \881\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \882\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [bond] CMS Innovation Center. Accessed November 23, 2021. 
Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \883\ Kamyck, D., Senior Director of Marketing. (2019). CMS 
releases standardized screening tool for health-related social 
needs. Activate Care. Available at: https://blog.activatecare.com/standardized-screening-for-health-related-social-needs-in-clinical-settings-the-accountable-health-communities-screening-tool/.

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[[Page 28500]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.186

    Utilization of screening tools to identify the burden of unmet 
HRSNs can be a helpful first step in identifying necessary community 
partners and

[[Page 28501]]

connecting individuals to resources in their communities. We believe 
collecting data across the same five HRSN domains that were screened 
under the AHC Model will illuminate their impact on health outcomes and 
disparities and the care-cost burden for hospitals, and in particular 
for hospitals that serve patients with disproportionately high levels 
of social risk factors. Additionally, the ability of medical providers 
to contextualize the interaction between HRSNs and poor health outcomes 
could strengthen referrals to and partnerships with community-based 
service providers for patients with the most complex needs. This data 
collection could inform meaningful and sustainable solutions for other 
provider-types through similar collections in other quality reporting 
programs.906 907 908 909 910
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    \884\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food 
insecurity, healthcare utilization, and high cost: A longitudinal 
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID: 
30222918; PMCID: PMC6426124.
    \885\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://care.diabetesjournals.org/lookup/doi/10.2337/dci20-0053.
    \886\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning 
Programs and Policies to Support Food Security and Public Health 
Goals in the United States. Annual Review of Public Health, 40(1), 
319-337. Available at: https://doi.org/10.1146/annurev-publhealth-04021044132.
    \887\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \888\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://care.diabetesjournals.org/lookup/doi/10.2337/dci20-0053.
    \889\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food 
insecurity, healthcare utilization, and high cost: a longitudinal 
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID: 
30222918; PMCID: PMC6426124.
    \890\ Dean, E.B., French, M.T., & Mortensen, K. (2020a). Food 
insecurity, health care utilization, and health care expenditures. 
Health Services Research, 55(S2), 883-893. Available at: https://doi.org/10.1111/1475-6773.13283.
    \891\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.
    \892\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://care.diabetesjournals.org/lookup/doi/10.2337/dci20-0053.
    \893\ Henry M., de Sousa, T., Roddey, C., Gayen, S., Bednar, T.; 
Abt Associates. The 2020 Annual Homeless Assessment Report (AHAR) to 
Congress; Part 1: Point-in-Time Estimates of Homelessness, January 
2021. U.S. Department of Housing and Urban Development. Accessed 
November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
    \894\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.
    \895\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H. 
(2019). Effects of Housing First approaches on health and well-being 
of adults who are homeless or at risk of homelessness, systematic 
review and meta-analysis of randomized controlled trials. Journal of 
Epidemiology and Community Health, 73; 379-387. Available at: 
jech.bmj.com/content/jech/73/5/379.full.pdf.
    \896\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \897\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \898\ Hill-Briggs, F. (2021, January 1), Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https:\\care.diabetesjournasl.org/lookup/doi/10.2337/dci20-0053.
    \899\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountants Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \900\Shier, G., Ginsberg, M., Howell, J., Volland, P., & Golden, 
R. (2013). Strong Social Support Services, Such as Transportation 
And Help for Caregivers, Can Lead To Lower Health Care Use And 
Costs. Health Affairs, 32(3), 544-551. Available at: https://doi.org/10.31478/201705b.
    \901\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H. 
(2019). Effects of Housing First approaches on health and well-being 
of adults who are homeless or at risk of homelessness: systematic 
review and meta-analysis of randomized controlled trials. Journal of 
Epidemiology and Community Health, 73; 379-387. Available at: 
https://jech.bmj.com/content/jech/73/5/379.full.pdf.
    \902\ Wright, B.J., Vartanian, K.B., Li, H.F., Royal, N., & 
Matson, J.K. (2016). Formerly Homeless People Had Lower Overall 
Health Care Expenditures After Moving into Supportive Housing. 
Health Affairs, 35(1), 20-27. Available at: https://doi.org/10.1377/hlthaff.2015.0393.
    \903\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \904\ Henry M., de Sousa, T., Roddey, C., Gayen, S., Bednar, T.; 
Abt Associates. The 2020 Annual Homeless Assessment Report (AHAR) to 
Congress; Part 1: Point-in-Time Estimates of Homelessness, January 
2021. U.S. Department of Housing and Urban Development. Accessed 
November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
    \905\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.
    \906\ The Physicians Foundation: 2020 Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \907\ 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.
    \908\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \909\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \910\ De Marchis, E., Knox, M., Hessler, D., Willard-Grace, R., 
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic 
Capacity to Address Patients' Social Needs. The Journal of the 
American Board of Family Medicine, 32 (1), 69-78.
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    For data collection of this measure, providers could use a self-
selected screening tool and collect these data in multiple ways, which 
can vary to accommodate the population they serve and their individual 
needs.911 912 One example of such data collection is the AHC 
Model, which uses the standard 10-item AHC Health-Related Social Needs 
Screening Tool to enable providers to identify HRSNs in the five core 
domains (described in Table IX.E-02.) of community-dwelling Medicare, 
Medicaid, and dually eligible beneficiaries.\913\ Since its inception, 
the AHC Model has been implemented across many care delivery sites in 
diverse geographic locations across the U.S.\914\ More than one million 
Medicare and Medicaid beneficiaries have been screened using the AHC 
Health-Related Social Needs Screening Tool, which has been evaluated 
psychometrically and demonstrated evidence of both reliability and 
validity, including inter-rater reliability and concurrent and 
predictive validity.\915\ Moreover, the screening instrument can be 
implemented in a variety of clinical settings, including primary care, 
EDs, labor and delivery units, inpatient units (including mental and 
behavioral health settings), and other places where patients seek 
healthcare.\916\
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    \911\ Social Interventions Research & Evaluation Network. 
(2019). Social Needs Screening Tool Comparison Table. Available at: 
https://sirenetwork.ucsf.edu/tools-resources/resources/screening-tools-comparison. Tool. Available at: https://www.mathematica.org/publications/a-guide-to-using-the-accountable-health-communities-health-related-social-needs-screening-tool. Accessed January 18, 
2021.
    \912\ Mathematica. A Guide to Using the Accountable Health 
Communities Health-Related Social Needs Screening Tool. Available 
at: https://www.mathematica.org/publications/a-guide-to-using-the-accountable-health-communities-health-related-social-needs-screening-tool. Accessed January 18, 2021.
    \913\ More information on the HRSN Screening Tool is available 
at: https://innovation.cms.gov/files/worksheets/ahcm-screeningtool.pdf.
    \914\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \915\ Lewis C., Wellman R., Jones S., Walsh-Bailey C., Thompson 
E., Derus A., Paolino A., Steiner J., De Marchis E., Gottlieb L., 
and Sharp A. (2020). Comparing the Performance of Two Social Risk 
Screening Tools in a Vulnerable Subpopulation. J Family Med Prim 
Care. 2020 Sep; 9(9): 5026-5034. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652127/.
    \916\ CMS. A Guide to Using the Accountable Health Communities 
Health-Related Social Needs Screening Tool: Promising Practices and 
Key Insights. June 2021. Accessed: November 23, 2021. Available at: 
https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
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    The intent of this measure is to promote adoption of HRSN screening 
by hospitals. We encourage hospitals to use the screening as a basis 
for developing their own individual action plans (which could include 
navigation services), as well as opportunities for initiating and 
improving partnerships between healthcare delivery and community-based 
services. This effort would yield actionable information to close the 
disparity gap by encouraging hospitals to identify patients with HRSNs, 
with a reciprocal goal of partnering with community-based organizations 
to connect those individuals to community support to help address those 
risks.
    Under our Meaningful Measures Framework,\917\ the Screening for 
Social Drivers of Health measure addresses the quality priority of 
``Work with Communities to Promote Best Practices of Healthy Living'' 
through the Meaningful Measures Area of ``Equity of Care.'' 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``healthcare equity'' priority area and aligns with our 
commitment to introduce plans to close health equity gaps and promote 
equity through quality measures, including to ``develop and implement 
measures that reflect social and economic determinants.'' \918\ 
Development and

[[Page 28502]]

proposal of this measure also aligns with our strategic pillar to 
advance health equity by addressing the health disparities that 
underlie our health system.\919\
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    \917\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \918\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \919\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
---------------------------------------------------------------------------

    If finalized, this measure (alongside the proposed Screen Positive 
Rate for Social Drivers of Health measure) would be the first patient-
level measurement of social drivers of health in the Hospital IQR 
Program. We believe this measure is appropriate for the measurement of 
the quality of care furnished by hospitals in inpatient settings. 
Screening during inpatient hospitalization would allow healthcare 
providers to identify and potentially help address HRSNs as part of 
discharge planning and contribute to long-term improvements in patient 
outcomes. This would have a direct and positive impact on hospital 
quality performance. Collecting baseline data via this measure would be 
crucial in informing design of future measures that could enable us to 
set appropriate performance targets for hospitals.
(b) Overview of Measure
    The Screening for Social Drivers of Health measure assesses whether 
a hospital implements screening for all patients that are 18 years or 
older at time of admission for food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety. 
To report on this measure, hospitals would provide: (1) The number of 
inpatients admitted to the hospital who are 18 years or older at time 
of admission and who are screened for each of the five HRSNs: Food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety; and (2) the total number of 
patients who are admitted to the hospital who are 18 years or older on 
the date they are admitted.
    The Screening for Social Drivers of Health (MUC21-136) measure was 
included in the publicly available ``List of Measures Under 
Consideration for December 1, 2021'' (MUC List).\920\ The MAP Rural 
Health Workgroup and the Health Equity Advisory Group reviewed the 
measure on December 8, 2021, and December 9, 2021, respectively. Both 
groups indicated that screening for social risk factors would inform 
future efforts to expand capabilities to capture data that demonstrate 
the extent to which improvements in healthcare quality contribute to 
reductions in health disparities and the impact of serving patients at 
higher risk for adverse health outcomes on healthcare quality at the 
organization level. Although MAP stakeholders expressed concerns 
regarding standardization and the need to emphasize the link between 
the measure and better healthcare outcomes for patients, the measure 
developer stated that the focus at this point was to establish standard 
social drivers of health screening measures and not to dictate to 
hospitals and providers which tool they use or how to address the needs 
of their patients, citing that multiple CMS models have demonstrated 
the feasibility of implementing HRSN screening. However, we acknowledge 
the value and importance of tools which support the interoperability of 
HRSN data and encourage the use of health IT-enabled assessment 
instruments with coded questions. We also refer readers to section 
IX.E.5.b.(1).(g). of the preamble of this proposed rule where we 
discuss measure reporting. The MAP Health Equity Advisory Group 
majority voted that this measure has potential or high potential to 
have a positive impact by decreasing health disparities. The MAP Rural 
Health Workgroup majority voted agreement or strong agreement that this 
measure is suitable for use with rural providers.
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    \920\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
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    On December 15, 2021, the MAP Hospital Workgroup reviewed the MUC 
List, including the Screening for Social Drivers (MUC21-136) measure. 
The MAP Hospital Workgroup discussion was similar to that of the MAP 
Health Equity Advisory Group and MAP Rural Health Workgroup, and 
ultimately voted to conditionally support the measure pending NQF 
endorsement. On January 19, 2022, the MAP Coordinating Committee 
reviewed the MUC List including the Screening for Social Drivers of 
Health (MUC21-136) measure and voted to uphold the MAP Hospital 
Workgroup recommendation of conditional support for rulemaking.\921\
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    \921\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
---------------------------------------------------------------------------

    We intend to submit this measure in future for NQF endorsement. We 
note that under section 1866(b)(3)(B)(viii)(IX)(aa) of the Act, each 
measure specified by the Secretary shall be endorsed by the entity with 
a contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 on 
this this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    Measure specifications for this measure are available on the 
QualityNet website at https://qualitynet.cms.gov (or other successor 
CMS designated websites).
(c) Cohort
    The Screening for Social Drivers of Health measure assesses the 
total number of patients, aged 18 years and older, screened for social 
risk factors (specifically, food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety) 
during a hospital inpatient stay. The measure cohort includes patients 
who are admitted to an inpatient hospital stay and are 18 years or 
older on the date of admission.
(d) Numerator
    The numerator consists of the number of patients admitted to an 
inpatient hospital stay who are 18 years or older on the date of 
admission and are screened for one or all of the following five HRSNs: 
Food insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety during their hospital inpatient 
stay.
(e) Denominator
    The denominator consists of the number of patients who are admitted 
to a hospital inpatient stay and who are 18 years or older on the date 
of admission. The following patients would be excluded from the 
denominator: (1) Patients who opt-out of screening; and (2) patients 
who are themselves unable to complete the screening during their 
inpatient stay and have no legal guardian or caregiver able to do so on 
the patient's behalf during their inpatient stay.

[[Page 28503]]

(f) Measure Calculation
    The Screening for Social Drivers of Health measure would be 
calculated as the number of patients admitted to an inpatient hospital 
stay who are 18 years or older on the date of admission screened for 
one or all five HRSNs (food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety) 
divided by the total number of patients 18 years or older on the date 
of admission admitted to the hospital.
(g) Data Submission and Reporting
    We are proposing voluntary reporting of the Screening for Social 
Drivers of Health measure beginning with the CY 2023 reporting period, 
followed by mandatory reporting on an annual basis beginning with the 
CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years.
    Due to variability across hospital settings and the populations 
they serve, we are proposing to allow hospitals flexibility with 
selection of tools to screen patients for food insecurity, housing 
instability, transportation needs, utility difficulties, and 
interpersonal safety.
    Potential sources of these data could include, for example, 
administrative claims data, electronic clinical data, standardized 
patient assessments, or patient-reported data and surveys. Multiple 
screening tools exist and many hospitals already have screening tools 
integrated into their electronic health records (EHRs). We suggest 
hospitals refer to the Social Interventions Research and Evaluation 
Network (SIREN) website, for example, for comprehensive information 
about the most widely used HRSN screening tools.922 923 
SIREN contains descriptions of the content and characteristics of 
various tools, including information about intended populations, 
completion time, and number of questions.
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    \922\ Social Interventions Research & Evaluation Network. 
(2019). Social Needs Screening Tool Comparison Table. Available at: 
https://sirenetwork.ucsf.edu/tools-resources/resources/screening-tools-comparison.
    \923\ The Social Interventions Research and Evaluation Network 
(SIREN) at University of California San Francisco was launched in 
the spring of 2016 to synthesize, disseminate, and catalyze research 
on the social determinants of health and healthcare delivery.
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    We note that providers participating in the Hospital IQR Program 
must use certified EHR technology (CEHRT) that has been certified to 
the 2015 Edition of health IT certification criteria under the Office 
of the National Coordinator for Health Information Technology (ONC) 
Health IT Certification Program, and extraction of structured data from 
a certified EHR can make the data more accessible for utilization and 
submission for quality measurement reporting (86 FR 45383). Use of 
certified health IT can also support capture of HSRN information in an 
interoperable fashion so that this data can be shared across the care 
continuum to support coordinated care. For instance, in the 2020 ONC 
21st Century Cures Act final rule, ONC 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). 
Version 2 of the USCDI, published in July 2021, includes new data 
classes for social determinants of health (SDOH). These include 
standards to capture SDOH Problems/Health Concerns, SDOH Interventions, 
SDOH Goals, and SDOH Assessments. While adoption of USCDI v2 is not a 
requirement for ONC Health IT Certification, pending approval under 
ONC's Standards Version Advancement Process,\924\ developers of 
certified health IT will be able to upgrade their certified health IT 
products to USCDI v2 to support the availability of information about 
social drivers of health.
---------------------------------------------------------------------------

    \924\ Office of the National Coordinator for Health IT. (2022). 
Standards Version Advancement Process. Available at: https://www.healthit.gov/topic/standards-version-advancement-process-svap.
---------------------------------------------------------------------------

    Additional stakeholder efforts underway to expand capabilities to 
capture additional social determinants of health data elements include 
initiatives such as the Gravity Project \925\ to identify and harmonize 
social risk factor data for interoperable electronic health information 
exchange. We note these various efforts and encourage use of tools that 
will meet information exchange standards and facility interoperability. 
We also encourage providers to identify and utilize tools that rely on 
standards-based approaches to data collection and utilization to 
support interoperability of these data.
---------------------------------------------------------------------------

    \925\ See https://thegravityproject.net/.
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    Hospitals are required to submit information for structural 
measures once annually using a CMS-approved web-based data collection 
tool available within the HQR System. We refer readers to section 
IX.E.10. of the preamble of this proposed rule (Form, Manner, and 
Timing of Quality Data Submission) for more details on our previously 
finalized data submission and deadline requirements across measure 
types, and specifically, section IX.E.10.i. for our data and submission 
requirements for structural measures.
    We invite public comment on this proposal.
(2) Proposed Screen Positive Rate for Social Drivers of Health Measure
(a) Background
    The impact of social risk factors on health outcomes has been well-
established in the literature.926 927 928 929 The Physicians 
Foundation reported that 73 percent of the physician respondents to 
their annual survey agreed that social risk factors like housing 
instability and food insecurity would drive health services demand in 
2021.\930\ As noted previously in this proposed rule, recognizing the 
need for a more comprehensive approach to eliminating the health equity 
gap, we have prioritized development and implementation of quality 
measures that will capture social risk factors and facilitate 
assessment of their impact on health outcomes and disparities and 
healthcare utilization and costs.931 932 933 Specifically, 
in the inpatient setting, we aim to identify patient HRSNs as part of 
discharge planning with the intention of promoting linkages with 
relevant community-based services that will

[[Page 28504]]

address those needs and support improvements in health outcomes 
following hospitalization.
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    \926\ Institute of Medicine 2014. Capturing Social and 
Behavioral Domains and Measures in Electronic Health Records: Phase 
2. Washington, DC: The National Academies Press. Available at: 
https://doi.org/10.17226/18951.
    \927\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [bond] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.
    \928\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \929\ 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.
    \930\ The Physicians Foundation. (2020) 2020 Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \931\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. 2016. Accountable Health Communities-Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \932\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [bond] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.
    \933\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
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    While the proposed Screening for Social Drivers of Health process 
measure (discussed previously in section IX.E.5.b.(1).) enables 
identification of individuals with HRSNs, use of the proposed Screen 
Positive Rate for Social Drivers of Health structural measure would 
allow us to estimate the impact of individual-level HRSNs on healthcare 
utilization, including hospitalizations, when evaluating quality of 
care.934 935 936 The Screen Positive Rate for Social Drivers 
of Health structural measure would require the reporting of the 
resulting screen positive rates for each domain. Reporting the social 
drivers of health screen positive rate for each domain would inform 
actionable planning by hospitals towards closing health equity gaps and 
enable the development of individual patient action plans (including 
navigation and referral). We believe this effort could yield actionable 
information to close the health equity gap in CMS programs and 
policies.
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    \934\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \935\ CMS. Accountable Health Communities Model. Accountable 
Health Communities Model [bond] CMS Innovation Center. Available at: 
https://innovation.cms.gov/innovation-models/ahcm. Accessed November 
23, 2021.
    \936\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule, we discussed ongoing 
consideration of potential approaches that could be implemented to 
address health equity through the Hospital IQR Program (85 FR 45414). 
As a result of the feedback we received, we identified the Screen 
Positive Rate for Social Drivers of Health measure to help inform 
efforts to address health equity. This structural measure assesses the 
percent of patients admitted to the hospital who are 18 years or older 
at time of admission who were screened for HRSNs and who screen 
positive for one or more of the core HRSNs, including food insecurity, 
housing instability, transportation problems, utility difficulties, or 
interpersonal safety (reported as five separate rates).\937\ We refer 
readers to section IX.E.5.b.(1).(a). of the preamble of this proposed 
rule where we previously discussed the CMS identification process 
resulting in the selection of these five domains.
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    \937\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
---------------------------------------------------------------------------

    The COVID-19 pandemic underscored the overwhelming impact that 
these five core domains have on disparities, health risk, healthcare 
access, and health outcomes, including premature 
mortality.938 939 Adoption of the Screen Positive Rate for 
Social Drivers of Health structural measure would encourage hospitals 
to track prevalence of specific HRSNs among patients over time and use 
the data to stratify risk as part of quality performance improvement 
efforts. This measure may also prove helpful for patients by providing 
data transparency and signifying hospitals' familiarity, expertise, and 
commitment regarding these issues. Evaluation of AHC Model 
participation demonstrated positive feedback and enhanced trust among 
patients.\940\ This measure also has the potential to reduce healthcare 
provider burnout by systematically acknowledging patients' social needs 
that contribute to adverse health outcomes and linking providers with 
community-based organizations to enhance patient-centered treatment and 
discharge planning.941 942 943 Finally, we believe there is 
a potential further value of this measure to facilitate data-informed 
collaboration with community-based services and targeted community 
investments, and enable quality improvement activities and efforts to 
address disparities, including the development of pathways and 
infrastructure to connect patients to community resources.
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    \938\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \939\ Centers for Disease Control and Prevention. (2019). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \940\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \941\ The Physicians Foundation. (2020). Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \942\ De Marchis, E., Knox, M., Hessler, D., Willard-Grace, R., 
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic 
Capacity to Address Patients' Social Needs. The Journal of the 
American Board of Family Medicine, 32 (1), 69-78.
    \943\ Kung, A., Cheung, T., Knox, M., Willard-Grace, R., 
Halpern, J., et al., (2019). Capacity to Address Social Needs Affect 
Primary Care Clinician Burnout. Annals of Family Medicine. 17 (6), 
487-494. Available at: https://doi.org/10.1370/afm.2470.
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    Underserved communities are disproportionately impacted by HRSNs, 
such as food insecurity, that impact health outcomes and 
cost.944 945 Unmet HRSNs have been directly associated with 
healthcare utilization, including hospitalization, especially for 
hospitals that serve such communities.\946\ In pursuit of eliminating 
health equity gaps, we are focused on supporting effective and 
sustainable collaboration between healthcare delivery and community-
based services organizations to meet the unmet needs of underserved 
populations. Reporting data from both the Screening for Social Drivers 
of Health measure and the proportion of admitted patients who screen 
positive for HRSNs across the five domains (via this complementary 
measure) would enable quantification of the levels of HRSNs in local 
communities served by a hospital and greater visibility into the 
interaction between HRSNs and health status, healthcare utilization, 
and quality of care. These measures would harmonize, as it is important 
to know both if a hospital or health system is using a screening tool 
and the results from the screening. Ultimately, we believe that, 
together, these two social drivers of health measures could enhance 
collaboration to meet the needs of underserved populations by 
identifying high-risk individuals who would benefit from engagement 
with community-based service providers. As with the theory of change 
for the AHC Model, we would expect such collaboration, and associated 
increase in capacity and community investments, to yield a net 
reduction in costly healthcare utilization, such as ED visits and 
avoidable hospitalizations and promote more appropriate healthcare 
service consumption.\947\
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    \944\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \945\ US Department of Agriculture Economic Research Service 
(2021). Food Security in the U.S. Accessed January 18, 2022. 
Available at: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics.aspx. 
Accessed January 18, 2022.
    \946\ 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.
    \947\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [bond] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.

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[[Page 28505]]

    Pursuant to Meaningful Measures 2.0, this measure addresses the 
``healthcare equity'' priority area and aligns with our commitment to 
introduce plans to close health equity gaps and promote equity through 
quality measures, including to ``develop and implement measures that 
reflect social and economic determinants.'' \948\ Under CMS' Meaningful 
Measures Framework, the Screen Positive Rate for Social Drivers of 
Health structural measure addresses the quality priority of ``Work with 
Communities to Promote Best Practices of Healthy Living'' through the 
Meaningful Measures Area of ``Equity of Care.'' \949\ Development and 
proposal of this measure also aligns with our strategic pillar to 
advance health equity by addressing the health disparities that 
underlie our health system.\950\
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    \948\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \949\ Centers for Medicare & Medicaid Services. (2020). CMS 
Measures Management System Blueprint (Blueprint v 16.0). Available 
at: https://www.cms.gov/Medicare/QualityInitiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf.
    \950\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
---------------------------------------------------------------------------

(b) Overview of Measure
    The Screen Positive Rate for Social Drivers of Health structural 
measure is intended to enhance standardized data collection that can 
identify high-risk individuals who will benefit from connection via the 
hospital to targeted community-based services.\951\ The measure would 
identify the proportion of patients who screened positive on the date 
of hospital admission for one or more of the following five HRSNs: Food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety. Hospitals would report this 
measure as five separate rates. We note that this measure is intended 
to provide information to hospitals on the level of unmet social needs 
among patients served, and not for comparison between hospitals.
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    \951\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights (June 
2021). Available at: https://innovation.cms.gov/media/document/ahcmscreeningtool-companion. Accessed November 23, 2021.
---------------------------------------------------------------------------

    The Screen Positive Rate for Social Drivers of Health (MUC21-134) 
measure was included in the publicly available ``List of Measures Under 
Consideration for December 1, 2021'' (MUC List), a list of measures 
under consideration for use in various Medicare and Medicaid 
programs.\952\ The MAP Rural Health Advisory Group and the Health 
Equity Advisory Group reviewed the measure on December 8, 2021, and 
December 9, 2021, respectively. Both groups expressed concerns about 
standardization of the measure and operationalization approaches that 
will yield real solutions for patients and clinicians. We intend to 
prioritize consideration of potential standardization approaches in 
future rulemaking. The MAP Health Equity Advisory Group members 
emphasized the importance of explaining to patients that self-report of 
HRSNs will not be used to stigmatize them or reduce healthcare 
benefits. We recommend that hospitals incorporate inclusive language in 
their screening activities to address this potential concern among 
patient and caregiver respondents. The measure developer stated that 
the focus of this measure is to establish standard social drivers of 
health screening measures, referencing data from the AHC Model as 
having demonstrated the feasibility of implementing HRSN screening and 
how essential the screening results are to enable action. Stakeholders' 
support for the measure was attributed, in part, to potential for 
hospitals, health systems, and community-based organizations to use the 
data to identify and prioritize opportunities for investment in 
community resources to address these HRSNs. Likewise, discussants 
reported that screening for HRSNs has allowed payors to enhance their 
understanding of the scope of such challenges among their patients, 
target resource investments, initiate changes in benefits designs, and 
prioritize community partnerships. We expect that hospitals will report 
similar findings and use the data to enhance resource allocation that 
will support referrals to relevant community-based services 
organizations.
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    \952\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
---------------------------------------------------------------------------

    On December 15, 2021, the MAP Hospital Workgroup met and reviewed 
the MUC List, including the Screen Positive Rate for Social Drivers of 
Health (MUC21-134) measure. Similar concerns and support as raised 
during the MAP Health Equity Advisory Group and MAP Rural Health 
Workgroup were also discussed during the MAP Hospital Workgroup 
meeting. The MAP Hospital Workgroup voted to conditionally support the 
measure for rulemaking pending NQF endorsement. On January 19, 2022, 
the MAP Coordinating Committee met and reviewed the MUC List including 
the Screen Positive Rate for Social Drivers of Health (MUC21-134) 
measure. The Coordinating Committee upheld the vote of the MAP Hospital 
Workgroup.\953\
---------------------------------------------------------------------------

    \953\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=9.
---------------------------------------------------------------------------

    We intend to submit this measure in future for NQF endorsement. We 
note that under section 1866 (b)(3)(B)(viii)(IX)(aa) of the Act, each 
measure specified by the Secretary shall be endorsed by the entity with 
a contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 on 
this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    If finalized, this measure (alongside the Screening for Social 
Drivers of Health) would be the first patient-level measurement of 
social drivers of health. We believe this is an important measure to 
include because of the connection between HRSNs and patient health. 
When patients are admitted to hospital for inpatient care, there is 
substantial opportunity to screen for HRSNs and include relevant 
community services referrals as part of discharge planning. Providers 
would be able to identify if patients have unmet health-related social 
needs and the rate would help gauge what percentage of the population 
they serve (who are screened) indicate they need help, by HRSN domain. 
We envision that hospitals could implement and assess their quality 
improvement efforts to address patients' unmet social needs such as by 
connecting admitted patients identified with unmet social

[[Page 28506]]

needs to local community resources. These efforts could include 
referring patients to services available through the hospital or the 
community. The information from this structural measure may serve as a 
baseline in future to assess the proportion of admitted patients whose 
unmet social needs were addressed by the hospital during the hospital 
stay to support safe discharge and improved health outcomes.
    Measure specifications for this measure are available on the 
QualityNet website at https://qualitynet.cms.gov (or other successor 
CMS designated websites).
(c) Cohort
    The Screen Positive Rate for Social Drivers of Health is a 
structural measure that provides information on the percent of patients 
admitted for an inpatient hospital stay and who are 18 years or older 
on the date of admission, were screened for an HSRN, and who screen 
positive for one or more of the following five HRSNs: Food insecurity, 
housing instability, transportation problems, utility difficulties, or 
interpersonal safety.
(d) Numerator
    The numerator consists of the number of patients admitted for an 
inpatient hospital stay who are 18 years or older on the date of 
admission, who were screened for an HSRN, and who screen positive for 
having a need in one or more of the following five HRSNs (calculated 
separately): Food insecurity, housing instability, transportation 
needs, utility difficulties or interpersonal safety.
(e) Denominator
    The denominator consists of the number of patients admitted for an 
inpatient hospital stay who are 18 years or older on the date of 
admission and are screened for an HSRN (food insecurity, housing 
instability, transportation needs, utility difficulties and 
interpersonal safety) during their hospital inpatient stay. The 
following patients would be excluded from the denominator: (1) Patients 
who opt-out of screening; and (2) patients who are themselves unable to 
complete the screening during their inpatient stay and have no 
caregiver able to do so on the patient's behalf during their inpatient 
stay.
(f) Measure Calculation
    The result of this measure would be calculated as five separate 
rates. Each rate is derived from the number of patients admitted for an 
inpatient hospital stay and who are 18 years or older on the date of 
admission, screened for an HSRN, and who screen positive for each of 
the five HRSNs--food insecurity, housing instability, transportation 
needs, utility difficulties, or interpersonal safety--divided by the 
total number of patients 18 years or older on the date of admission 
screened for all five HRSNs.
(g) Data Submission and Reporting
    We are proposing voluntary reporting of the Screen Positive Rate 
for Social Drivers of Health measure beginning with the CY 2023 
reporting period, followed by mandatory reporting on an annual basis, 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years.
    Hospitals are required to submit information for structural 
measures once annually using a CMS-approved web-based data collection 
tool available within the HQR System. We refer readers to section 
IX.E.10. (Form, Manner, and Timing of Quality Data Submission) of the 
preamble of this proposed rule for more details on our previously 
finalized data submission and deadline requirements across measure 
types, and specifically, section IX.E.10.i. for our data and submission 
requirements for structural measures.
    We invite public comment on this proposal.
c. Proposed Cesarean Birth eCQM Beginning With the CY 2023 Reporting 
Period/FY 2025 Payment Determination With Mandatory Reporting Beginning 
With the CY 2024 Reporting Period/FY 2026 Payment Determination and for 
Subsequent Years
    In this proposed rule, we are proposing to adopt the Cesarean Birth 
eCQM as one of the eCQMs in the Hospital IQR Program measure set that 
hospitals can self-select to report for the CY 2023 reporting period/FY 
2025 payment determination. We are also proposing to make reporting of 
this eCQM mandatory beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years.
(1) Background
    A Cesarean section (C-section) is the use of surgery to deliver a 
baby (or babies) in lieu of vaginal delivery. The procedure entails 
surgical and anesthesia risks and requires mothers to undergo several 
days of inpatient, post-operative recovery. A C-section may occur on an 
elective or nonelective basis.\954\ Elective C-sections may be planned 
due to the presence of a complicating medical condition, abnormal 
positioning of the baby, or other medical indications.\955\ Elective C-
sections may also occur for non-medical reasons, including maternal 
preference (in consultation with their healthcare provider), local 
practice patterns, malpractice risk, or other 
factors.956 957 958 C-sections that occur upon a mother's 
request are rare, but occur after consultation with a clinician.\959\
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    \954\ National Quality Forum. Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/0471.
    \955\ Xu, X., Yan, J.Y., Chen, L.C. (2021). Risk factors and 
maternal-fetal outcomes of pregnancies complicated by pre-eclampsia, 
following cesarean section after a trial vaginal birth. Chin Med J 
(Engl). 2021;134(18):2249-2251. doi:10.1097/CM9.0000000000001452.
    \956\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol. 
2014 Mar;210(3):179-93. doi: 10.1016/j.ajog.2014.01.026.
    \957\ Schifrin BS, Cohen WR. (2013). The effect of malpractice 
claims on the use of caesarean section. Best Pract Res Clin Obstet 
Gynaecol. 2013 Apr;27(2):269-83. doi: 10.1016/j.bpobgyn.2012.10.004. 
Epub 2012 Dec 1. Review.
    \958\ Chen CS, Liu TC, Chen B, Lin CL. (2014). The failure of 
financial incentive? The seemingly inexorable rise of cesarean 
section. Soc Sci Med. 2014 Jan;101:47-51. doi: 10.1016/
j.socscimed.2013.11.010. Epub 2013 Nov 15.
    \959\ Committee on Obstetric Practice. (2019) Cesarean Delivery 
on Maternal Request. The American College of Obstetricians and 
Gynecologists, 133(1). Available at: https://www.acog.org/clinical/clinical-guidance/committee-opinion/articles/2019/01/cesarean-delivery-on-maternal-request.
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    The total rate of (elective and nonelective) C-sections has risen 
in the U.S. since the 1990s.\960\ C-sections accounted for 31.8 percent 
of U.S. live births in 2020,\961\ and there is a considerable amount of 
variation in the rates based on U.S. region, state, and healthcare 
institution.\962\ There is also substantial variability across races 
and ethnicities; the rate of C-sections is: 30.8 percent among Non-
Hispanic White women, 36.3 percent among Black women, 28.8 percent 
among American Indian or Alaska Native women, 32.6 among Asian women, 
and 31.4 percent among Hispanic women.\963\ U.S.

[[Page 28507]]

practice guidelines have not indicated an optimal rate of C-section or 
an appropriate variance rate; while international studies suggest a 
preference for a lower range than current U.S. 
rates.964 965 966
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    \960\ Osterman, M.J.K., Martin, J.A. (2014). Trends in Low-risk 
Cesarean Delivery in the United States, 1990-2013. National Vital 
Statistics Reports, 63(6): 1-16.
    \961\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \962\ Kozhimannil, K.B., Law, M.R. & Virnig, B.A. (2013). 
Cesarean delivery rates vary tenfold among US hospitals; reducing 
variation may address quality and cost issues. Health Affairs, 
32(3): 527-35.
    \963\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \964\ National Collaborating Centre for Women's and Children's 
Health. (2011). Caesarean Section: NICE Clinical Guideline 
(commissioned by the United Kingdom National Institute for Health 
and Clinical Excellence).
    \965\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \966\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
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    When medically indicated, a C-section can effectively prevent 
maternal and neonatal morbidity and mortality.\967\ However, clinicians 
and consensus groups agree that increased C-section rates have not 
improved overall perinatal outcomes and that C-sections are 
overused.968 969 Additionally, low risk C-sections--defined 
as deliveries by nulliparous, term, or singleton vertex (NTSV) women--
have seen an increase. ``Nulliparous'' women are those who have never 
given birth to a live baby but may have had a miscarriage, stillbirth, 
or elective abortion. They have a lower risk of maternal morbidity and 
mortality during vaginal birth than do women who have undergone a 
previous C-section.970 971 ``Term'' indicates a term birth 
(that is on or after 37 weeks' gestation), which has better outcomes 
than a preterm birth, and ``singleton'' refers to the birth of a single 
child during one delivery. Vertex presentations, which are those where 
the child is positioned headfirst, carry less risk than breech or 
transverse presentations.\972\ The rate of low-risk C-section 
deliveries also varies by race and ethnicity; low-risk C-section births 
in 2020 were: 24.9 percent among NTSV Non-Hispanic White women, 30.6 
percent among NTSV Non-Hispanic Black women, 23.6 percent among NTSV 
American Indian or Alaska Native women, 27.7 percent among NTSV Asian 
women, and 25.2 percent among NTSV Hispanic women.\973\ A majority of 
which are still higher than the Centers for Disease Control and 
Prevention's (CDC's) Healthy People 2020 goal to reduce C-section 
births among NTSV women to 23.9 percent by 2020.\974\
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    \967\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \968\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \969\ National Collaborating Centre for Women's and Children's 
Health. (2011). Caesarean Section: NICE Clinical Guideline 
(commissioned by the United Kingdom National Institute for Health 
and Clinical Excellence).
    \970\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \971\ National Quality Forum. (2016). Perinatal and Reproductive 
Health 2015-2016 Final Report. Available at: https://www.qualityforum.org/Publications/2016/12/Perinatal_and_Reproductive_Health_2015-2016_Final_Report.aspx.
    \972\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \973\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \974\ Centers for Disease Control and Prevention, Maternal Child 
and Infant Health. Healthy People 2020. Available at: https://www.cdc.gov/nchs/data/hpdata2020/HP2020MCR-C26-MICH.pdf.
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    C-sections have higher morbidity and mortality (9.2 percent) than 
vaginal deliveries (8.6 percent).\975\ Existing literature largely does 
not distinguish whether inferior outcomes derive from cause (higher-
risk patients undergo C-section) or effect (surgery carries inherent 
risks due to anesthesia, bleeding, infection, post-operative recovery, 
etc.).\976\ However, taking an aggregate view of multiple studies over 
time, it appears that C-sections carry a higher risk of subsequent 
miscarriage, placental abnormalities, and repeat C-section.\977\ The 
rates of transfusions, ruptured uteri, unplanned hysterectomies, and 
intensive care unit (ICU) admissions are higher among women who deliver 
via C-section for the first time than those who deliver vaginally for 
the first time across all races and ethnicities. However, non-Hispanic 
Black women who deliver via C-section for the first time had the 
highest rates of uterine rupture and ICU admission compared with all 
other races and ethnicities.\978\
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    \975\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \976\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \977\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \978\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports. Volume 64, 
Number 4. Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
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    In terms of neonatal outcomes, C-sections have higher respiratory 
morbidity (1 percent to 4 percent) than vaginal births (<1 
percent).\979\ Again, it is unclear whether this is because of cause 
(high-risk fetuses are more likely to be delivered by C-section) or 
effect (surgery carries inherent risks due to anesthesia, bleeding, 
infection, post-operative recovery, etc.). The medical indications for 
a C-section entail broad provider discretion because of the need to: 
(1) Balance any conflicting medical conditions of mother versus fetus; 
and (2) balance the C-section against any other competing clinical 
considerations or external constraints (for example, availability of 
operation room, personnel, and/or blood). It should also be noted that 
reducing the rate of C-sections does not result in worse outcomes for 
the mother or newborn, with newborn complications even declining in 
some hospitals with significant C-section reductions.\980\
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    \979\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \980\ Main, E.K., Chang, S.C., Cape, V., Sakowski, C. Smith, H., 
Vasher, J. (2019) Safety Assessment of a Large-Scale Improvement 
Collaborative to Reduce Nulliparous Cesarean Delivery Rates. 
Obstetrics & Gynecology, 133(4):613-623. doi: 10.1097/
AOG.0000000000003109.
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    Furthermore, C-sections receive higher reimbursement than vaginal 
deliveries (typically about 50 percent more). The prevalence of non-
medically indicated C-sections carries economic impacts because C-
sections are more expensive than vaginal deliveries and may be 
accompanied by adverse outcomes and complications, which similarly have 
substantial cost implications.\981\
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    \981\ Kozhimannil, K.B., Law, M.R. & Virnig, B.A. (2013). 
Cesarean delivery rates vary tenfold among US hospitals; reducing 
variation may address quality and cost issues. Health Affairs, 
32(3): 527- 35. doi: 10.1377/hlthaff.2012.1030.
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    We believe this eCQM will help further our goal of addressing 
maternal health outcomes in the Hospital IQR Program. Currently, the 
Hospital IQR Program includes two measures that address improving 
maternal health: The Elective Delivery measure (PC-01) (77 FR 53530) 
and the Maternal Morbidity Structural measure (86 FR 45361 through 
45365). However, neither of these measures directly address the factors 
contributing to maternal mortality, such as the high rates of C-
sections in the U.S. We believe adopting measures like the Cesarean 
Birth eCQM presents unique opportunities for large-scale quality 
measurement and activities that can improve the short- and long-

[[Page 28508]]

term health outcomes for mothers and children.\982\ We also refer 
readers to section IX.E.5.d. of the preamble of this proposed rule, 
where we are also proposing the adoption of the Severe Obstetric 
Complications eCQM as part of the Hospital IQR Program measure set.
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    \982\ Department of Health and Human Services. (2020). Healthy 
Women, Healthy Pregnancies, Health Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
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    In response to increases in low-risk C-sections, HHS has included a 
goal of reducing low-risk C-sections by 25 percent in the next five 
years as part of the Maternal Action Plan.\983\ To build on the 
previously established HHS Maternal Health Action Plan, the Vice 
President's nationwide call to action to reduce maternal morbidity and 
mortality, and ongoing efforts with HHS and across the Federal 
Government,\984\ the Biden-Harris Administration seeks to use a whole-
of-government approach for improving maternal health and advancing 
maternal health equity that reduces maternal mortality and morbidity, 
reduces persistent disparities, and among other activities, increases 
hospital participation in HHS-sponsored maternal health quality 
improvement initiatives. A critical focus is reducing existing 
disparities in maternal health outcomes across race, ethnicity, and 
geographic area. The Cesarean Birth eCQM is intended to facilitate 
safer patient care by assessing the rate of NTSV C-sections to 
ultimately reduce the occurrence of non-medically indicated C-sections, 
promoting adherence to recommended clinical guidelines, and encouraging 
hospitals to track and improve their practices of appropriate 
monitoring and care delivery for pregnant and postpartum patients. The 
2020 performance measurement data for the Cesarean Birth eCQM indicates 
a 27.5 percent average rate of C-section birth for NTSV women (across 
15 hospitals, N=933). A group of subject matter experts for NQF noted 
that decreasing the rate of non-medically indicated C-sections can 
result in increased patient safety, decreased maternal and neonatal 
morbidity, and substantial savings in healthcare costs.\985\ 
Additionally, considering that Non-Hispanic Black women have the 
highest rate of low-risk C-sections along with the highest rates of 
uterine ruptures and ICU admissions as a result of C-sections, reducing 
low-risk C-section rates could improve maternal health outcomes for 
this population in particular by reducing the excess maternal morbidity 
they experience.986 987 988
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    \983\ Department of Health and Human Services. HHS Initiative to 
Improve Maternal Health. Available at: https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \984\ Department of Health and Human Services. HHS Initiative to 
Improve Maternal Health. Available at: https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \985\ National Quality Forum. (2008) Perinatal and Reproductive 
Health ProjectNQF #0471 PC-02 Cesarean Section: Measure Submission 
and Evaluation Worksheet 5.0. Available at: https://www.qualityforum.org/Projects/n-r/Perinatal_Care_Endorsement_Maintenance_2011/0471.aspx.
    \986\ Department of Health and Human Services. (2020). Healthy 
Women, Healthy Pregnancies, Health Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
    \987\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports. Volume 64, 
Number 4. https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
    \988\ Debbink, M.P. Ugwu, L.G. Grobman, W.A. et al. (2022) 
Racial and Ethnic Inequities in Cesarean Birth and Maternal 
Morbidity in a Low-Risk, Nulliparous Cohort. Obstetrics & 
Gynecology;139(1): 73-82. doi: 10.1097/AOG.0000000000004620.
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    Under CMS' Meaningful Measures Framework,\989\ the Cesarean Birth 
eCQM 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.'' \990\ Additionally, pursuant 
to Meaningful Measures 2.0,\991\ this measure addresses the ``Safety'' 
priority area and aligns with our commitment to a patient-centered 
approach in quality measurement to ensure that patients are safe and 
receive the highest quality care.\992\ Finally, this measure aligns 
with our strategic priorities including the pillar to advance health 
equity by addressing the health disparities that underlie our health 
system.\993\
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    \989\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \990\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \991\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \992\ Centers for Medicare & Medicaid Services. (2021) CMS 
Quality Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf.
    \993\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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    Therefore, in this proposed rule, we are proposing to adopt the 
Cesarean Birth eCQM beginning with the CY 2023 reporting period/FY 2025 
payment determination. As part of the currently finalized eCQM 
reporting and submission requirements, hospitals must report on three 
self-selected eCQMs and the Safe Use of Opioids--Concurrent Prescribing 
eCQM, for a total of four eCQMs (85 FR 58939). We are proposing to 
adopt this measure such that hospitals may choose to report it as one 
of the three self-selected eCQMs for the CY 2023 reporting period/FY 
2025 payment determination. After which, beginning with the CY 2024 
reporting period/FY 2026 payment determination and for subsequent 
years, we are proposing that the Cesarean Birth eCQM would have to be 
reported by all hospitals, except those hospitals that do not have an 
obstetrics department and do not perform deliveries. We also refer 
readers to section IX.E.10.e. of the preamble of this proposed rule for 
our proposal to modify the eCQM reporting and submission requirements 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination.
(2) Overview of Measure
    This measure assesses the rate of NTSV pregnancies delivered via C-
section. Determining the NTSV C-section rate permits a hospital to 
compare its outcomes to other hospitals while focusing only on the NTSV 
population which can impact the rates of first time and possibly 
subsequent C-section rates. We note that the NQF has endorsed the 
chart-abstracted form of this measure (PC-02: Cesarean Birth, NQF 
#0471) as a voluntary consensus standard since 2008 and continuously 
renewed its endorsement (most recently in 2020).\994\ The Rural Health 
Workgroup of the NQF's MAP also identified the chart-abstracted version 
as a measure that holds particular relevance for rural hospitals, 
noting how important it is to focus on best practices in obstetric care 
in rural areas.\995\ We acknowledge that there are instances where C-
sections are medically

[[Page 28509]]

indicated, and we emphasize that this measure is not intended to 
discourage practitioners from performing C-sections when they are 
medically indicated. We believe that assessing the rate of NTSV C-
sections may ultimately reduce the occurrence of non-medically 
indicated C-sections. We encourage hospitals whose measure rates are 
higher than rates at other hospitals to explore and evaluate 
differences in the clinical management of women in labor.\996\ Further, 
this measure would help ensure that the Hospital IQR Program includes 
measures which are applicable to rural hospitals.
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    \994\ National Quality Forum. Quality Measure PC-02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/0471.
    \995\ National Quality Forum, Measure Applications Partnership. 
(2018). A Core Set of Rural-Relevant Measures and Measuring and 
Improving Access to Care: 2018 Recommendations from the MAP Rural 
Health Workgroup. Available at: https://www.qualityforum.org/Publications/2018/08/MAP_Rural_Health_Final_Report_-_2018.aspx.
    \996\ Centers for Medicare & Medicaid Services. (2015). Cesarean 
Birth (PC-02) Measure Public Comment Summary. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/PC-02-Public-Comment-Summary-Memo.pdf?msclkid=a582dfc0b52411ecbab8ba3255a5b678.
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    The Cesarean Birth eCQM was included in a publicly available 
document entitled ``List of Measures Under Consideration for December 
1, 2018'' (MUC List).\997\ The MAP's Final Report on February 15, 2019 
conditionally supported the eCQM for rulemaking pending NQF evaluation 
and endorsement.\998\ The MAP suggested further feasibility testing, 
consultation with multiple stakeholders, and examination of unintended 
consequences.
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    \997\ Centers for Medicare & Medicaid Services. (2018). List of 
Measures Under Consideration for December 1, 2018. Available at: 
https://www.cms.gov/files/document/2018rmuc-listclearancerpt.pdf.
    \998\ National Quality Forum. (2019). Measure Applications 
Partnership, MAP 2019 Considerations for Implementing Measures in 
Federal Programs: Hospitals Final Report. Available at: https://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
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    Given the importance of this measure, we sought stakeholder input 
on the potential future inclusion of this measure in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19491 through 19494). Many stakeholders 
supported inclusion of the measure, though some stakeholders shared 
similar concerns as the MAP (84 FR 42493 through 42496). Thereafter, 
the measure steward conducted further reliability and validity testing 
in 2021 and submitted the measure to the NQF for consideration of 
endorsement in Spring 2022. Given the additional testing performed and 
feedback provided, we are proposing to adopt this measure in this 
proposed rule.
    We also note that in 2020, the measure steward introduced the 
Cesarean Birth eCQM as one of the available eCQMs hospitals can choose 
for data submission to meet The Joint Commission's ORYX[supreg] 
requirements.\999\ The ORYX initiative integrates performance 
measurement data into The Joint Commission's accreditation 
process.\1000\ Currently, we understand that The Joint Commission uses 
both the chart-abstracted (PC-02) and the eCQM versions. A total of 15 
hospitals (representing 6 sites) submitted production data for one 
quarter of calendar year 2020. We note that the measure steward reached 
out to all 15 hospitals to recruit sites willing to participate in 
reliability testing on the data submitted. Seven hospitals 
(representing 2 sites) volunteered. One site is a system representing 
six hospitals. The seventh hospital is a stand-alone facility that uses 
a different EHR system. During the third quarter of 2021, feasibility 
scorecards were completed, and the feasibility rate was found to be 98 
percent across the two EHR systems. Reliability and validity testing 
revealed the Cesarean Births eCQM to have a measure outcome agreement 
rate of 83.7 percent with a kappa score of .750 indicating substantial 
agreement. Overall, the data element agreement rate for all hospitals 
was 92.2 percent.
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    \999\ The Joint Commission. (2020). 2020 ORYX Performance 
Measure Reporting Requirements. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/oryx/cy2020-oryx-reporting-requirements_.pdf.
    \1000\ The Joint Commission. Accreditation-ORYX. Available at: 
https://www.jointcommission.org/measurement/reporting/accreditation-oryx/.
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    As mentioned above, the NQF has endorsed the chart-abstracted form 
of this measure. Additionally, the measure steward submitted the eCQM 
to the NQF for consideration of endorsement during Spring 2022. We note 
that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that any 
measure specified by the Secretary must have been endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 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 note 
that while the chart-abstracted version is endorsed, we were unable to 
identify any other NQF-endorsed measures on this topic, and, therefore 
we believe the exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act applies.
    The measure specifications for the Cesarean Birth eCQM can be found 
on the eCQI Resource Center website, available at https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Measure Calculation
    This eCQM assesses the rate of nulliparous women with a term, 
singleton baby in a vertex position delivered by C-section birth.\1001\ 
The eCQM uses one of the following: Nulliparous defined as Parity = 0, 
Gravidity = 0, or Preterm and Term both = 0. Parity is the number of 
completed pregnancies reaching 20 weeks gestation regardless of the 
number of fetuses or outcome of the pregnancy. Gravidity is the number 
of pregnancies, current and past, regardless of the pregnancy outcome. 
Preterm is less than 37 weeks and 0 days, and Term is greater than or 
equal to 37 weeks and 0 days using best Estimated Due Delivery (EDD).
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    \1001\ The Joint Commission. (2021). eCQM Specifications 2022 
Reporting Period. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/specification-manuals/2022-reporting-period/january-2022/ecqm_specifications_reportingperiod_2022.zip.
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(5) Outcome
    The outcome of interest is the number of C-sections to NTSV women 
divided by all live, term (>=37 weeks gestation) singleton deliveries 
to NTSV women.
(6) Cohort
    The cohort consists of all patients in the denominator: Nulliparous 
women with a singleton, vertex fetus at >=37 weeks of gestation who 
deliver a liveborn infant. The cohort includes all pertinent patients 
regardless of payer (for example, Medicare, Medicaid, other public 
programs, private insurance, self-pay, or charity care) or admission 
source (for example, home, ED, nursing home, hospice, another hospital, 
or law enforcement).
(7) Numerator
    The measure numerator consists of the subset of patients delivering 
by C-section.

[[Page 28510]]

(8) Denominator
    The measure denominator consists of the number of nulliparous women 
with a singleton, vertex fetus at >=37 weeks of gestation who deliver a 
liveborn infant.
(9) Exclusion Criteria
    The measure excludes patients with abnormal presentations or 
placenta previa.
(10) Risk Adjustment
    This measure is not currently risk adjusted. When developing the 
measure, the exclusion criteria were chosen to ensure that the focus 
population would be women with NTSV pregnancies. Nulliparous women are 
those experiencing their first birth. These women have a lower risk of 
maternal morbidity and mortality during a vaginal birth delivery than 
do women who have undergone a previous C-section.\1002\ The population 
of women in the denominator as a result of the exclusions allow the 
measure to focus on a more homogeneous group of women where the 
greatest improvement opportunity exists as evidenced by variation in 
rates of NTSV C-sections, indicating clinical practice patterns may 
affect this rate.\1003\ Lowering the C-section rate in NTSV pregnancies 
is important because C-sections may carry a higher risk of subsequent 
miscarriage, placental abnormalities, and repeat C-section.\1004\ The 
rates of ruptured uteri, unplanned hysterectomies, and ICU admission 
are higher among women who deliver via C-section for the first time 
than those who deliver vaginally for the first time across all races 
and ethnicities. However, non-Hispanic Black women who deliver via C-
section for the first time had the highest rates of uterine rupture and 
ICU admission compared with all other races.\1005\ Focusing on the NTSV 
population aligns with the measure intent to have a significant effect 
on cesarean birth rates. We believe this could encourage a decrease in 
C-section rates in the NTSV population, which would in turn have a 
meaningful impact on future pregnancies and maternal health. Including 
a comprehensive set of maternal medical exclusions would add data 
collection burdens without commensurate benefit.
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    \1002\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \1003\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \1004\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \1005\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports, 64(4). 
Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
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(11) Data Submission and Reporting
    We refer readers to: Section IX.E.10.e. of the preamble of this 
proposed rule for a discussion of our previously finalized eCQM 
reporting and submission policies; and section IX.E.13.b. for the 
public reporting of eCQM data. Additionally, we refer readers to 
section IX.E.10.e.(4). where we discuss the use of the zero denominator 
declarations and case threshold exemption policies for hospitals.
    We also refer readers to four related proposals discussed in the 
preamble of this proposed rule: (1) Section IX.E.10.e. where we discuss 
newly proposed modifications to our reporting and submission 
requirements for eCQMs, including a discussion of our proposal to 
require hospitals to report on the Cesarean Birth eCQM; (2) section 
IX.E.5.d. for our proposal to adopt the Severe Obstetric Complications 
eCQM; (3) section IX.H.10.a.(2). of the preamble of this proposed rule 
for a discussion of similar proposals to adopt these two perinatal 
eCQMs in the Medicare Promoting Interoperability Program for Eligible 
Hospitals and Critical Access Hospitals (CAHs); and (4) section IX.E.8. 
where we are proposing to establish a publicly-reported hospital 
designation to capture the quality and safety of maternity care and 
other related activities in advancing maternal health equity.
    We invite public comment on this proposal.
d. Proposed Severe Obstetric Complications eCQM Beginning With the CY 
2023 Reporting Period/FY 2025 Payment Determination With Mandatory 
Reporting Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
    In this proposed rule, we are proposing to adopt the Severe 
Obstetric Complications eCQM as one of the eCQMs in the Hospital IQR 
Program measure set on which hospitals can self-select to report for 
the CY 2023 reporting period/FY 2025 payment determination. We are also 
proposing to make reporting of this eCQM mandatory beginning with the 
CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years.
(1) Background
    Severe maternal morbidity (SMM) refers to unexpected outcomes due 
to complications at labor and delivery that result in significant 
consequences to a woman's health, and includes, but is not limited to, 
hemorrhage, embolism, severe hypertension, stroke, and other serious 
complications.\1006\ Despite the highest rate of spending on maternity 
care, totaling $1.4 billion dollars in FY 2021,\1007\ the U.S. ranks 
worse than most other developed nations in pregnancy-related deaths and 
the rate of SMM is continuing to steadily increase.1008 1009 
As reported by the CDC, the overall rate of SMM increased almost 200 
percent, from 49.5 per 10,000 delivery hospitalizations in 1993 to 144 
per 10,000 delivery hospitalizations in 2014.1010 1011 1012 
Increasing rates of SMM are resulting in increased healthcare costs, 
longer hospitalization stays, and short- and long-term negative 
outcomes to women's health.1013 1014 1015 1016
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    \1006\ Centers for Disease Control and Prevention. (2021). 
Severe Maternal Morbidity in the United States. Available at: 
https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \1007\ Kaiser Family Foundation. (2021). The US Government and 
Global Maternal and Child Health Efforts. Available at: https://www.kff.org/global-health-policy/fact-sheet/the-u-s-government-and-global-maternal-and-child-health-efforts/.
    \1008\ Centers for Disease Control and Prevention. (2021). 
Severe Maternal Morbidity in the United States. Available at: 
https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \1009\ Maternal Health Task Force. (2015). Maternal Health in 
the United States. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \1010\ Centers for Disease Control and Prevention. (2021). 
Severe Maternal Morbidity in the United States. Available at: 
https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \1011\ Leonard SA et al. (2019). Racial and ethnic disparities 
in severe maternal morbidity prevalence and trends. Annals of 
epidemiology. 2019;33:30-36.
    \1012\ Petersen EE, Davis NL, Goodman D, et al. (2019). Vital 
signs: Pregnancy-related deaths, United States, 2011-2015, and 
strategies for prevention, 13 states, 2013-2017. Morbidity and 
Mortality Weekly Report. 68(18):423.
    \1013\ Vesco KK et al. (2020). Costs of Severe Maternal 
Morbidity During Pregnancy in US Commercially Insured and Medicaid 
Populations: An Observational Study. Maternal and Child Health 
Journal, 24(1):30-38.
    \1014\ Chen HY, Chauhan SP, Blackwell SC. (2018). Severe 
Maternal Morbidity and Hospital Cost among Hospitalized Deliveries 
in the United States. Am J Perinatol. 2018 Nov;35(13):1287-1296. 
doi: 10.1055/s-0038-1649481. Epub 2018 May 3. PMID: 29723900.
    \1015\ Lin, Ching-Ching Claire, et al. (2020). ``Rural-urban 
differences in delivery hospitalization costs by severe maternal 
morbidity status.'' Annals of Internal Medicine 173.11_Supplement: 
S59-S62.
    \1016\ Premier Inc. (2019). Report 2: The Added Cost of 
Complications During and After Delivery. Available at: https://explore.premierinc.com/Global/FileLib/Quick_Start_Cloud/19250_BudleofJoyReport_Report2_v7_digital.pdf.

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[[Page 28511]]

    Without proper treatment and awareness surrounding SMM, such 
complications can lead to mortality.\1017\ While partially attributed 
to changes in reporting standards, the maternal mortality rate has also 
risen in the U.S. from 17 deaths per 100,000 live births in 1990 to 26 
deaths per 100,000 live births in 2015.\1018\ Recent maternal mortality 
data from 2018 reveal that 658 women died from pregnancy-related 
complications, resulting in a rate of 17.4 deaths per 100,000 live 
births, with 77 percent of the deaths attributed to direct obstetric 
causes like hemorrhage, preeclampsia, obstetric embolism, and other 
complications.1019 1020 Researchers have found that the 
presence of select maternal morbidities such as chronic hypertension, 
preeclampsia, and sepsis were strongly associated with increased odds 
of mortality at the time of delivery.1021 1022 Similar to 
maternal mortality, the existing literature on maternal morbidity 
indicates that a significant proportion of maternal morbidity is highly 
preventable.\1023\ Therefore, timely and appropriate treatment of 
maternal morbidities is imperative to prevent complications that can 
lead to maternal mortality.\1024\
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    \1017\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17-B22.
    \1018\ Maternal Health Task Force. (2015). Maternal Health in 
the United States. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \1019\ Hoyert, D.L., & Mini[ntilde]o, A.M. (2020). Maternal 
mortality in the United States: Changes in coding, publication, and 
data release, 2018.
    \1020\ St Pierre A, Zaharatos J, Goodman D, Callaghan WM. 
Challenges and Opportunities in Identifying, Reviewing, and 
Preventing Maternal Deaths. Obstet Gynecol. 2018 Jan;131(1):138-142. 
doi: 10.1097/AOG.0000000000002417. PMID: 29215526; PMCID: 
PMC6511983.
    \1021\ Campbell, K.H. et al. (2013). Maternal Morbidity and Risk 
of Death at Delivery Hospitalization. Obstetrics and Gynecology, 
122(3): 627-633. Available at: https://journals.lww.com/greenjournal/fulltext/2013/09000/Maternal_Morbidity_and_Risk_of_Death_at_Delivery.20.aspx.
    \1022\ Mocumbi, A.O., Sliwa, K., & Soma-Pillay, P. (2016). 
Medical disease as a cause of maternal mortality: The pre-imminence 
of cardiovascular pathology: Review articles. Cardiovascular journal 
of Africa, 27(2), 84-88.
    \1023\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3): B17.
    \1024\ 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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    Additionally, racial and ethnic disparities are significant; non-
Hispanic Black women are at considerably higher risk for developing 
these maternal complications than are non-Hispanic White 
women.1025 1026 Maternal death rate data indicate wide 
ethnic and racial gaps exist in maternal healthcare and outcomes. The 
maternal death rate for Black women is more than double that of White 
women--37.1 deaths per 100,000 live births compared to 14.7--and almost 
three times the rate compared to Hispanic women--11.8 deaths per 
100,000 live births.\1027\
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    \1025\ Leonard, S.A., Main, E.K., Scott, K.A., Profit, J., & 
Carmichael, S.L. (2019). Racial and ethnic disparities in severe 
maternal morbidity prevalence and trends. Annals of epidemiology, 
33, 30-36.
    \1026\ Petersen, E.E. et al. (2019). Vital signs: Pregnancy-
related deaths, United States, 2011-2015, and strategies for 
prevention, 13 states, 2013-2017. Morbidity and Mortality Weekly 
Report, 68(18), 423.
    \1027\ Centers for Disease Control and Prevention. (2020). First 
Data Released on Maternal Mortality in Over a Decade. Available at: 
https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2020/202001_MMR.htm.
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    As stated in the HHS Action Plan to Improve Maternal Health in 
America,\1028\ we are pursuing a vision for improving maternal health 
by focusing on: (1) Reducing maternal mortality, including disparities 
by race, ethnicity, and geography, in 5 years; (2) reducing SMM, 
including disparities by race and ethnicity, in five years; and (3) 
increasing hospital participation in HHS-sponsored maternal health 
quality improvement initiatives. As reflected in these goals, a 
critical focus of our maternal health efforts is reducing existing 
disparities in maternal health outcomes across race, ethnicity, and 
geographic area. This is further reflected in the Biden-Harris 
Administration's first ever Presidential proclamation recognizing Black 
Maternal Health Week.\1029\ CMS is also interested in promoting 
policies that ensure Americans who live in rural areas have access to 
high quality care, particularly in the area of maternal health where 
residents in rural settings have a 9 percent greater probability of SMM 
and mortality, compared with urban residents.\1030\ Ultimately, driving 
the development and execution of evidence-based best practices in 
maternity care, improving overall maternal health, and closing the 
racial and ethnic disparity gaps in outcomes are among our agency's top 
healthcare quality and safety goals.\1031\
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    \1028\ US Department of Health and Human Services. Healthy 
Women, Healthy Pregnancies, Healthy Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
    \1029\ 86 FR 20023, April 16, 2021.). A Proclamation on Black 
Maternal Health Week. Available at: https://www.federalregister.gov/documents/2021/04/16/2021-08008/black-maternal-health-week-2021.
    \1030\ Kozhimannil, K.B., Interrante, J.D., Henning-Smith, C., & 
Admon, L.K. (2019). Rural-urban differences in severe maternal 
morbidity and mortality in the US, 2007-15. Health affairs, 38(12), 
2077-2085.
    \1031\ Centers for Medicare & Medicaid Services. (2021). 
Evidence-based best practices for hospitals in managing obstetric 
emergencies and other key contributors to maternal health 
disparities. Available at: https://www.cms.gov/files/document/qso-22-05-hospitals.pdf.
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    Currently, the Hospital IQR Program includes two measures that 
address improving maternal health: The Elective Delivery measure (PC-
01) (77 FR 53530) and the Maternal Morbidity Structural measure (86 FR 
45361 through 45365). In section IX.E.5.c. of the preamble of this 
proposed rule, we are proposing the adoption of the Cesarean Birth eCQM 
as part of the Hospital IQR Program measure set. However, there are 
currently no maternal morbidity or obstetric complications outcome-
based measures in the Hospital IQR Program.
    The Severe Obstetric Complications eCQM has been developed to focus 
on the high maternal morbidity and mortality rates in the U.S., which 
we believe will present important opportunities for large-scale quality 
measurement and improvement activities in the Hospital IQR 
Program.\1032\ Statistics on preventability vary but suggest that a 
considerable proportion of maternal morbidity and mortality events 
could be prevented.1033 1034 This measure is intended to 
facilitate safer patient care by increasing awareness of the danger of 
obstetric complications, promoting adherence to recommended clinical 
guidelines, and encouraging hospitals to track and improve their 
practices of appropriate monitoring and care delivery for pregnant and 
postpartum patients.
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    \1032\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
    \1033\ Davis, N.L., Smoots, A.N., & Goodman, D.A. (2019). 
Pregnancy-Related Deaths: Data from 14 US Maternal Mortality Review 
Committees. Education, 40(36), 8-2.
    \1034\ Geller SE, Rosenberg D, Cox SM, et al. (2004). The 
continuum of maternal morbidity and mortality: Factors associated 
with severity. American journal of obstetrics and gynecology, 
191(3):939-944.
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    Under CMS' Meaningful Measures Framework, the Severe Obstetric 
Complications eCQM 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.'' 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``Safety'' priority area and aligns with our

[[Page 28512]]

commitment to a patient-centered approach in quality measurement to 
ensure that patients are safe and receive the highest quality 
care.\1035\
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    \1035\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
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    Therefore, in this proposed rule, we are proposing to adopt the 
Severe Obstetric Complications eCQM beginning with the CY 2023 
reporting period/FY 2025 payment determination. We previously finalized 
that hospitals must report on three self-selected eCQMs and the Safe 
Use of Opioids--Concurrent Prescribing eCQM, for a total of four eCQMs 
in the CY 2023 reporting period/FY 2025 payment determination (85 FR 
58939). In this proposed rule, we are proposing to include this measure 
as part of the measure set in the Hospital IQR Program which hospitals 
would be able to self-select for the CY 2023 reporting period/FY 2025 
payment determination. After which, beginning with the CY 2024 
reporting period/FY 2026 payment determination and for subsequent 
years, we are proposing the Severe Obstetric Complications eCQM would 
be reported by all hospitals except those hospitals that do not perform 
deliveries or have an obstetrics department. We refer readers to 
section IX.E.10.e. of this proposed rule for our related proposal to 
modify the eCQM reporting and submission requirements beginning with 
the CY 2024 reporting period/FY 2026 payment determination.
(2) Overview of Measure
    This measure assesses the proportion of patients with severe 
obstetric complications which occur during the inpatient delivery 
hospitalization. The Severe Obstetric Complications eCQM was included 
in the publicly available ``List of Measures Under Consideration for 
December 1, 2021'' (MUC List).\1036\ The MAP Rural Health Advisory 
Group reviewed the MUC List and the Severe Obstetric Complications eCQM 
(MUC 2021-104) on December 8, 2021.\1037\ The MAP Rural Health Advisory 
Workgroup discussed questions regarding the specifications of the 
measure. First, there was discussion about the use of blood 
transfusions as an intervention and concern that blood transfusions 
would be excluded and/or delayed when clinical evidence indicates that 
patients would benefit from transfusions as an earlier intervention. 
The measure developer provided clarification that this measure reports 
two outcomes, one that includes all patients that meet the numerator 
criteria, and one that excludes patients whose only qualification for 
the numerator is a transfusion.\1038\ This is as a recognition that 
transfusions may be necessary for a number of reasons and for less 
severe complications. Second, the MAP Rural Health Advisory Workgroup 
discussed that rural settings have high maternal morbidity and 
mortality and that this measure would help improve maternal health 
outcomes, and that since the measure is risk-adjusted for the presence 
of economic/housing instability the measure has a focus on accounting 
for potential disparities. The measure developer added that as an EHR-
based measure, these data are patient-specific and the measure was 
tested in both rural and urban settings.\1039\ The Workgroup voted 
majority support in agreement of the applicability of the Severe 
Obstetric Complications eCQM to rural health settings.\1040\
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    \1036\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \1037\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \1038\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \1039\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \1040\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
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    The Severe Obstetric Complications eCQM (MUC2021-104) was also 
reviewed by the NQF MAP Hospital Workgroup on December 15, 2021, and 
received conditional support pending NQF endorsement.\1041\ Some MAP 
stakeholders expressed concerns about the minimum sample size and low 
case volumes as well as the risk adjustment methodology. The measure 
developer underscored for the MAP that this measure was tested in ten 
health systems which represented 28 hospitals and tested over 60,000 
delivery encounters, and there was no concern about case volumes.\1042\ 
The measure developer also clarified that testing was underway to 
evaluate the ideal risk adjustment methodology to determine approaches 
that would consider stratification based on sociodemographic factors, 
such as race and ethnicity, pre- and post-risk adjustment. We 
emphasized the importance of this measure and its role in helping 
hospitals to understand the disparities existent in maternal health 
outcomes.\1043\ Ultimately, MAP Hospital Workgroup stakeholders 
supported this measure and recommended conditional support because it 
would assist in surveillance on maternal morbidity, a clinical area 
that needs further measurement.\1044\ The MAP Coordinating Committee, 
which provides direction to the MAP workgroups, reviewed the Severe 
Obstetric Complications eCQM (MUC2021-104) on January 19, 2022, and 
voted to uphold the MAP Hospital Workgroup recommendation for 
conditional support pending NQF endorsement.\1045\
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    \1041\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \1042\ National Quality Forum. (2022). Meeting Transcript--
Virtual Review Meeting. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96632.
    \1043\ National Quality Forum. (2022). Meeting Transcript--
Virtual Review Meeting. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96632.
    \1044\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \1045\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    In January 2022, the Severe Obstetric Complications eCQM was 
submitted for endorsement by NQF, and is currently under review. We 
note that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that 
any measure specified by the Secretary must have been endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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

[[Page 28513]]

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 on this topic, and, therefore, 
we believe the exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act applies.
    To evaluate the validity, feasibility, and reliability of the 
measure, in 2021, the measure developer, conducted pilot testing in a 
total of 10 sites, consisting of 28 hospitals. The measure developer 
conducted alpha testing (formative testing) \1046\ and beta testing 
(field testing) \1047\ on the measure. Feasibility testing was 
conducted to assess data collection and accessibility, and included 
nine sites in the analysis, which consisted of 27 hospitals and three 
different EHR systems.\1048\ Using NQF's eCQM Feasibility Scorecard 
template,\1049\ the measure developer calculated results which 
indicated high feasibility of data elements defining the measure 
specifications (98 percent), clinical and documentation workflows 
compared to measure intent (99 percent), data element availability (95 
percent) and accuracy (98 percent), and use of data standards (96 
percent).
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    \1046\ Centers for Medicare & Medicaid Services. (2018). Alpha 
tests include methods to determine if individual data elements are 
available and if the form in which they exist is consistent with the 
intent of the measure. Measure Testing NMS Newsletter. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Measure_Testing_MMS_Newsletter_April_2018.pdf.
    \1047\ Centers for Medicare & Medicaid Services. (2018). Beta 
tests serve as the primary means to assess scientific acceptability 
and usability of a measure including gathering further information 
about feasibility. Measure Testing NMS Newsletter. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Measure_Testing_MMS_Newsletter_April_2018.pdf.
    \1048\ Centers for Medicare & Medicaid Services. (2018). eCQM 
Feasibility: How Stakeholders Inform Measure Development. Available 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/eCQM-Feasibility.pdf.
    \1049\ National Quality Forum. (2022). NQF eCQM Feasibility 
Scorecard. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=89036.
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    Following feasibility testing, one site representing two hospitals 
withdrew from the project, one site representing one hospital was 
unable to submit beta testing data in the timeline requested, and one 
site representing one hospital was added; as a result, the measure 
developer conducted beta testing in eight healthcare test sites and 25 
hospitals, representing three different EHR systems. The measure 
developer pulled data for delivery hospital encounters discharged from 
January 1 to December 31, 2020. During measure testing, the measure 
score reliability was assessed, which is the degree to which repeated 
measurements of the same entity agree with each other.\1050\ The 
measure developer estimated the measure score reliability using a 
signal-to-noise ratio to assess the values according to conventional 
standards. They assessed signal-to-noise reliability that describes how 
well the measure can distinguish the performance of one hospital from 
another. The signal is the proportion of the variability in measured 
performance that can be explained by real differences in performance. 
Scores can range from zero to one, where a score of zero implies that 
all the variability in a measure is attributable to measurement error, 
and a score of one implies that all the variability is attributable to 
real difference in performance. The reliability analysis yielded a 
median reliability score of 0.991 (range: 0.983-0.997) for any severe 
obstetric complication and 0.957 (range: 0.918-0.984) for severe 
obstetric complications excluding blood transfusion-only cases.
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    \1050\ Centers for Medicare & Medicaid Services. (2018). CMS 
Measures Management System (MNS) Testing Scientific Acceptability 
for de novo eCQMS. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/CMS-MMS-Webinar-BP101-%E2%80%93-Scientific-Acceptability-of-eCQMs.pptx.
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    The measure developer completed validity testing on six sites 
representing 15 hospitals, which was a statistically relevant sample of 
electronically submitted inpatient encounters selected for re-
abstraction for reliability testing and clinical adjudication from six 
of the beta testing sites. Validity testing of the measure refers to 
the correctness of conclusions about the quality of measured entities 
that can be made based on the measure scores (that is a higher score on 
a quality measure reflects higher quality).\1051\ Overall, the data 
element agreement rate for all six sites was 90.4 percent. Further, 
validity testing of the measure showed a performance score agreement 
rate of 91.2 percent with a kappa score of .881 indicating good 
agreement. Measure score validity testing revealed a high positive 
predictive value (rate of agreement) of 94.7 percent, and a negative 
predictive value of 100 percent. Likewise, sensitivity (responsiveness 
to change) and specificity (accuracy) across test sites for the measure 
score were high, at 100 percent and 90.5 percent, respectively.
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    \1051\ National Quality Forum. (2011). Guidance for Measure 
Testing and Evaluating Scientific Acceptability of Measure 
Properties. Available at: http://www.qualitylowbar;Process/
Measure_Testing_Task_Force_Final_Report.aspx#:~:text=Validity%20of%20
the%20measure%20score,quality%20measure%20reflects%20higher%20quality
.
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    The measure developer conducted testing of the Severe Obstetric 
Complications eCQM and found that across 60,184 delivery encounters at 
8 different sites, the current observed rate of any severe obstetric 
complications was 244 and the mean risk-standardized rate across test 
sites was 247 (per 10,000 delivery hospitalizations). The severe 
obstetric complications rate excluding blood transfusion-only cases was 
50 for both the observed rate and the mean risk-standardized rate 
across test sites (per 10,000 delivery hospitalizations). Through 
rigorous testing, the measure developer found that the measure was 
feasible, reliable, and valid.
    The measure specifications for the Severe Obstetric Complications 
eCQM can be found on the eCQI Resource Center website, available at 
https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Outcome
    The outcome of interest (numerator) for the Severe Obstetric 
Complications eCQM is the number of inpatient hospitalizations for 
patients with severe obstetric complications occurring during the 
delivery hospitalization, not present on admission, which include the 
following: Severe maternal morbidity diagnoses (we refer readers to the 
subsequent table); severe maternal morbidity procedures, including 
blood transfusion, conversion of cardiac rhythm, hysterectomy, 
temporary tracheostomy, and ventilation; or a discharge disposition of 
expired.1052 1053 Table IX.E-03. summarizes the severe 
maternal morbidity categories along with their corresponding diagnoses:
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    \1052\ eCQI Resource Center. (2022). Eligible Hospital/Critical 
Access Hospital Pre-rulemaking eCQMs. Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    \1053\ The Joint Commission. (2021). eCQM Specifications 2022 
Reporting Period. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/specification-manuals/2022-reporting-period/january-2022/ecqm_specifications_reportingperiod_2022.zip.

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[[Page 28514]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.187

    This measure is intended to report two outcomes: (1) Severe 
obstetric complications; and (2) severe obstetric complications but 
excluding delivery hospitalizations for which blood transfusion was the 
only numerator event.
(5) Cohort
    The measure cohort (denominator) consists of inpatient 
hospitalizations for patients between eight years of age and less than 
65 years of age admitted to the hospital for inpatient acute care who 
undergo a delivery procedure for a stillbirth or livebirth greater than 
or equal to 20 weeks' gestation, with a discharge date that ends during 
the measurement period. Patients with confirmed diagnosis of COVID-19 
with COVID-19-related respiratory condition or patients with confirmed 
diagnosis of COVID-19-related respiratory procedure are excluded from 
the measure calculation.\1054\
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    \1054\ eCQI Resource Center. (2022). Eligible Hospital/Critical 
Access Hospital Pre-rulemaking eCQMs. Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
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(6) Risk Adjustment
    The Severe Obstetric Complications eCQM is a risk-adjusted measure. 
The measure developer identified candidate risk variables for severe 
obstetric complications for consideration in the measure risk 
adjustment model by utilizing literature and research findings, 
consulting with an expert clinical consultant, and by soliciting input 
from a technical expert panel (TEP). Following the identification of 
candidate risk adjustment variables, the measure developer developed 
risk models for the outcomes of severe obstetric complications and 
severe obstetric complications excluding blood transfusion-only 
encounters. The measure developer then utilized the variables included 
in the final risk models for use as the risk adjustment variables when 
calculating the risk standardized severe obstetric complication rates 
for the two versions of the measure outcome (with and without 
transfusion-only encounters).
    Variables included in the measure's risk adjustment are: Patient 
age; several preexisting conditions that are present on admission 
defined by ICD-10 codes (listed later in the section); pregnancy 
characteristics; laboratory tests and vital signs upon hospital arrival 
(hematocrit, white blood cell (WBC) count, heart rate, systolic blood 
pressure); long term anticoagulant medication use; and social risk 
measured by the presence of economic/housing instability.
    The following preexisting conditions and pregnancy characteristics, 
defined by ICD-10 codes, are included in the measure's risk adjustment: 
Anemia, asthma, autoimmune disease, bariatric surgery, bleeding 
disorder, Body Mass Index (BMI), cardiac disease, gastrointestinal 
disease, gestational diabetes, Human Immunodeficiency Virus (HIV), 
Hypertension, mental health disorder, multiple pregnancy, neuromuscular 
disease, obstetric venous thromboembolism (VTE), other pre-eclampsia, 
placental accreta spectrum, placental abruption, placenta previa, 
preexisting diabetes, preterm birth, previous cesarean, pulmonary 
hypertension, renal disease, severe pre-eclampsia, substance abuse, and 
thyrotoxicosis.
(7) Measure Calculation
    The measure is an outcome measure that assesses the risk-
standardized proportion of eligible patients with severe obstetric 
complications, and the risk-standardized proportion of eligible 
patients with severe obstetric complications excluding transfusion-only 
hospital delivery encounters, which occur during the inpatient delivery 
hospitalization. The measure calculates the proportion of inpatient 
hospitalizations with severe obstetric complications occurring during 
the delivery hospitalization out of the total number of inpatient 
hospitalizations for patients delivering stillborn or live birth with 
greater than or equal to least 20 weeks and 0 days of gestation 
completed. The measure score will be reported as a rate per 10,000 
deliveries.
(8) Data Submission and Reporting
    We refer readers to: Section IX.E.10.e. of the preamble of this 
proposed rule for discussion of our previously finalized eCQM reporting 
and submission policies; and section IX.E.13.b. for the public 
reporting of eCQM data. Additionally, we refer readers to section 
IX.E.10.e.(4). where we discuss the use of the zero denominator 
declarations and case threshold exemption policies for hospitals.

[[Page 28515]]

    We also refer readers to four related proposals discussed in the 
preamble of this proposed rule: (1) Section IX.E.10.e. where we discuss 
our newly proposed modifications to our reporting and submission 
requirements for eCQMs, including a discussion of our proposal to 
require hospitals to report on the Severe Obstetric Complications eCQM; 
(2) section IX.E.5.c. for our proposal to adopt the Cesarean Birth 
eCQM; (3) section IX.H.10.a.(2). of the preamble of this proposed rule 
for a discussion of similar proposals to adopt these two perinatal 
eCQMs in the Medicare Promoting Interoperability Program for Eligible 
Hospitals and CAHs; and (4) section IX.E.8. where we are proposing to 
establish a publicly-reported hospital designation to capture the 
quality and safety of maternity care and other related activities in 
advancing maternal health equity.
    We invite public comment on this proposal.
e. Proposed Hospital-Harm--Opioid-Related Adverse Events eCQM (NQF 
#3501e) Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
(1) Background
    Opioids are among the most frequently implicated medications in 
adverse drug events among hospitalized patients.\1055\ The most serious 
opioid-related adverse events include those involving respiratory 
depression, which can lead to brain damage and 
death.1056 1057 1058 Opioid-related adverse events have both 
a negative impact on patients and financial implications. Patients who 
experience adverse events due to opioid administration have been noted 
to have 55 percent longer lengths of stay, 47 percent higher costs, 36 
percent higher risk of 30-day readmission, and 3.4 times higher 
payments than patients without these adverse events.\1059\ While noting 
that data are limited, The Joint Commission suggested that opioid-
induced respiratory arrest may contribute substantially to the 350,000 
to 750,000 in-hospital cardiac arrests annually.\1060\
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    \1055\ Davies EC, Green CF, Taylor S, Williamson PR, Mottram DR, 
et al. (2009) Adverse Drug Reactions in Hospital In-Patients: A 
Prospective Analysis of 3695 Patient-Episodes. PLoS ONE 4(2): e4439. 
doi:10.1371/journal.pone.0004439.
    \1056\ Jungquist CR, Quinlan-Colwell A, Vallerand A, et al. 
(2020). American Society for Pain Management Nursing Guidelines on 
Monitoring for Opioid-Induced Advancing Sedation and Respiratory 
Depression: Revisions. Pain Manag Nurs.21(1):7-25. Epub 2019 Jul 31.
    \1057\ Ramachandran SK, Haider N, Saran KA, et al. (2011). Life-
threatening critical respiratory events: A retrospective study of 
postoperative patients found unresponsive during analgesic therapy. 
Journal of Clinical Anesthesia. 23(3):207-213.
    \1058\ Dahan A, Aarts L, Smith TW. (2010). Incidence, Reversal, 
and Prevention of Opioid-induced Respiratory Depression. 
Anesthesiology. 112(1):226-238.
    \1059\ Kessler, E.R., Shah, M., Gruschkkus, S.K., et al. (2013). 
Cost and quality implications of opioid-based postsurgical pain 
control using administrative claims data from a large health system: 
Opioid-related adverse events and their impact on clinical and 
economic outcomes. Pharmacotherapy, 33(4): 383-91.
    \1060\ Overdyk, F.J. (2009). Postoperative Respiratory 
Depression and Opioids. Initiatives in Safe Patient Care. Available 
at: https://www.initiatives-patientsafety.org/_files/ugd/ba15f5_d52da446e2f141d7be95d3a99b538a42.pdf.
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    Most opioid-related adverse events are preventable.\1061\ Of the 
opioid-related adverse drug events reported to The Joint Commission's 
Sentinel Event database, 47 percent were due to a wrong medication 
dose, 29 percent due to improper monitoring, and 11 percent due to 
other causes (for example, medication interactions and/or drug 
reactions).\1062\ In addition, in a review of cases from a malpractice 
claims database in which there was opioid-induced respiratory 
depression among post-operative surgical patients, 97 percent of these 
adverse events were judged preventable with better monitoring and 
response.\1063\
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    \1061\ Lee LA, Caplan RA, Stephens LS, et al. Postoperative 
opioid-induced respiratory depression: A closed claims analysis. 
Anesthesiology. 2015;122(3):659-665.
    \1062\ The Joint Commission. (2012.) Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5. 
Available at: https://www.jointcommission.org/-/media/deprecated-unorganized/imported-assets/tjc/system-folders/topics-library/sea_49_opioids_8_2_12_finalpdf.pdf?db=web&hash=0135F306FCB10D919CF7572ECCC65C84.
    \1063\ Lee, L.A., Caplan, R.A., Stephens, L.S., et al. (2015). 
Postoperative opioid-induced respiratory depression: A closed claims 
analysis. Anesthesiology, 122(3): 659-65.
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    While hospital quality interventions such as proper dosing, 
adequate monitoring, and attention to potential drug interactions that 
can lead to overdose are key to prevention of opioid-related adverse 
events, the use of these practices can vary substantially across 
hospitals.1064 1065 1066 In addition, administration of 
opioids also varies widely by hospital, ranging from 5 percent in the 
lowest-use hospital to 72 percent in the highest-use hospital.\1067\ 
Notably, hospitals that use opioids most frequently have increased 
adjusted risk of severe opioid-related adverse events.\1068\ The 
measure developer, under contract with CMS, developed the Hospital 
Harm-Opioid-Related Adverse Events eCQM to assess the rates of adverse 
events as well as the variation in rates among hospitals.
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    \1064\ Willens JS, Jungquist CR, Cohen A, Polomano R. (2013). 
ASPMN survey--nurses' practice patterns related to monitoring and 
preventing respiratory depression. Pain Management Nursing. 
14(1):60-65.
    \1065\ Meisenberg B, Ness J, Rao S, Rhule J, Ley C. (2017). 
Implementation of solutions to reduce opioid-induced oversedation 
and respiratory depression. Am J Health Syst Pharm. 74:162-169.
    \1066\ Jungquist CR, Correll DJ, Fleisher LA, et al. (2016). 
Avoiding Adverse Events Secondary to Opioid-Induced Respiratory 
Depression: Implications for Nurse Executives and Patient Safety. 
Journal of Nursing Administration. 46(2):87-94.
    \1067\ Herzig, S.J., Rothberg, M.B., Cheung, M., et al. (2014). 
Opioid utilization and opioid-related adverse events in nonsurgical 
patients in US hospitals. Journal of Hospital Medicine, 9(2): 73-81.
    \1068\ Ibid.
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(2) Overview of Measure
    The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome 
measure focusing specifically on opioid-related adverse events during 
an admission to an acute care hospital by assessing the administration 
of naloxone. Naloxone is a lifesaving emergent therapy with clear and 
unambiguous applications in the setting of opioid 
overdose.1069 1070 1071 1072 Naloxone administration has 
also been used in a number of studies as an indicator of opioid-related 
adverse events to indicate harm to a patient during inpatient admission 
to a hospital.1073 1074 The intent of this measure is for 
hospitals to track and improve their monitoring and response to 
patients administered opioids during hospitalization, and to avoid 
harm, such as respiratory depression, which can lead to brain damage 
and death. This measure focuses specifically on in-hospital opioid-
related adverse events,

[[Page 28516]]

rather than opioid overdose events that happen in the community and may 
bring a patient into the ED.
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    \1069\ Surgeon General's Advisory on Naloxone and Opioid 
Overdose. (2018). Available at: https://www.surgeongeneral.gov/priorities/opioid-overdose-prevention/naloxone-advisory.html.
    \1070\ Agency for Healthcare Research and Quality (AHRQ). 
(2017). Management of Suspected Opioid Overdose with Naloxone by 
Emergency Medical Services Personnel. Comparative Effectiveness 
Review No. 193. Available at: https://effectivehealthcare.ahrq.gov/topics/emt-naloxon/systematic-review.
    \1071\ Substance Abuse and Mental Health Services Administration 
(SAMHSA). (2018). Opioid Overdose Prevention Toolkit: Information 
for Prescribers. Available at: https://store.samhsa.gov/product/Opioid-Overdose-Prevention-Toolkit/SMA18-4742.
    \1072\ Harm Reduction Coalition. (2020). Guide To Developing and 
Managing Overdose Prevention and Take-Home Naloxone Projects. 
Available at: https://harmreduction.org/issues/overdose-prevention/developing-overdose-prevention-and-naloxone-projects/.
    \1073\ Eckstrand, J.A., Habib, A.S., Williamson, A., et al. 
(2009). Computerized surveillance of opioid-related adverse drug 
events in perioperative care: A cross-sectional study. Patient 
Safety Surgery, 3:18.
    \1074\ Nwulu, U., Nirantharakumar, K., Odesanya, R., et al. 
(2013). Improvement in the detections of adverse drug events by the 
use of electronic health and prescription records: An evaluation of 
two trigger tools. European Journal of Clinical Pharmacology, 69(2): 
255-59.
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    The goal of this measure is to incentivize hospitals to closely 
monitor patients who receive opioids during their hospitalization to 
prevent serious adverse events. The measure requires evidence of 
hospital opioid administration prior to the naloxone administration 
during the first 24 hours after hospital arrival to ensure that the 
harm was hospital acquired and not due to an overdose that happened 
outside of the hospital.\1075\ This measure does not identify 
preventability of an individual harm instance or whether each instance 
of harm was an error, but rather, it assesses the overall rate of harm 
within a hospital by incorporating a definition of harm that is likely 
to be reduced as a result of hospital best practice.
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    \1075\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Measure Information Form. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
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    The Hospital Harm--Opioid-Related Adverse Events eCQM was included 
as a measure undergoing field testing in the publicly available ``List 
of Measures Under Consideration for December 1, 2017'' (MUC 
List).\1076\ The measure was reviewed by the NQF MAP Hospital Workgroup 
in December 2017, and received the recommendation to refine and 
resubmit with completed test results demonstrating reliability and 
validity prior to rulemaking, as referenced in the ``2017-2018 
Spreadsheet of Final Recommendations to HHS and CMS.'' \1077\
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    \1076\ National Quality Forum. (2017). List of Measures Under 
Consideration for December 1, 2017. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \1077\ National Quality Forum. 2017-2018 Spreadsheet of Final 
Recommendations to HHS and CMS. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
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    This measure was submitted for endorsement consideration to NQF's 
Patient Safety Standing Committee for the Spring 2019 cycle. NQF 
reviewed the measure on June 21, 2019, but did not proceed with full 
endorsement consideration due to concerns with the performance gap 
criterion. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19477), we 
proposed but did not finalize the adoption of the Hospital-Harm--
Opioid-Related Adverse Events eCQM. Commenters provided measure 
suggestions and refinements, as outlined in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42459), and we decided to further assess the measure 
and the suggested considerations with intent to re-propose the measure. 
The main areas of suggestions were to better establish the connection 
between naloxone administration and an opioid-related event and 
consider narrowing the broad denominator that, as specified, may result 
in the calculation of very low rates of adverse events.
    In response to the feedback received, the measure developer refined 
and retested the measure specifications. The measure developer limited 
the denominator to encounters where patients received at least one 
opioid during the hospitalization. The measure developer constrained 
the numerator to those patients with an opioid administration that 
preceded the subsequent naloxone administration by no more than a 12-
hour time window, to ensure that a hospital administered opioid was the 
cause for the naloxone administration. The measure developer also 
updated the value sets to ensure that the most current codes for 
hospital administered opioids and naloxone are used and that the codes 
harmonize across other current eCQMs in our quality reporting programs. 
Finally, the measure was re-tested by the measure developer for 
feasibility at 23 hospital test sites using four different EHR vendor 
systems and for the scientific acceptability of the measure's 
properties including reliability and validity at six beta 
implementation test sites.\1078\ Participant test sites varied by EHR 
vendor systems, bed size, geographic location, teaching/non-teaching 
status, and urban/rural representation.
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    \1078\ National Quality Forum. #3501e Hospital Harm--Opioid-
Related Adverse Events. Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3501e.
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    The Hospital Harm--Opioid-Related Adverse Events eCQM (NQF #3501e) 
was then re-submitted to the NQF for the Spring 2021 review cycle and 
received NQF endorsement on December 7, 2021.\1079\ The MAP Rural 
Health Advisory Group also reviewed the MUC List and Hospital Harm--
Opioid-Related Adverse Events eCQM (MUC2021-084) on December 8, 2021 
and voted majority support in agreement on the applicability of the 
eCQM to rural health settings.\1080\ The refined and retested eCQM was 
also re-considered by the MAP Hospital Workgroup on December 15, 2021, 
which voted to support the measure for rulemaking.\1081\ The MAP 
Coordinating Committee, which provides direction to the MAP workgroups, 
then reviewed the measure on January 19, 2022 \1082\ and upheld the MAP 
Hospital Workgroup recommendation to support the measure for 
rulemaking.\1083\
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    \1079\ National Quality Forum. (2021). Hospital Harm--Opioid 
Related Adverse Events. Available at: https://www.qualityforum.org/QPS/3501e.
    \1080\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting 
Summary, December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \1081\ Measure Applications Partnership Hospital Workgroup Web 
Review Meeting: Meeting Summary. December 15, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \1082\ Measure Applications Partnership Coordinating Committee 
2021-2022 Review Web Meeting: Meeting Summary. January 19, 2022. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96709.
    \1083\ Measure Applications Partnership 2021-2022 Considerations 
for Implementing Measures in Federal Programs: Clinician, Hospital, 
and Post-Acute Care Long-Term Care Final Report. March 3, 2022. 
Available at: https://www.qualityforum.org/Projects/i-/MAP/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report.aspx#onclick=%E2%80%9D_gaq.push([%E2%80%98_trackEvent%E2%80%99,%E2%80%99Downloa
d%E2%80%99,%E2%80%99PDF%E2%80%99,this.href]);%E2%80%9D.
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    We believe this measure would provide hospitals with reliable and 
timely measurement of their opioid-related adverse event rates, which 
is a high-priority measurement area. We believe implementation of this 
measure can lead to safer patient care by incentivizing hospitals to 
implement or refine clinical workflows that facilitate evidence-based 
use and monitoring when administering opioids. We also believe 
implementation of this measure may result in fewer patients 
experiencing adverse events associated with the administration of 
opioids, such as respiratory depression, which can lead to brain damage 
and death. This measure addresses the quality priority of ``Making Care 
Safer by Reducing Harm Caused in the Delivery of Care'' through the 
Meaningful Measures Area of ``Preventable Healthcare Harm.'' \1084\
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    \1084\ 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.html.
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    For detailed information on the Hospital Harm-Opioid-Related 
Adverse Events eCQM, we refer readers to the measure specifications, 
available at https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
    As with all quality measures we develop, testing was performed to 
confirm the feasibility of the measure,

[[Page 28517]]

data elements, and validity of the numerator, using clinical 
adjudicators who validated the EHR data compared with medical chart-
abstracted data. Testing demonstrated no missing or erroneous data (0 
percent) for all six implementation test sites. These results suggest 
that all critical data elements are reliably and consistently captured 
in patient EHRs, and that measure implementation is feasible. Testing 
also showed that the positive predictive value (PPV),\1085\ which 
describes the probability that a patient with a positive result 
(numerator case) identified by the EHR data was also a positive result 
verified by review of the patient's medical record done by a clinical 
adjudicator, was high at all hospital testing sites (98 percent in one 
hospital to 100 percent in the five other hospitals). Testing was 
completed using output from the Measure Authoring Tool (MAT) in 23 
hospitals using four different EHR systems for feasibility and six 
different hospitals for implementation testing for reliability and 
validity.
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    \1085\ ``Predictive Value.'' Farlex Partner Medical Dictionary. 
Available at: https://medical-dictionary.thefreedictionary.com/predictive+value.
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(4) Outcome
    This measure assesses the proportion of inpatient hospital 
encounters where patients 18 years of age or older have been 
administered an opioid medication, subsequently suffer the harm of an 
opioid-related adverse event, and are administered an opioid antagonist 
(naloxone) within 12 hours. This measure excludes opioid antagonist 
(naloxone) administration occurring in the operating room setting.
(5) Cohort
    This measure's cohort includes all patients ages 18 years and older 
at the start of the encounter, and for whom at least one opioid 
medication was administered during the encounter. An inpatient 
hospitalization includes time spent in the ED or in observation status 
when the patients are ultimately admitted to inpatient status.
(6) Inclusion and Exclusion Criteria
    This measure excludes opioid antagonist (naloxone) administration 
occurring in the operating room setting. There are no denominator 
exclusions.
(7) Risk Adjustment
    This measure is not risk adjusted for chronic opioid use, as most 
instances of opioid-related adverse events should be preventable for 
all patients regardless of prior exposure to opioids or chronic opioid 
use.
    Generally, patient characteristics, including gender, age, race/
ethnicity, reasons for hospitalization, clinical status when patients 
arrive at the hospital, or comorbidities can influence the risk of harm 
occurring during a hospitalization.\1086\ Therefore, if hospitals care 
for patients with different degrees of risk, then it may be important 
to account for such case mix to compare hospital performance.\1087\ 
However, opioid-related adverse events should be avoidable regardless 
of patient risk, particularly when the opioid was given after patients 
have arrived at the hospital.\1088\ During measure development, in 
evaluating whether this measure needed to be risk adjusted, the measure 
developer considered the following in determining whether risk 
adjustment is warranted for this measure: Patients are at risk of the 
harm regardless of their demographic and clinical characteristics; most 
incidents of harm are linkable to care provision under the hospital 
control, for example, harms caused by excessive or inappropriate 
medication dosing; and there is evidence that the risk of harm can be 
largely reduced by following best care practices independent of patient 
inherent risks. For example, patients with multiple risk factors can 
still avoid the harm event when providers adhere to care guidelines.
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    \1086\ National Quality Forum. Glossary of Terms. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=73681.
    \1087\ National Quality Forum. Developing and Testing Risk 
Adjustment Models for Social and Functional Status-Related Risk 
Within Healthcare Performance Measurement: Final Technical 
Guidance--Version 4. August 30, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96087.
    \1088\ The Joint Commission. (2012). Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5. 
Available at: https://www.jointcommission.org/-/media/deprecated-unorganized/imported-assets/tjc/system-folders/topics-library/sea_49_opioids_8_2_12_finalpdf.pdf?db=web&hash=0135F306FCB10D919CF7572ECCC65C84.
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    Opioid-related adverse events should be avoidable regardless of 
patient risk, particularly when the opioid was given after patients 
have arrived at the hospital.\1089\ While certain patients may require 
higher doses to achieve pain control or are more sensitive to opioids 
(depending on their age, sex, and weight), the most common cause is 
hospital administration of excessive doses and inadequate 
monitoring.\1090\ Because the dosing of opioids and the intensity of 
patient monitoring is entirely under the control of providers in 
hospitals, the risk of an opioid-related adverse event can be reduced 
by following best practices.1091 1092 1093 Therefore, the 
measure developer did not believe risk adjustment is warranted for this 
measure.
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    \1089\ Ibid.
    \1090\ Dahan A, Aarts L, Smith TW. Incidence, Reversal, and 
Prevention of Opioid-induced Respiratory Depression. Anesthesiology. 
2010;112(1):226-238.
    \1091\ Practice Guidelines for the Prevention, Detection, and 
Management of Respiratory Depression Associated with Neuraxial 
Opioid Administration: An Updated Report by the American Society of 
Anesthesiologists Task Force on Neuraxial Opioids and the American 
Society of Regional Anesthesia and Pain Medicine. Anesthesiology. 
2016 Mar;124(3):535-52.
    \1092\ Jungquist CR, Quinlan-Colwell A, Vallerand A, et al. 
American Society for Pain Management Nursing Guidelines on 
Monitoring for Opioid-Induced Advancing Sedation and Respiratory 
Depression: Revisions. Pain Manag Nurs. 2020 Feb;21(1):7-25. Epub 
2019 Jul 31.
    \1093\ Dahan A, Aarts L, Smith TW. Incidence, Reversal, and 
Prevention of Opioid-induced Respiratory Depression. Anesthesiology. 
2010;112(1):226-238.
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    To provide supportive evidence of the clinical rationale for not 
risk adjusting, the measure developer examined the measure performance 
rate in various subgroups of population. All these analyses 
demonstrated no pattern in measure performance rates across 
subgroups.\1094\ During measure development, TEP members gave feedback 
on whether the measure required risk adjustment and agreed with this 
rationale. Subsequently the NQF Scientific Methods Panel (SMP), the 
Patient Safety Standing Committee, and the Consensus Standards Advisory 
Committee (CSAC) also agreed with this 
approach.1095 1096 1097
---------------------------------------------------------------------------

    \1094\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Measure Information Form. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
    \1095\ National Quality Forum. Scientific Methods Panel Measure 
Evaluation Web Meeting--Spring 2021 Meeting Summary. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95246.
    \1096\ National Quality Forum. Patient Safety Spring 2021 Cycle. 
Memo: Consensus Standards Approval Committee (CSAC). November 30, 
2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96423.
    \1097\ National Quality Forum. Consensus Standards Approval 
Committee (CSAC) Voting Results and Decisions for Spring 2021 
Measures. November 30, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96528.
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(8) Measure Calculation
    The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome 
measure that defines the indication of a harm for an opioid-related 
adverse event by assessing administration of an opioid antagonist 
(naloxone). The numerator is the number of inpatient hospitalizations 
where an opioid antagonist (naloxone) was administered outside of the

[[Page 28518]]

operating room and within 12 hours following administration of an 
opioid medication. Only one numerator event is counted per encounter. 
The denominator includes inpatient hospitalizations for patients 18 
years or older during which at least one opioid medication was 
administered. An inpatient hospitalization includes time spent in the 
ED or in observation status when the patients are ultimately admitted 
to inpatient status.
    To calculate the hospital-level measure result, divide the total 
numerator events by the total number of qualifying inpatient encounters 
(denominator). Qualifying inpatient encounters include all patients 18 
years of age or older at the start of the encounter with at least one 
opioid medication administered during the encounter. The measure does 
not include naloxone use in the operating room where it could be part 
of the sedation plan as administered by an anesthesiologist or nurse 
anesthetist. Uses of naloxone for procedures outside of the operating 
room (such as bone marrow biopsy) are counted in the numerator as its 
use would indicate the patient was over sedated.\1098\ The measure 
numerator identifies a harm using the administration of naloxone, and 
purposely does not include any medications that combine naloxone with 
other agents.
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    \1098\ Nwulu, U., Nirantharakumar, K., Odesanya, R., McDowell, 
S.E., & Coleman, J.J. Improvement in the detection of adverse drug 
events by the use of electronic health and prescription records: An 
evaluation of two trigger tools. Eur J Clin Pharmacol. 2013;69(2), 
255-259.
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(9) Data Submission and Reporting
    We are proposing the adoption of the Hospital-Harm--Opioid-Related 
Adverse Events eCQM as part of the Hospital IQR Program for which 
hospitals can self-select beginning with the CY 2024 reporting period/
FY 2026 payment determination and for subsequent years. We refer 
readers to section IX.E.10.e. of the preamble of this proposed rule for 
a discussion of our previously finalized eCQM reporting and submission 
policies, as well as our proposal to modify these eCQM reporting and 
submission requirements. Additionally, we refer readers to section 
IX.H.10.a.(2). of the preamble of this proposed rule for a discussion 
of a similar proposal to adopt this measure in the Medicare Promoting 
Interoperability Program for Eligible Hospitals and CAHs.
    We invite public comment on this proposal.
f. Proposed Global Malnutrition Composite Score eCQM (NQF #3592e) 
Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
(1) Background
    From 1960 until the start of the COVID-19 pandemic,\1099\ life 
expectancy for the total population in the U.S. increased by almost 10 
years.\1100\ While adults are living longer lives, the amount of time 
spent in poor health at the end of life is similarly increasing.\1101\ 
Studies found that healthy nutrition is indeed more important for 
healthy aging than generally recognized.\1102\ Malnutrition includes 
undernutrition (wasting, stunting, underweight), inadequate vitamins or 
minerals, overweight, and obesity, and can result in diet-related 
noncommunicable diseases.\1103\ The developmental, economic, social, 
and medical impacts of the global burden of malnutrition are serious 
and lasting, for individuals and their families, for communities, and 
for countries.\1104\ Malnutrition is complex and may be both associated 
with and exacerbated by chronic conditions, age-related cognitive or 
physical changes, medication side effects, and poverty.\1105\ Evidence 
shows that healthy eating contributes to prevention and risk reduction 
of many common chronic health conditions prevalent in older adults 
including hypertension, heart disease, heart failure, diabetes, 
obesity, certain cancers, and osteoporosis.\1106\ While it is estimated 
that sixty percent of older adults manage two or more chronic health 
conditions, many underuse preventive services, including those related 
to nutrition.\1107\ Research indicates that preventive screening and 
interventions may reduce risk of malnutrition in older adults and 
improve quality of life, particularly for individuals with chronic 
conditions.\1108\ While disease-related malnutrition is not limited to 
older adults, it is more frequent among those with higher age, and the 
consequences appear to be more severe in older persons due to their 
impaired regenerative capacity, inflammation, and other factors.\1109\ 
Malnutrition remains a challenge for older adults in the U.S. as 
approximately 7.7 percent of seniors, or 5.5 million, are food insecure 
annually with reports of reduced quality, variety, or desirability of 
diet while 3.1 percent, or 2.1 million are very low food insecure with 
reports of multiple indications of disrupted eating patterns and 
reduced food intake.1110 1111 From late September through 
mid-October 2021, U.S. Census Bureau data indicates that more than 2.5 
million adults ages 65 and older responded ``sometimes'' or ``often'' 
when asked the frequency of not having enough food to eat in the past 
seven days.\1112\
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    \1099\ Islam N, Jdanov DA, Shkolnikov VM, Khunti K, Kawachi I, 
White M et al. (2021). Effects of covid-19 pandemic on life 
expectancy and premature mortality in 2020: Time series analysis in 
37 countries. BMJ 375:e066768 doi:10.1136/bmj-2021-066768.
    \1100\ United States Census Bureau. (2020). Living Longer: 
Historical and Projected Life Expectancy in the United States, 1960 
to 2060. Available at: https://www.census.gov/content/dam/Census/library/publications/2020/demo/p25-1145.pdf.
    \1101\ Roberts SB, Silver RE, Das SK, Fielding RA, Gilhooly CH, 
Jacques PF, et al. (2021) Healthy Aging-Nutrition Matters: Start 
Early and Screen Often. Adv Nutr. 12(4):1438-1448. doi: 10.1093/
advances/nmab032.
    \1102\ Ibid.
    \1103\ World Health Organization. (2021). Malnutrition. 
Available at: https://www.who.int/news-room/fact-sheets/detail/malnutrition.
    \1104\ World Health Organization. (2021). Malnutrition. 
Available at: https://www.who.int/news-room/fact-sheets/detail/malnutrition.
    \1105\ Barker CA, Gout BS, et al. (2011). Hospital malnutrition 
prevalence, identification, and impact on patients and the 
healthcare system. International Journal of Environmental Research 
and Public Health.8:514-527.
    \1106\ Wright NC, Looker AC, Saag KG, et al. (2014). The recent 
prevalence of osteoporosis and low bone mass in the United States 
based on bone mineral density at the femoral neck or lumbar spine. J 
Bone Miner Res. 29(11):2520-2526. https://onlinelibrary.wiley.com/doi/10.1002/jbmr.2269/epdf.
    \1107\ U.S. Department of Health and Human Services. (2020). 
Office of Disease Prevention and Health Promotion. Older Adults: 
Overview. Healthy People 2020 website. Available at: https://www.healthypeople.gov/2020/topics-objectives/topic/older-adults.
    \1108\ Mangels, AR. (2018). Malnutrition in Older Adults. 
American Journal of Nursing. 118(3):34-41. doi: 10.1097/
01.NAJ.0000530915.26091.be.
    \1109\ Norman K, Ha[szlig] U, Pirlich M. (2021). Malnutrition in 
Older Adults--Recent Advances and Remaining Challenges. Nutrients. 
13, 2764. Available at: https://doi.org/10.3390/nu13082764.
    \1110\ Feeding America. (2019). The State of Senior Hunger in 
America in 2017: An Annual Report. Available at: https://www.feedingamerica.org/sites/default/files/2019-05/state-of-senior-hunger-2017_full-report.pdf.
    \1111\ United States Department of Agriculture Economic Research 
Service. (2021). Definitions of Food Security. Available at: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/definitions-of-food-security.aspx.
    \1112\ United States Census Bureau. (2021). Week 39 Household 
Pulse Survey: September 29-October 11. Available at: https://www.census.gov/data/tables/2021/demo/hhp/hhp39.html.

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[[Page 28519]]

As our population continues to age, it is expected that 1 in 5 
residents will be 65 years or older by the year 2030 \1113\ and 
malnutrition risk among seniors is likely to increase.\1114\
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    \1113\ United States Census Bureau. (2018). Older People 
Projected to Outnumber Children for First Time in U.S. History. 
Available at: https://www.census.gov/newsroom/press-releases/2018/cb18-41-population-projections.html.
    \1114\ Haines J, LeVan D, Roth-Kauffman MM. (2020). Malnutrition 
in the Elderly: Underrecognized and Increasing in Prevalence. 
Clinical Advisor. Available at: https://www.clinicaladvisor.com/home/topics/geriatrics-information-center/malnutrition-in-the-elderly-underrecognized-and-increasing-in-prevalence/.
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    One factor contributing to the burden of malnutrition is health 
disparity across racial and ethnic groups.\1115\ Black, Hispanic, and 
other non-White older adult populations have higher hunger rates than 
White populations.\1116\ Black Americans and Hispanic Americans are 
nearly 2.5 times and 1.4 times as likely as White Americans, 
respectively, to lack access to a full-service grocery store; this 
contributes to higher rates of food insecurity and can increase risk of 
malnutrition.\1117\ Black, Hispanic, and other non-White Americans are 
also at higher risk for many chronic diseases, emphasizing the 
importance of addressing nutrition through both prevention and 
management of these conditions--especially when they cannot access 
healthy food.\1118\
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    \1115\ Betor N, Badaracco C, Mitchell K. (2022). Leveraging 
Inpatient Malnutrition Care to Address Health Disparities. Avalere 
Insights. Available at: https://avalere.com/insights/leveraging-inpatient-malnutrition-care-to-address-health-disparities).
    \1116\ United States Department of the Treasury CDFI Fund 
Capacity Building Initiative. (2012). A Summary of Searching for 
Markets: The Geography of Inequitable Access to Healthy & Affordable 
Food in the United States. Available at: https://www.reinvestment.com/wp-content/uploads/2015/12/Searching_For_Markets-Summary_2011.pdf.
    \1117\ Ibid.
    \1118\ Dawson MD, Blancato B. (2021). To Advance Health Equity, 
Measure Hospital Malnutrition Care. Health Affairs. Available at: 
https://www.healthaffairs.org/do/10.1377/hblog20210930.667648/full/.
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    Patients over 65 comprise more than one-third of all discharges and 
nearly 13 million seniors are hospitalized each 
year.1119 1120 While Federal data indicate that 
approximately 8 percent of all hospitalized adults have a diagnosis of 
malnutrition,1121 1122 additional research finds that 
malnutrition and malnutrition risk can be found in 20 to 50 percent of 
hospitalized adults.1123 1124 This indicates that between 
910,000 and 6.5 million hospitalized seniors may experience 
malnutrition.\1125\ Hospitalized adults with a diagnosis of 
malnutrition have a longer length of stay, higher costs, more 
comorbidities, five times the likelihood of death, and greater risk of 
infectious disease and injury compared with other adult inpatients 
without malnutrition.1126 1127 Malnutrition may also 
contribute to post-hospital syndrome--described as ``an acquired, 
transient period of vulnerability'' following hospitalization \1128\--
which may dramatically increase the risk of 
readmission.1129 1130
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    \1119\ Gorman A. (2016). Elderly Hospital Patients Arrive Sick, 
Often Leave Disabled. Kaiser Health Network. Available at: https://khn.org/news/elderly-hospital-patients-arrive-sick-often-leave-disabled/.
    \1120\ Mattison M. (2021). Hospital Management of Older Adults. 
Available at: https://www.uptodate.com/contents/hospital-management-of-older-adults.
    \1121\ Barrett ML, Bailey MK, Owens PL. (2016). Non-maternal and 
non-neonatal inpatient stays in the United States involving 
malnutrition, 2016. Available at: https://www.hcup-us.ahrq.gov/reports/HCUPMalnutritionHospReport_083018.pdf.
    \1122\ Valladares AF, McCauley SM, Khan M, D'Andrea C, Kilgore 
K, Mitchell K. (2021). Development and Evaluation of a Global 
Malnutrition Composite Score. Journal of the Academy of Nutrition 
and Dietetics. doi: https://doi.org/10.1016/j.jand.2021.02.002.
    \1123\ Pereira GF., Bulik CM, Weaver MA, Holland WC, Platts-
Mills TF. (2015). Malnutrition among cognitively intact, 
noncritically ill older adults in the emergency department. Ann 
Emerg Med. 65: 85-91.
    \1124\ Barker CA, Gout BS, et al. (2011). Hospital malnutrition 
prevalence, identification, and impact on patients and the 
healthcare system. International Journal of Environmental Research 
and Public Health. 8:514-527.
    \1125\ United States Government Accountability Office. (2019). 
Report to Congressional Requestors. Nutrition Assistance Programs: 
Agencies Could Do More to Help Address the Nutritional Needs of 
Older Adults. Available at: https://www.gao.gov/assets/gao-20-18.pdf.
    \1126\ United States Agency for Healthcare Research and Quality. 
(2016). Healthcare Cost and Utilization Project: Non-maternal and 
Non-Neonatal Inpatient Stays in the United States Involving 
Malnutrition 2016. Available at: https://www.hcup-us.ahrq.gov/reports/HCUPMalnutritionHospReport_083018.pdf.
    \1127\ United States Agency for Healthcare Research and Quality. 
(2013). Characteristics of Hospital Stays Involving Malnutrition, 
2013. HCUP Statistical Brief #210. Available at: https://www.hcup-us.ahrq.gov/reports/statbriefs/sb210-Malnutrition-Hospital-Stays-2013.pdf.
    \1128\ Krumholz, HM. (2013). Post-hospital syndrome--an 
acquired, transient condition of generalized risk. New England 
Journal of Medicine. 368(2):100-2.
    \1129\ Sauer, A, Luo M. (2015) Role of Malnutrition in 
Increasing Risk of Hospital Readmissions. Abbott Nutrition Health 
Institute. Available at: http://static.abbottnutrition.com/cms-prod/anhi.org/img/Role-Of-Malnutrition-In-Increasing-Risk-Of-Hospital-Readmissions-article.pdf.
    \1130\ Guenter P, Jensen G, Patel V, Miller S, Mogensen KM, 
Malone A, et al. (2015). Addressing disease-related malnutrition in 
hospitalized patients: A call for a national goal. Joint Commission 
Journal on Quality and Patient Safety.41(10):469-73.
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    Partly due to the substantial impacts on clinical outcomes,\1131\ 
malnutrition imposes a serious burden on the healthcare system.\1132\ 
Hospitalized patients with poor nutrition have been estimated to incur 
approximately 300 percent higher healthcare costs than those who are 
adequately nourished.\1133\ Reports indicate that the average cost for 
an individual hospital stay (including both direct and indirect costs) 
for a malnourished patient is $25,600 while it is only $13,900 for a 
well-nourished patient; \1134\ further, malnutrition-associated 
diseases among older adults in the U.S. has been estimated to cost 
$51.3 billion annually.\1135\
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    \1131\ Norman K, Pichard C, Lochs H, Pirlich M. (2008). 
Prognostic impact of disease-related malnutrition. Clin. Nutr. 27, 
5-15.
    \1132\ Khalatbari-Soltani S, Marques-Vida, P. (2015). The 
economic cost of hospital malnutrition in Europe; a narrative 
review. Clin. Nutr. ESPEN. 10, e89-e94.
    \1133\ Correia MI, Waitzberg DL. (2003). The impact of 
malnutrition on morbidity, mortality, length of hospital stay and 
costs evaluated through a multivariate model analysis. Clin Nutr. 
22(3):235-9.
    \1134\ Ibid.
    \1135\ Snider JT, Linthicum MT, Wu Y, et al. (2014). Economic 
burden of community-based disease-associated malnutrition in the 
United States. JPEN. 38(2 Suppl):77s-85s.
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    Hospitals have an opportunity to identify malnutrition during the 
patient admission process and to address it efficiently and effectively 
with individualized interventions that could optimize outcomes 
including reduced readmissions and lengths of stay.\1136\ Research 
demonstrates that there is significant room to improve identification, 
diagnosis, and treatment of malnutrition in hospitalized 
patients.1137 1138 Nutrition screening is the first step in 
optimal malnutrition care and triggers a nutrition assessment for 
patients found to be at risk.1139 1140
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    \1136\ Ibid.
    \1137\ Kabashneh S, Alkassis S, Shanah L, Ali H. (2020). A 
Complete Guide to Identify and Manage Malnutrition in Hospitalized 
Patients. Cureus. doi: 10.7759/cureus.8486.
    \1138\ Fitall E, Jones Pratt K, McCauley SM, Astrauskas G, Heck 
T, Hernandez B, et al. (2019). Improving Malnutrition in 
Hospitalized Older Adults: The Development, Optimization, and Use of 
a Supportive Toolkit. Journal of the Academy of Nutrition and 
Dietetics. 119(9):S25-S31 Available at: https://www.sciencedirect.com/science/article/pii/S2212267219305039.
    \1139\ Skipper A. (2008). Nutrition care process and model part 
I: the 2008 update. J Am Diet Assoc.108(7):1113-7.
    \1140\ Swan W, Vivanti A, Hakel-Smith NA, Trostler N, Beck 
Howarter N, Papoutsakis C. (2017). Nutrition Care Process and Model 
Update: Toward Realizing People-Centered Care and Outcomes 
Management. Journal of the Academy of Nutrition and Dietetics. 
117(12):2003-2014.
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    We have consistently received stakeholder input requesting the 
addition of nutrition measures to the Hospital IQR Program measure set 
to address malnutrition of hospitalized patients, including comments 
described in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51639), the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53535), the

[[Page 28520]]

FY 2014 IPPS/LTCH PPS final rule (78 FR 50810), the FY 2015 IPPS/LTCH 
PPS final rule (79 FR 50056), and the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49561). In the FY 2018 IPPS/LTCH PPS proposed rule, we solicited 
public comments on potential future inclusion of malnutrition eCQMs in 
the Hospital IQR Program (82 FR 20060 through 20061), and in the FY 
2018 IPPS/LTCH PPS final rule we provided a summary of these comments 
(82 FR 38379 through 38380). Commenters expressed support and stated 
that Medicare beneficiaries would benefit from the adoption of 
malnutrition eCQMs that support prompt malnutrition screening, 
assessment, diagnosis, and development of a care plan (82 FR 38379). In 
addition, the commenters stated that eCQMs specifically designed and 
tested to be used with patient data documented directly in the EHR 
would likely impose minimal data collection and reporting burden (82 FR 
38379 through 38380). The commenters further stated that the inclusion 
of malnutrition eCQMs in the Hospital IQR Program measure set could 
help improve outcomes and quality of life for patients, especially for 
seniors and the disadvantaged (82 FR 38380). We believe adopting a 
malnutrition measure would address several priority areas identified in 
the CMS Equity Plan for Medicare, including evaluating impacts of 
disparities, integrating equity solutions across CMS programs, and 
increasing the ability of the healthcare workforce to meet the needs of 
underserved populations.\1141\
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    \1141\ Centers for Medicare & Medicaid Services. CMS Equity Plan 
for Medicare. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/equity-initiatives/equity-plan.
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    Therefore, in this proposed rule, we are proposing to adopt the 
Global Malnutrition Composite Score eCQM (NQF #3592e) beginning with 
the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years. At this time, CMS quality reporting programs do not 
include quality measures that specifically address malnutrition. In the 
CY 2022 Physician Fee Schedule (PFS) final rule (86 FR 65970 through 
65971), we adopted the Implement Food Insecurity and Nutrition Risk 
Identification and Treatment Protocols Improvement Activity (IA) as 
part of the Merit-based Incentives Payment System (MIPS), which 
incentivizes MIPS-eligible clinicians to create or improve, and then 
implement, protocols for identifying and providing appropriate support 
to: (a) Patients with or at risk for food insecurity, and (b) patients 
with or at risk for poor nutritional status.\1142\ In conjunction with 
adopting the IA under MIPS, we believe adoption of the Global 
Malnutrition Composite Score eCQM in the Hospital IQR Program has the 
potential to improve care delivery in the inpatient setting and is 
likely to ameliorate food insecurity and malnutrition and lead to 
better health outcomes.
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    \1142\ Centers for Medicare & Medicaid Services. Quality Payment 
Program. Improvement Activities Performance Category: Traditional 
MIPS Requirements. Available at: https://qpp.cms.gov/mips/improvement-activities.
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    Under the CMS Meaningful Measures Framework,\1143\ the Global 
Malnutrition Composite Score eCQM addresses the quality priority of 
``Promote Effective Communication & Coordination of Care'' as well as 
``Promote Effective Prevention and Treatment of Chronic Disease.'' 
Under the CMS Meaningful Measures 2.0 Initiative, the Global 
Malnutrition Composite Score eCQM addresses the quality priority of 
``Affordability and Efficiency.'' \1144\
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    \1143\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \1144\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
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(2) Overview of Measure
    The Global Malnutrition Composite Score eCQM assesses adults 65 
years of age and older admitted to inpatient hospital service who 
received care appropriate to their level of malnutrition risk and 
malnutrition diagnosis, if properly identified. Best practices for 
malnutrition care recommend inpatients be screened for malnutrition 
risk, assessed to confirm findings of malnutrition if found at-risk, 
and have the proper severity of malnutrition indicated in their 
diagnosis along with a corresponding nutrition care plan that addresses 
the respective severity of malnutrition.1145 1146
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    \1145\ Nepple KG, Tobert CM, Valladares AF, Mitchell K, Yadrick 
M. (2019). Enhancing Identification and Management of Hospitalized 
Patients Who Are Malnourished: A Pilot Evaluation of Electronic 
Quality Improvement Measures. Journal of the Academy of Nutrition 
and Dietetics. 119(9):S32-S39.
    \1146\ McCauley SM, Barrocas A, Malone A. (2019). Hospital 
Nutrition Care Betters Patient Clinical Outcomes and Reduces Costs: 
The Malnutrition Quality Improvement Initiative Story. Journal of 
the Academy of Nutrition and Dietetics. 119(9):S11-S14.
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    The proposed malnutrition composite measure includes four component 
measures, which are first scored separately, and then integrated into 
an overall composite score. The overall composite score is derived from 
averaging the individual performance scores of the following four 
component measures:
     Screening for malnutrition risk at admission;
     Completing a nutrition assessment for patients who 
screened for risk of malnutrition;
     Appropriate documentation of malnutrition diagnosis in the 
patient's medical record if indicated by the assessment findings; and
     Development of a nutrition care plan for malnourished 
patients including the recommended treatment plan.

Together, the four component measures represent the key processes of 
care of malnutrition associated with the risk identification, 
diagnosis, and treatment of malnutrition in older hospitalized adults 
as supported by clinical guidelines and submitted evidence.\1147\
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    \1147\ Valladares AF, McCauley SM, Khan M, D'Andrea C, Kilgore 
K, Mitchell K. (2021). Development and Evaluation of a Global 
Malnutrition Composite Score. Journal of the Academy of Nutrition 
and Dietetics. 122(2):P251-P253.
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    The four component measures were initially submitted for 
endorsement as individual process measures in the NQF 2015-2017 Health 
and Well-Being Project.\1148\ The NQF declined to endorse any of the 
individual component measures based on evidence, provider burden 
concern (including timing of malnutrition screening and assessment), 
and the unavailability of necessary data elements to report the 
eCQMs.\1149\ The 2015-2017 Health and Well-Being Standing Committee 
recommended combining individual measures or all measures into a 
composite measure to make the measure more meaningful by including both 
the screening and the development of a nutrition care plan into one 
measure.\1150\
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    \1148\ National Quality Forum. Health and Well-Being Project 
2015-2017. Available at: https://www.qualityforum.org/ProjectDescription.aspx?projectID=80741.
    \1149\ National Quality Forum. Prevention and Population Health, 
Fall 2020 Cycle: CDP Report. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=86178.
    \1150\ National Quality Forum. Health and Well-Being 2015-2017 
Final Report. Available at: https://www.qualityforum.org/Publications/2017/04/Health_and_Well-Being_2015-2017_Final_Report.aspx.
---------------------------------------------------------------------------

    Based on these recommendations, the measure developer conducted 
additional testing. The four component measures were piloted as a 
single composite measure at a large hospital in

[[Page 28521]]

the Midwest and the testing results demonstrated that the measures were 
usable for identifying key improvement areas in malnutrition care 
related to identifying risk, assessing for malnutrition, developing the 
appropriate care plan, and ensuring the diagnosis of malnutrition was 
documented to support follow-up care.\1151\ Subsequently, a group of 27 
hospitals adopted and reported on the use of the four component 
measures to guide various projects focused on improving care provided 
to hospitalized patients who were malnourished or at risk of 
malnutrition.\1152\ The participating hospitals reported changes in 
measure performance based on implementation of cyclical quality 
improvement initiatives at their respective institutions. Multivariate 
analyses were then conducted to identify the relationships between 
performance on the four component measures with patient outcomes of 30-
day readmission and length of stay. The study results concluded that 
the four component measures could be implemented in a cohort of diverse 
hospitals and lead to meaningful improvements in measure performance as 
all four components of the composite measure were significantly 
associated with improved outcomes for 30-day 
readmissions.1153 1154 Prior analyses also reported early 
nutrition interventions were associated with reduced patient length of 
stay.1155 1156 1157 1158 1159 Following measure testing, the 
measure developer returned to NQF with the composite eCQM for 
consideration in the Fall 2020 measure cycle.
---------------------------------------------------------------------------

    \1151\ Nepple KG, Tobert CM, Valladares AF, Mitchell K, Yadrick 
M. (2019). Enhancing identification and management of hospitalized 
patients who are malnourished: A pilot evaluation of electronic 
quality improvement measures. Journal of the Academy of Nutrition 
and Dietetics. 119: S32-S39.
    \1152\ Valladares AF, Kilgore KM, Partridge J, Sulo S, Kerr KW, 
McCauley S. (2021). How a malnutrition quality improvement 
initiative furthers malnutrition measurement and care: Results from 
a hospital learning collaborative. JPEN J Parenter Enteral Nutr. 45: 
366-371.
    \1153\ Ibid.
    \1154\ Anghel S, Kerr KW, Valladares AF, Kilgore KM, Sulo S. 
(2021). Identifying patients with malnutrition and improving use of 
nutrition interventions: A quality study in four US hospitals. 
Nutrition. 91-92; 111360.
    \1155\ Silver HJ, Pratt KJ, Bruno M, Lynch J, Mitchell K, 
McCauley SM. (2018). Effectiveness of the malnutrition quality 
improvement initiative on practitioner malnutrition knowledge and 
screening, diagnosis, and timeliness of malnutrition-related care 
provided to older adults admitted to a tertiary care facility: A 
pilot study. Journal of the Academy of Nutrition and Dietetics. 
118(1): 101-109.
    \1156\ Meehan A, Loose C, Bell J, Partridge J, Nelson J, Goates 
S. (2017). Health system quality improvement: Impact of prompt 
nutrition care on patient outcomes and health care costs. J Nurs 
Care Qual. 2016; 31(3): 217-223.
    \1157\ Sriram K, Sulo S, VanDerBosch G, et al. A comprehensive 
nutrition-focused Quality Improvement Program reduces 30-day 
readmissions and length of stay in hospitalized patients. JPEN J 
Parenter Enteral Nutr. 41(3): 384-391.
    \1158\ Somanchi M, Tao X, Mullin GE. (2011). The facilitated 
early enteral and dietary management effectiveness trial in 
hospitalized patients with malnutrition. JPEN J Parenter Enteral 
Nutr. 35(2): 209-216.
    \1159\ Deutz NE, Matheson EM, Matarese LE, et al. (2016). 
Readmission and mortality in malnourished, older, hospitalized 
adults treated with a specialized oral nutritional supplement: A 
randomized clinical trial. Clin Nutr. 35(1): 18-26.
---------------------------------------------------------------------------

    The Global Malnutrition Composite Score eCQM (MUC20-0032) was 
included in the publicly available ``List of Measures Under 
Consideration for December 21, 2020'' (MUC List).\1160\ The measure was 
voted on and approved by the Scientific Methods Panel in October 
2020.\1161\ The MAP Rural Health Advisory Group reviewed the measure 
during its January 2021 meeting and agreed that this measure was 
suitable for use with rural providers in the Hospital IQR 
Program.\1162\ The MAP subsequently offered conditional support for 
rulemaking, pending NQF endorsement of the measure.\1163\
---------------------------------------------------------------------------

    \1160\ Centers for Medicare & Medicaid Services. List of 
Measures Under Consideration for December 21, 2020. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf.
    \1161\ National Quality Forum. MAP 2020-2021 Considerations for 
Implementing Measures in Federal Programs: Clinician, Hospital & 
PAC/LTC. Available at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \1162\ National Quality Forum. Measure Applications Partnership 
Rural Health Workgroup Virtual Review Meeting Summary. January 2021. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94656.
    \1163\ National Quality Forum. MAP 2020-2021 Considerations for 
Implementing Measures Final Report--Clinicians, Hospitals, and PAC-
LTC. March 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.
---------------------------------------------------------------------------

    The composite measure was initially reviewed by the NQF Prevention 
and Population Health (PPH) Standing Committee for endorsement 
suitability during its February 2021 measure evaluation meeting \1164\ 
and the full review of the measure was detailed in the NQF Prevention 
and Population Health Fall 2020 Consensus Development Process (CDP) 
Report.\1165\ The NQF PPH Standing Committee members agreed 
malnutrition is a significant contributor to infections and pressure 
ulcers requiring treatment, especially for patients transferred to 
other care facilities (such as an inpatient rehabilitation hospital), 
and held a robust discussion with most members supporting the presented 
evidence and topic area importance that assigns accountability to the 
hospital team.\1166\ Some PPH Standing Committee members questioned the 
lack of validated and standardized screening and assessment tools 
specified in the first two components. The measure developer along with 
the measure steward stated that objective, validated screening tools 
\1167\ and standardized assessment tools \1168\ can be implemented to 
capture variables from structured EHR data fields, such as BMI, dietary 
history, recent weight loss, illness severity, laboratory values, and 
age. After further discussion on performance gaps and the ability to 
discern differences within and between populations, many PPH Standing 
Committee members stated they wanted to review additional performance 
data for the eCQM.\1169\ The measure developer submitted the requested 
performance data for the PPH NQF Standing Committee to review, discuss, 
and revote at the NQF Standing Committee post-comment meeting on June 
3, 2021.\1170\ At that time, the NQF PPH Standing Committee voted on 
the overall suitability for endorsement and the NQF Consensus Standards 
Approval Committee (CSAC) subsequently endorsed the measure (NQF 
#3592e).\1171\
---------------------------------------------------------------------------

    \1164\ National Quality Forum. Measure Evaluation Web Meeting 
#1: Prevention and Population Health. February 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94816.
    \1165\ National Quality Forum. Prevention and Population Health 
Fall 2020 CDP Report. October 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96457.
    \1166\ National Quality Forum. Measure Worksheet--3592--Fall 
2020 Cycle. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95961.
    \1167\ Skipper A, Coltman A, Tomesko J, Piemonte TA, Handu D, 
Cheng FW, et al. Position of the Academy of Nutrition and Dietetics: 
Malnutrition (Undernutrition) Screening Tools for All Adults. 
Journal of the Academy of Nutrition and Dietetics. 120(4):709-713.
    \1168\ White JV, Guenter P, Jensen G, Malone A, Schofield M. 
Consensus Statement of the Academy of Nutrition and Dietetics/
American Society for Parenteral and Enteral Nutrition: 
Characteristics Recommended for the Identification and Documentation 
of Adult Malnutrition (Undernutrition). J Am Diet Assoc;112(5):730-
738.
    \1169\ National Quality Forum. Post-Comment Web Meeting (Fall 
2020 Cycle) Comments Received. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95422.
    \1170\ National Quality Forum. Post-Comment Web Meeting (Fall 
2020 Cycle) Memo. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95421.
    \1171\ National Quality Forum. Consensus Standards Approval 
Committee Prevention and Population Health Fall 2020 Review. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95602.

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

[[Page 28522]]

    The measure specifications for the Global Malnutrition Composite 
Score eCQM can be found on the eCQI Resource Center website, available 
at https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Measure Calculation
    The Global Malnutrition Composite Score eCQM consists of four 
component measures, which are first scored 
separately.1172 1173 The overall composite score is derived 
from averaging the individual performance scores of the four component 
measures. The malnutrition component measures are all fully specified 
for use in EHRs. Table IX.E-04. outlines the data specification(s) and 
data sources for each of the four components.
---------------------------------------------------------------------------

    \1172\ Valladares AF, McCauley SM, Khan M, D'Andrea C, Kilgore 
K, Mitchell K. (2021). Development and Evaluation of a Global 
Malnutrition Composite Score. Journal of the Academy of Nutrition 
and Dietetics. Available at: https://www.jandonline.org/article/S2212-2672(21)00075-7/fulltext.
    \1173\ National Quality Forum. #3592e Global Malnutrition 
Composite Score. Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3592e.
---------------------------------------------------------------------------

BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.188

(5) Measure Numerator
    The Global Malnutrition Composite Score eCQM numerator is comprised 
of the four component measures, that are individually scored for 
patients 65 years of age and older who are admitted to an acute 
inpatient hospital. Details on the numerator for each component are 
specified in Table IX.E-05.
[GRAPHIC] [TIFF OMITTED] TP10MY22.189


[[Page 28523]]


(6) Measure Denominator
    The measure denominator is the composite, or total, of the four 
component measures for patients aged 65 years and older who are 
admitted to an acute inpatient hospital. Details on the denominator 
(and any exclusions) for each component are specified in Table IX.E-06.
[GRAPHIC] [TIFF OMITTED] TP10MY22.190

BILLING CODE 4120-01-C
    Each measure component is a proportion with a possible performance 
score of 0 to 100 percent. After each component score is calculated 
individually, an unweighted average of all four scores is completed to 
determine the final composite score with a total score ranging from 0 
to 100 percent.\1174\
---------------------------------------------------------------------------

    \1174\ Valladares AF, McCauley SM, Khan M, D'Andrea C, Kilgore 
K, and Mitchell K. (2022). Development and Evaluation of a Global 
Malnutrition Composite Score. Journal of the Academy of Nutrition 
and Dietetics. 122(2): p251-253.
---------------------------------------------------------------------------

(7) Data Submission and Reporting
    We are proposing to adopt the Global Malnutrition Composite Score 
eCQM as part of the Hospital IQR Program measure set for which 
hospitals can self-select beginning with the CY 2024 reporting period/
FY 2026 payment determination and for subsequent years. We refer 
readers to section IX.E.10.e. of this proposed rule for our previously 
finalized eCQM reporting and submission requirements, as well as 
proposed modifications for these requirements. We also refer readers to 
section IX.H.10.a.(2). of the preamble of this proposed rule for 
discussion of a similar proposal to adopt this measure in the Medicare 
Promoting Interoperability Program for Eligible Hospitals and CAHs.
    We invite public comment on this proposal.
g. Proposed Hospital-Level, Risk Standardized Patient-Reported Outcomes 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #3559), Beginning With Two Voluntary 
Reporting Periods in CYs 2025 and 2026, Followed by Mandatory Reporting 
for Eligible Elective Procedures Occurring July 1, 2025 Through June 
30, 2026, Impacting the FY 2028 Payment Determination and for 
Subsequent Years
(1) Background
    Approximately six million adults aged 65 or older suffer from 
osteoarthritis in the U.S.\1175\ Osteoarthritis accounts for more than 
half of all arthritis-related hospitalizations,\1176\ and in 2013 there 
were approximately 1,023,000 hospitalizations for osteoarthritis.\1177\ 
Hip and knee osteoarthritis is one of the leading causes of disability 
among non-institutionalized adults,\1178\ and roughly 80 percent of 
patients with osteoarthritis have some limitation in mobility.\1179\ 
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.\1180\ 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.1181 1182 1183 1184 However, not all

[[Page 28524]]

patients experience benefit from these procedures.\1185\ Many patients 
note that their pre-operative expectations for functional improvement 
have not been met.1186 1187 1188 1189 In addition, clinical 
practice variation has been well documented in the 
U.S.,1190 1191 1192 readmission and complication rates vary 
across hospitals,1193 1194 and international experience 
documents wide hospital-level variation in patient-reported outcome 
measure results following THA and TKA.\1195\
---------------------------------------------------------------------------

    \1175\ Arthritis Foundation. Arthritis By the Numbers Book of 
Trusted Facts and Figures. 2018: https://www.arthritis.org/getmedia/e1256607-fa87-4593-aa8a-8db4f291072a/2019-abtn-final-march-2019.pdf. 
Accessed March 8, 2019.
    \1176\ Levit K, Stranges E, Ryan K, Elixhauser A. HCUP Facts and 
Figures, 2006: Statistics on Hospital-based Care in the United 
States. 2008. Available at: https://www.hcup-us.ahrq.gov/reports.jsp.
    \1177\ 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.
    \1178\ 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.
    \1179\ 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. doi: 10.1186/1478-7954-4-11.
    \1180\ Centers for Disease Control and Prevention (CDC). 
Osteoarthritis (OA). https://www.cdc.gov/arthritis/basics/osteoarthritis.htm. Accessed March 8, 2019. Available at: https://www.cdc.gov/arthritis/basics/osteoarthritis.htm.
    \1181\ 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.
    \1182\ 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.
    \1183\ 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.
    \1184\ 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.
    \1185\ National Joint Registry. National Joint Registry for 
England and Wales 9th Annual Report 2012. available at 
www.njrcentre.org.uk: National Joint Registry;2012.
    \1186\ 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.
    \1187\ 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.
    \1188\ 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.
    \1189\ Jourdan C, Poiraudeau S, Descamps S, et al. Comparison of 
patient and surgeon expectations of total hip arthroplasty. PloS 
one. 2012;7(1):e30195.
    \1190\ Roos EM. Effectiveness and practice variation of 
rehabilitation after joint replacement. Current opinion in 
rheumatology. 2003;15(2):160-162.
    \1191\ 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.
    \1192\ 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.
    \1193\ 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.
    \1194\ 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: 
https://qualitynet.org/.
    \1195\ 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/bitstream/handle/2077/23722/gupea_2077_23722_1.pdf?sequence=1. Accessed July 
20, 2013.
---------------------------------------------------------------------------

    For example, data from the United Kingdom demonstrate that there is 
a greater than 15 percent difference across hospitals in the proportion 
of patients showing improvement after surgery.1196 1197
---------------------------------------------------------------------------

    \1196\ National Health System: Provisional Patient Reported 
Outcome Measures (PROMs) in England--for Hip and Knee Replacement 
Procedures (April 2020 to March 2021): Score Comparison Tool. 
https://digital.nhs.uk/data-and-information/publications/statistical/patient-reported-outcome-measures-proms/hip-and-knee-replacement-procedures-april-2020-to-march-2021#resources.
    \1197\ 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.
---------------------------------------------------------------------------

    Peri-operative care and care coordination across provider groups 
and specialties have important effects on clinical 
outcomes.1198 1199 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 post-operative 
care.1200 1201 1202 1203 1204 1205
---------------------------------------------------------------------------

    \1198\ Feng J, Novikov D, Anoushiravani A, Schwarzkopf R. Total 
knee arthroplasty: Improving outcomes with a multidisciplinary 
approach. J Multidiscip Healthc. 2018;11:63-73.
    \1199\ 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.
    \1200\ 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.
    \1201\ 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.
    \1202\ 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.
    \1203\ 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.
    \1204\ 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.
    \1205\ 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 we established an incentivized, 
voluntary PRO data collection opportunity within the Comprehensive Care 
for Joint Replacement (CJR) model \1206\ to support measure 
development. Requirements for successful submission of PRO data for 
eligible elective primary THA/TKA procedures were set forth 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 (THA/TKA) performance measure (THA/TKA PRO-PM) 
was developed and tested using PRO instruments and risk variable data 
collected 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.
---------------------------------------------------------------------------

    \1206\ Centers for Medicare & Medicaid Services. Comprehensive 
Care for Joint Replacement Model. Available at: https://innovation.cms.gov/innovation-models/cjr.
---------------------------------------------------------------------------

    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.\1207\ 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 healthcare 
environment continues to change. Meaningful Measures 2.0 \1208\ is 
currently underway and aims to promote better collection and 
integration of patients' voices by incorporating patient reported 
outcome measures that are embedded into the clinical workflow, are easy 
to use, and reduce reporting burden.\1209\ The THA/TKA PRO-PM is fully 
developed and aligns with these future Meaningful Measures 2.0 goals, 
which are still under development.
---------------------------------------------------------------------------

    \1207\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1208\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \1209\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    Elective THA/TKAs are important, effective procedures performed on 
a

[[Page 28525]]

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,1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222
 are influenced by a range of improvements in 
care,1223 1224 1225 1226 1227 1228 1229 1230 and demonstrate 
hospital-level variation even after patient case mix 
adjustment.1231 1232 Further, THA/TKA procedures are 
specifically intended to improve function and reduce pain, making 
patient reported outcomes a meaningful outcome metric to assess.\1233\
---------------------------------------------------------------------------

    \1210\ 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.
    \1211\ 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.
    \1212\ 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.
    \1213\ 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.
    \1214\ 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.
    \1215\ Lau RL, Gandhi R, Mahomed S, Mahomed N. Patient 
satisfaction after total knee and hip arthroplasty. Clin Geriatr 
Med. 2012;28(3):349-365.
    \1216\ 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.
    \1217\ 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.
    \1218\ 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.
    \1219\ 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.
    \1220\ 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.
    \1221\ 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.
    \1222\ White D, Master H. Patient Reported Measures of Physical 
Function in Knee Osteoarthritis. Rheum Dis Clin North Am. 
2016;42(2):239-252.
    \1223\ 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.
    \1224\ 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.
    \1225\ 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.
    \1226\ 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.
    \1227\ 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.
    \1228\ 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.
    \1229\ 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.
    \1230\ 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.
    \1231\ 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.
    \1232\ M[auml]kel[auml] KT, Peltola M, Sund R, Malmivaara A, 
Hakkinen 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.
    \1233\ 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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    Several stakeholder groups were engaged throughout the development 
process of the THA/TKA PRO-PM, as recommended in the Measures 
Management System (MMS) Blueprint,\1234\ including a Technical Advisory 
Group (TAG), a Patient Working Group, and a national, multi-stakeholder 
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 provided feedback on the measure concept, 
outcome, cohort, risk model variables, reporting results, and data 
collection. We received feedback from patients and providers that they 
had a desire for a flexible data collection approach. For example, 
providers wanted the option to choose to collect their own data or have 
data collected through an external entity, such as a vendor. Patients 
wanted to choose from multiple modes of data collection, such as 
telephone, paper, and/or electronic. We also received feedback from 
patients and providers that they would like to utilize their patient 
reported outcome results as part of the shared decision-making process. 
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. In response 
to this feedback, we are not proposing a specific mode for data 
collection for the THA/TKA PRO-PM. Rather, we are proposing that 
hospitals may determine a data collection mode that accommodates their 
clinical workflow. We also received multiple public comments as 
summarized in the 2015 CJR final rule (80 FR 73274) that we used to 
support the development of this measure.
---------------------------------------------------------------------------

    \1234\ CMS Measures Management System Blueprint (Blueprint v 
17.0). 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.'' \1235\ The MAP 
Coordinating Committee supported the measure, as referenced in the 
2020-2021 Final Recommendations report to HHS and CMS.\1236\ The NQF 
endorsed the THA/TKA PRO-PM (NQF #3559) in November 2020.\1237\
---------------------------------------------------------------------------

    \1235\ 2020 Measures Under Consideration List. Available at 
https://www.cms.gov/media/492911.
    \1236\ 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.
    \1237\ NQF Quality Positioning System. Available at https://www.qualityforum.org/QPS.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25588 through 
25592), we requested public comment on the potential future inclusion 
of the THA/TKA PRO-PM in the Hospital IQR Program. Many commenters 
expressed support for the measure, with many commending joint-specific 
PRO-PMs as an effective way to provide insights to quality improvement 
opportunities, PRO-PMs for assessing results of surgery as interpreted 
by patients, and describing the measure as essential for value-based 
payment models (86 FR 45411 through 45414). Many commenters recommended 
that the measure be implemented in a phased approach, with voluntary 
reporting occurring prior to public reporting (86 FR 45411 through 
45414). In response to these comments, we are proposing a phased 
implementation approach, with

[[Page 28526]]

two voluntary reporting periods in CY 2025 and 2026 reporting periods 
prior to mandatory reporting beginning with the CY 2027 reporting 
period/FY 2028 payment determination, as described in further detail in 
our discussion on data submission in section IX.E.5.g.(9) of the 
preamble of this proposed rule.
    Furthermore, many commenters recommended that we offer multiple 
options for data submission, including through the hospital directly or 
by an external vendor engaged by a hospital for this purpose, to ensure 
hospitals have the flexibility needed to implement the measure (86 FR 
45411 through 45414). In response to those comments, in this proposed 
rule, we are proposing flexible options for data submission as 
discussed in more detail in subsequent section. For a more detailed 
description of the public comments received, we refer readers to the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45411 through 45414).
    Additionally, we note that many hospitals have already incorporated 
PRO data collection into their workflows. While we are not proposing to 
require how hospitals collect data, hospitals new to collecting PRO 
data have multiple options for when and how they would collect this 
data and can best determine the mode of data collection that works for 
their patient population.
(2) Overview of Measure
    The THA/TKA PRO-PM reports the hospital-level risk-standardized 
improvement rate (RSIR) in patient reported outcomes 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 pre-operative 
assessment (data collected 90 to 0 days before surgery) to the post-
operative 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 at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(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 data collected by hospitals pre-operatively and post-
operatively (described in section IX.E.5.g.(9).) and limited patient-
level risk factor data collected with PRO data and identified in 
claims. The measure includes PRO data collected with several PRO 
instruments, among them are two joint-specific PRO instruments--the Hip 
dysfunction and Osteoarthritis Outcome Score for Joint Replacement 
(HOOS, JR) \1238\ for completion by THA recipients and the Knee injury 
and Osteoarthritis Outcome Score for Joint Replacement (KOOS, JR) 
\1239\ for completion by TKA recipients--from which scores are used to 
assess substantial clinical improvement. For risk adjustment by pre-
operative mental health score, hospitals would submit one of two 
additional PRO instruments, either all of the items in the Patient-
Reported Outcomes Measurement Information System (PROMIS)-Global Mental 
Health subscale or all of the items in the Veterans RAND 12-Item Health 
Survey (VR-12) Mental Health subscale.1240 1241 The risk 
model also includes a one-question patient-reported assessment of 
health literacy--the Single Item Literacy Screener questionnaire.
---------------------------------------------------------------------------

    \1238\ Lyman S, Lee Y-Y, Franklin PD, Li W, Mayman DJ, Padgett 
DE. Validation of the HOOS, JR: A Short-form Hip Replacement Survey. 
Clinical Orthopaedics and Related Research.[supreg] 
2016;474(6):1472-1482.
    \1239\ Lyman S, Lee Y-Y, Franklin PD, Li W, Cross MB, Padgett 
DE. Validation of the KOOS, JR: A Short-form Knee Arthroplasty 
Outcomes Survey. Clinical Orthopaedics and Related Research.[supreg] 
2016;474(6):1461-1471.
    \1240\ National Institutes of Health (NIH). (Patient Reported 
Outcomes Measurement Information Systems) PROMIS Instrument Details. 
Available at: https://www.nihpromis.org/measures/instrumentdetails.
    \1241\ Iqbal US, Rogers W, Selim A, et al. The Veterans Rand 12 
Item Health Survey (VR-12): What It Is and How It Is Used. https://www.hosonline.org/globalassets/hos-online/publications/veterans_rand_12_item_health_survey_vr-12_2007.pdf.
---------------------------------------------------------------------------

    Furthermore, the following data are collected for identification of 
the measure cohort, outcome and for risk adjustment purposes. Claims 
data are used to identify eligible elective primary THA/TKA procedures 
for the measure cohort to which submitted PRO data can be matched, and 
to identify additional variables for risk adjustment and in the 
statistical approach to accounting for response bias, including patient 
demographics and clinical comorbidities up to 12 months prior to 
surgery. The Medicare Enrollment Database (EDB) identifies Medicare FFS 
enrollment and race, and the Master Beneficiary Summary File allows for 
determination of Medicare and Medicaid dual eligibility enrollment 
status. Demographic information from the U.S. Census Bureau's American 
Community Survey \1242\ allows for derivation of the AHRQ SES Index 
score. Race, dual eligibility, and AHRQ SES Index score are used in the 
statistical approach to accounting for non-response bias. We refer 
readers to section IX.E.5.g.(9). for further details regarding the 
variables required for data collection and submission.
---------------------------------------------------------------------------

    \1242\ American Community Survey, available at: https://www.census.gov/programs-surveys/acs.
---------------------------------------------------------------------------

(4) Outcome
    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 pre-operative and 
post-operative 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 would 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 pre-operative and post-operative 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 will be evaluating 
options to address measurement of those procedures and settings.
    For additional details regarding the measure cohort, we refer 
readers to the Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure--

[[Page 28527]]

Measure Methodology Report, available in Hip and Knee Arthroplasty 
Patient-Reported Outcomes folder at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(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 a 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, and patients 
who leave the hospital against medical advice following the procedure.
(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. The risk model includes some of the same risk 
variables collected with PRO data by hospitals in the CJR model as well 
as risk variables identified in claims. The pre-operative score of the 
Mental Health subscale from one of two global PRO instruments (the 
PROMIS-Global or the VR-12) 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, poorly or incompletely collected PRO data may be 
asymmetrically distributed across lower socioeconomic or disadvantaged 
populations, potentially affecting measure scores. Research on PRO-PM 
response has indicated that patients of non-White race, patients of 
lower socio-economic status, and patients with Medicare and Medicaid 
coverage have lower response rates.1243 1244 1245 Therefore, 
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, social drivers of health, 
and demographic variables (such as non-White individuals, 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.
---------------------------------------------------------------------------

    \1243\ Hutchings A, Neuburger J, Frie K, Black N, van der Meulen 
J. Factors associated with nonresponse in routine use of patient 
reported outcome measures after elective surgery in England. Health 
and Quality of Life Outcomes. 2012;10(34).
    \1244\ Schamber E, Takemoto S, Chenok K, Bozic K. Barriers to 
completion of patient reported outcome measures. The Journal of 
arthroplasty. 2013;28:1449-1453.
    \1245\ Patel J, Lee J, Zhongmin L, SooHoo N, Bozic K, Huddleston 
J. Predictors of low patient-reported outcomes response rates in the 
California Joint Replacement Registry. The Journal of arthroplasty. 
2015;30:2071-2075.
---------------------------------------------------------------------------

    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 in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder 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 elective primary THA and TKA. 
Response rates for PRO data would be calculated as the percentage of 
elective primary THA or TKA procedures for which complete and matched 
pre-operative and post-operative PRO data have been submitted divided 
by the total number of eligible THA or TKA procedures performed at each 
hospital.
(9) Data Submission
    Comments submitted on a request for information in the FY 2022 
IPPS/LTCH PPS proposed rule and summarized in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45411 through 45414) recommended CMS provide multiple 
options for data submission mechanisms to ensure flexibility, including 
through qualified clinical data registries, as well as through the 
hospital.
    In response to ongoing stakeholder feedback and public comments in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45411through 45414), we are 
proposing to adopt the THA/TKA PRO-PM in the Hospital IQR Program 
utilizing multiple submission approaches. For example, hospitals may 
choose to: (1) Send their data to CMS for measure calculation directly; 
or (2) utilize an external entity, such as through a vendor or 
registry, to submit data on behalf of the hospital to CMS for measure 
calculation. Furthermore, hospitals or vendors would use the HQR System 
as part of data submission for the THA/TKA PRO-PM. Use of the HQR 
System leverages existing CMS infrastructure already utilized for other 
quality measures (such as the Hospital Consumer Assessment of 
Healthcare Providers and Systems (HCAHPS) Survey). The HQR System 
allows for data submission using multiple file formats (such as CSV, 
XML) and a manual data entry option, allowing hospitals and vendors 
additional flexibility in data submission. We would provide hospitals 
with more detailed instructions and information regarding data 
submission through CMS' existing website QualityNet, and through list 
servs. This data submission approach is consistent with stakeholder 
input received by the measure developer during measure development and 
comments as summarized in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45411 through 45414) which recommended CMS provide multiple options for 
data submission mechanisms to ensure flexibility.
    Hospitals would submit the following pre-operative assessment 
variables collected between 90 and zero days prior to the THA/TKA 
procedure: Medicare provider number, Medicare health insurance claim 
(HIC) number/Medicare beneficiary identifier (MBI), date of birth, date 
of procedure, date of PRO data collection, procedure type, mode of 
collection, person completing the survey, date of admission to anchor 
hospitalization, generic patient reported outcome measure version, 
PROMIS-Global (mental health subscale items) or VR-12 (mental health 
subscale items), HOOS, JR (for THA patients), KOOS, JR (for TKA 
patients), Single-Item Health Literacy Screening (SILS2) questionnaire, 
BMI or weight (kg)/height (cm), chronic (>=90 day) narcotic use, total 
painful joint count (patient-reported in non-operative lower extremity 
joint), and quantified spinal

[[Page 28528]]

pain (patient-reported back pain, Oswestry index question 
1246 1247).
---------------------------------------------------------------------------

    \1246\ Fairbank JC, Pynsent PB. The Oswestry Disability Index. 
Spine (Phila Pa 1976). 2000 Nov 15;25(22):2940-52; discussion 2952. 
doi: 10.1097/00007632-200011150-00017. PMID: 11074683.
    \1247\ The Oswestry Disability Index is in the public domain and 
available for all hospitals to use.
---------------------------------------------------------------------------

    Hospitals would submit the following post-operative assessment 
variables collected between 300 and 425 days following the THA/TKA 
procedure: Medicare provider number, Medicare health insurance claim 
number/Medicare beneficiary identifier, date of birth, procedure date, 
date of PRO data collection, procedure type, mode of collection, person 
completing the survey, date of admission to anchor hospitalization, 
KOOS, JR (TKA patients), and HOOS, JR (THA patients). The data 
submission period for the THA/TKA PRO-PM would also serve as the review 
and correction period. Data would not be able to be corrected following 
the submission deadline.
    For additional details 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 in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(a) Voluntary Reporting Period
    We are proposing a phased implementation approach for adoption of 
this measure to the Hospital IQR Program, with two voluntary reporting 
periods prior to mandatory reporting in the Hospital IQR Program. 
Voluntary reporting prior to mandatory reporting would allow time for 
hospitals to incorporate the THA/TKA PRO-PM data collection into their 
clinical workflows and is responsive to stakeholder comments as 
summarized in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45411through 
45414). For each voluntary and subsequent mandatory reporting period, 
we would collect data on the THA/TKA PRO-PM 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.
    The first voluntary reporting period proposed for CY 2025 would 
include pre-operative PRO data collection from October 3, 2022 through 
June 30, 2023 (for eligible elective primary THA/TKA procedures 
performed from January 1, 2023 through June 30, 2023) and post-
operative PRO data collection from October 28, 2023 to August 28, 2024. 
Hospitals would submit comm data in 2023 and post-operative data in 
2024, and we intend to provide hospitals with their results in 
confidential feedback reports in 2025. We refer readers to section 
IX.E.10.k., where we propose the form, manner, and timing for PRO-PMs, 
including submission deadlines.
    The second voluntary reporting period proposed for CY 2026 would 
include pre-operative PRO data collection from April 2, 2023 through 
June 30, 2024 (for eligible elective primary THA/TKA procedures 
performed from July 1, 2023 through June 30, 2024) and post-operative 
PRO data collection from April 26, 2024 to August 29, 2025. Hospitals 
would submit pre-operative data in 2024 and post-operative data in 
2025, and we intend to provide hospitals with their results in 
confidential feedback reports in 2026. We refer readers to section 
IX.E.10.k., where we propose the form, manner, and timing for PRO-PMs, 
including submission deadlines.
    Hospitals that voluntarily submit data for this measure would 
receive confidential feedback reports that detail submission results 
from the reporting period. If feasible, we would calculate and provide 
each participating hospital with their risk-standardized improvement 
rate as part of the confidential feedback reports. This would provide 
each hospital with an indication of their performance relative to the 
other hospitals that participate in the voluntary reporting period. We 
refer readers to Table IX.E-07. for an overview of the pre- and post-
operative performance periods, data collection windows, and data 
submission deadlines during voluntary reporting.
[GRAPHIC] [TIFF OMITTED] TP10MY22.191

(b) Mandatory Reporting
    Following the two voluntary reporting periods, we are proposing 
that mandatory reporting of the THA/TKA PRO-PM would begin with 
eligible elective primary THA/TKA procedures from July 1, 2024, through 
June 30, 2025 with affecting the FY 2028 payment determination. 
Hospitals' data reporting requirements would be based on pre-operative 
PRO data collection from April 2, 2024, through June 30, 2025 (for 
eligible elective THA/TKA procedures from July 1, 2024 through June 30, 
2025) and post-operative PRO data collection from April 27, 2025, to 
August 29, 2026. Pre-operative data submission would occur in 2025 and 
post-data submission in 2026 and we intend to provide hospitals with 
their results in 2027 before publicly reporting results on the Compare 
tool hosted by HHS, currently available at https://www.medicare.gov/care-compare, or its successor website. For this first mandatory 
reporting period, hospitals that fail to timely meet the reporting 
requirements would receive a reduction of their Annual Payment Update 
(APU) in FY 2028. We refer readers to the section IX.E.10.k.,

[[Page 28529]]

where we propose the form, manner, and timing for PRO-PMs, including 
submission deadlines. We refer readers to Table IX.E-08. for an 
overview of the pre- and post-operative performance periods, data 
collection windows, and data submission deadlines during mandatory 
reporting.
[GRAPHIC] [TIFF OMITTED] TP10MY22.192

(10) Public Reporting
(a) Proposed Voluntary Reporting Periods
    We are proposing to provide hospitals with their THA/TKA PRO-PM 
results in confidential feedback reports during the two voluntary 
reporting periods occurring in 2025 and 2026. While we do not propose 
to publicly report voluntary THA/TKA PRO-PM hospital-level risk-
standardized improvement rates (RSIR) during this period, to 
acknowledge the efforts of stakeholders who choose to participate in 
voluntary reporting, and to support their efforts to improve quality in 
this important area, we are proposing to publicly report which 
hospitals choose to participate in voluntary reporting and/or the 
percent of pre-operative data submitted by participating hospitals for 
the first voluntary reporting period, and their percent of pre-
operative and post-operative matched PRO data submitted for subsequent 
voluntary reporting periods. For example, if out of 100 eligible 
procedures a hospital submits 45 pre-operative cases that match to 
post-operative cases, then we would report that hospital submitted 45% 
of matched pre-operative and post-operative PRO surveys during 
voluntary reporting
(b) Mandatory Reporting
    The THA/TKA PRO-PM results and response rates would be publicly 
reported on the Compare tool hosted by HHS, currently available at 
https://www.medicare.gov/care-compare, or its successor website, 
beginning with the first mandatory reporting period for the FY 2028 
payment determination. Reporting would be based on pre-operative PRO 
data April 2, 2024, through June 30, 2025 (for eligible elective THA/
TKA procedures from July 1, 2024, through June 30, 2025) and post-
operative PRO data collection from April 27, 2025, to August 29, 2026. 
Hospitals would receive confidential feedback reports prior to public 
reporting that detail results from the reporting period. If feasible, 
confidential feedback reports would include the risk-standardized 
improvement rate as well as other results that support understanding of 
their performance.
    We invite public comment on this proposal.
h. Proposed Medicare Spending per Beneficiary (MSPB) Hospital Measure 
(NQF #2158) Beginning With the FY 2024 Payment Determination
    For the purpose of continuing to assess hospitals' efficiency and 
resource use and to meet statutory requirements under section 
1886(o)(2)(B)(ii) of the Act, we are proposing the adoption of the re-
evaluated version of the MSPB Hospital measure in the Hospital IQR 
Program. We plan to subsequently propose this for the Hospital VPB 
Program measure set under the Efficiency and Cost Reduction Domain 
sometime in the future.
(1) Background
    In the FY 2012 IPPS/LTCH PPS final rule, we adopted a prior version 
of the MSPB Hospital measure in both the Hospital IQR Program (76 FR 
51618) and the Hospital VPB Program (under the Efficiency and Cost 
Reduction Domain) (76 FR 51654). The original MSPB Hospital measure was 
subsequently removed from the Hospital IQR Program beginning with the 
FY 2020 payment determination, under the proposed removal Factor 8, the 
costs associated with a measure outweigh the benefit of its continued 
use in the program (83 FR 41559). The original version of the MSPB 
Hospital measure that was removed from the Hospital IQR Program was 
identical to the version that was concurrently, and continues to be 
used in the Hospital VBP Program. For more information on the removal 
of the original MSPB Hospital measure from the Hospital IQR Program, 
please see section VIII.A.4.b of the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41540 through 41544). We note that adding the updated MSPB 
Hospital measure with the refinements outlined above to the Hospital 
IQR Program would follow the process associated with adopting new 
measures into the Hospital VBP Program, as specified under section 
1889(o)(2)(C)(i) of the Act, and provide beneficiaries, hospitals, and 
other stakeholders with an opportunity to familiarize themselves with 
this updated version of the measure before we propose to replace the 
original MSPB Hospital measure in the Hospital VBP Program and 
calculate incentive payment adjustments for eligible hospitals. Given 
that the proposed updated MSPB Hospital measure is different from the 
original MSPB Hospital measure currently in use in the Hospital VBP 
Program, we believe that including the updated MSPB Hospital measure in 
the Hospital IQR program will not incur costs that justified the 
removal of the original MSPB Hospital measure from the Hospital IQR 
program in the FY 2019 IPPS/LTCH PPS final rule.
    The original MSPB Hospital measure evaluated hospitals' efficiency 
relative to the efficiency of the national median hospital. 
Specifically, it assessed the cost to Medicare during an episode of 
care, which is composed of the period three days prior to an IPPS 
hospital admission through 30 days after discharge. The measure 
included Medicare Part A and B payments for services provided to a 
Medicare beneficiary during an episode. The costs included in this 
measure were payment standardized to remove sources of variation not 
directly related to hospitals' care decisions, such as geographic 
differences in practice expenses. The measure was risk-adjusted to 
account for factors outside of hospitals' influence. The details of the 
original MSPB Hospital episode construction and measure calculation can 
be found in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51618 through 
51627).

[[Page 28530]]

    As part of our measure maintenance process (as required in section 
8 of the Blueprint for the CMS Measures Management System Version 17.0 
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf), we comprehensively 
re-evaluated the original MSPB Hospital measure in 2020, after it was 
removed from the Hospital IQR Program beginning with the FY 2020 
payment determination period. The re-evaluation was informed by 
feedback received on this measure through prior public comment periods 
\1248\ and the literature. Specifically, regarding the all-cost nature 
of the measure, some stakeholders raised concerns that an all-cost 
approach may result in the measure capturing services that are not 
under the influence of the facilities or practitioners, while others 
noted that there is a need for all-cost/condition measures such as the 
MSPB Hospital measure to promote broad incentives for care 
coordination. Regarding readmissions triggering new episodes, 
commenters noted that potentially high cost services occurring after an 
inpatient readmission are not fully captured under the current 
methodology that does not allow readmissions to initiate new episodes, 
and that the correlation between the MSPB Hospital measure and the 
Hospital Readmission Reduction Program's readmission measures is weak. 
Finally, some commenters suggested potential need for social risk 
factor (SRF) adjustments.\1249\ Relatedly, the literature has 
identified dual enrollment in Medicare and Medicaid as a potentially 
meaningful SRF to adjust for in the VBP programs.\1250\
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    \1248\ We received feedback during the public comment periods of 
the FY 2012 and FY 2013 IPPS/LTCH PPS proposed rules. We refer 
readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51619 through 
51627) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53584 through 
53592) for a summary of the comments received.
    \1249\ FY 2012 IPPS/LTCH PPS final rule (76 FR 51624 through 
51625) and FY 2013 IPPS/LTCH PPS final rule (77 FR 53586 through 
53587).
    \1250\ Johnston, K.J., & Maddox, K.E.J. (2019). The Role of 
Social, Cognitive, And Functional Risk Factors In Medicare Spending 
For Dual And Nondual Enrollees.
---------------------------------------------------------------------------

    In the process of evaluating this feedback, the TEP reviewed four 
main topics to explore as potential changes to the specifications, 
including--
     Narrowing the all-cost approach through service inclusion 
and exclusion rules;
     Including SRFs in the measure's risk adjustment model;
     Allowing readmissions to trigger a new episode and include 
an indicator variable in the risk adjustment model for whether there 
was an inpatient stay in the 30 days prior to episode start date; and
     Changing the measure calculation from the sum of observed 
costs divided by the sum of expected costs to the mean of observed 
costs divided by expected costs.
    After reviewing the analyses prepared by the measure development 
contractor and discussed during the February 2020 meeting, the TEP 
members provided feedback on each of the potential refinements during 
the process of re-evaluation. In brief, the TEP believed that the 
current all-cost methodology approach appropriately reflected the broad 
scope of a hospital's responsibility of care, and that this was needed 
to promote broad incentive for care coordination. TEP members 
highlighted the need for further testing around the impact of including 
SRF variables in the risk adjustment model. The TEP supported the 
refinement to allow readmissions to trigger new episodes, as they 
believed it was clinically appropriate to hold the hospital responsible 
for these costs. The members also agreed that the slight change to the 
measure calculation would reduce the impact of outliers on the final 
measure scores. The summary of the TEP's discussions of the MSBP 
Hospital measure is in the February 2020 Physician Cost Measures and 
Patient Relationship Codes TEP Summary Report.\1251\
---------------------------------------------------------------------------

    \1251\ Physician Cost Measures and Patient Relationship Codes 
TEP Summary Report. (2020). Available at: https://www.cms.gov/files/zip/physician-cost-measures-and-patient-relationship-codes-pcmp.zip.
---------------------------------------------------------------------------

    Through the re-evaluation process and the feedback that was 
provided by the TEP, we identified three refinements to the measure 
which would ensure a more comprehensive and consistent reflection of 
hospital performance by capturing more episodes and adjusting the 
measure calculation. First, we refined the measure to include all 
readmissions to trigger new episodes to account for episodes and costs 
that are currently not included in the measure but that could be within 
the hospital's reasonable influence. Second, we added an indicator 
variable in the risk adjustment model for whether there was an 
inpatient stay in the 30 days prior to episode start date. And third, 
we revised the measure to change one step in the measure calculation 
from the sum of observed costs divided by the sum of expected costs 
(ratio of sums) to the mean of observed costs divided by expected costs 
(mean of ratios). Based on our measure development contractor's 
recommendations, informed by the guidance from the TEP and the 
additional testing of the potential refinements suggested by the TEP, 
we believe that these changes would benefit the MSPB Hospital measure's 
relevance and statistical stability as well as ensure a more 
comprehensive and consistent reflection of hospital performance by 
capturing more episodes and adjusting the measure calculation. We 
describe these changes in a summary of the measure re-evaluation on the 
CMS QualityNet website posted in July 2020.\1252\
---------------------------------------------------------------------------

    \1252\ Medicare Spending Per Beneficiary (MSPB) Measure 
Methodology. Available at: https://qualitynet.cms.gov/inpatient/measures/mspb/methodology.
---------------------------------------------------------------------------

    We are proposing the updated MSPB Hospital measure for the Hospital 
IQR Program that incorporates the three changes, which are detailed in 
the subsequent discussion. We note that aside from these three 
described refinements, all other aspects of the updated measure are the 
same as compared to the original measure.
(a) Update To Allow Readmissions To Trigger New Episodes
    First, we refined the measure to allow readmissions to trigger new 
episodes to account for episodes and costs that are currently not 
included in the measure but that could be within the hospital's 
reasonable influence. It is clinically appropriate to hold the hospital 
responsible for the costs that are associated with the readmissions 
(that is, from 3 days prior to the readmission through 30 days post-
discharge) to encourage care transitions and coordination in improving 
patient care and reducing unnecessary readmissions. Under the 
previously adopted measure methodology, the measure only included 
episodes that are triggered by initial hospital admissions, and 
inpatient readmissions occurring in the 30-day post-discharge period of 
an existing episode are excluded from initiating new episodes (76 FR 
51620 through 51624). Allowing readmissions to trigger new episodes 
would increase the number of episodes for which a provider can be 
scored and align the incentives of the measure during readmissions, by 
encouraging hospitals to provide cost efficient care and improve care 
coordination not only during initial hospitalizations, but also during 
readmissions. This refinement would also ensure that the measure 
captures potentially high-cost services that would otherwise be 
excluded.

[[Page 28531]]

    To illustrate this refinement, take for example a beneficiary who 
is admitted to an inpatient hospital for a spinal procedure with major 
complication or comorbidity (MS-DRG 028). This hospital admission 
triggers an episode (Episode 1), where the episode window starts three 
days prior to the admission date and ends 30 days after discharge. 
Episode 1 is attributed to the hospital where the inpatient stay 
occurs. Fifteen days after being discharged from the hospital, the 
beneficiary needs to receive additional inpatient hospital care for 
pneumonia (MS-DRG 194). This readmission occurs within the 30-day post-
discharge period of Episode 1 (that is, the episode triggered by the 
initial hospitalization), and would trigger a new episode (Episode 2). 
Episode 2's window would start three days prior to this readmission and 
end 30 days after discharge. Episode 2 would be attributed to the 
hospital managing this readmission. Under the previous methodology, the 
readmission would not be calculated under the measure as a new episode 
because it occurred during the 30-day post-discharge period of Episode 
1. However, under the proposed new methodology, the readmission would 
trigger a new episode (Episode 2), and the episode would be included in 
the MSPB rate for the hospital managing the readmission. Episode 2 
would include the costs in the post-discharge period of the readmission 
that would not be previously captured. Additionally, the costs where 
Episode 1 and Episode 2 overlap would be counted towards each episode. 
We note that the services being assigned to these episodes would only 
be counted once per episode. In other words, costs would not be double-
counted. The revised measure calculation compares each hospital's 
observed episode costs to predicted episode costs among their peers for 
patients with the same observable characteristics, rather than to a 
pre-defined standard. By comparing hospitals to other hospitals that 
are all attributed in the same way, we expect this comparison to be 
fair. This also helps to maintain care coordination incentives of the 
MSPB Hospital measure.
(b) New Indicator Variable in the Risk Adjustment Model
    Additionally, to account for the differences in expected costs for 
episodes that are triggered by readmissions, the updated methodology 
includes an indicator variable in the risk adjustment model showing 
whether there was an inpatient stay in the 30 days prior to episode 
start date. The previous methodology does not include this indicator 
variable, given that all episodes with an inpatient stay in the 30 days 
prior to the episode start date (that is, episodes that are based on a 
hospital readmission) are excluded from the measure calculation (76 FR 
51620 through 51624). Continuing with the example used earlier, given 
that Episode 2 is based on a hospital readmission and there was an 
inpatient stay within 30 days prior to its episode start date, the risk 
adjustor indicator would be turned on for Episode 2. This means that 
when we calculate predicted spending for Episode 2, the risk adjustment 
model would take into account the fact that this episode was triggered 
by a readmission, and not an initial admission. This would ensure that 
the hospital is not unfairly penalized for providing care to the 
patient during the episode that could be more high cost due to its 
readmission status.
    An illustration of this refinement that compares the previously 
adopted methodology where a readmission does not trigger a new episode 
and the proposed new methodology where a readmission does trigger a new 
episode, is available in Appendix B of the Measure Information Form 
(MIF) document available at https://qualitynet.cms.gov/files/5f1b3bd12bd4670021abc1b4?filename=MSPB_Hospital_MIF_2020.pdf.
(c) Updated MSPB Amount Calculation Methodology
    The third refinement changes one step in the measure calculation 
from the sum of observed costs divided by the sum of expected costs 
(ratio of sums) to the mean of observed costs divided by expected costs 
(mean of ratios). Under the previously adopted methodology, we 
calculated the MSPB Amount as follows: ((Sum of Observed Costs//# of 
Attributed Episodes)/(Sum of Expected Costs/# of Attributed Episodes)) 
* Average Observed Cost Nationally (76 FR 51626). The revised 
methodology calculates the MSPB Amount instead as follows: (Sum 
(Observed Costs/Expected Costs)/# of Attributed Episodes) * Average 
Observed Cost Nationally. Under this refinement, changing the measure 
calculation would: (a) Slightly increase measure reliability with 
minimal score changes; and (b) evenly weight attributed episodes in the 
final performance score, where previously good or poor performance on 
more expensive episodes would have more weight in the provider's final 
score. Specifically, by changing the measure calculation, the impact of 
outlier episodes on a measure score would be reduced (under the 
previously adopted calculation methodology, most costly episodes are 
weighted proportionately, which would make the measure slightly more 
sensitive to outlier episodes).
    Additionally, the updated MSPB Hospital measure would further align 
with MSPB cost measures in other settings, including the MSPB Clinician 
measure in MIPS (84 FR 62974 through 62977), and the MSPB-Post Acute 
Care (PAC) measures, including MSPB-PAC for Inpatient Rehabilitation 
Facilities (81 FR 52087 through 52095), Long-Term Care Hospitals (81 FR 
57199 through 57207), Skilled Nursing Facilities (81 FR 52014 through 
52021), and Home Health Agencies (81 FR 76757 through 76765). The 
updated MSPB Hospital measure would also align with the acute inpatient 
medical condition episode-based cost measures in MIPS (83 FR 59767 
through 59773, 84 FR 62962 through 62968. and 86 FR 65446 through 
65453). We note that while the scope of care is different for 
clinician, hospital, and post-acute care level measures, we believe 
aligning these measures would help to ensure consistent care 
coordination incentives between the hospital, post-acute care facility, 
and the clinician(s) providing care in those settings.
(2) NQF Re-Endorsement
    This original MSPB Hospital measure was first endorsed by the NQF 
in 2013 \1253\ and then again in 2017.\1254\ We presented the updated 
MSPB Hospital measure (NQF ID #2158) with these three refinements to 
NQF in the Fall 2020 cycle for measure re-endorsement. During the Fall 
2020 NQF endorsement cycle, the updated MSPB Hospital measure was 
reviewed by the Scientific Methods Panel (SMP), Cost and Efficiency 
Standing Committee, and Consensus Standards Approval Committee (CSAC) 
during the 11-month endorsement process.\1255\ The updated measure 
passed on the reliability and validity criteria when reviewed by the 
SMP. The Cost and Efficiency Standing Committee reviewed each aspect of 
the updated measure in detail across three meetings. They also closely 
reviewed

[[Page 28532]]

our testing around the impact of social risk factors. Specifically, we 
had tested whether the inclusion of sex, dual eligibility status, race/
ethnicity, the AHRQ SES index, components of the AHRQ SES index, and 
the Area Deprivation Index could meaningfully be incorporated into the 
measure, so as not to penalize the hospital for the patients they 
treat, while also not setting a lower standard of care for hospitals 
with patients that have social risk factors. Results showed that the 
inclusion of these social risk factors had a limited and inconsistent 
effect on measure scores, and some of the variation that was captured 
by tested covariates was attributable to the hospital in which the 
episodes were initiated. Therefore, social risk factors continue to not 
be included in the measure's risk adjustment model. The CSAC approved 
the Standing Committee's endorsement recommendation unanimously, 
meaning that the updated MSPB Hospital measure (NQF #2158) was re-
endorsed in June 2021 with the three refinements we are 
proposing.\1256\
---------------------------------------------------------------------------

    \1253\ The NQF Cost and Resource Use--Phase 3 Final Report is 
available at: https://www.qualityforum.org/Publications/2015/02/Cost_and_Resource_Use_-_Phase_3_Final_Report.aspx, and the 2013 NQF 
measure evaluation form is available at: https://www.qualityforum.org/Projects/c-d/Cost_and_Resource_Project/2158.aspx.
    \1254\ NQF. (2017). Cost and Resource Use 2016-2017 Final 
Technical Report. Available at: https://www.qualityforum.org/Publications/2017/08/Cost_and_Resource_Use_2016-2017_Final_Technical_Report.aspx.
    \1255\ The submission materials, including the testing results, 
are available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020.
    \1256\ NQF. (2020). Cost and Efficiency Final Report--Fall 2020 
Cycle. Available at: https://www.qualityforum.org/Publications/2021/09/Cost_and_Efficiency_Final_Report_-_Fall_2020_Cycle.aspx.
---------------------------------------------------------------------------

(3) Measure Applications Partnership Review
    Following NQF re-endorsement, the updated measure was included in 
CMS's ``List of Measures Under Consideration for December 1, 2021.'' 
\1257\ The updated MSPB Hospital measure (MUC2021-131) underwent MAP 
review during the 2021-2022 cycle. On December 15, 2021, the MAP 
Hospital Workgroup supported the updated measure for rulemaking. On 
January 19, 2022, the MAP Coordinating Committee upheld the MAP 
Hospital Workgroup's preliminary recommendation to support the updated 
measure for rulemaking. More detail on the discussion is available in 
the MAP's final report.\1258\
---------------------------------------------------------------------------

    \1257\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \1258\ National Quality Forum, (2022) Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care (https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.)
---------------------------------------------------------------------------

    In this proposed rule, we are proposing the updated MSPB Hospital 
measure (NQF #2158) for the Hospital IQR Program beginning with the FY 
2024 payment determination and for subsequent years. This will allow us 
to assess hospitals' efficiency and resource use and meet statutory 
requirements for future adoption in the Hospital VBP Program.\1259\
---------------------------------------------------------------------------

    \1259\ Sections 1886(o)(2)(B)(ii) and 1886(o)(2)(C)(i) of the 
Social Security Act (https://www.ssa.gov/OP_Home/ssact/title18/1886.htm).
---------------------------------------------------------------------------

    We invite public comment on this proposal.
i. Proposed Hospital-Level Risk-Standardized Complication Rate (RSCR) 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) Measure (NQF #1550) Beginning With the FY 2024 
Payment Determination
(1) Background
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53516 through 53521) 
and the FY 2015 IPPS/LTCH PPS final rule (79 FR 50062 through 50063), 
we adopted the Hospital-Level RSCR Following Elective Primary THA/TKA 
(hereinafter referred to as the THA/TKA Complication measure) for use 
in both the Hospital IQR and Hospital VBP Programs, respectively. We 
refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49674) for 
information on the previously adopted measure specifications. Although 
the measure is still included in the Hospital VBP Program and measure 
results are still publicly reported, in the FY 2018 IPPS/LTCH PPS final 
rule (83 FR 41150) we finalized the removal of the measure from the 
Hospital IQR Program as part of agency-wide efforts to reduce provider 
burden since the measure was also being reported under the Hospital VBP 
Program. We, however, believe it is important to assess the quality of 
care provided to Medicare beneficiaries who undergo one or both of 
these procedures. In this proposed rule, we are proposing to adopt the 
re-evaluated form of the THA/TKA Complication measure with an expanded 
measure outcome. Since the measure was removed from the Hospital IQR 
Program, it has been revised to include 26 additional mechanical 
complication ICD-10 codes which were identified during measure 
maintenance. The statutory requirements of the Hospital VBP Program are 
set forth in section 1886(o) of the Act. As noted at 42 CFR 412.164(b) 
measures must be publicly reported for one year prior to the beginning 
of the performance period in the Hospital VBP Program. Therefore, we 
are proposing to adopt this measure into the Hospital IQR Program with 
the intention to eventually propose the updated measure into the 
Hospital VBP Program after the required year of public reporting in 
Hospital IQR Program.
    THA and TKA are commonly performed procedures for the Medicare 
population that improve quality of life. From 2016 to 2019, there were 
1,012,190 THA and TKA procedures performed on Medicare fee-for-service 
(FFS) patients 65 years and older.\1260\ The number of procedures being 
performed has steadily increased over the last decade and is projected 
to reach over four million by 2030.1261 1262 While these 
procedures can dramatically improve a person's quality of life, they 
are costly. Based on projections of the annual demand for THA and TKA 
procedures, researchers estimate that Medicare expenditures on Total 
Joint Arthroplasty (TJA) could climb from $3.95 billion and $7.42 
billion for both primary THA and TKA, respectively, in 2005,\1263\ to 
$50 billion by 2030.\1264\ Complications following elective THA and TKA 
procedures are rare, but the results can be devastating. Evidence shows 
that periprosthetic joint infection rates following THA and TKA range 
from 0.7 percent to 1.6 percent depending upon the 
population.1265 1266 Reported 30- and 90-day death rates 
following THA range from 0.4 percent to 0.7 percent.\1267\ Rates for 
pulmonary embolism following THA range from 0.5 percent to 1.22 
percent\1268\ and range

[[Page 28533]]

from 0.5 percent to 0.9 percent\1269\ following TKA. Rates for wound 
infection in Medicare population-based studies vary between 0.21 
percent and 1.0 percent.\1270\ Rates for sepsis/septicemia range from 
0.09 percent during the index admission to 0.3 percent 90 days 
following discharge for primary TKA. Rates for bleeding and hematoma 
following TKA range from 0.94 percent to 1.7 percent.\1271\
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    \1260\ Triche, E., J.N. Grady, and J.e.a. Debuhr, Procedure 
Specific Complication Measure Updates and Specifications Report: 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) Risk-Standardized Complication Measure (Version 
9.0). 2020.
    \1261\ Kurtz, S., et al., Projections of primary and revision 
hip and knee arthroplasty in the United States from 2005 to 2030. J 
Bone Joint Surg Am, 2007. 89(4): p. 780-5.
    \1262\ Kurtz, S.M., et al., Impact of the economic downturn on 
total joint replacement demand in the United States: updated 
projections to 2021. J Bone Joint Surg Am, 2014. 96(8): p. 624-30.
    \1263\ Kurtz, S.M., et al., Future clinical and economic impact 
of revision total hip and knee arthroplasty. J Bone Joint Surg Am, 
2007. 89 Suppl 3: p. 144-51.
    \1264\ Wilson, N.A., et al., Hip and knee implants: current 
trends and policy considerations. Health Aff (Millwood), 2008. 
27(6): p. 1587-98.
    \1265\ Kurtz S, Ong K, Lau E, Bozic K, Berry D, Parvizi J. 
Prosthetic joint infection risk after TKA in the Medicare 
population. Clin Orthop Relat Res. 2010; 468:5.
    \1266\ Bozic KJ, Grosso LM, Lin Z, et al. Variation in hospital-
level risk-standardized complication rates following elective 
primary total hip and knee arthroplasty. J Bone Joint Surg Am. 
2014;96(8):640-647. doi:10.2106/JBJS.L.01639.
    \1267\ Soohoo NF, Farng E, Lieberman JR, Chambers L, Zingmond 
DS. Factors That Predict Short-term Complication Rates After Total 
Hip Arthroplasty. Clin Orthop Relat Res. Sep 2010;468(9):2363-2371.
    \1268\ Arshi A, Leong NL, Wang C, Buser Z, Wang JC, SooHoo NF. 
Outpatient total hip arthroplasty in the United States: A 
population-based comparative analysis of complication rates. J Am 
Acad Orthop Surg. 2019;27(2):61-7.
    \1269\ Khatod M, Inacio M, Paxton EW, et al. Knee replacement: 
epidemiology, outcomes, and trends in Southern California: 17,080 
replacements from 1995 through 2004. Acta Orthop. Dec 
2008;79(6):812-819.
    \1270\ Browne J, Cook C, Hofmann A, Bolognesi M. Postoperative 
morbidity and mortality following total knee arthroplasty with 
computer navigation. Knee. Mar 2010;17(2):152-156.
    \1271\ Huddleston JI, Maloney WJ, Wang Y, Verzier N, Hunt DR, 
Herndon JH. Adverse Events After Total Knee Arthroplasty: A National 
Medicare Study. The Journal of Arthroplasty. 2009;24(6, Supplement 
1):95-100.
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    The updated THA/TKA Complication measure was listed in the publicly 
available document entitled ``List of Measures Under Consideration for 
December 1, 2021'' \1272\ (MUC List) with identification number 
MUC2021-118. The MAP reviewed the updated measure and voted to 
conditionally support the measure for rulemaking for use in the 
Hospital IQR Program pending NQF review and endorsement of the measure 
update. The MAP Rural Health Advisory Group reviewed this updated 
measure on December 8, 2021 and voted to majority support the measure 
given that there would be no undue consequences for rural 
hospitals.\1273\
---------------------------------------------------------------------------

    \1272\ https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \1273\ https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    The NQF re-endorsed the original measure in July of 2021; and we 
intend to submit the updated measure to NQF for endorsement in Fall 
2024.\1274\ We note that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act 
requires that any measure specified by the Secretary must have been 
endorsed by the entity with a contract under section 1890(a) of the Act 
(the NQF is the entity that currently holds this contract). Under 
section 1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 on this topic, and, therefore, we believe the 
exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
---------------------------------------------------------------------------

    \1274\ National Quality Forum. Hospital-level risk-standardized 
complication rate (RSCR) following elective primary total hip 
arthroplasty (THA) and/or total knee arthroplasty (TKA) Measure 
Specifications. 2021. https://www.qualityforum.org/QPS/1550.
---------------------------------------------------------------------------

(2) Overview of Measure
    The original THA/TKA Complication measure (NQF #1550) was 
previously removed from the Hospital IQR Program, but is currently 
implemented in the Hospital VBP Program (79 FR 50062 through 50063). We 
are proposing to adopt the newly refined version of this measure into 
the Hospital IQR Program that would expand the measure outcome to 
include 26 additional mechanical complication ICD-10 codes. We note 
that aside from the additional ICD-10 codes, measure specifications 
would align with the version of the measure currently in use in the 
Hospital VBP Program.
(3) Data Sources
    The proposed updated THA/TKA Complication measure uses index 
admission diagnoses and in-hospital comorbidity data from Medicare Part 
A claims. Additional comorbidities prior to the index admission are 
assessed using Part A inpatient, outpatient, and Part B office visit 
Medicare claims in the 12 months prior to index (initial) admission. 
Enrollment status is obtained from the Medicare Enrollment Database 
which contains beneficiary demographic, benefit/coverage, and vital 
status information. We are proposing to use claims data with admission 
dates beginning from April 1, 2019-March 31, 2022 (excluding data from 
the period covered by the ECE granted by CMS related to the COVID-19 
Public Health Emergency (PHE)) that is associated with the FY 2024 
payment determination. As a claims-based measure, hospitals would not 
be required to submit additional data for calculating the measure.
(4) Outcome
    The outcome for the proposed updated THA/TKA Complication measure 
is any complication occurring during the index admission (not coded as 
present on admission (POA)) to 90 days post-date of the index 
admission. Complications are counted in the measure only if they occur 
during the index hospital admission or during a readmission. The 
complication outcome is a dichotomous (yes/no) outcome. If a patient 
experiences one or more of these complications in the applicable time 
period, the complication outcome for that patient is counted in the 
measure as a ``yes.''
    The proposed updated measure includes the following 26 additional 
clinically vetted mechanical complication ICD-10 codes:
     M96.65 Fracture of pelvis following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
     M96.661 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg.
     M96.662 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg.
     M96.669 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg.
     M96.671 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg.
     M96.672 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg.
     M96.679 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg.
     M97.01XA Periprosthetic fracture around internal 
prosthetic right hip joint, initial encounter.
     M97.01XD Periprosthetic fracture around internal 
prosthetic right hip joint, subsequent encounter.
     M97.01XS Periprosthetic fracture around internal 
prosthetic right hip joint, sequela.
     M97.02XA Periprosthetic fracture around internal 
prosthetic left hip joint, initial encounter.
     M97.02XD Periprosthetic fracture around internal 
prosthetic left hip joint, subsequent encounter.
     M97.02XS Periprosthetic fracture around internal 
prosthetic left hip joint, sequela.
     M97.11XA Periprosthetic fracture around internal 
prosthetic right knee joint, initial encounter.
     M97.11XD Periprosthetic fracture around internal 
prosthetic right knee joint, subsequent encounter.
     M97.11XS Periprosthetic fracture around internal 
prosthetic right knee joint, sequela.
     M97.12XA Periprosthetic fracture around internal 
prosthetic left knee joint, initial encounter.

[[Page 28534]]

     M97.12XD Periprosthetic fracture around internal 
prosthetic left knee joint, subsequent encounter.
     M97.12XS Periprosthetic fracture around internal 
prosthetic left knee joint, sequela.
     M97.8XXA Periprosthetic fracture around other internal 
prosthetic joint, initial encounter.
     M97.8XXD Periprosthetic fracture around other internal 
prosthetic joint, subsequent encounter.
     M97.8XXS Periprosthetic fracture around other internal 
prosthetic joint, sequela.
     M97.9XXA Periprosthetic fracture around unspecified 
internal prosthetic joint, initial encounter.
     M97.9XXD Periprosthetic fracture around unspecified 
internal prosthetic joint, subsequent encounter.
     M97.9XXS Periprosthetic fracture around unspecified 
internal prosthetic joint, sequela.
     M96.69 Fracture of other bone following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
    During routine measure maintenance, our analyses showed the 
addition of these clinically relevant codes contributed to an increase 
in the THA/TKA national observed complication rate. Findings 
demonstrated an increase of approximately 0.5 percent (from 2.42 
percent to 2.93 percent) in the THA/TKA national observed complication 
rate when evaluated for the FY 2021 performance period (April 1, 2016 
through March 30, 2019). These findings suggest that the expanded 
outcome will allow the updated THA/TKA Complication measure to capture 
a more complete outcome.
    The updated THA/TKA Complication measure as with the version of 
measure currently implemented in the Hospital VBP Program (86 FR 45279 
through 45281), excludes admissions with a principal or secondary 
COVID-19 diagnosis, POA, from the measure outcome, as outcomes for 
patients with COVID-19 who are receiving THA/TKA surgery may differ 
from patients without COVID-19. The four medical complication outcomes 
that this applies to are: (1) Acute myocardial infarction (AMI) during 
a subsequent inpatient admission that occurs within 7 days from the 
start of the index admission; (2) pneumonia or other acute respiratory 
complication during a subsequent inpatient admission that occurs within 
7 days from the start of the index admission; (3) sepsis/septicemia/
shock during a subsequent inpatient admission that occurs within 7 days 
from the start of the index admission; and (4) pulmonary embolism 
during the index admission or a subsequent inpatient admission within 
30 days from the start of the index admission. In these cases, 
readmissions with a principal or secondary diagnosis POA of COVID-19 
(U07.1) will be removed from the numerator.
    We refer readers to the Hip and Knee Arthroplasty Complications 
(ZIP) folder on the CMS.gov Measure Methodology website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology for measure 
specification details on this newly restructured measure.
(5) Cohort
    The proposed updated THA/TKA Complication measure continues to 
include Medicare FFS beneficiaries, aged 65 years or older, having a 
qualifying elective primary THA or TKA procedure during the index 
admission. Beneficiaries must be enrolled in Medicare FFS Part A and 
Part B for the 12 months prior to the date of admission and enrolled in 
Part A during the index admission. We also note that the updated THA/
TKA Complication measure excludes admissions with a principal or 
secondary COVID-19 diagnosis, POA, from the measure cohort.
(6) Risk Adjustment
    The proposed updated THA/TKA Complication measure is risk adjusted 
using clinically relevant risk variables identified from inpatient and 
outpatient claims in the 12 months prior to the procedure. We would 
also include a covariate adjustment for patient history of COVID-19 in 
the 12 months prior to the admission.
(7) Measure Calculation
    The updated THA/TKA Complication measure would be calculated using 
a hospital risk-standardized complication rate by producing a ratio of 
the number of ``predicted'' complications (that is, the adjusted number 
of complications at a specific hospital based on its patient 
population) to the number of ``expected'' complications (that is, the 
number of complications if an average quality hospital treated the same 
patients) for each hospital and then multiplying the ratio by the 
national observed complication rate. For each hospital, the numerator 
of the ratio is the number of complications within the specified time 
period (up to 90 days) predicted on the basis of the hospital's 
performance with its observed case mix, and the denominator is the 
number of complications expected based on the nation's performance with 
that hospital's case mix. This approach is analogous to a ratio of 
``observed'' to ``expected'' used in other types of statistical 
analyses. It conceptually allows for a comparison of a particular 
hospital's performance given its case mix to an average hospital's 
performance with the same case mix.
    We are proposing to adopt the newly restructured version of the 
THA/TKA Complication measure beginning with admission dates from April 
1, 2019-March 31, 2022 (excluding data from the period covered by the 
ECE granted by CMS related to the COVID-19 Public Health Emergency 
(PHE)) affecting the FY 2024 payment determination.
(8) Public Reporting
    If finalized as proposed, we would also publicly report the updated 
THA/TKA Complication measure on the Compare tool hosted by HHS, 
currently available at https://www.medicare.gov/care-compare, or its 
successor website, beginning in 2023.
    We invite public comment on this proposal.
6. Proposed Refinements to Current Measures in the Hospital IQR Program 
Measure Set
    In this proposed rule, we are proposing refinements to two measures 
currently in the Hospital IQR Program measure set--
Hospital[hyphen]Level, Risk-Standardized Payment Associated with an 
Episode-of-Care for Primary Elective THA and/or TKA and Excess Days in 
Acute Care (EDAC) After Hospitalization for Acute Myocardial Infarction 
(AMI)--beginning with the FY 2024 payment determination. We provide 
more details on our proposals in the subsequent discussion.
a. Proposed Refinement of the Hospital-Level, Risk-Standardized Payment 
Associated With an Episode of Care for Primary Elective Total Hip 
Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) Measure (NQF 
#3474) Beginning With the FY 2024 Payment Determination and for 
Subsequent Years
(1) Background
    In this proposed rule, we are proposing a refinement to the 
Hospital-Level, Risk-Standardized Payment Associated with an Episode of 
Care for Primary Elective THA and/or TKA Measure (NQF #3474) 
(hereinafter referred to as the THA/TKA Payment measure), which expands 
the measure outcome to include 26 clinically vetted mechanism 
complication ICD-10 codes, for the FY 2024 payment determination and 
subsequent years. For the purposes of describing the refinement of this 
measure, we note that the ``outcome'' is defined as hospital-level, 
risk-

[[Page 28535]]

standardized payment associated with a 90-day episode-of-care for 
primary elective THA and/or TKA.
    The THA/TKA Payment measure was first adopted into the Hospital IQR 
Program in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49680) for the 
FY 2018 payment determination and subsequent years. Prior to adopting 
the measure, the MAP conditionally supported it on December 10, 2014, 
pending a timely review by the NQF Cost and Resource Use Standing 
Committee.\1275\ The MAP recommended harmonizing and determining the 
most parsimonious approach to measure the costs of hip and knee 
replacements to minimize the burden and confusion of competing 
methodologies.\1276\ The original measure was initially NQF endorsed in 
June 2019 and will be submitted for the first re-endorsement in Fall 
2022.\1277\
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    \1275\ https://www.qualityforum.org/Publications/2014/01/MAP_Pre-Rulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Programs.aspx.
    \1276\ https://www.qualityforum.org/Publications/2014/01/MAP_Pre-Rulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Programs.aspx.
    \1277\ https://www.qualityforum.org/QPS/QPSTool.aspx.
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    The proposed refined measure was included on a publicly available 
document entitled ``List of Measures Under Consideration for December 
1, 2021'' \1278\ (MUC List) with identification number MUC2021-120. The 
refined measure was reviewed by the MAP and conditionally supported for 
rulemaking pending NQF review and endorsement of the measure 
update.\1279\
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    \1278\ https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    As noted earlier, we intend to submit the revised measure for the 
first NQF re-endorsement in the Fall of 2022. We note that section 
1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that any measure 
specified by the Secretary must have been endorsed by the entity with a 
contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, 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 on 
this topic, and, therefore, we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
(2) Overview of Measure
    The proposed measure refinement would expand the measure outcome to 
include 26 mechanical complication ICD-10 codes to the outcome. This 
refinement is in alignment with the refinement of the updated THA/TKA 
Complication measure proposed in section IX.E.5.i. of the preamble of 
this proposed rule. The data sources, cohort, inclusion and exclusion 
criteria, and risk adjustment remain substantively unchanged. We are 
proposing this measure refinement for the FY 2024 payment determination 
and subsequent years, reflecting data collected beginning from April 1, 
2019 through March 31, 2022 admissions (excluding data from the period 
covered by the ECE granted by CMS related to the COVID-19 PHE).
(3) Data Sources
    We are not proposing any changes to the data sources for the THA/
TKA Payment measure. The measure uses Part A and Part B Medicare 
administrative claims data that contain payments for Medicare FFS 
beneficiaries who were hospitalized and underwent an elective THA/TKA. 
This measure uses three years of data.
(4) Outcome
    The primary outcome of this measure is the hospital-level risk-
standardized payment for an elective primary THA/TKA episode-of-care. 
This measure captures payments for Medicare FFS patients across 
multiple care settings, services, and supplies (inpatient, outpatient, 
skilled nursing facility, home health, hospice, physician/clinical 
laboratory/ambulance services, and durable medical equipment, 
prosthetics/orthotics, and supplies). This measure includes patient 
copayments as well as payments from coinsurance.
    This measure uses the index admission for an elective primary THA/
TKA to 90 days postadmission. The measurement includes all payments for 
the first 30 days after admission and only certain payments based on a 
pre-defined set of care settings and services for days 31-90. Payments 
in the 31-90-day window include readmissions for complications as 
defined in the THA/TKA Complication measure (Mechanical Complications 
and Periprosthetic Joint Infection/Wound Infection and Other Wound 
Complications) (see section IX.E.5.i. of this proposed rule for 
discussion on this measure), therefore, the expansion of the definition 
of mechanical complications impacts this measure as well.
    As we are proposing no changes besides the addition of the 26 
mechanical complication codes, we refer readers to the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49674) for information on the previously 
adopted measure specifications. We refer readers to Hip and Knee 
Arthroplasty Payment (ZIP) folder on the CMS.gov Methodology website at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology for updated 
specifications on this measure.
    The proposed additional 26 mechanical complication ICD-10 codes are 
the following:
     M96.65 Fracture of pelvis following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
     M96.661 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg.
     M96.662 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg.
     M96.669 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg.
     M96.671 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg.
     M96.672 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg.
     M96.679 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg.
     M97.01XA Periprosthetic fracture around internal 
prosthetic right hip joint, initial encounter.
     M97.01XD Periprosthetic fracture around internal 
prosthetic right hip joint, subsequent encounter.
     M97.01XS Periprosthetic fracture around internal 
prosthetic right hip joint, sequela.
     M97.02XA Periprosthetic fracture around internal 
prosthetic left hip joint, initial encounter.
     M97.02XD Periprosthetic fracture around internal 
prosthetic left hip joint, subsequent encounter.
     M97.02XS Periprosthetic fracture around internal 
prosthetic left hip joint, sequela.

[[Page 28536]]

     M97.11XA Periprosthetic fracture around internal 
prosthetic right knee joint, initial encounter.
     M97.11XD Periprosthetic fracture around internal 
prosthetic right knee joint, subsequent encounter.
     M97.11XS Periprosthetic fracture around internal 
prosthetic right knee joint, sequela.
     M97.12XA Periprosthetic fracture around internal 
prosthetic left knee joint, initial encounter.
     M97.12XD Periprosthetic fracture around internal 
prosthetic left knee joint, subsequent encounter.
     M97.12XS Periprosthetic fracture around internal 
prosthetic left knee joint, sequela.
     M97.8XXA Periprosthetic fracture around other internal 
prosthetic joint, initial encounter.
     M97.8XXD Periprosthetic fracture around other internal 
prosthetic joint, subsequent encounter.
     M97.8XXS Periprosthetic fracture around other internal 
prosthetic joint, sequela.
     M97.9XXA Periprosthetic fracture around unspecified 
internal prosthetic joint, initial encounter.
     M97.9XXD Periprosthetic fracture around unspecified 
internal prosthetic joint, subsequent encounter.
     M97.9XXS Periprosthetic fracture around unspecified 
internal prosthetic joint, sequela.
     M96.69 Fracture of other bone following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
    We are proposing the addition of these codes as proposed 
refinements to the THA/TKA Payment measure in response to recent 
analyses during routine measure maintenance showing that the addition 
of these codes would increase the national observed complication rate 
within the proposed THA/TKA Complication measure (NQF #1550) discussed 
earlier in this proposed rule. This demonstrates that the exclusion of 
these codes could result in missed complications. A number of 
clinicians in the field of orthopedics vetted the proposed addition of 
the new ICD-10 codes to identify the complications of care. As 
described in section IX.E.5.i. of the preamble of this proposed rule, 
we anticipate the inclusion of these additional complication codes 
would increase the national observed complication rate and therefore 
may impact payments. Payments in the 31-90-day window are included 
readmissions for complications as defined in the proposed THA/TKA 
Complication measure (Mechanical Complications and Periprosthetic Joint 
Infection/Wound Infection and Other Wound Complications), therefore, 
the expansion of the definition of mechanical complications impacts the 
THA/TKA Payment measure as well. Since the payment measure uses these 
codes for payment included in the post-30-day window, we would also 
anticipate an increase in total payments.
    If finalized as proposed, these refinements to the measure would be 
effective for admissions from April 1, 2019 through March 31, 2022 
(excluding data from the period covered by the ECE granted by CMS 
related to the COVID-19 PHE) and impacting the FY 2024 payment 
determination and subsequent years.
    We invite public comment on this proposal.
b. Proposed Refinement of the Excess Days in Acute Care (EDAC) After 
Hospitalization for Acute Myocardial Infarction (AMI) Measure (NQF 
#2881) Beginning With the FY 2024 Payment Determination and for 
Subsequent Years
(1) Background
    The EDAC After Hospitalization for AMI (hereinafter referred to as 
AMI EDAC) measure was initially adopted in the Hospital IQR Program in 
the FY 2016 IPPS/LTCH PPS final rule (FR 80 49660 through 49690) 
beginning with the FY 2018 payment determination. The measure is 
intended to capture the quality-of-care transitions provided to 
discharged patients hospitalized with AMI by collectively measuring a 
set of adverse acute care outcomes that can occur post-discharge: (1) 
ED visits, (2) observation stays, and (3) unplanned readmissions at any 
time during the 30 days post-discharge. Safely transitioning patients 
from hospital to home requires a complex series of tasks including 
timely and effective communication between providers, prevention of and 
response to complications, patient education about post-discharge care 
and self-management, timely follow-up, and more. Suboptimal transitions 
contribute to a variety of adverse events post-discharge, including ED 
evaluation, need for observation, and readmission. Within the Hospital 
IQR Program's measure set, the AMI EDAC measure illuminates post-
discharge outcomes that are important to patients, better informs 
consumers about care quality, and incentivizes improvement in 
transitional care.
(2) Overview of Measure
    We are proposing to refine this measure by increasing the minimum 
case count for reporting. The NQF Scientific Methods Panel Committee 
and stakeholder feedback indicated that the measure's reliability was 
not adequate. Therefore, we are proposing to increase the reporting 
threshold to 50 cases in an effort to balance the need to include as 
many hospitals as possible while maintaining acceptable measure 
reliability.\1280\ The remainder of the AMI EDAC measure 
specifications, including the data sources, outcome, cohort, exclusion 
criteria, risk adjustment approach, and measure calculation would 
remain unchanged as compared to what is currently adopted in the 
Hospital IQR Program.
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    \1280\ National Quality Forum. Scientific Methods Panel: Spring 
2021 Measure Evaluation Meeting Transcript. March 30, 2021. https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95191.
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    For more detailed measure specifications, we refer readers to the 
``2017 Condition-Specific Measures Updates and Specifications Report 
Hospital-Level 30-Day Risk-Standardized Excess Days in Acute Care 
Measures: Acute Myocardial Infarction--Version 2.0'' available in the 
AMI, HF Excess Days in Acute Care folder on the CMS.gov Measure 
Methodology website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology and the CMS.gov QualityNet website at https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
(3) Proposed Update to Minimum Case Count
    In this proposed rule, we are proposing a refinement to the 
currently adopted version of the AMI EDAC measure to increase the 
minimum case count of 25 to a minimum case count of 50 during the 
measurement period. The increase to the minimum case count would 
improve the measure's reliability. Based on internal analyses using the 
reporting period July 1, 2016 through June 30, 2019, the split-sample 
intraclass correlation (ICC) with Spearman Brown Adjustment increased 
when we increased the minimum case count from .384 with 25 admissions 
to .402 with 50 admissions. Based on our analysis, the mean performance 
rate for all hospitals was 3.6 excess days per 100 discharges, with a 
standard deviation of 26.3. For hospitals with at least 50 admissions 
in the same performance period, the mean performance rate was 6.9 per 
100 discharges, with a standard deviation of 22. Additionally, 1,805 
hospitals of 4,074 hospitals (or 44.3 percent) meet the minimum case 
count of 50 admissions for the same performance period.

[[Page 28537]]

    Based on this improvement in reliability, we are proposing to 
increase the AMI EDAC measure's minimum case count reporting threshold 
from 25 to 50 beginning with the FY 2024 payment determination using 
the reporting period July 1, 2019 through June 30, 2022 (excluding data 
from the period covered by the ECE granted by CMS related to the COVID-
19 PHE), for which public display of the measure results would occur as 
part of a 2023 Compare website refresh (or as soon as operationally 
feasible thereafter), and for subsequent years. We are proposing that 
hospitals with fewer than 50 cases for the AMI EDAC measure would 
continue to receive confidential feedback reports containing measure 
results to understand their performance. Public reporting of measure 
results on the Compare tool hosted by HHS, currently available at 
https://www.medicare.gov/care-compare, or its successor website, would 
only occur for hospitals meeting the 50 minimum cases required for 
reporting. Hospitals would not need to submit additional data as the 
AMI EDAC measure is calculated using administrative claims submitted to 
CMS for payment purposes.
    We invite public comment on this proposal.
7. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures
a. 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:
BILLING CODE 4120-01-P

[[Page 28538]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.193


[[Page 28539]]


b. 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 28540]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.194


[[Page 28541]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.195

c. 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 28542]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.292


[[Page 28543]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.196

d. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2027 Payment Determination
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2027 payment determination:

[[Page 28544]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.197


[[Page 28545]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.198

e. Summary of Previously Finalized and Proposed Hospital IQR Program 
Measures for the FY 2028 Payment Determination and for Subsequent Years
    This table summarizes the previously finalized and newly proposed 
Hospital IQR Program measure set for the FY 2028 payment determination 
and for subsequent years:

[[Page 28546]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.199


[[Page 28547]]


[GRAPHIC] [TIFF OMITTED] TP10MY22.200

BILLING CODE 4120-01-C
8. Proposed Establishment of a Publicly-Reported Hospital Designation 
To Capture the Quality and Safety of Maternity Care
    In this proposed rule, we are proposing to establish a hospital 
quality designation that we would publicly report on a CMS website 
beginning Fall 2023. This designation would be awarded to hospitals 
based on their attestation of submission of the Maternal Morbidity 
Structural measure, which we believe would reflect their commitment to 
the quality and safety of maternity care they furnish. This would be 
the first-ever hospital quality designation by HHS or CMS that 
specifically focuses on maternal health. We are proposing this policy 
in conjunction with Vice President Harris' ``Maternal Health Day of 
Action'' announcement \1281\ which also signaled CMS' intent to 
establish this proposed ``birthing-friendly'' hospital designation.
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    \1281\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    Additionally, we are requesting feedback on potential additional 
activities that we could undertake to advance maternal health equity.
a. The U.S. Maternal Health Crisis
    Despite the highest rate of spending on maternity care, maternal 
mortality rates in the U.S. are among the highest in the developed 
world. Every year, approximately 700 women die of complications related 
to pregnancy and childbirth, and over 25,000 women experience severe 
complications of pregnancy (severe maternal 
morbidity).1282 1283 Approximately one-third of all 
pregnancy-related deaths occur at the time of delivery and immediately 
postpartum, with nearly 20 percent occurring between one and six days 
postpartum.\1284\ Yet, three out of five pregnancy-related deaths are 
considered preventable.\1285\
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    \1282\ Petersen EE et al. Vital Signs: Pregnancy-Related Deaths, 
United States, 2011-2015, and Strategies for Prevention, 13 States, 
2013-2017. MMWR Morbidity and Mortality Weekly Report 2019;68:423-
29.
    \1283\ Maternal and Child Health Bureau. Federally Available 
Data (FAD) Resource Document. Health Resources and Services 
Administration. Available at: https://mchb.tvisdata.hrsa.gov/Admin/FileUpload/DownloadContent?fileName=FadResourceDocument.pdf&isForDownload=False.

    \1284\ Davis N.L., Smoots A.N., and Goodman D.A. (2019). 
Pregnancy-Related Deaths: Data from 14 U.S. Maternal Mortality 
Review Committees, 2008-2017. Available at: https://www.cdc.gov/reproductivehealth/maternal-mortality/erase-mm/MMR-Data-Brief_2019-h.pdf.
    \1285\ The Centers for Disease Control and Prevention. 
Pregnancy-Related Deaths in the United States. September 2021. 
Available at: https://www.cdc.gov/hearher/pregnancy-related-deaths/index.html.
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    Racial, ethnic, and geographic disparities intensify the U.S. 
maternal health crisis. Adverse maternal health outcomes vary 
considerably by race and ethnicity, and are highest among Black and 
American Indian/Alaskan Native women, regardless of their income or 
education levels.1286 1287 Black and American Indian/Alaskan 
Native women die from pregnancy-related causes at a rate two to three 
times higher \1288\ and experience severe

[[Page 28548]]

maternal morbidity at a rate nearly two times higher than their white, 
Asian Pacific Islander, and Hispanic counterparts.\1289\ The COVID-19 
pandemic in the U.S. has exacerbated such racial and ethnic disparities 
in maternal outcomes, likely associated with Black and Hispanic women 
facing higher rates of economic hardship and reporting higher rates of 
mental health concerns compared to their White 
counterparts.1290 1291 1292 1293 Finally, geographic 
disparities in maternal outcomes also exist. Pregnant women who live in 
rural communities are at higher risk for severe maternal morbidity and 
about 60 percent more likely to die before, during, or after delivery 
than those living in urban settings.\1294\
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    \1286\ Hoyert DL and Mini[ntilde]o AM. Maternal Mortality in the 
United States: Changes in Coding, Publication, and Data Release. 
National Vital Statistics Report. Vol 69, No. 2 (Jan. 2020): 1-18.
    \1287\ Centers for Disease Control and Prevention. Racial/Ethnic 
Disparities in Pregnancy-Related Deaths--United States, 2007-2016. 
September 6, 2019. Vol. 68, No. 35. Available at: https://www.cdc.gov/mmwr/volumes/68/wr/pdfs/mm6835a3-H.pdf.
    \1288\ Centers for Disease Control and Prevention. Pregnancy 
Mortality Surveillance System. Available at: https://www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm. Accessed November 10, 2021.
    \1289\ US Government Accountability Office. MATERNAL MORTALITY 
Trends in Pregnancy-Related Deaths and Federal Efforts to Reduce 
Them. March 2020. Available at: https://www.gao.gov/assets/gao-20-248.pdf.
    \1290\ Raman S. COVID-19 Amplifies Racial Disparities in 
Maternal Health. Roll Call. May 14, 2020. Available at: https://www.rollcall.com/2020/05/14/covid-19-amplifies-racial-disparities-in-maternal-health/.
    \1291\ National Partnership for Women & Families. Black Women's 
Maternal Health: A Multifaceted Approach to Addressing Persistent 
and Dire Health Disparities. April 2018. Available at: https://www.nationalpartnership.org/our-work/health/reports/black-womens-maternal-health.html.
    \1292\ Bion X-S. Efforts to Reduce Black Maternal Mortality 
Complicated by COVID-19. California Health Care Foundation. April 
2020. Available at: https://www.chcf.org/blog/efforts-reduce-black-maternal-mortality-complicated-covid-19/.
    \1293\ Getachew Y et al. Beyond the Case Count: The Wide-Ranging 
Disparities of COVID-19 in the United States The Commonwealth Fund. 
September 2020. Available at: https://www.commonwealthfund.org/publications/2020/sep/beyond-case-count-disparities-covid-19-united-states.
    \1294\ White House Fact Sheet: Vice President Kamala Harris 
Announces Call to Action to Reduce Maternal Mortality and Morbidity. 
https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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b. HHS Focus on Improving Maternal Health in the U.S.
    To build on the previously established HHS Maternal Health Action 
Plan, the Vice President's nationwide call to action to reduce maternal 
morbidity and mortality, and ongoing efforts with HHS and across the 
Federal Government,\1295\ the Administration seeks to use a whole-of-
government approach for improving maternal health and advancing 
maternal health equity that reduces maternal mortality and morbidity, 
reduces persistent disparities, and among other activities, increases 
hospital participation in HHS-sponsored maternal health quality 
improvement initiatives. A critical focus is reducing existing 
disparities in maternal health outcomes across race, ethnicity, and 
geographic area. This targeted strategy is further embodied by other 
efforts spearheaded by the Biden-Harris Administration, including the 
first-ever Presidential Proclamation in recognition of Black Maternal 
Health Week in April 2021, as well as the first-ever Federal ``Maternal 
Health Day of Action'' on December 7, 2021.1296 1297
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    \1295\ HHS Initiative to Improve Maternal Health. https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \1296\ 86 FR 20023, April 16, 2021. A Proclamation on Black 
Maternal Health Week, 2021. Available at: https://www.federalregister.gov/documents/2021/04/16/2021-08008/black-maternal-health-week-2021.
    \1297\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    As part of the ``Day of Action,'' Vice President Harris issued a 
nationwide call to action to reduce maternal mortality and morbidity 
and made several key announcements, including CMS' intention to 
establish the proposed hospital designation.\1298\ Additionally, we 
released a quality, safety, and oversight memorandum (QSO-22-05-
Hospitals) to state survey agencies. In that memorandum, we encourage 
hospitals to consider implementation of evidence-based best practices 
for the management of obstetric emergencies, along with interventions 
to address other key contributors to maternal health disparities, to 
support the delivery of equitable, high-quality care for all pregnant 
and postpartum individuals.\1299\ Such best practices include 
participation in local/regional perinatal quality collaboratives, 
application of early warning sign tools, and the use of patient safety 
``bundles.'' We encourage hospitals to review the guidance and 
resources provided in the memorandum to assess their own capacity to 
provide optimal management of obstetric emergencies and to combat 
maternal health disparities.
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    \1298\ Ibid.
    \1299\ Centers for Medicare & Medicaid Services. Evidence-Based 
Best Practices for Hospitals in Managing Obstetric Emergencies and 
Other Key Contributors to Maternal Health Disparities. Accessed 
December 20, 2021. Available at: https://www.cms.gov/files/document/qso-22-05-hospitals.pdf.
---------------------------------------------------------------------------

    As part of our commitment to reducing high maternal morbidity and 
mortality rates, the Hospital IQR Program adopted the Maternal 
Morbidity Structural measure in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45361 through 45365). This measure is designed to determine 
hospital participation in a state or national Perinatal Quality 
Improvement (QI) Collaborative and implementation of patient safety 
practices or bundles through that QI initiative. As noted in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45361 through 45365), hospital 
participation in QI collaboratives has been shown to be effective in 
improving the infrastructure surrounding management of obstetric 
conditions that may lead to severe maternal morbidity or 
mortality.\1300\ Additionally, hospital implementation of related QI 
efforts has been associated with both enhanced quality and safety of 
maternity care as well as a reduction in the maternal health disparity 
gap.1301 1302 1303 1304
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    \1300\ 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.
    \1301\ Callaghan-Koru JA et al. Implementation of the Safe 
Reduction of Primary Cesarean Births safety bundle during the first 
year of a statewide collaborative in Maryland. Obstet Gynecol 
2019;134:109-19.
    \1302\ Main EK et al. Reduction of severe maternal morbidity 
from hemorrhage using a state perinatal quality collaborative. Am J 
Obstet Gynecol 2017;216(3):298.e1-298.e11.
    \1303\ King PL et al. Reducing time to treatment for severe 
maternal hypertension through statewide quality improvement. Am J 
Obstet Gynecol 2018;218:S4.
    \1304\ Main EK et al. Reduction in racial disparities in severe 
maternal morbidity from hemorrhage in a large-scale quality 
improvement collaborative. Am J Obstet Gynecol 2020;223:123.e1-14.
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    The Maternal Morbidity Structural measure is specified to capture 
whether hospitals are: (1) Currently participating in a structured 
state or national Perinatal QI Collaborative; and (2) implementing 
patient safety practices or bundles as part of these QI initiatives. In 
reporting on this measure, hospitals respond ``Yes,'' ``No,'' or ``N/A 
(our hospital does not provide inpatient labor/delivery care)'' to a 
two-part question assessing these two topic areas.\1305\ Data 
collection began with fourth quarter 2021 data, which hospitals must 
report by May 2022. We

[[Page 28549]]

refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45361 
through 45365) for more details on the measure.
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    \1305\ To report on this measure, hospitals will respond to a 
two-part question: ``Does your hospital or health system participate 
in a Statewide and/or National Perinatal Quality Improvement 
Collaborative Program aimed at improving maternal outcomes during 
inpatient labor, delivery and post-partum care, and has it 
implemented patient safety practices or bundles related to maternal 
morbidity to address complications, including, but not limited to, 
hemorrhage, severe hypertension/preeclampsia or sepsis?.'' Further 
details on this measure can be found in the FY 2022 IPPS/LTCH PPS 
final rule at 86 FR 45361 through 45365.
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c. Proposed Establishment of a Publicly-Reported Hospital Designation 
To Capture the Quality and Safety of Maternity Care
    In alignment with the announcement made during the ``Maternal 
Health Day of Action,'' \1306\ we are proposing to establish a hospital 
designation to be publicly reported on a CMS website beginning in Fall 
2023. Under this proposal, we would give this designation to hospitals 
that report ``Yes'' to both questions in the Maternal Morbidity 
Structural measure. This designation would initially be based only on 
data from hospitals reporting an affirmative attestation to the 
Maternal Morbidity Structural measure. This would allow us to initially 
award the designation based on the data hospitals are currently 
reporting on the Maternal Morbidity Structural measure under the 
Hospital IQR Program. In future notice and comment rulemaking, we 
intend to propose a more robust set of criteria for awarding the 
designation that may include other maternal health-related measures 
that may be finalized for the Hospital IQR Program measure set in the 
future. We note that in this proposed rule, we are proposing to adopt 
two new eCQMs for the Hospital IQR Program--the Cesarean Birth (ePC-02) 
and Severe Obstetric Complications (ePC-07)--in sections IX.E.5.c. and 
IX.E.5.d. of the preamble of this proposed rule, respectively.
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    \1306\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    Section 1886(b)(3)(B)(viii)(VII) of the Act, as amended by section 
3001(a)(2) of the Affordable Care Act, requires that the Secretary 
establish procedures for making information regarding Hospital IQR 
Program measures available to the public (74 FR 43864; 75 FR 50184 
through 50815). We believe adding this designation to a consumer-facing 
CMS website would allow patients and families to choose hospitals that 
have demonstrated a commitment to improving maternal health through 
their participation in related perinatal QI collaboratives and their 
implementation of best practices that support the delivery of high-
quality maternity care.
    We invite public comment on this proposal.
d. Solicitation of Comments on Designation Name and Additional Data 
Sources To Consider for Purposes of Awarding This Publicly-Reported 
Hospital Designation
    While our goal is to designate hospitals with demonstrated 
commitment to the provision of high-quality and safe maternity care, we 
wish to do so in a way that is meaningful and useful to patients and 
their families as well as clinicians and hospitals pursuing high-
quality maternal health care delivery. Therefore, we are soliciting 
comments on a name for this designation for future years.
    In addition as noted previously, we are proposing to designate 
hospital commitment to maternity care quality and safety based 
initially on data collected on the Maternal Morbidity Structural 
measure. Our intent is to expand the criteria we use to award this 
designation so that it more comprehensively captures the quality and 
safety of the maternity care delivered by hospitals. Other future 
sources of data potentially include data collected on the two eCQMs we 
are proposing to add to the Hospital IQR Program measure set, if those 
proposals are finalized, or data on other Hospital IQR Program maternal 
health measures, should such measures be adopted in the future. We are 
also considering the feasibility of including other quality measurement 
data sources. In particular, we welcome comments about patient 
experience measures that could be relevant for this designation, 
including patient experience measures that are currently in use in care 
settings, patient experience measures that have been developed but 
require additional testing in pilot settings, or other measures of 
patient experience that would be appropriate for inclusion in the 
designation.
    We invite public comment on these and other potential quality 
measurement data sources that would be appropriate to include in a 
designation that captures the quality and safety of maternity care 
furnished by hospitals, including quality measures used in other 
quality reporting programs or care delivery settings.
e. Additional Activities To Advance Maternal Health Equity--Request for 
Information
    We are committed to advancing equity for all, including those in 
underserved communities (American Indian or Alaska Native, Asian or 
Pacific Islander, Black, Hispanic, 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 others who have been historically underserved, marginalized, 
and adversely affected by persistent poverty and inequality).
    We specifically seek to explore how we can address the U.S. 
maternal health crisis through policies and programs, including, but 
not limited to, the Conditions of Participation (CoPs) and through 
measures in our quality reporting programs. The CoPs are the health and 
safety standards that Medicare-certified providers and suppliers must 
meet to receive Medicare and Medicaid payment. CMS has broad statutory 
authority to establish health and safety regulations for various 
providers and suppliers; that statutory authority is usually found 
within the statutory definition of each provider and supplier type. In 
the case of hospitals, section 1861(e)(9) of the Act defines 
``hospital'' as in institution that, among other things, ``meets such 
other requirements as the Secretary finds necessary in the interest of 
the health and safety of individuals who are furnished services in the 
institution.''
    We invite public comment on the following:
     CMS outlines best practices in the memorandum to state 
survey agencies entitled ``Evidence-Based Best Practices for Hospitals 
in Managing Obstetric emergencies and Other Key Contributors to 
Maternal Health Disparities.'' \1307\ What other additional effective 
best practices or quality improvement initiatives are currently being 
utilized by hospitals? How else can hospitals improve maternal health 
outcomes, enhance their quality of maternity care, and reduce maternal 
health disparities?
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    \1307\ Evidence-based best practices for hospitals in managing 
obstetric emergencies and other key contributors to maternal health 
disparities. U.S. Department of Health and Human Services. https://www.hhs.gov/guidance/document/evidence-based-best-practices-hospitals-managing-obstetric-emergencies-and-other-key.
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     For hospitals that offer inpatient maternity services, 
including labor and delivery care, how could the CoPs be modified to 
improve maternity care and address disparities in maternal health 
outcomes? How would hospitals focus their governance, provider and 
staff training, and care-delivery activities to effectively demonstrate 
compliance with CoPs related to improving maternal health outcomes? 
What types of measurable activities targeting maternal health outcomes 
might demonstrate a reduction in maternal health care disparities or 
improvement in maternal health care delivery?

[[Page 28550]]

     Are there new requirements that could be established in 
the CoPs that would require hospitals to address and improve the 
quality of postpartum care and support provided to patients? How can 
the CoPs specifically address the need to improve behavioral health 
services and monitoring offered during prenatal and postpartum care?
     Might the potential additional maternal health-focused 
CoPs have unintended consequences on providers with certain 
characteristics (such as being located in a rural area or having low-
volume)? Please provide details on how certain providers might be 
differentially affected by potential maternal health CoPs. Are there 
barriers or facilitators that would influence rural hospital 
achievement of a publicly-reported maternal health designation that may 
not relate directly to the quality of services provided? How might 
maternal health CoPs impact providers considering whether it is 
feasible or viable to offer labor and delivery services in their area?
     What services and staff training should hospitals without 
inpatient maternity services have in place in preparation for patients 
in labor?
     What are the best practices that hospitals are utilizing 
to educate and conduct outreach to patients in underserved communities 
to increase access to timely maternity care?
     What are best practices for hospitals to actively engage 
with patients and their families, community-based organizations, and 
others within their local community to obtain information on ways to 
improve maternity care? Are there barriers to such engagement (if so, 
what are the barriers)?
     Do hospitals provide prevention-related education and 
community outreach on the specific maternal health conditions that have 
the greatest impact on disadvantaged and underserved communities?
     How can hospitals review and monitor aggregate data on the 
maternal health risks of the patient population that they serve? What 
data should hospitals review related to the maternal health risks of 
the patient population they serve? What data sharing best practices are 
required for hospitals to share data with external entities, including 
local and state health departments, community-based organizations, or 
other health care providers? How can hospitals connect data collected 
for mothers and their babies after delivery to support research and 
evaluation of maternal health care after delivery?
     What challenges are there to collecting data on patients 
with specific maternal health risks? Can these data be stratified by 
demographics (for example, race and ethnicity)? In addition, how can 
these data be used in a hospital's quality improvement efforts, and 
specifically, in their quality assurance and performance improvement 
(QAPI) program, to improve maternal health outcomes and advance health 
equity and reduce disparities within their facility? How can maternity 
care can be incorporated into an ongoing QAPI program?
     How do hospitals conduct reviews of maternal deaths that 
have occurred within the facility?
     Are hospitals currently utilizing community health needs 
assessments to determine the specific maternity care needs and social 
determinants of health of the patient population that they serve? For 
those hospitals that are utilizing community health needs assessments, 
are there certain best practices or examples of ways that this 
assessment can be used to reduce disparities in maternal outcomes?
     Do hospitals have reporting relationships or mechanisms 
among primary care physicians, obstetrician-gynecologists, and other 
healthcare providers such as nurses and certified nurse midwives, and 
community-based perinatal workers, such as doulas, for optimal 
coordination of care?
     Do hospitals have readily available referral relationships 
and points of contact with community resources or community-based 
organizations to address additional services that a postpartum patient 
may need upon discharge? This could include the consideration of 
behavioral and mental health services or resources to address health-
related social needs, such as food insecurity, housing instability, and 
transportation challenges. If hospitals do not have readily available 
referral relationships and points of contact within the community, what 
barriers and facilitators impact hospital relationships with community 
resources or community-based organizations?
     How do hospitals evaluate their perinatal customer 
experience? What are best practices that are currently being utilized 
for getting robust input from patients on their perinatal experience?
     What best practices exist for ensuring systemic racism and 
biases, including implicit bias are not perpetuated in maternity care?
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. We have 
identified potential future measures for future development, which we 
believe address areas that are important to stakeholders, but which are 
not currently covered in the Hospital IQR Program. Therefore, we seek 
comment on these potential future considerations, as detailed later in 
the section.
    We also refer readers to the following sections: (1) Section IX.A. 
where we are seeking comments from stakeholders on the health impacts 
due to climate change, especially on underserved populations, and how 
we could potentially support hospitals and health systems to more 
effectively determine and plan for climate impacts, reduce greenhouse 
gas emissions, and track progress; (2) section IX.B. where we are 
seeking input on overarching principles in measuring healthcare quality 
disparities in hospital quality programs and value-based purchasing 
programs; and (3) section IX.C. where we are seeking input on ongoing 
ways we can advance digital quality measurement and use of Fast 
Healthcare Interoperability Resources (FHIR) in quality reporting 
programs.
a. Potential Future Inclusion of Two Digital National Healthcare Safety 
Network (NHSN) Measures
    The Hospital IQR Program previously included NHSN measures that 
were finalized for removal from the measure set in the FY 2019 IPPS/
LTCH PPS final rule (83 FR 4157 through 41553), and retained in the 
Hospital-Acquired Condition (HAC) Reduction Program (83 FR 41474 
through 41477; 83 FR 41449 through 41452) and the Hospital VBP Program 
(83 FR 41449 through 41452). We have recently identified two new 
potential measures that utilize EHR-derived data to help address 
hospital-based adverse events, specifically, hospital-onset infections.
    We discuss these two measures in more detail later in the section 
and seek public comment on the future inclusion of these measures in 
the Hospital IQR Program. We also invite public comment on other 
aspects of these two measures related to future implementation. In 
addition, we seek public comment on the application of one or both of 
these measures in other quality reporting programs, including the HAC 
Reduction Program, the Hospital VBP Program, the PCHQR Program, and the 
LTCH QRP.

[[Page 28551]]

(1) National Healthcare Safety Network (NHSN) Healthcare-Associated 
Clostridioides Difficile Infection Outcome Measure
(a) Background
    Clostridioides difficile \1308\ is a bacterium that causes 
diarrhea, pseudomembranous colitis, and toxic megacolon which can lead 
to sepsis or death.1309 1310 1311 Clostridioides difficile 
infections (CDI) can be reduced in healthcare settings using a multi-
faceted approach, including development of an infrastructure for 
monitoring CDI, implementation of effective antibiotic stewardship to 
reduce the use of unnecessary antibiotics, isolation and contact 
precautions for patients with CDI, performance of environmental 
cleaning with sporicidal agents, and other measures.\1312\ CDI is one 
of the most common healthcare-associated infections (HAIs) in the 
U.S.1313 1314 At any given time, 1 in 31 patients has an HAI 
in the U.S., and over a million cases of HAIs are reported every year, 
making HAIs one of the most common adverse events that occurs in a 
healthcare setting.1315 1316
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    \1308\ The Clostridioides difficile bacterium was previously 
called clostridium difficile. The naming was updated in 2016 due to 
taxonomic updates.
    \1309\ Centers for Disease Control and Prevention (CDC). What is 
C. diff? Available at: https://www.cdc.gov/cdiff/what-is.html.
    \1310\ Centers for Disease Control and Prevention (CDC). 
Clostridioides difficile Infection (CDI) Tracking. Available at: 
https://www.cdc.gov/hai/eip/cdiff-tracking.html.
    \1311\ Centers for Medicare & Medicaid Services National 
Healthcare Safety Network (NHSN) Facility-wide Inpatient Hospital-
onset Clostridium difficile Infection (CDI) Outcome Measure. 
Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=606&sectionNumber=1.
    \1312\ Centers for Disease Control and Prevention (CDC) CDI 
Prevention Strategies. Available at: https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
    \1313\ Kwon, J.H., Olsen, M.A., Dubberke, E.R. (2015). The 
Morbidity, Mortality, and Costs Associated with Clostridium 
difficile Infection. Infect Dis Clin North Am. 29(1):123-34. 
Available at: https://www.sciencedirect.com/science/article/abs/pii/S0891552014000804?via%3Dihub.
    \1314\ Magil, S.S., O'Leary, E., Janelle, S.J., Thompson, D.L., 
Ghinwa, D., Nadle, J., et al. (2018). Changes in Prevalence of 
Health Care-Associated Infections in U.S. Hospitals. N Engl J Med. 
379:1732-1744. DOI: 10.1056/NEJMoa1801550.
    \1315\ Magil, S.S., O'Leary, E., Janelle, S.J., Thompson, D.L., 
Ghinwa, D., Nadle, J., et al. (2018). Changes in Prevalence of 
Health Care-Associated Infections in U.S. Hospitals. N Engl J Med. 
379:1732-1744. DOI: 10.1056/NEJMoa1801550.
    \1316\ Haque M, Sartelli M, McKimm J, Abu Bakar M. (2018). 
Health care-associated infections--an overview. Infect Drug Resist. 
11:2321-2333. doi:10.2147/IDR.S177247.
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    As one of the most common HAIs, CDIs are a significant contributor 
to inpatient morbidity and mortality, particularly among older 
adults.\1317\ Incidence of CDI is higher among White patients, female 
patients, and patients over 65 years of age.\1318\ CDIs result in an 
estimated 500,000 cases annually and between 15,000 and 20,000 
deaths.\1319\ Additionally, costs associated with CDIs average about 
$11,400 per case and can have a significant impact on the U.S. 
healthcare system.\1320\ More broadly, HAIs cost over $9.8 billion 
dollars annually with CDIs contributing to 15.4 percent, or about $1.5 
billion dollars of these total annual costs.\1321\ Therefore, we 
currently require reporting of CDI outcomes, along with other HAIs, in 
value-based purchasing programs like the Hospital VBP Program and HAC 
Reduction Program, in order to connect performance on HAI measures with 
payment adjustments.\1322\
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    \1317\ Centers for Disease Control and Prevention. (2018). 
Analysis and Recommendations on the NHSN Clostridioides difficile 
Outcome. Available at: https://www.cdc.gov/hicpac/pdf/NHSN-C-diff-
H.pdf#:~:text=NHSN%20is%20the%20most%20widely%20used%20secure%2C%20in
ternet-based,decreasing%20in%20contrast%20to%20other%20healthcare-
associated%20infections.%202.
    \1318\ Lessa FC, Mu Y, Bamberg WM, et al. (2015). Burden of 
Clostridium difficile infection in the United States. N Engl J Med. 
372(9):825-34. doi: 10.1056/NEJMoa1408913.
    \1319\ Zaver, H.B., Moktan, V.P, Harper, E.P., et al. (2021). 
Reduction in Health Care Facility--Onset Clostridioides difficile 
Infection: A Quality Improvement Initiative. Mayo Clin Proc Innov 
Qual Outcomes. 5(6):1066-1074. doi: 10.1016/j.mayocpiqo.2021.09.004.
    \1320\ Zimlichman E, Henderson D, Tamir O, et al. (2013). Health 
care-associated infections: A meta-analysis of costs and financial 
impact on the US health care system. JAMA Intern Med. 173(22):2039-
46. doi: 10.1001/jamainternmed.2013.9763.
    \1321\ Zimlichman E, Henderson D, Tamir O, et al. (2013). Health 
care-associated infections: A meta-analysis of costs and financial 
impact on the US health care system. JAMA Intern Med. 173(22):2039-
46. doi: 10.1001/jamainternmed.2013.9763.
    \1322\ Centers for Disease Control and Prevention. (2018). 
Analysis and Recommendations on the NHSN Clostridioides difficile 
Outcome. Available at: https://www.cdc.gov/hicpac/pdf/NHSN-C-diff-
H.pdf#:~:text=NHSN%20is%20the%20most%20widely%20used%20secure%2C%20in
ternet-based,decreasing%20in%20contrast%20to%20other%20healthcare-
associated%20infections.%202.
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    The CDC has developed the National Healthcare Safety Network (NHSN) 
Healthcare-Associated Clostridioides difficile Infection Outcome 
measure that utilizes EHR-derived data. The goal of this measure is to 
drive an increase in prevention practices, which would result in fewer 
CDI cases and reduced morbidity and mortality in patients. We believe 
this would be especially useful given that most cases of CDIs may be 
prevented or stopped from spreading to other patients when inpatient 
facilities utilize infection control steps recommended by the CDC. We 
believe utilizing the CDC's NHSN reporting and submission 
infrastructure will impose less administrative burden related to data 
collection and submission for this measure.
    Previously, the Hospital IQR Program included a CDI measure which 
only required CDI facility-wide Lab-ID event reporting (we refer 
readers to the FY 2012 IPPS/LTCH PPS final rule, 76 FR 51630 through 
51631).\1323\ The newly developed version of the measure would improve 
on the original version of the measure by requiring both microbiologic 
evidence of CDI in stool and evidence of antimicrobial treatment, 
whereas the original measure only required CDI facility-wide Lab-ID 
event reporting. The addition of anti-microbial treatment evidence may 
provide further validity in the reporting of CDIs, as it serves as a 
surrogate for test results that were clinically interpreted as true 
infections.
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    \1323\ In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41547 
through 41553) we removed the NHSN Facility-Wide Inpatient Hospital-
Onset Clostridium difficile Infection (CDI) Outcome measure (NQF 
#1717) from the Hospital IQR Program measure set but retained it in 
the HAC Reduction Program and Hospital VBP Program where it is 
reported via the CDC NHSN portal (83 FR 41474 through 41477; 83 FR 
41449 through 41452). We removed this measure under removal Factor 
8, the costs associated with a measure outweigh the benefit of its 
continued use in the program (83 FR 41547).
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    The NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure addresses the quality priority of ``Make Care Safer by 
Reducing Harm Caused in the Delivery of Care'' through the Meaningful 
Measures Area of ``Healthcare Associated Infections.'' \1324\ 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``Safety'' and ``Wellness and Prevention'' priority areas 
and aligns with our commitment to a patient-centered approach in 
quality measurement to ensure that patients are safe and receive the 
highest quality care.\1325\
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    \1324\ Centers for Medicare & Medicaid Services. (2021). 
Meaningful Measures Hub. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1325\ Centers for Medicare & Medicaid Services. (2021). Quality 
Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf. We note that Meaningful Measures 2.0 is still 
under development.
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    In this proposed rule, we are requesting feedback on the potential 
future inclusion of the NHSN Healthcare-Associated Clostridioides 
difficile Infection Outcome measure into the Hospital IQR Program 
measure set to aid in disease monitoring, provide hospitals and 
patients with more

[[Page 28552]]

information to inform care delivery, and improve patient outcomes.
(b) Overview of Measure
    The NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure would track the development of new CDIs among patients 
already admitted to healthcare facilities, using algorithmic 
determinations from data sources widely available in EHRs. Both the 
original and new measure employ the Standardized Infection Ratio (SIR), 
a statistic used to track HAIs over time. Along with the SIR, this new 
measure would also use the Adjusted Ranking Metric (ARM) of hospital-
onset CDIs among hospitalized patients. The SIR is a primary summary 
statistic used by the NHSN to track HAIs, and ARM is a new statistic 
available for acute care hospitals that accounts for differences in the 
volume of exposure (specifically, denominator) between facilities. ARM 
provides complementary information to the SIR as ARM provides the 
reliability-adjusted number of events and allows for ranking 
facilities.\1326\
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    \1326\ More information on how ARM and SIR compare can be found 
at: https://www.cdc.gov/nhsn/ps-analysis-resources/arm/index.html.
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    The measure was previously endorsed by MAP on June 11, 2019. The 
CDC submitted the measure for re-endorsement and it was included in the 
publicly available ``List of Measures Under Consideration for December 
1, 2021'' (MUC List),\1327\ a list of measures under consideration for 
use in various Medicare programs. The NHSN Healthcare-Associated 
Clostridioides difficile Infection Outcome measure (MUC2021-098) was 
reviewed by the NQF MAP Hospital Workgroup on December 15, 2021, and 
received conditional support pending NQF review and re-endorsement once 
the revised measure is fully tested.\1328\ The MAP Coordinating 
Committee, which provides direction to the MAP workgroups, concurred 
with the recommendations of the MAP Hospital Workgroup.\1329\ We 
understand that the CDC intends to submit the measure in the future for 
NQF review and endorsement.
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    \1327\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \1328\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
    \1329\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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(c) Data Sources
    Hospitals would provide data for this measure from their EHRs. The 
primary sources of data for determining numerator events include 
microbiology data (CDI test), medication administration data (CDI 
antimicrobial treatment), and patient encounter, demographic, and 
location information.
    To facilitate rapid, automated, and secure data exchange, the CDC's 
NHSN is planning to enable and promote reporting of this measure using 
FHIR. However, as FHIR capabilities are evolving and not yet uniform 
across healthcare systems, the CDC is also planning on enabling 
reporting using the existing Health Level 7 (HL7) Clinical Document 
Architecture (CDA), and potentially other formats as well to provide 
all facilities with an option for reporting. We are also working with 
the CDC and ONC to consider how certified health IT can support 
reporting of data for this measure. We invite public comment on 
potential reporting formats for this measure.
(d) Outcome
    The outcome of interest is the number of new CDIs among patients 
already admitted to healthcare facilities.
(e) Cohort
    The measure cohort consists of all patients in the denominator: The 
expected number of hospital-acquired CDIs based on predictive models 
using facility- and patient-care location data as predictors.
(f) Exclusion Criteria
    The measure excludes patients in the denominator who are not 
assigned to an inpatient bed in an applicable location, including 
outpatient clinics and ED visits. Patients <365 days old will also be 
excluded. As an aside, inpatient rehabilitation locations and inpatient 
psychiatric locations that have their own CMS Certification Number 
(CCN) are also excluded from the denominator.
(g) Risk Adjustment
    The risk adjustment was developed with a statistical risk model. 
The SIR is risk-adjusted for each facility, and the ARM adjusts for 
volume of exposure between facilities as well as risk adjustment.
(h) Measure Calculation
    The measure assesses the development of new CDI among patients 
already admitted to healthcare facilities.
(i) Numerator and Denominator
    The measure's denominator consists of the expected number of 
hospital-associated CDIs based on predictive models using facility and 
patient care location data as predictors.
    The numerator consists of the total observed number of observed 
CDIs among all inpatients in the facility based on the combination of 
laboratory test for CDIs plus a therapeutic administered within a 
window period around the specimen date.
(2) National Healthcare Safety Network (NHSN) Hospital-Onset Bacteremia 
& Fungemia Outcome Measure
(a) Background
    HAIs are the most frequent adverse event in the delivery of 
healthcare globally.\1330\ Incidence rates for most types of HAIs had 
been declining for several years in the U.S., but the COVID-19 pandemic 
reversed these trends.\1331\ Central line-associated bloodstream 
infections (CLABSI) declined 31 percent between 2015 and 2019.\1332\ 
Despite this initial trend, the SIR for CLABSI increased in 2020 
compared to 2019 in the later quarters due to the pandemic. The NHSN 
found a 47 percent increase in CLABSI in Quarter 4 of 2020 compared to 
Quarter 4 of 2019. Overall, CLABSI increased by 24 percent from 2019 to 
2020, with the largest increase (50 percent) being found in the ICU. 
Other types of infections also rose during this period, including 
hospital-onset MRSA by 15 percent, and Ventilator-Associated Events 
(VAE) by 35 percent.\1333\
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    \1330\ Hongsuwan M, Srisamang P, Kanoksil M, et al. (2014). 
Increasing incidence of hospital-acquired and healthcare-associated 
bacteremia in northeast Thailand: a multicenter surveillance study. 
PLoS One. 2014;9(10):e109324. doi:10.1371/journal.pone.0109324.
    \1331\ Weiner-Lastinger, L., Pattabiraman, V., Konnor, R., 
Patel, P., Wong, E., Xu, S., Dudeck, M. (2022). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, 43(1), 12-25. doi:10.1017/ice.2021.362.
    \1332\ Centers for Disease Control and Prevention. Central Line-
Associated Bloodstream Infections. Accessed on Available at: https://arpsp.cdc.gov/profile/infections/clabsi?year-select-report=year2019&year-select-hai-state-list=year2019.
    \1333\ Centers for Disease Control and Prevention. 2020 National 
and State Healthcare-Associated Infections Progress Report. 
Available at: https://www.cdc.gov/hai/pdfs/progress-report/2020-Progress-Report-Executive-Summary-H.pdf.
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    One likely reason for this reversal was the staffing and 
institutional challenges

[[Page 28553]]

of caring for COVID-19 patients, which led to a breakdown in previous 
standards of care. In qualitative studies, infection prevention teams 
have reported that the pandemic made it difficult to maintain routine 
CLABSI prevention practices in the ICU.\1334\ Another possible reason 
is that many hospitals underwent large staffing changes, leading to 
more workers who were not accustomed to the hospital's standard HAI 
prevention practices.\1335\
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    \1334\ Fakih, M., Bufalino, A., Sturm, L., Huang, R., 
Ottenbacher, A., Saake, K. Cacchione, J. (2021). Coronavirus disease 
2019 (COVID-19) pandemic, central-line-associated bloodstream 
infection (CLABSI), and catheter-associated urinary tract infection 
(CAUTI): The urgent need to refocus on hardwiring prevention 
efforts. Infection Control & Hospital Epidemiology, 1-6. 
doi:10.1017/ice.2021.70.
    \1335\ Fakih, M., Bufalino, A., Sturm, L., Huang, R., 
Ottenbacher, A., Saake, K. Cacchione, J. (2021). Coronavirus disease 
2019 (COVID-19) pandemic, central-line-associated bloodstream 
infection (CLABSI), and catheter-associated urinary tract infection 
(CAUTI): The urgent need to refocus on hardwiring prevention 
efforts. Infection Control & Hospital Epidemiology, 1-6. 
doi:10.1017/ice.2021.70.
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    The NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure was 
developed to help further our goal of addressing patient safety 
outcomes in the hospital care setting. The frequency of hospital 
fungemia and bacteremia infection rates in the U.S. present unique 
opportunities for large-scale quality measurement and improvement 
activities. Statistics on preventability vary but suggest that a 
considerable proportion of fungemia and bacteremia could be 
prevented.\1336\ The NHSN Hospital-Onset Bacteremia & Fungemia Outcome 
measure is intended to facilitate safer patient care by increasing 
awareness of the dangers of fungemia and bacteremia, promoting 
adherence to recommended clinical guidelines, and encouraging hospitals 
to track and improve their practices of appropriate monitoring and care 
delivery for patients. For these reasons, we are requesting feedback on 
the potential future inclusion of this measure into the Hospital IQR 
Program measure set to aid in disease monitoring, provide hospitals and 
patients with more information to inform care delivery, and improve 
patient outcomes.
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    \1336\ Dantes RB, Rock C, Milstone AM, Jacob JT, Chernetsky-
Tejedor S, Harris AD, Leekha S. (2019). Preventability of hospital 
onset bacteremia and fungemia: A pilot study of a potential 
healthcare-associated infection outcome measure. Infect Control Hosp 
Epidemiol, 40(3):358-361. doi: 10.1017/ice.2018.339.
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    Under CMS' Meaningful Measures Framework, the NHSN Hospital-Onset 
Bacteremia & Fungemia Outcome measure addresses the quality priority of 
``Make Care Safer by Reducing Harm Caused in the Delivery of Care'' 
through the Meaningful Measures Area of ``Healthcare Associated 
Infection.'' \1337\ Additionally, pursuant to Meaningful Measures 2.0, 
this measure addresses the ``Safety'' priority area and aligns with our 
commitment to a patient-centered approach in quality measurement to 
ensure that patients are safe and receive the highest quality 
care.\1338\
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    \1337\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \1338\ Centers for Medicare & Medicaid Services. (2021). CMS 
Quality Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf.
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    While the HAC Reduction Program and Hospital VBP Program use 
several HAI measures, we believe that the NHSN Hospital-Onset 
Bacteremia & Fungemia Outcome measure may be necessary to build upon 
previous efforts to reduce HAIs because it encompasses all types of 
bacteremia and fungemia that occur among already hospitalized patients. 
Meanwhile, the NHSN Central Line-Associated Bloodstream Infection 
(CLABSI) Outcome measure and NHSN Facility-wide Inpatient Hospital-
onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia 
Outcome measure only capture specific types of HAIs.
    We invite public comment on the potential use of this measure in 
the Hospital IQR Program. We are also considering its use in the PCHQR 
Program and the possibility of replacing the current CLABSI and MRSA 
measures in the HAC Reduction Program and Hospital VBP Program with the 
NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure.
(b) Overview of Measure
    This measure captures the development of new bacteremia and 
fungemia among patients already admitted to acute care hospitals, using 
algorithmic determinations from data sources widely available in EHRs.
    The NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure was 
previously endorsed by MAP on June 11, 2019. The CDC submitted the 
measure for re-endorsement and it was included in the publicly 
available ``List of Measures Under Consideration for July 15, 2021'' 
(MUC List),\1339\ a list of measures under consideration for use in 
various Medicare programs. The NHSN Hospital-Onset Bacteremia & 
Fungemia Outcome measure (MUC2021-100) was reviewed by the NQF MAP 
Hospital Workgroup on December 15, 2021 and received conditional 
support pending NQF review and re-endorsement once the revised measure 
is fully tested.\1340\ The MAP Coordinating Committee, which provides 
direction to the MAP workgroups, concurred with the recommendations of 
the MAP Hospital Workgroup. We understand that the CDC intends to 
submit the measure in the future for NQF review and endorsement.
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    \1339\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \1340\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
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(c) Data Sources
    The data submission and reporting standard procedures for the NHSN 
Hospital-Onset Bacteremia & Fungemia Outcome measure have been set 
forth by the CDC for NHSN participation in general and for submission 
of measure data. Although the NHSN Hospital-Onset Bacteremia & Fungemia 
Outcome measure is not specified as an eCQM, manual data entry is not 
available. The primary sources of data for determining numerator events 
include microbiology data (blood culture) and patient encounter, 
demographic, and location information often located in Admission-
Discharge-Transfer data (Fast Healthcare Interoperability Resources 
(FHIR): Encounter, Patient, Observation, Location).
    To facilitate rapid, automated, and secure data exchange, the CDC's 
NHSN is planning to enable and promote reporting of this measure using 
FHIR. However, as FHIR capabilities are evolving and not uniform across 
healthcare systems, the CDC is also planning on enabling reporting 
using the existing Health Level 7 (HL7) Clinical Document Architecture 
(CDA), and potentially other formats as well to provide all facilities 
with an option for reporting. We are also working with the CDC and ONC 
to consider how certified health IT can support reporting of data for 
this measure. We invite public comment on potential reporting formats 
for this measure.
(d) Outcome
    The measures outcome (numerator) is defined as the observed number 
of HOB events. This is defined as growth of a recognized bacterial or 
fungal pathogen

[[Page 28554]]

from a blood culture specimen collected on the fourth calendar day of 
admission or later (where the date of admission to an inpatient 
location is calendar day 1).
(e) Cohort
    The measures outcome (numerator) is defined as the observed number 
of hospital-onset bacteremia and fungemia (HOB) events based on 
predictive models using facility-level factors (community-onset 
incidence of bacteremia and fungemia, blood culture utilization rates), 
patient care location, and potentially other data as predictors.
(f) Exclusion Criteria
    The measure has two numerator exclusions for patients with previous 
matching POA bacteremia or fungemia. The first numerator exclusion is 
HOB infections in which the pathogen is the same species or genus level 
as the one identified from a blood specimen by culture that the 
hospital collected in the POA window (defined as hospital calendar day 
three or earlier). Additionally, if multiple pathogens are identified 
from the same blood culture, then a match of any of those pathogens to 
a POA blood pathogen is sufficient to exclude the event from the HOB 
measure. The measure also excludes patients with a previous HOB event 
who experience additional HOB events during the same hospital 
admission. We understand that the CDC may consider additional exclusion 
criteria for patients with significant risk factors for bacteremia or 
fungemia infections that are judged not likely to be preventable in 
rigorous studies.
    The measure has one denominator exclusion for data from patients 
who are not assigned to an inpatient bed in an applicable location. As 
an aside, denominator counts exclude data from inpatient rehabilitation 
units and inpatient psychiatric units with a unique CCN from the acute 
care facility.
(g) Measure Calculation
    The measure is an outcome measure that assesses the observed number 
of HOB events. The measure calculates the ratio of the observed number 
of HOB events out of the expected number of HOB events based on 
predictive models using facility and patient care location data as 
predictors.
10. 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. To successfully participate in the Hospital 
Inpatient Quality Reporting (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 2023 payment determination will begin the ninth year 
that the Hospital IQR Program will reduce the applicable percentage 
increase by one-quarter of such applicable percentage increase.
b. Maintenance of Technical Specifications for Quality Measures
    For each Hospital IQR Program payment determination, we require 
that hospitals submit data on each specified measure in accordance with 
the measure's specifications for a particular period of time. We refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538), in which 
we summarized how the Hospital IQR Program maintains the technical 
measure specifications for quality measures and the subregulatory 
process for incorporation of nonsubstantive updates to the measure 
specifications to ensure that measures remain up-to-date. We 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 https://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 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 2022 reporting period/FY 2024 payment determination, 
hospitals are collecting and will submit eCQM data using the May 2021 
Annual Update and any applicable addenda. 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 
Hospital Quality Reporting (HQR) System (previously referred to as the 
QualityNet Secure Portal) (86 FR 45520). The HQR System 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 IX.C. of the preamble of this 
proposed rule where we are requesting information on potential actions 
that would continue to transform the Hospital IQR Program's quality 
measurement enterprise toward the use of the FHIR standard for data 
submission.
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). The previously finalized 
requirements, including setting up a QualityNet account and the 
associated timelines, are described at 42 CFR 412.140(a)(2) and 
(e)(2)(iii) and in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51639 
through 51640). In the FY 2022 IPPS/LTCH PPS final rule, we finalized 
the following changes to the Hospital IQR Program regulation text: (1) 
Update references to the QualityNet website at 42 CFR 412.140(a)(1) and 
(c)(2)(i); and (2) use the term ``QualityNet security official'' 
instead of ``QualityNet Administrator'' at 42 CFR 412.140(a)(2). We are 
not proposing any changes to these policies in this proposed rule.
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

[[Page 28555]]

IPPS/LTCH PPS final rule (79 FR 50241 through 50253; 50256 through 
50259; and 50273 through 50276), the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49692 through 49698; and 49704 through 49709), the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57150 through 57161; and 57169 through 
57172), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38355 through 
38361; 38386 through 38394; 38474 through 38485; and 38487 through 
38493), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41567 through 
41575; 83 FR 41602 through 41607), the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42501 through 42506), the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58932 through 58940), and the FY 2022 IPPS/LTCH PPS final rule (86 
FR 45417 through 45421).
    In the FY 2018 IPPS/LTCH PPS final rule, 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 (82 FR 38358 through 38361). Those reporting requirements 
were extended to the CY 2019 reporting period/FY 2021 payment 
determination through the CY 2021 reporting period/FY 2023 payment 
determination (83 FR 41603 through 41604; 84 FR 42501 through 42503). 
In the FY 2020 IPPS/LTCH PPS final rule, 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, for a total of four eCQMs (84 FR 42503 through 
42505).
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a progressive 
increase in the number of required reported quarters of eCQM data, from 
one self-selected quarter of data to four quarters of data over a 
three-year period (85 FR 58932 through 58939). Specifically, for the CY 
2021 reporting period/FY 2023 payment determination, hospitals were 
required to report two self-selected calendar quarters of data for each 
of the four self-selected eCQMs (85 FR 58939). For the CY 2022 
reporting period/FY 2024 payment determination, hospitals are required 
to report three self-selected calendar quarters of data for each eCQM: 
(a) Three self-selected eCQMs, and (b) the Safe Use of Opioids--
Concurrent Prescribing eCQM (85 FR 58939). We 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 consecutive or non-
consecutive self-selected quarters of data (85 FR 58939). In the FY 
2022 IPPS/LTCH PPS final rule, we did not propose any changes to these 
policies, and we clarified that the self-selected eCQMs must be the 
same eCQMs across quarters in a given reporting year (86 FR 45418). We 
are not proposing any changes to these policies in this proposed rule. 
The following Table IX.E-14. summarizes our finalized policy:
[GRAPHIC] [TIFF OMITTED] TP10MY22.201

    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 eCQM: (a) Three self-selected eCQMs; and (b) 
the Safe Use of Opioids-Concurrent Prescribing eCQM (85 FR 58939). We 
are not proposing any changes to the eCQM reporting or submission 
requirements for the CY 2023 reporting period/FY 2025 payment 
determination.
    In this proposed rule, we are proposing to modify eCQM reporting 
and submission requirements beginning with the CY 2024 reporting 
period/FY 2026 payment determination and for subsequent years.
(2) Proposed Reporting and Submission Requirements for eCQMs for the CY 
2024 Reporting Period/FY 2026 Payment Determination and for Subsequent 
Years
    In this proposed rule, we are proposing to modify the eCQM 
reporting and submission requirements, such that beginning with the CY 
2024 reporting period/FY 2026 payment determination hospitals would be 
required to report four calendar quarters of data for each required 
eCQM: (1) Three self-selected eCQMs; (2) the Safe Use of Opioids--
Concurrent Prescribing eCQM; (3) the proposed Cesarean Birth eCQM; and 
(4) the proposed Severe Obstetric Complications eCQM; for a total of 
six eCQMs. We refer readers to Table IX.E-15. which represents the 
progressive increase in eCQM reporting requirements, including our 
proposed changes.

[[Page 28556]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.202

    This proposal is made in conjunction with our proposals discussed 
in sections IX.E.5.c. and IX.E.5.d. of the preamble of this proposed 
rule, in which we are proposing to adopt the Cesarean Birth eCQM and 
Severe Obstetric Complications eCQM, respectively. Addressing the 
maternal health crisis, improving maternal health, and closing any gaps 
that exist as a result of health disparities are among our top goals 
for quality improvement. The high maternal mortality and morbidity 
rates in the U.S. necessitate large-scale quality measurement and 
improvement activities. As part of the effort to reduce maternal 
mortality and morbidity, we believe it to be important to receive data 
from all hospitals that provide perinatal care and not to limit data to 
just hospitals that may self-select those eCQMs. Requiring these eCQMs 
would also aid in the surveillance of maternal morbidity, mortality, 
and associated comorbidities and complications as we collect data from 
all of the hospitals participating in the Hospital IQR Program. 
Additionally, no maternal morbidity or obstetric complications outcome-
based measures exist in national reporting programs, and we believe 
these measures have the potential to reduce preventable harm and costs 
associated with adverse events related to perinatal care.
    Accordingly, if our proposals to adopt the Cesarean Birth eCQM and 
the Severe Obstetric Complications eCQM are finalized, all hospitals 
participating in the Hospital IQR Program would also be required to 
report these two eCQMs, increasing the total number of eCQMs reported 
from four to six beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years.
    At the start of required eCQM reporting, we stated that increasing 
the reporting requirements over time is consistent with our goal of 
reporting on all eCQMs in the Hospital IQR Program in a stepwise manner 
while being responsive to hospitals' concerns about timing, readiness, 
and burden associated with the increased number of measures required to 
be reported (81 FR 57151 through 57152). With the addition of new 
measures to the eCQM measure set and increasing the quarters of eCQM 
data to be reported, our approach to eCQM reporting requirements has 
supported the goal to incrementally increase eCQM reporting 
requirements as hospitals continue to gain experience with eCQMs (84 FR 
42502). After several years of a steady eCQM reporting requirement, we 
believe a proposed change to the reporting requirement is timely. We 
believe that allowing hospitals to continue self-selection of three 
eCQMs from the measure set for the CY 2024 reporting period/FY 2026 
payment determination while requiring reporting of three additional 
eCQMs provides sufficient flexibility to report on eCQMs applicable to 
a hospital's quality improvement priorities while also reporting on 
measures that address the opioid and maternal health crises and that 
advance health equity. Additionally, we believe that our proposal for 
hospitals to submit data from three self-selected eCQMs and three 
required eCQMs continues our approach to collect data derived from EHRs 
and make progress toward a transition to fully digital quality 
measurement (86 FR 45345).
    We invite public comment on our proposal to increase the number of 
mandatory measures to be reported from one to three, as described 
previously, and thereby increase the total number of required eCQMs 
from four to six.
    We refer readers to section IX.H.10.b. of the preamble of this 
proposed rule for a discussion of a similar proposal by the Medicare 
Promoting Interoperability Program for Eligible Hospitals and Critical 
Access Hospitals (CAHs).
(3) Continuation of Certification Requirements for eCQM Reporting
(a) Requiring Use of the 2015 Edition and 2015 Edition Cures Update 
Certification Criteria
    In the CY 2021 Physician Fee Schedule (PFS) final rule (85 FR 84825 
through 84828), we expanded 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 for 
Eligible Hospitals and CAHs.

[[Page 28557]]

    In the FY 2022 IPPS/LTCH PPS final rule, beginning with the CY 2023 
reporting period/FY 2025 payment determination and subsequent years, we 
finalized the requirement for hospitals to use only certified 
technology updated consistent with the 2015 Edition Cures Update to 
submit data for the Hospital IQR Program data (86 FR 45418). 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 are not proposing any changes to this policy.
(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. In 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45418), we finalized the 
requirement for hospitals to use the 2015 Edition Cures Update 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination, then all available eCQMs used in the Hospital IQR 
Program for the CY 2023 reporting period/FY 2025 payment determination 
and subsequent years would need to be reported using certified 
technology updated to the 2015 Edition Cures Update. We are not 
proposing any changes to this policy.
(4) 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 to then input these data into Certified EHR 
Technology (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 this policy.
(5) 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 
Program and the Medicare Promoting Interoperability Program for 
Eligible Hospitals and CAHs. 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 for Eligible Hospitals and CAHs--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 will be moved to the next business day if 
it falls on a weekend or Federal holiday. We are not proposing any 
changes to this policy.
f. Data Submission and Reporting Requirements for Hybrid Measures
(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 (Hybrid 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). In the FY 2022 IPPS/LTCH PPS final rule, we also 
finalized the adoption of 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 (86 FR 45365). 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). In this proposed rule, we are proposing changes specific to the 
zero denominator declarations and case threshold exemptions policies 
for hybrid measures, as discussed further in the subsequent section.
(2) Certification and File Format Requirements
    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 the period of 
transition as providers are updating certified technology to be 
consistent with the 2015 Edition Update. This flexibility applies to 
all Hospital IQR Program measures which use EHR data elements to 
calculate measure rates, including eCQMs and hybrid measures.
    In the FY 2022 IPPS/LTCH PPS final rule, to align with the health 
IT certification requirements for eCQM reporting, we finalized to 
require hospitals to use only certified technology that has been 
updated

[[Page 28558]]

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 (86 FR 45421). We are not 
proposing any changes to these policies in this proposed rule.
(3) Additional Submission Requirements
    In the FY 2020 IPPS/LTCH PPS final rule, 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 case threshold exemptions (84 FR 
42507). 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 remove 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 HQR System, to allow additional time for testing and make sure 
all required data files are successfully submitted by the deadline.
(4) Proposed Modification of the Zero Denominator Declarations Policy 
and Case Threshold Exemptions Policy for Hybrid Measures
    As stated in the previous section (section IX.E.10.f.(3).), in the 
FY 2020 IPPS/LTCH PPS final rule, we finalized applying the zero 
denominator declarations policy and case threshold exemptions policy to 
hybrid measure reporting (84 FR 42507 through 42508). Additionally, in 
the FY 2020 IPPS/LTCH PPS final rule, we indicated that zero 
denominator declarations and case threshold exemptions would not be 
necessary during the voluntary reporting periods for hybrid measures 
but would be an option for hospitals to utilize when hybrid measure 
reporting became mandatory (84 FR 42508).
    In this proposed rule, we are proposing to remove zero denominator 
declarations and case threshold exemptions as an option for the 
reporting of hybrid measures beginning with the FY 2026 payment 
determination for reasons discussed in the subsequent section. We note 
that the FY 2026 payment determination is the first year for which 
hybrid measures, finalized as part of the Hospital IQR Program measure 
set, will become mandatory for reporting.
    Zero denominator declarations allow a hospital whose EHR is capable 
of reporting hybrid measure data to submit a zero in the denominator 
for the reporting of a measure if the hospital does not have patients 
that meet the denominator criteria of that hybrid measure (84 FR 
42507). Similarly, the case threshold exemptions policy allows for a 
hospital with five or fewer inpatient discharges per quarter or 20 or 
fewer inpatient discharges per year in a given denominator declaration 
be exempted from reporting on that individual hybrid measure (84 FR 
42507). These policies were originally developed for eCQMs and were 
extended to hybrid measures to ensure hospitals were not penalized for 
the absence of patients that meet the denominator criteria in the 
reporting of those measures.
    Upon further analysis, however, we do not believe that these 
policies are applicable for hybrid measures due to the process of 
reporting the measure data. Hybrid measures do not require that 
hospitals report a traditional denominator as is required for the 
submission of eCQMs. Instead, hybrid measures utilize the Initial 
Patient Population (IPP), as per their measure specifications, that 
identifies the patients for which hospitals need to extract the EHR 
data and annual claims data. Additionally, we calculate hybrid measures 
by merging both the claims and EHR data received. Therefore, since we 
would confirm the measure cohort to determine whether a hospital has 
met the denominator criteria, both the zero denominator declaration and 
the case threshold exemption for hybrid measures would not be 
applicable to hospitals.
    We invite public comment on our proposal.
(5) 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 https://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 using a CMS-approved web-based 
data collection tool available within the HQR System. The data 
submission period for structural measures begins in April and has the 
same submission deadline as the fourth calendar quarter chart-
abstracted measure deadline. For example, for the FY 2025 payment 
determination, hospitals would be required to submit the required 
information between April 1, 2024 and May 15, 2024, with respect to the 
time period of January 1, 2023 through December 31, 2023.
    We note that, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45361), for the Maternal Morbidity Structural Measure and the CY 2021 
reporting period/FY 2023 payment determination only, we finalized a 
shortened reporting period from October 1, 2021, through December 31, 
2021, while retaining the standard data submission period. 
Specifically, for the shortened reporting period hospitals will be 
required to submit the data between April 1, 2022, and May 16, 2022 (we 
note that May 15, 2022, falls on a weekend and therefore the close of 
this data submission period is moved to May 16, 2022). Thereafter,

[[Page 28559]]

we finalized that the reporting period for the Maternal Morbidity 
Structural Measure will run from: January 1 through December 31 on an 
annual basis, and that the data submission period will continue to be 
consistent with our current policy (beginning in April until the same 
submission deadline as for the fourth calendar quarter of the chart-
abstracted measures with respect to the reporting period for the 
previous calendar year) (86 FR 45361).
    We are not proposing any changes to these policies in this proposed 
rule.
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.
    We note that in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
the adoption of the COVID-19 Vaccination Among Health Care Personnel 
measure, beginning in October 2021 for the October 1, 2021 through 
December 31, 2021 reporting period affecting the FY 2023 payment 
determination and continuing for each quarter in subsequent years (86 
FR 45374). Specific details on data submission for this measure can be 
found in the CDC's Overview of the Healthcare Safety Component, 
available at https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. We are not proposing any changes to these policies in 
this proposed rule.
k. Proposed Data Submission and Reporting Requirements for Patient-
Reported Outcome-Based Performance Measures (PRO-PMs)
    In this proposed rule, in section IX.E.5.g., we are proposing the 
adoption of the hospital-level THA/TKA PRO-PM into the Hospital IQR 
Program measure set. In this section of the proposed rule, we are 
proposing the reporting and submission requirements for PRO-PM measures 
as a new type of measure to the Hospital IQR Program.
(1) Submission of PRO-PM Data
(a) Data Submission Generally
    In section IX.E.5.g. of the preamble of this proposed rule, we are 
proposing adoption of the THA/TKA PRO-PM in the Hospital IQR Program. 
We are proposing that hospitals would have the choice of selecting from 
multiple submission approaches.
    First we are proposing that hospitals may choose to: (1) Send their 
data to CMS for measure calculation directly; or (2) utilize an 
external entity, such as through a vendor or registry, to submit their 
data on behalf of the hospital to CMS for measure calculation. This 
data submission approach is consistent with stakeholder input received 
by the measure developer during measure development and comments as 
summarized in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45411 through 
45414) which recommended CMS provide multiple options for data 
submission mechanisms to ensure flexibility.
    Whether a hospital chooses to submit the data itself or via a 
vendor, we are also proposing to allow a range of file formats. We are 
proposing that both hospitals and vendors use the HQR System for data 
submission for the THA/TKA PRO-PM. Use of the HQR System leverages 
existing CMS infrastructure already utilized for other quality measures 
(such as, HCAHPS or the Sepsis measure). The HQR System allows for data 
submission using the following file formats: CSV, XML, and a manual 
data entry option; allowing hospitals and vendors flexibility in data 
submission. We would provide hospitals with additional detailed 
information and instructions for submitting data using the HQR System 
through CMS' existing websites, such as on QualityNet, and through 
listservs or both.
(b) Data Submission Reporting Requirements
(1) Voluntary Reporting Requirements for the Proposed THA/TKA PRO-PM
    As discussed earlier in this proposed rule, we are proposing a 
phased implementation approach for adoption of the THA/TKA PRO-PM, with 
two voluntary reporting periods for the CY 2025 and 2026 reporting 
periods prior to mandatory reporting beginning with the FY 2028 payment 
determination. Voluntary reporting prior to mandatory reporting would 
allow time for hospitals to incorporate the THA/TKA PRO-PM data 
collection into their clinical workflows and is responsive to 
stakeholder comments summarized in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45411 through 45414). For each voluntary and subsequent 
mandatory reporting periods, we would collect data on the THA/TKA PRO-
PM 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 Federal law.
    For hospitals participating in voluntary reporting, we are 
proposing that hospitals submit pre-operative PRO data, as well as 
matching post-operative PRO data for at least 50 percent of their 
eligible elective primary THA/TKA procedures. We are proposing that the 
first voluntary reporting period for CY 2025 would include pre-
operative PRO data collection from October 3, 2022, through June 30, 
2023 (for eligible elective THA/TKA procedures performed from January 
1, 2023, through June 30, 2023) and post-operative PRO data collection 
from October 28, 2023, to August 28, 2024. Hospitals would submit pre-
operative data in 2023 and post-operative data in 2024, and we intend 
to provide hospitals with their results in confidential feedback 
reports in 2025. We are proposing that hospitals submit pre-operative 
data for the first voluntary reporting three months following the end 
of the performance period. For post-operative data, we are proposing 
that hospitals would be required to submit data one month following the 
end of the performance period. If that day falls on a weekend, 
submissions would be due the following Monday. For example, for 
procedures performed between January 1, 2023, and June 30, 2023, pre-
operative data would need to be submitted by October 2, 2023. After the 
initial submission of pre-operative data in the first voluntary period, 
hospitals would submit both pre-operative and post-operative data by 
the same day, but for different time periods. For example, hospitals 
would need to submit: (1) Post-operative data for the first voluntary 
reporting (for procedures performed between January 1, 2023, and June 
30, 2023); and (2) pre-operative data for the second voluntary 
reporting (for procedures performed between July 1, 2023, and June 30, 
2024) of the THA/TKA PRO-PM by September 30, 2024.
    We are proposing that the second voluntary reporting period would 
include pre-operative PRO data collection from April 2, 2023, through 
June 30, 2024 (for eligible elective THA/TKA procedures performed from 
July 1, 2023, through June 30, 2024) and post-operative PRO data 
collection from April 26, 2024, to August 29, 2025. Hospitals would 
submit pre-operative data in 2024 and post-operative data in 2025, and 
we intend to provide hospitals with their results in confidential 
feedback reports in 2026.

[[Page 28560]]

    We refer readers to Table IX.E-16. for an overview of the proposed 
performance period, pre- and post-operative data collection timeframes, 
and data submission deadlines during voluntary reporting.
[GRAPHIC] [TIFF OMITTED] TP10MY22.203

(2) Mandatory Reporting
    Following the two voluntary reporting periods, we are proposing 
that mandatory reporting of the THA/TKA PRO-PM would begin with 
reporting PRO data for eligible elective THA/TKA procedures from July 
1, 2024, through June 30, 2025 (performance period), impacting the FY 
2028 payment determination. This initial mandatory reporting would 
include pre-operative PRO data collection from three months preceding 
the applicable performance period and from 10 to 14 months after the 
performance period. For example, pre-operative data from April 2, 2024, 
through June 30, 2025 (for eligible elective primary THA/TKA procedures 
from July 1, 2024, through June 30, 2025) and post-operative PRO data 
collection from April 27, 2025, to August 29, 2026. Pre-operative data 
submission would occur in 2025 and post-operative data submission in 
2026 and we intend to provide hospitals with their results in 2027 
before publicly reporting results on the Compare tool hosted by HHS, 
currently available at https://www.medicare.gov/care-compare, or its 
successor website. We are proposing that hospitals would be required to 
submit 50 percent of eligible, complete pre-operative data with 
matching eligible, complete post-operative data as a minimum amount of 
data for mandatory reporting in the Hospital IQR Program.
    We refer readers to Table IX.E-17. for an overview of the proposed 
performance period, pre- and post-operative data collection timeframes, 
and data submission deadlines during the mandatory reporting period.
[GRAPHIC] [TIFF OMITTED] TP10MY22.204

    We invite comment on all of these proposals.
11. Validation of Hospital IQR Program Data
    In this proposed rule, we are proposing to update our eCQM 
validation process. Specifically, we are proposing to update our 
validation requirements for eCQMs from our current requirement that 
hospitals submit timely and complete data for 75 percent of requested 
records to submission of timely and complete data for 100 percent of 
requested records beginning with CY 2022 eCQM data affecting the FY 
2025 payment determination and for subsequent years. We note that this 
proposal will not affect finalized policies with respect to validation 
of chart-abstracted measures.
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), the FY 2020 IPPS/LTCH PPS final rule (84 FR 42509), the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58942 through 58953), and the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45423 through 45426) for 
detailed information on and previous changes to chart-abstracted and 
eCQM validation requirements for the Hospital IQR Program.
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized our policy to 
require submission of at least 75 percent of sampled eCQM medical 
records in a timely and complete manner for validation (81 FR 57181). 
To ensure we have adequate data to assess and validate eCQMs, we 
finalized a requirement that hospitals submit at least 75 percent of 
sampled eCQM medical records (81 FR 57173 through 57175). In the FY 
2021 IPPS/LTCH PPS final rule, we combined the validation processes for 
eCQMs and chart-abstracted measures, but did not update the threshold 
submission percent for eCQM medical records (85 FR 58952 through 
58944). In that rule, we adopted a policy to remove the separate 
process for eCQM validation, beginning with the

[[Page 28561]]

validation affecting the FY 2024 payment determination (for validation 
commencing in CY 2022 using data from the CY 2021 reporting period) (85 
FR 58942 through 58953). Beginning with validation affecting the FY 
2024 payment determination and subsequent years, we finalized a policy 
to incorporate eCQMs into the existing validation process for chart-
abstracted measures such that there would be one pool of hospitals 
selected through random selection and one pool of hospitals selected 
using targeting criteria, for both chart-abstracted measures and eCQMs 
(85 FR 58942 through 58953). Under the aligned validation process, a 
single hospital could be selected for validation of both eCQMs and 
chart-abstracted measures and is expected to submit data for both 
chart-abstracted measures and eCQMs (85 FR 58942 through 58953). We 
refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57179 
through 57180) for details on the Hospital IQR Program data submission 
requirements for chart-abstracted measures. We are not proposing any 
changes to finalized policies for validation of chart-abstracted 
measures.
b. Proposed Modifications to the Existing Processes for Validation of 
Hospital IQR Program eCQM Data
    In this proposed rule, we are proposing to update our eCQM 
validation requirement to require that hospitals selected for 
validation submit timely and complete data for 100 percent of requested 
records for eCQM validation beginning with CY 2022 eCQM data, affecting 
the FY 2025 payment determination and for subsequent years. Hospitals 
selected for eCQM validation are required to submit timely and 
sufficient medical records. As finalized in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 5718 through 57179), hospitals must submit timely 
medical records--within 30 days of the records request--to meet eCQM 
validation requirements. To meet the eCQM validation requirement for 
sufficient medical records, we are proposing to increase the submission 
threshold from 75 percent to 100 percent beginning with validation of 
CY 2022 eCQM data affecting the FY 2025 payment determination and for 
subsequent years.
    Ever since validation of eCQMs commenced with CY 2017 data (81 FR 
57173 through 57181), all hospitals selected for eCQM validation have 
successfully submitted at least 75 percent of eCQM medical records 
requested by the Clinical Data Abstraction Center (CDAC). Additionally, 
95 percent of hospitals selected for participation in eCQM validation 
for the FY 2020 and FY 2021 payment determinations, which are the most 
recently available periods, voluntarily and successfully submitted 100 
percent of requested records. We believe that increasing the submission 
threshold from 75 percent to 100 percent of the requested records would 
support our ongoing goal of continuing to assess the accuracy of eCQM 
measure data (81 FR 57155). Also, given the high rate of hospitals 
voluntarily submitting 100 percent of records, we believe updating the 
submission threshold to 100 percent will be feasible for hospitals.
    We note that under our current policy, the accuracy of eCQM data 
(the extent to which data abstracted for validation matches the data 
submitted in the QRDA I file) submitted for validation does not affect 
a hospital's validation score as described in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57180 through 57181) and would not be impacted by 
this proposed update to the submission threshold. We also note that 
hospitals that fail to submit timely and complete medical records would 
not meet the eCQM validation requirement and be subject to payment 
reduction as described in our previously finalized policy (81 FR 
57180). Chart-abstracted data continue to be weighted at 100 percent 
for payment determination as finalized in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58942 through 58953) and would not be impacted by our 
proposed modification to the eCQM validation.
    The previously finalized eCQM validation requirements, including 
data submission requirements, are described at 42 CFR 
412.140(d)(2)(ii). We are also proposing to update the references to 
``at least 75 percent'' in this Hospital IQR Program regulation text. 
Specifically, we propose to remove the phrase ``at least 75 percent'' 
and add in its place the phrase ``100 percent.'' We continue to 
evaluate data submitted for validation for potential future policy 
changes.
    Our previously finalized and newly proposed validation scoring 
changes are summarized in Table IX.E-18.

[[Page 28562]]

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    We invite public comment on our proposals.
12. 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.
13. 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 Compare 
tool hosted by HHS, currently available at https://www.medicare.gov/care-compare, or its successor website, after a 30-day preview period 
(78 FR 50776 through 50778). We refer readers to the FY 2008 IPPS/LTCH 
PPS final rule (72 FR 47364), the FY 2011 IPPS/LTCH PPS final rule (75 
FR 50230), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51650), the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53554), the FY 2014 IPPS/LTCH PPS 
final rule (78 FR 50836), the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50277), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49712 through 
49713), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38403 through 
38409), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538 through 
41539), and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58953) for 
details on public display requirements. The Hospital IQR Program 
quality measures are typically reported on the Compare tool hosted by 
HHS, currently available at https://www.medicare.gov/care-compare.
    In this proposed rule, we are also proposing a publicly-reported 
hospital designation on a public-facing website to capture the quality 
and safety of maternity care. We refer readers to section IX.E.8. of 
the preamble of this proposed rule for more details on our proposal.
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 utilizes 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 (85 FR 86193 through 86236). 
We are not proposing any changes to these policies in this proposed 
rule.
14. 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.
15. 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

[[Page 28563]]

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 https://qualitynet.cms.gov for our current requirements for 
submission of a request for an exception. As finalized in the FY 2017 
IPPS/LTCH PPS final rule, if a hospital is granted an Extraordinary 
Circumstances Exception with respect to eCQM reporting for the 
applicable eCQM reporting period, the hospital would be excluded from 
the eCQM validation sample due to its inability to supply data for 
validation (81 FR 57181). We are not proposing any changes to these 
policies in this proposed rule.

F. 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 1886(d)(1)(B)(v) (referred to as ``PPS-Exempt 
Cancer Hospitals'' or ``PCHs''). For additional background information, 
including previously finalized measures and other policies for the 
PCHQR Program, we refer readers to the following final rules:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53555 through 
53567);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50837 through 
50853);
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50277 through 
50286);
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49713 through 
49723);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57182 through 
57193);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38411 through 
38425);
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41609 through 
41624);
     The CY 2019 OPPS/ASC final rule with comment period (83 FR 
59149 through 59154);
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42509 through 
42524);
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58959 through 
58966); and
     The FY 2022 IPPS/LTCH PPS final rule (86 FR 45426 through 
45437).
    We also refer readers to 42 CFR 412.23(f) and 412.124 for the PCHQR 
Program regulations.
2. Measure Retention and Removal Factors for the PCHQR Program
a. Current Measure Retention and Removal Factors
    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 our measure retention policy in this 
proposed rule. We describe our proposal to update our measure removal 
policy in the following section.
b. Proposal To Adopt a Patient Safety Exception to the Measure Removal 
Policy
    To further align with the measure removal policies adopted in other 
quality programs such as the Hospital IQR Program (74 FR 43864), 
Hospital VBP Program (83 FR 41446), and HAC Reduction Program (84 FR 
42404 to 42406), we are proposing that if we believe continued use of a 
measure in the PCHQR Program raises specific patient safety concerns, 
we may promptly remove the measure from the program without rulemaking 
and notify hospitals and the public of the removal of the measure, 
along with the reasons for its removal through routine communication 
channels to hospitals, vendors, and QIOs, including, but not limited 
to, issuing memos, emails, and notices on the QualityNet website. We 
would then provide notice of the removal in the Federal Register. In 
circumstances where we do not believe that continued use of a measure 
raises specific patient safety concerns, we would use the regular 
rulemaking process to remove a measure. This proposed policy mirrors 
that of the Hospital IQR Program, Hospital VBP Program, and HACRP 
Program, and we continue to believe that a mechanism to immediately 
remove a quality measure that is causing specific and unintended 
patient harm aligns with our patient-centered focus.
    We further propose to add this patient safety exception to our 
regulations by revising 42 CFR 412.24(d)(3) to add a new paragraph 
(d)(3)(iii). We invite public comment on these proposals.
3. Potential Adoption of Two National Healthcare Safety Network (NHSN) 
Measures--Request for Information
    We are seeking comment on a potential future proposal to adopt the 
NHSN Healthcare-associated Clostridioides difficile Infection Outcome 
measure and NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure 
into the PCHQR Program. Details regarding these measures can be found 
in section IX.E.9.a. of the preamble of this proposed rule, where we 
request information on potentially adopting them for the Hospital IQR 
Program, and we note that we are also considering proposing them for 
the HAC Reduction Program. With respect to the PCHQR Program, we are 
considering adopting these measures because cancer patients are often 
immunosuppressed and therefore more vulnerable to healthcare-associated 
infections (HAIs). We believe these measures will drive an increase in 
prevention practices, which may lead to a reduction in the number of 
HAI cases, morbidity, and mortality.
4. Summary of PCHQR Program Measures for the FY 2024 Program Year and 
Subsequent Years
    Table IX.F.-01 summarizes the PCHQR Program measure set for the FY 
2024 program year and subsequent years. We are not proposing any 
changes to the PCHQR Program measure set in this proposed rule.
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5. 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 in this proposed rule.
6. Proposals Regarding Public Display Requirements
a. Background
    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. Such procedures must ensure that a PCH has the 
opportunity to review its data before they are made public. We are 
specifically required to report quality measures of process, structure, 
outcome, patients' perspective on care, efficiency, and costs of care 
that relate to services furnished by PCHs on the CMS website.
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57191 through 
57192), we finalized that although we would continue to use rulemaking 
to establish what year we first publicly report data on each measure, 
we would publish the data as soon as feasible during that year. We also 
stated that our intent is to make the data available on at least a 
yearly basis, and that the time period for PCHs to review their data 
before the data are made public would be approximately 30 days in 
length. We announce the exact data review and public reporting 
timeframes on a CMS website and our applicable Listservs. Currently, 
the PCHQR measures' performance data are made publicly available on the 
Provider Data Catalog available at https://data.cms.gov/provider-data/.
    We recognize the importance of being transparent and keeping the 
public abreast of any changes that arise with the PCHQR Program measure 
set. As such, in this proposed rule, we are making two proposals 
regarding the timetable for the public display of data for specific 
PCHQR Program measures.
b. Proposal To Begin Public Display of the End-of-Life (EOL) Measures 
Beginning With the FY 2024 Program Year Data
    We are proposing to begin public display of the EOL-Chemo, EOL-
Hospice, EOL-ICU, and EOL-3DH measures (collectively, the ``EOL 
measures'') beginning with FY 2024 program year data. We adopted these 
measures for the PCHQR measure set beginning with FY 2020 program year

[[Page 28565]]

data (82 FR 38414 through 38420). In the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42523 through 42524), we finalized that we would 
confidentially report PCH performance on these measures to individual 
PCHs, and we indicated that we would propose to publicly display PCH 
performance on the measures after this initial confidential reporting 
period. We anticipate providing confidential reports on the data 
collected on the measures for the FY 2022 and FY 2023 program years, 
which correspond to data collected from July 1, 2019, to June 30, 2020 
and July 1, 2020, to June 30, 2021, respectively, within calendar year 
2022.Under our current policy, the measures are calculated on a yearly 
basis based on data collected from July 1 of the year 3 years prior to 
the program year to June 30 of the year 2 years prior to the program 
year. Therefore, we are proposing to begin public reporting of these 
measures beginning with the FY 2024 program year data, which 
corresponds to data collected from July 1, 2021, through June 30, 2022. 
We would make these data publicly available following a 30-day period 
in which PCHs would have an opportunity to review the data. Public 
display would occur during the July 2023 refresh cycle or as soon as 
feasible thereafter. We would announce the exact timeframe on a CMS 
website and our applicable listservs.
    We invite public comment on the proposal to begin public display of 
the four EOL measures beginning with the FY 2024 program year data.
c. Proposal To Begin Public Display of the 30-Day Unplanned 
Readmissions for Cancer Patients Measure Beginning With the FY 2024 
Program Year Data
    We are proposing to begin public display of the 30-Day Unplanned 
Readmissions for Cancer Patients measure beginning with FY 2024 program 
year data. We adopted this measure for the PCHQR measure set beginning 
with FY 2021 program year data (83 FR 41613 through 41616). In the FY 
2020 IPPS/LTCH PPS final rule (84 FR 42523 through 42524), we finalized 
that we would confidentially report this measure to individual PCHs, 
and we indicated that we would propose public display after this 
initial confidential reporting period. We provided confidential reports 
on the data collected on this measure for the FY 2022 program year in 
July 2021. In addition, we anticipate confidentially reporting data 
collected on the measures for the FY 2023 program year, which 
corresponds to data collected from October 1, 2020, to September 30, 
2021, this summer.
    Under our current policy, the measure is calculated on a yearly 
basis based on data collected from October 1 of the year 3 years prior 
to the program year to September 30 of the year 2 years prior to the 
program year. We are proposing to begin public reporting of this 
measure beginning with the FY 2024 program year data, which corresponds 
to data collected from October 1, 2021, through September 30, 2022. We 
would make these data publicly available following a 30-day period in 
which PCHs would have an opportunity to review the data. Public display 
would occur during the October 2023 refresh cycle or as soon as 
feasible thereafter. We would announce the exact timeframe on a CMS 
website and our applicable listservs.
    We invite public comment on the proposal to begin public display of 
the 30-Day Unplanned Readmissions for Cancer Patients measure beginning 
with the FY 2024 program year data.
d. Summary of Previously Finalized and Proposed Public Display 
Requirements for the PCHQR Program
    Our previously finalized and proposed public display requirements 
for the PCHQR Program measures are shown in the following Table IX.F.-
02:
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7. Form, Manner, and Timing of Data Submissions
    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. 
We are not proposing any updates to our previously finalized data 
submission requirements and deadlines.
8. 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.

G. 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), the FY 2020 IPPS/LTCH PPS final rule

[[Page 28567]]

(84 FR 42524 through 42591), and the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45438 through 45446). 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 2023 LTCH QRP
    The LTCH QRP currently has 18 measures for the FY 2023 LTCH QRP, 
which are set out in the following Table FF1. For a discussion of the 
factors used to evaluate whether a measure should be removed from the 
LTCH QRP, we refer readers to the 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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[[Page 28568]]

    There are no proposals in this proposed rule for new measures for 
the LTCH QRP.
4. LTCH QRP Quality Measure Concepts Under Consideration for Future 
Years: Request for Information (RFI)
    We are seeking input on the importance, relevance, and 
applicability of the concepts under consideration listed in Table 
IX.G.-02 for future years in the LTCH QRP. More specifically, we are 
seeking input on a cross-setting functional measure that would 
incorporate the domains of self-care and mobility. Our measure 
development contractor for the cross-setting functional outcome measure 
convened a Technical Expert Panel (TEP) on June 15 and June 16, 2021 to 
obtain expert input on the development of a functional outcome measure 
for PAC. During this meeting, the possibility of creating one measure 
to capture both self-care and mobility was discussed. We are also 
seeking input on measures of health equity, such as structural measures 
that assess an organization's leadership in advancing equity goals or 
assess progress towards achieving equity priorities. Finally, we seek 
input on the value of a COVID-19 Vaccination Coverage measure that 
would assess whether LTCH patients were up to date on their COVID-19 
vaccine.
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    While we will not be responding to specific comments submitted in 
response to this RFI in the FY 2023 IPPS/LTCH PPS final rule, we intend 
to use this input to inform our future measure development efforts.
5. Inclusion of the National Healthcare Safety Network (NHSN) 
Healthcare-Associated Clostridioides difficile Infection Outcome 
Measure in the LTCH QRP--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 healthcare quality priorities and gaps, including 
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 healthcare 
environment, initially focusing on measure and burden reduction to 
include the promotion of innovation and modernization of all aspects of 
quality.\1341\ As a result, CMS has identified 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.
---------------------------------------------------------------------------

    \1341\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

b. Potential Future Inclusion of a Digital National Healthcare Safety 
Network (NHSN) Measure
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50865 through 
50868), we finalized the NHSN Facility-Wide Inpatient Hospital-onset 
Clostridium difficile Infection (CDI) Outcome Measure (NQF #1717) for 
inclusion in the LTCH QRP.
    Clostridioides difficile (C. difficile) is responsible for a 
spectrum of CDIs, including uncomplicated diarrhea, pseudomembranous 
colitis, and toxic megacolon, which can, in some instances, lead to 
sepsis and even death. CDIs are one of the most common healthcare-
associated infections (HAIs), as healthcare-associated CDIs affected 
0.54 percent of all hospitalizations in a 2015 survey.\1342\ In 2017, 
the CDC estimated there were 223,900 CDIs requiring hospitalizations in 
the United States with 12,800 resulting in deaths.\1343\ We have 
recently identified the NHSN Healthcare-Associated Clostridioides 
Difficile Infection (HA-CDI) Outcome measure as a potential measure 
which utilizes Electronic Health Record (EHR)-derived data to help 
address hospital-based adverse events, specifically hospital-onset 
infections.
---------------------------------------------------------------------------

    \1342\ Magil SM, O'Leary E, Janelle SJ, et al. Changes in 
Prevalence of Health Care-Associated Infections in U.S. Hospitals. N 
Engl J Med 2018;379:1732-1744. Available at: https://www.nejm.org/doi/full/10.1056/NEJMoa1801550. Accessed February 3, 2022.
    \1343\ U.S. Department of Health and Human Services. Centers for 
Disease Control and Prevention. Antibiotic Resistance Threats in the 
United States, 2019. Available at: https://www.cdc.gov/drugresistance/pdf/threats-report/2019-ar-threats-report-508.pdf. 
Accessed February 3, 2022.
---------------------------------------------------------------------------

    CDIs are currently reported to the CDC's NHSN by various 
mechanisms, one of which is based on laboratory-identified events 
collected in the NHSN. The LTCH QRP measure, the NHSN Facility-Wide 
Inpatient Hospital CDI Outcome Measure, does not utilize EHR-derived 
data. Rather LTCHs collect data and submit them on a monthly basis to 
the CDC's NHSN using the CDC's NHSN Multidrug-Resistant Organism & 
Clostridioides difficile Infection (MDRO/CDI) Module. The CDC has now 
developed the NHSN HA-CDI measure that utilizes EHR-derived data.
    The newly-developed version of the measure, the NHSN HA-CDI, would 
improve on the original version of the measure in two ways. First, the 
new measure would require both microbiologic evidence of C. difficile 
in stool and evidence of antimicrobial treatment, whereas the original 
measure only requires C. difficile facility-wide Laboratory-Identified 
(Lab-ID) event reporting. Second, consistent with the Meaningful 
Measures Framework, we specifically believe it would reduce reporting 
and regulatory burden on providers and accelerate the move to

[[Page 28569]]

fully digital measures.\1344\ We discuss each of these improvements 
below.
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    \1344\ Centers for Medicare & Medicaid Services. (2021) Quality 
Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf.
---------------------------------------------------------------------------

    CDI testing practices have continued to evolve, with recent 
guidelines from the Infectious Disease Society of America recommending 
a multi-step testing algorithm to better distinguish between C. 
difficile colonization and active infection.\1345\ However, the growing 
number of testing algorithms in use, each with different performance 
characteristics, poses a challenge for CDI surveillance. This new CDI 
measure defines CDI using both a positive microbiological test for C. 
difficile and evidence of treatment, increasing the specificity and 
sensitivity of the measure. Adding a requirement of CDI treatment to a 
CDI surveillance measure would increase the clinical validity of the 
measure, since a record of CDI treatment serves as a proxy for C. 
difficile test results that were interpreted as true infections by the 
clinician.
---------------------------------------------------------------------------

    \1345\ Clinical Practice Guidelines for Clostridium difficile 
Infection in Adults and Children: 2017 Update by the Infectious 
Diseases Society of America (IDSA) and Society for Healthcare 
Epidemiology of America (SHEA) (idsociety.org).
---------------------------------------------------------------------------

    We believe there are important reasons for LTCHs to adopt and 
utilize EHRs, although we understand that for LTCHs who do not yet use 
EHRs there will be initial implementation and training costs. EHRs 
facilitate moving to fully digital measures, which we believe reduces 
reporting and regulatory burden on providers. Additionally, both 
surveys 1346 1347 and studies 1348 1349 have 
demonstrated that when healthcare providers have access to complete and 
accurate information, patients receive better medical care. We believe 
the utilization of EHRs can improve the ability to diagnose diseases 
and reduce (even prevent) medical errors, both of which improve patient 
outcomes. Additionally, the use of a fully digital measure using a 
Measure Calculation Tool (MCT) that pulls data directly from the EHR 
via a standardized Fast Healthcare Interoperability Resources (FHIR) 
interface would eliminate multiple steps for the provider, including 
creating or updating monthly reporting plans, and completing the data 
fields required for both numerator and denominator every month, even 
when no events were identified. Finally, the locally installed MCT 
would be responsible for extracting data, calculating the measure, and 
submitting the data and would eliminate the need for the LTCH to 
manually enter the data into the NHSN web-based application or via file 
imports. For example, if each LTCH executed approximately 6 C. 
difficile events per month (72 events per LTCH annually), then using 
2020 Bureau of Labor Statistics (BLS) data,\1350\ we estimate a 
potential time savings of approximately 2.5 hours per LTCH per month 
and a total cost savings of $1,598.25 per LTCH per year if a digital 
version of the measure replaced the NHSN-based measure.\1351\
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    \1346\ King J, Patel V, Jamoom E, Furukawa M. Clinical Benefits 
of Electronic Health Record Use: National Findings. Health Serv Res. 
2014 Feb; 49(1 pt 2):392-404. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925409/.
    \1347\ Hoover R. Benefits of using an electronic health record. 
Nurs Crit Care. 2017;12(1):9-10. Available at: https://journals.lww.com/nursingcriticalcare/fulltext/2017/01000/benefits_of_using_an_electronic_health_record.3.aspx.
    \1348\ Escobar G, Turk B, Ragins A, Ha J, et al. Piloting 
electronic medical record-based early detection of inpatient 
deterioration in community hospitals. J Hosp Med. 2016 Nov;11(Suppl 
1):S18-S24. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5510649/.
    \1349\ Uslu A, Stausberg J. Value of the Electronic Medical 
Record for Hospital Care: Update from the literature. J Med internet 
Res. 2021;23(12):e26323. Available at: https://www.jmir.org/2021/12/e26323.
    \1350\ U.S. Bureau of Labor Statistics. Occupational Employment 
and Wage Statistics. May 2020 National Occupational Employment and 
Wage Estimates. United States. Available at: https://www.bls.gov/oes/current/oes_nat.htm#43-0000. Accessed February 3, 2022.
    \1351\ Estimated using 10 minutes of clinical nursing time 
(Occupation Code 29-1141) and 15 minutes of clerical time 
(Occupation Code 43-6013) necessary to enter the data into the NHSN.
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c. Overview of the NHSN Healthcare-Associated Clostridioides difficile 
Infection Outcome Measure
    The EHR-driven digital version of the NHSN HA-CDI measure would 
track the development of new CDI among patients already admitted to 
LTCHs, using algorithmic determinations from data sources widely 
available in EHRs.
    The numerator would include those patient records with a qualifying 
C. difficile-positive assay on an inpatient encounter on day 4 or later 
of an LTCH admission and with no previously positive event in <=14 days 
before the LTCH encounter, and new qualifying antimicrobial therapy for 
C. difficile started within the appropriate window period of stool 
specimen collection. The denominator would be the number of patients 
admitted to LTCHs.
    The NHSN HA-CDI measure would use the Standardized Infection Ratio 
(SIR) of hospital-onset CDIs among patients to compare within facility 
types. SIR is a primary summary statistic used by the NHSN to track 
HAIs. The Adjusted Ranking Metric (ARM) is a new statistic currently 
available for acute-care hospitals that accounts for differences in the 
volume of exposure (specifically, in the denominator) between 
facilities. ARM provides complementary information to SIR and was 
developed for use in acute-care hospitals, but is also intended for use 
in post-acute care facilities.\1352\
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    \1352\ More information on how ARM and SIR compare can be found 
at: https://www.cdc.gov/nhsn/ps-analysis-resources/arm/index.html.
---------------------------------------------------------------------------

d. Measure Application Partnership (MAP) Review
    The NHSN HA-CDI measure (MUC2021-098) was included in the publicly 
available ``List of Measures Under Consideration for December 1, 2021'' 
(MUC List),\1353\ a list of measures under consideration for use in 
various Medicare programs, including the LTCH QRP. This allows multi-
stakeholder groups to provide recommendations to the Secretary on the 
measures included on the list.
---------------------------------------------------------------------------

    \1353\ Centers for Medicare & Medicaid Services. List of 
Measures Under Consideration for December 1, 2021. Available at 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf. Accessed February 7, 2022.
---------------------------------------------------------------------------

    The NHSN HA-CDI measure (MUC2021-098) was included under the LTCH 
QRP Program on the MUC List. The National Quality Forum (NQF)-convened 
MAP Post-Acute Care--Long-Term Care (PAC-LTC) Workgroup met on January 
19, 2022 and provided input on the proposed measure. The MAP offered 
conditional support of the NHSN HA-CDI measure for rulemaking 
contingent upon NQF endorsement, noting that the measure has the 
potential to mitigate unintended consequences from the current 
measure's design, which counts a case based on a positive test only, 
which may have led to a historical under-counting of observed HA-CDIs. 
The MAP recognized that the measure is consistent with the program's 
priority to measure HAIs and the Patient Safety Meaningful Measures 2.0 
area.\1354\ The final MAP report is available at https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    \1354\ 2021-2022 MAP Final Recommendations. Available at https://www.qualityforum.org/map/. Accessed February 3, 2021.
---------------------------------------------------------------------------

e. Data Sources
    The data source for the NHSN HA-CDI would be the LTCHs' EHRs. The 
primary sources of data for determining numerator events would include 
microbiology data (C. difficile infection test), medication 
administration data (C. difficile infection antimicrobial

[[Page 28570]]

treatment), and patient encounter, demographic, and location 
information.
    To facilitate rapid, automated, and secure data exchange, the CDC's 
NHSN is planning to enable and promote reporting of this measure using 
Health Level 7 (HL7) FHIR. However, as HL7 FHIR capabilities are 
evolving and not uniform across healthcare systems, CDC is also 
planning to enable reporting using the existing HL7 Clinical Document 
Architecture (CDA), and potentially other formats as well in order to 
provide all facilities with an option for reporting. Furthermore, this 
measure would not immediately replace the current NHSN CDI measure. 
NHSN would continue to host and support the current CDI measure until 
sufficient experience is achieved with the new measure to phase out the 
current CDI measure in each applicable setting.
f. Solicitation of Public Comment
    In this proposed rule, we are requesting stakeholder input on the 
potential electronic submission of quality data from LTCHs via their 
EHRs under the LTCH QRP. We specifically seek public comment on the 
future inclusion of the NHSN Healthcare-Associated Clostridioides 
difficile Infection Outcome measure (HA-CDI) (MUC2021-098) as a digital 
quality measure in the LTCH QRP.
    Specifically, we seek public comment on the following:
     Would you support utilizing LTCH EHRs as the mechanism of 
data collection and submission for LTCH QRP measures?
     Would your EHR support exposing data via HL7 FHIR to a 
locally installed MCT? For LTCHs using certified health IT systems, how 
can existing certification criteria under the Office of the National 
Coordinator (ONC) Health Information Technology (IT) Certification 
Program support reporting of these data? What updates, if any, to the 
Certification Program would be needed to better support capture and 
submission of these data?
     Is a transition period between the current method of data 
submission and an electronic submission method necessary? If so, how 
long of a transition would be necessary, and what specific factors are 
relevant in determining the length of any transition?
     Would vendors, including those that service LTCHs, be 
interested in or willing to participate in pilots or voluntary 
electronic submission of quality data?
     Do LTCHs anticipate challenges, other than the adoption of 
EHR, to adopting the NHSN HA-CDI measure, and if so, what are potential 
solutions for those challenges?
    While we will not be responding to specific comments submitted in 
response to this RFI in the FY 2023 IPPS/LTCH PPS final rule, we will 
actively consider all input as we develop future regulatory proposals. 
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.
6. Overarching Principles for Measuring Equity and Healthcare Quality 
Disparities Across CMS Quality Programs--Request for Information (RFI)
    Significant and persistent inequities in healthcare outcomes exist 
in the United States. Belonging to an underserved community 
1355 1356 1357 is often associated with worse health 
outcomes.1358 1359 1360 1361 1362 1363 With this in mind, 
CMS aims to advance health equity, by which we mean the attainment of 
the highest level of health for all people, where everyone has a fair 
and just opportunity to attain their optimal health regardless of race, 
ethnicity, disability, sexual orientation, gender identity, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes. CMS is working to 
advance health equity by designing, implementing, and operationalizing 
policies and programs that support health for all the people served by 
our programs, eliminating avoidable differences in health outcomes 
experienced by people who are disadvantaged or underserved, and 
providing the care and support that our enrollees need to thrive.\1364\
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    \1355\ 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.
    \1356\ 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. BMJ. 2013 
Feb 14;346:f521. doi: 10.1136/bmj.f521.
    \1357\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and 
equity of care in U.S. hospitals. N Engl J Med. 2014;371(24):2298-
2308.
    \1358\ Polyakova M, Udalova V, Kocks G, 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.
    \1359\ Rural Health Research Gateway. (2018). Rural communities: 
Age, Income, and Health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf. Accessed 
February 3, 2022.
    \1360\ U.S. Department of Health and Human Services. Office of 
the Secretary. Progress Report to Congress. HHS Office of Minority 
Health. 2020 Update on the Action Plan to Reduce Racial and Ethnic 
Health Disparities. FY 2020. Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf. Accessed February 3, 2022.
    \1361\ Heslin, KC, Hall JE. Sexual Orientation Disparities in 
Risk Factors for Adverse COVID-19-Related Outcomes, by Race/
Ethnicity--Behavioral Risk Factor Surveillance System, United 
States, 2017-2019. Morbidity and Mortality Weekly Report (MMWR). 
2021;70(5):149-154. Centers for Disease Control and Prevention. 
February 5, 2021. Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm?s_cid=mm7005a1_w. Accessed February 3, 2022.
    \1362\ 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. doi:10.1101/2020.07.21.20159327. PMID: 
32743608; PMCID: PMC7386532.
    \1363\ Vu M, Azmat A, Radejko T, Padela AI. Predictors of 
Delayed Healthcare Seeking Among American Muslim Women. Journal of 
Women's Health. 2016 Jun;25(6):586-593; Nadimpalli SB, Cleland CM, 
Hutchinson MK, et al. The Association between Discrimination and the 
Health of Sikh Asian Indians. Health Psychol. 2016 Apr;35(4):351-
355.
    \1364\ Centers for Medicare & Medicaid Services. Available at: 
https://www.cms.gov/pillar/health-equity. Accessed February 9, 2022.
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    We are committed to achieving equity in healthcare outcomes for our 
beneficiaries by supporting healthcare providers' quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting healthcare provider accountability 
for healthcare disparities.\1365\ Measuring healthcare disparities in 
quality measures is a cornerstone of our approach to advancing 
healthcare equity. Hospital performance results that illustrate 
differences in outcomes between patient populations have been reported 
to hospitals confidentially since 2015. We provide additional 
information about this program in section IX.E.6.a.1. of this proposed 
rule.
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    \1365\ CMS Quality Strategy. 2016. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Qualityinitiativesgeninfo/downloads/cms-quality-strategy.pdf. Accessed February 3, 2022.
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    This RFI consists of three sections. The first section discusses a 
general framework that could be utilized across CMS quality programs to 
assess disparities in healthcare quality. The next section outlines 
approaches that could be used in the LTCH QRP to assess drivers of 
healthcare quality disparities in the LTCH QRP. Additionally, this 
section discusses measures of health equity that could be adapted for 
use in the LTCH QRP. Finally, the third section solicits public comment 
on the principles and approaches listed in the first two sections as 
well as seeking other thoughts about disparity measurement guidelines 
for the LTCH QRP.

[[Page 28571]]

a. Cross-Setting Framework To Assess Healthcare Quality Disparities
    CMS has identified five key considerations that we could apply 
consistently across CMS programs when advancing the use of measurement 
and stratification as tools to address healthcare disparities and 
advance health equity. The remainder of this section describes each of 
these considerations.
(1) Identification of Goals and Approaches for Measuring Healthcare 
Disparities and Using Measure Stratification Across CMS Quality 
Programs
    By quantifying healthcare disparities through quality measure 
stratification (that is, measuring performance differences among 
subgroups of beneficiaries), we aim to provide useful tools for 
healthcare providers to drive improvement based on data. We hope that 
these results support healthcare provider efforts in examining the 
underlying drivers of disparities in their patients' care and to 
develop their own innovative and targeted quality improvement 
interventions. Quantification of health disparities can also support 
communities in prioritizing and engaging with healthcare providers to 
execute such interventions, as well as providing additional tools for 
accountability and decision-making.
    There are several different conceptual approaches to reporting 
health disparities. In the acute care setting, two complementary 
approaches are already used to confidentially provide disparity 
information to hospitals for a subset of existing measures. The first 
approach, referred to as the ``within-hospital disparity method,'' 
compares measure performance results for a single measure between 
subgroups of patients with and without a given factor. This type of 
comparison directly estimates disparities in outcomes between subgroups 
and can be helpful to identify potential disparities in care. This type 
of approach can be used with most measures that include patient-level 
data. The second approach, referred to as the ``between-hospital 
disparity methodology,'' provides performance on measures for only the 
subgroup of patients with a particular social risk factor (SRF). These 
approaches can be used by a healthcare provider to compare their own 
measure performance on a particular subgroup of patients against 
subgroup-specific state and national benchmarks. Alone, each approach 
may provide an incomplete picture of disparities in care for a 
particular measure, but when reported together with overall quality 
performance, these approaches may provide detailed information about 
where differences in care may exist or where additional scrutiny may be 
appropriate. For example, the ``between-hospital'' disparity method may 
indicate that an LTCH underperformed (when compared to other facilities 
on average) for patients with a given SRF, which would signal the need 
to improve care for this population. However, if the LTCH also 
underperformed for patients without that SRF (the ``within-hospital'' 
disparity, as described above), the measured difference, or disparity 
in care could be negligible even though performance for the group that 
has been historically marginalized remains poor. 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.\1366\
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    \1366\ Centers for Medicare & Medicaid Services (CMS), HHS. 
Disparity Methods Confidential Reporting. Available at: https://qualitynet.cms.gov/inpatient/measures/disparity-methods. Accessed 
February 3, 2022.
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    CMS is interested in whether similar approaches to the two 
discussed in the previous paragraph could be used to provide 
confidential stratified measure results for selected LTCH QRP measures, 
as appropriate and feasible. However, final decisions regarding 
disparity reporting will be made at the program level, as CMS intends 
to tailor the approach used in each setting to achieve the greatest 
benefit and avoid unintentional consequences or biases in measurement 
that may exacerbate disparities in care.
(2) Guiding Principles for Selecting and Prioritizing Measure for 
Disparity Reporting
    We intend to expand our efforts to provide stratified reporting for 
additional clinical quality measures, provided they offer meaningful, 
actionable, and valid feedback to healthcare providers on their care 
for populations that may face social disadvantage or other forms of 
discrimination or bias. We are mindful, however, that it may not be 
possible to calculate stratified results for all quality measures, and 
that there may be situations where stratified reporting is not desired. 
To help inform prioritization of candidate measures for stratified 
reporting, we aim to receive feedback on several systematic principles 
under consideration that we believe will help us prioritize measures 
for disparity reporting across programs:
     Programs may consider stratification, among existing 
clinical quality measures for further disparity reporting, prioritizing 
recognized measures which have met industry standards for measure 
reliability and validity.
     Programs may consider measures for prioritization that 
show evidence that a treatment or outcome being measured is affected by 
underlying healthcare disparities for a specific social or demographic 
factor. Literature related to the measure or outcome should be reviewed 
to identify disparities related to the treatment or outcome, and should 
carefully consider both SRFs and patient demographics. In addition, 
analysis of Medicare-specific data should be done in order to 
demonstrate evidence of disparity in care for some or most healthcare 
providers that treat Medicare patients.
     Programs may consider establishing statistical reliability 
and representation standards (for example, the percent of patients with 
a SRF included in reporting facilities) prior to reporting results. 
They may also consider prioritizing measures that reflect performance 
on greater numbers of patients to ensure that the reported results of 
the disparity calculation are reliable and representative.
     After completing stratification, programs may consider 
prioritizing the reporting of measures that show differences in measure 
performance between subgroups across healthcare providers.
(3) Principles for SRF and Demographic Data Selection and Use
    SRFs are the wide array of non-clinical drivers of health known to 
negatively impact patient outcomes. These include factors such as 
socioeconomic status, housing availability, and nutrition (among many 
others), often inequitably affecting historically marginalized 
communities on the basis of race and ethnicity, rurality, sexual 
orientation and gender identity, religion, and 
disability.1367 1368 1369 1370 1371 1372 1373 1374
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    \1367\ 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.
    \1368\ 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. BMJ. 2013 
Feb 14;346:f521.
    \1369\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and 
equity of care in U.S. hospitals. N Engl J Med. 2014;371(24):2298-
2308.
    \1370\ Polyakova M, Udalova V, Kocks G, 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.
    \1371\ Rural Health Research Gateway. (2018). Rural communities: 
Age, Income, and Health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf. Accessed 
February 3, 2022.
    \1372\ HHS Office of Minority Health (2020). 2020 Update on the 
Action Plan to Reduce Racial and Ethnic Health Disparities. 
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf. Accessed February 3, 2022.
    \1373\ 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. medRxiv [Preprint]. 
2020.07.21.20159327. doi: 10.1101/2020.07.21.20159327. PMID: 
32743608; PMCID: PMC7386532.
    \1374\ Vu M, Azmat A, Radejko T, Padela AI. Predictors of 
Delayed Healthcare Seeking Among American Muslim Women. Journal of 
Women's Health. 2016 Jun;25(6):586-593; Nadimpalli SB, Cleland CM, 
Hutchinson MK, et al. The Association between Discrimination and the 
Health of Sikh Asian Indians. Health Psychol. 2016 Apr;35(4):351-
355.

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[[Page 28572]]

    Identifying and prioritizing social risk or demographic variables 
to consider for disparity reporting can be challenging. This is due to 
the high number of variables that have been identified in the 
literature as risk factors for poorer health outcomes and the limited 
availability of many self-reported SRFs and demographic factors across 
the healthcare sector. Several proxy data sources, such as area-based 
indicators of social risk and imputation methods, may be used if 
individual patient-level data are not available. Each source of data 
has advantages and disadvantages for disparity reporting.
     Patient-reported data are considered to be the 
gold standard for evaluating quality of care for patients with 
SRFs.\1375\ While data sources for many SRFs and demographic variables 
are still developing among several CMS settings, demographic data 
elements collected through assessments already exist in LTCHs. 
Beginning October 1, 2022, LTCHs (86 FR 62390) will begin collecting 
additional standardized patient data elements about race, ethnicity, 
preferred language, transportation, health literacy, and social 
isolation.
---------------------------------------------------------------------------

    \1375\ Jarr[iacute]n OF, Nyandege AN, Grafova IB, Dong X, Lin H. 
Validity of race and ethnicity codes in Medicare administrative data 
compared with gold-standard self-reported race collected during 
routine home health care visits. Med Care. 2020;58(1):e1-e8. doi: 
10.1097/MLR.0000000000001216. PMID: 31688554; PMCID: PMC6904433.
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     CMS Administrative Claims data have long been used for 
quality measurement due to their availability and will continue to be 
evaluated for usability in measure development and or stratification. 
Using these existing data allows for high impact analyses with 
negligible healthcare provider burden. For example, dual eligibility 
for Medicare and Medicaid has been found to be an effective indicator 
of social risk in beneficiary populations.\1376\ There are, however, 
limitations in these data's usability for stratification analysis.
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    \1376\ Office of the Assistant Secretary for Planning and 
Evaluation. Report to Congress: Social Risk Factors and Performance 
Under Medicare's Value-Based Purchasing Program. December 20, 2016. 
Available at: https://www.aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs. Accessed February 3, 2022.
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     Area-based indicators of social risk create approximations 
of patient risk based on neighborhood context. Several indexes, such as 
the Agency for Healthcare Research and Quality (AHRQ) Socioeconomic 
Status (SES) Index,\1377\ the Centers for Disease Control and 
Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) 
Social Vulnerability Index (SVI),\1378\ and the Health Resources and 
Services Administration (HRSA) Area Deprivation Index (ADI),\1379\ 
provide multifaceted contextual information about an area and may be 
considered as an efficient way to stratify measures that include many 
SRFs.
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    \1377\ Bonito A, 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 & 
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://archive.ahrq.gov/research/findings/final-reports/medicareindicators/medicareindicators1.html. Accessed February 7, 
2022.
    \1378\ Flanagan BE, Gregory EW, Hallisey EJ, Heitgerd JL, Lewis 
B. A social vulnerability index for disaster management. Journal of 
Homeland Security and Emergency Management. 2011;8(1):1-22. 
Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/img/pdf/Flanagan_2011_SVIforDisasterManagement-508.pdf. Accessed February 3, 
2022.
    \1379\ Center for Health Disparities Research. University of 
Wisconsin School of Medicine and Public Health. Neighborhood Atlas. 
Available at: https://www.neighborhoodatlas.medicine.wisc.edu/. 
Accessed February 3, 2022.
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     Imputed data sources use statistical techniques to 
estimate patient-reported factors, including race and ethnicity. One 
such tool is the Medicare Bayesian Improved Surname Geocoding (MBISG) 
method (currently in version 2.1), which combines information from 
administrative data, surname, and residential location to estimate race 
and ethnicity of patients at a population level.\1380\
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    \1380\ 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. Epub 2018 Dec 3. PMID: 30506674; PMCID: PMC6338295. 
Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338295/pdf/HESR-54-13.pdf. Accessed February 3, 2022.
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(4) Identifying Meaningful Performance Differences
    While we aim to use standardized approaches where possible, 
differences in performance on stratified results will be identified at 
the program level due to contextual variations across programs and 
settings. We look forward to feedback on the benefits and limitations 
of the possible reporting approaches described below:
     Statistical approaches could be used to reliably 
group results, such as using confidence intervals, creating cut points 
based on standard deviations, or using a clustering algorithm.
     Programs could use a ranked ordering and percentile 
approach, ordering providers in a ranked system based on their 
performance on disparity measures to quickly allow them to compare 
their performance to other similar providers.
     LTCHs could be categorized into groups based on their 
performance using defined thresholds, such as fixed intervals of 
results of disparity measures, indicating different levels of 
performance.
     Benchmarking, or comparing individual results to 
a state or national average, is another potential reporting strategy.
     Finally, a ranking system is not appropriate for all 
programs and healthcare settings, and some programs may only report 
disparity results.
(5) Guiding Principles for Reporting Disparity Measures
    Reporting of the results discussed above can be employed in several 
ways to drive improvements in quality. Confidential reporting, or 
reporting results privately to healthcare providers, is generally used 
for new programs or new measures recently adopted for programs through 
notice-and-comment rulemaking to give healthcare providers an 
opportunity to become more familiar with the calculation methods and to 
improve before other forms of reporting are used. In addition, many 
results are reported publicly, in accordance with the statute. This 
method provides all stakeholders with important information on 
healthcare provider quality, and in turn, relies on market forces to 
incentivize healthcare providers to improve and become more competitive 
in their markets without directly influencing payment from CMS.

[[Page 28573]]

One important consideration is to assess differential impact on LTCHs, 
such as those located in rural or critical access areas, to ensure that 
reporting does not disadvantage already resource-limited settings. The 
type of reporting chosen by programs will depend on the program 
context.
    Regardless of the methods used to report results, it is important 
to report stratified measure data alongside overall measure results. 
Review of both measures results along with stratified results can 
illuminate greater levels of detail about quality of care for subgroups 
of patients, providing important information to drive quality 
improvement. Unstratified quality measure results address general 
differences in quality of care between healthcare providers and promote 
improvement for all patients, but unless stratified results are 
available, it is unclear if there are subgroups of patients that 
benefit most from initiatives. Notably, even if overall quality measure 
scores improve, without identifying and measuring differences in 
outcomes between groups of patients, it is impossible to track progress 
in reducing disparity for patients with heightened risk of poor 
outcomes.
b. Approaches To Assessing Drivers of Healthcare Quality Disparities 
and Developing Measures of Healthcare Equity in the LTCH QRP
    This section presents information on two approaches for the LTCH 
QRP. The first section presents information about a method that could 
be used to assist LTCHs in identifying potential drivers of healthcare 
quality disparities. The second section describes measures of 
healthcare equity that might be appropriate for inclusion in the LTCH 
QRP.
(1) Performance Disparity Decomposition
    In response to the FY 2022 IPPS/LTCH PPS proposed rule's RFI (86 FR 
25616 through 25618), ``Closing the Health Equity Gap in Post-Acute 
Care Quality Reporting Programs,'' some stakeholders noted that, while 
stratified results provide more information about disparities compared 
to overall measure scores, they provide limited information toward 
understanding the drivers of these disparities. As a result, it is up 
to the LTCHs to determine which factors are leading to performance gaps 
so that they can be addressed. Unfortunately, identifying which factors 
are contributing to the performance gaps may not always be 
straightforward, especially if the LTCH has limited information or 
resources to determine the extent to which a patient's social 
determinants of health (SDOH) or other mediating factors (for example, 
health histories) explain a given disparity. An additional complicating 
factor is the reality that there are likely multiple SDOH and other 
mediating factors responsible for a given disparity, and it may not be 
obvious to the LTCH which of these factors are the primary drivers.
    Consequently, CMS may consider methods to use the data already 
available in enrollment, claims, and assessment data to estimate the 
extent to which various SDOH (for example, transportation, health 
literacy) and other mediating factors drive disparities in an effort to 
provide more actionable information. Researchers have utilized 
decomposition techniques to examine inequality in health care and, 
specifically, as a way to understand and explain the underlying causes 
of inequality.\1381\ At a high level, regression decomposition is a 
method that allows one to estimate the extent to which disparities 
(that is, differences) in measure performance between subgroups of 
patient populations are due to specific factors. These factors can be 
either non-clinical (for example, SDOH) or clinical. Similarly, CMS may 
utilize regression decomposition to identify and calculate the specific 
contribution of SDOHs and other mediating factors to observed 
disparities. This approach may better inform our understanding of the 
extent to which providers and policy-makers may be able to narrow the 
gap in healthcare outcomes. Additionally, provider-specific 
decomposition results could be shared through confidential feedback so 
that LTCHs can see the disparities within their facility with more 
granularity, allowing them to set priority targets in some performance 
areas while knowing which areas of their care are already relatively 
equitable. Importantly, these results could help providers identify 
reasons for disparities that might not be obvious without having access 
to additional data sources (for example, the ability to link data 
across providers).
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    \1381\ Rahimi E, Hashemi Nazari S. A detailed explanation and 
graphical representation of the Blinder-Oaxaca decomposition method 
with its application in health inequalities. Emerg Themes Epidemiol. 
2021;18:12. https://doi.org/10.1186/s12982-021-00100-9. Accessed 
February 24, 2022.
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    To more explicitly demonstrate the types of information that could 
be provided through decomposition of a measure disparity, consider the 
following example for a given LTCH. Figures 1 through 3 depict an 
example (using hypothetical data) of how a disparity in a measure of 
Medicare Spending Per Beneficiary (MSPB) between dually eligible 
beneficiaries (that is, those enrolled in Medicare and Medicaid) and 
non-dually eligible beneficiaries (that is, those with Medicare only) 
could be decomposed among two mediating factors, one SDOH and one 
clinical factor: (1) Low health literacy; and (2) high volume of 
emergency department (ED) use. These examples were selected because if 
they were shown to be drivers of disparity in their LTCH, the 
healthcare provider could mitigate their effects. Additionally, high-
volume ED use is used as a potential mediating factor that could be 
difficult for LTCHs to determine on their own, as it would require 
having longitudinal data for patients across multiple facilities.
    In the example in Figure 1, the overall Medicare spending disparity 
is $1,000: Spending, on average, is $5,000 per non-dual beneficiary and 
$6,000 per dual beneficiary. We can also see from Figure 2 that in this 
LTCH, the dual population has twice the prevalence of beneficiaries 
with low health literacy and high ED use compared to the non-dual 
population. Using regression techniques, the difference in overall 
spending between non-dual and dual beneficiaries can be divided into 
three causes: (1) A difference in the prevalence of mediating factors 
(for example, low health literacy and high ED use) between the two 
groups, (2) a difference in how much spending is observed for 
beneficiaries with these mediating factors between the two groups, and 
(3) differences in baseline spending that are not due to either (1) or 
(2). In Figure 3, the Non-Dual beneficiaries column breaks down the 
overall spending per non-dual beneficiary, $5,000, into a baseline 
spending of $4,600 plus the effects of the higher spending for the 10 
percent of non-dual beneficiaries with low health literacy ($300) and 
the 5 percent with high ED use ($100). The Dual beneficiaries column 
similarly decomposes the overall spending per dual beneficiary ($6,000) 
into a baseline spending of $5,000, plus the amounts due to dual 
beneficiaries' 20 percent prevalence of low health literacy ($600, 
twice as large as the figure for non-dual beneficiaries because the 
prevalence is twice as high), and dual beneficiaries' 10 percent 
prevalence of high-volume ED use ($200, similarly twice as high as for 
non-dual beneficiaries due to higher prevalence). This column also 
includes an additional $100 per risk factor because dual beneficiaries 
experience a higher cost than non-dual beneficiaries

[[Page 28574]]

within the low health literacy risk factor, and similarly within the 
high ED use risk factor. Based on this information, an LTCH can 
determine that the overall $1,000 disparity can be divided into 
differences simply due to risk factor prevalence ($300 + $100 = $400 or 
40 percent of the total disparity), disparities in costs for 
beneficiaries with risk factors ($100 + $100 = $200 or 20 percent) and 
disparities that remain unexplained (differences in baseline costs: 
$400 or 40 percent).
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP10MY22.210

[GRAPHIC] [TIFF OMITTED] TP10MY22.211

[GRAPHIC] [TIFF OMITTED] TP10MY22.212

BILLING CODE 4120-01-C
    In particular, the LTCH can see that simply having more patients 
with low health literacy and high ED use accounts for a disparity of 
$400. In addition, there is still a $200 disparity stemming from 
differences in costs between non-dual and dual patients for a given 
risk factor, and another $400 that is not explained by either low 
health literacy or high ED use. These differences may instead be 
explained by other SDOH that have not yet been included in this 
breakdown, or by the distinctive pattern of care decisions made by 
providers for dual and non-dual beneficiaries. These cost estimates 
would provide additional information that facilities could use when 
determining where to devote resources aimed at achieving equitable 
health outcomes (for example, facilities may choose to focus efforts on 
the largest drivers of a disparity).
(2) Measures Related to Health Equity
    Beyond identifying disparities in individual health outcomes and by 
individual risk factors, there is interest in developing more 
comprehensive measures of health equity that reflect organizational 
performance. When determining which equity measures could be 
prioritized for development for the LTCH QRP, CMS will draw from its 
experience with the CMS Measures Management System (MMS)

[[Page 28575]]

Blueprint \1382\ and may consider the following:
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    \1382\ Centers for Medicare & Medicaid Services. CMS Measures 
Management System Blueprint. Version 17.0. September 2021. Available 
at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf.
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     Measures should be actionable in terms of quality 
improvement.
     Measures should help beneficiaries and their caregivers 
make informed healthcare decisions.
     Measures should not create incentives to lower the quality 
of care.
     Measures should adhere to high scientific acceptability 
standards.
    CMS has developed measures assessing health equity, or designed to 
promote health equity, in other settings outside of the LTCH. As a 
result, there may be measures that could be adapted for use in the LTCH 
QRP. The remainder of this section discusses two such measures, 
beginning with the Health Equity Summary Score (HESS), and then a 
structural measure assessing the degree of hospital leadership 
engagement in health equity performance data.
(a) Health Equity Summary Score
    The HESS measure was developed by the CMS Office of Minority Health 
(OMH) \1383\ to identify and to reward healthcare providers (that is, 
Medicare Advantage [MA] plans) that perform relatively well on measures 
of care provided to beneficiaries with SRFs, as well as to discourage 
the non-treatment of patients who are potentially high-risk, in the 
context of value-based purchasing. Additionally, a version of the HESS 
is in development for the Hospital Inpatient Quality Reporting (HIQR) 
program.\1384\ This composite measure provides a summary of equity of 
care delivery by combining performance and improvement across multiple 
measures and multiple at-risk groups. The HESS was developed with the 
following goals: Allow for ``multiple grouping variables, not all of 
which will be measurable for all plans,'' allow for ``disaggregation by 
grouping variable for nuanced insights,'' and allow for the future 
usage of additional and different SRFs for grouping.\1385\
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    \1383\ 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. 2021;36(7):1847-1857. doi: 10.1007/s11606-019-
05473-x. Epub 2019 Nov 11. PMID: 31713030; PMCID: PMC8298664. 
Available at: https://link.springer.com/content/pdf/10.1007/s11606-019-05473-x.pdf. Accessed February 3, 2022.
    \1384\ Centers for Medicare & Medicaid Services, FY 2022 IPPS/
LTCH PPS proposed rule. 88 FR 25560. May 10, 2021.
    \1385\ Centers for Medicare & Medicaid Services Office of 
Minority Health (CMS OMH). 2021. ``Health Equity as a `New Normal': 
CMS Efforts to Address the Causes of Health Disparities.'' Presented 
at CMS Quality Conference, March 2-3, 2021.
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    The HESS computes across-provider disparity in performance, as well 
as within-provider and across-provider disparity improvement in 
performance. Calculation starts with a cross-sectional score and an 
overall improvement score for each SRF of race/ethnicity and dual 
eligibility, for each plan. The overall improvement score is based on 
two separate improvement metrics: Within-plan improvement and 
nationally benchmarked improvement. Within-plan improvement is defined 
as how that plan improves the care of patients with SRFs relative to 
higher-performing patients between the baseline period and performance 
period, and is targeted at eliminating within-plan disparities. 
Nationally benchmarked improvement is improvement of care for 
beneficiaries with SRFs served by that MA plan, relative to the 
improvement of care for similar beneficiaries across all MA plans, and 
is targeted at improving the overall care of populations with SRFs. 
Within-plan improvement and nationally benchmarked improvement are then 
combined into an overall improvement score. Meanwhile, the cross-
sectional score measures overall measure performance among 
beneficiaries with SRFs during the performance period, regardless of 
improvement.
    To calculate a provider's overall score, the HESS uses a composite 
of five clinical quality measures based on Healthcare Effectiveness 
Data and Information Set (HEDIS) data and seven MA Consumer Assessment 
of Healthcare Providers and Systems (CAHPS) patient experience 
measures. A provider's overall HESS score is calculated once using only 
CAHPS-based measures and once using only HEDIS-based measures, due to 
incompatibility between the two data sources. The HESS uses a composite 
of these measures to form a cross-sectional score, a nationally 
benchmarked improvement score, and a within-plan improvement score, one 
for each SRF. These scores are combined to produce an SRF-specific 
blended score, which is then combined with the blended score for 
another SRF to produce the overall HESS.
(b) Degree of Hospital Leadership Engagement in Health Equity 
Performance Data
    CMS has developed a structural measure for use in acute care 
hospitals assessing the degree to which hospital leadership is engaged 
in the collection of health equity performance data, with the 
motivation that that organizational leadership and culture can play an 
essential role in advancing equity goals. This structural measure, 
entitled the Hospital Commitment to Health Equity measure (MUC2021-
106), was included on the CMS List of Measures under Consideration (MUC 
List) \1386\ and assesses hospital commitment to health equity using a 
suite of equity-focused organizational competencies aimed at achieving 
health equity for racial and ethnic minorities, people with 
disabilities, sexual and gender minorities, individuals with limited 
English proficiency, rural populations, religious minorities, and 
people facing socioeconomic challenges. We are proposing the Hospital 
Commitment to Health Equity measure for the Hospital Inpatient Quality 
Reporting (IQR) program beginning with the CY 2023 Reporting Period/FY 
2025 Payment Determination (see section IX.D.5.a. of this proposed 
rule). The measure will include five attestation-based questions, each 
representing a separate domain of commitment. A hospital will receive a 
point for each domain where it attests to the corresponding statement 
(for a total of 5 points). At a high level, the five domains cover the 
following: (1) Strategic plan to reduce health disparities; (2) 
approach to collecting valid and reliable demographic and SDOH data; 
(3) analyses performed to assess disparities; (4) engagement in quality 
improvement activities; \1387\ (5) leadership involvement in activities 
designed to reduce disparities. The specific questions asked within 
each domain, as well as the detailed measure specification are found in 
the CMS MUC List for December 2021 here: https://www.cms.gov/files/
document/measures-under-consideration-list-2021-

[[Page 28576]]

report.pdf. An LTCH could receive a point for each domain where data 
are submitted through a CMS portal to reflect actions taken by the LTCH 
for each corresponding domain (for a point total).
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    \1386\ Centers for Medicare & Medicaid Services. List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf. Accessed March 1, 2022.
    \1387\ Quality is defined by the National Academy of Medicine as 
the degree to which health services for individuals and populations 
increase the likelihood of desired health outcomes and are 
consistent with current professional knowledge. Quality improvement 
is the framework used to systematically improve care. Quality 
improvement seeks to standardize processes and structure to reduce 
variation, achieve predictable results, and improve outcomes for 
patients, healthcare systems, and organizations. Structure includes 
things like technology, culture, leadership, and physical capital; 
process includes knowledge capital (for example, standard operating 
procedures) or human capital (for example, education and training). 
Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Quality-Measure-and-Quality-Improvement-. Accessed March 1, 2022.
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    CMS believes this type of organizational commitment structural 
measure may complement the health disparities approach described in 
previous sections, and support LTCHs 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 
healthcare provider's capacity, systems, and processes to provide high-
quality care.'' \1388\ We acknowledge that collection of this 
structural measure may impose administrative and reporting requirements 
or both for LTCHs.
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    \1388\ Agency for Healthcare Research and Quality. Types of 
Health Care Quality Measures. 2015. Available at: https://www.ahrq.gov/talkingquality/measures/types.html. Accessed February 
3, 2022.
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    We are interested in obtaining feedback from stakeholders on 
conceptual and measurement priorities for the LTCH QRP to better 
illuminate organizational commitment to health equity.
7. Solicitation of Public Comment
    The goal of this request for information is to describe some key 
principles and approaches that we will consider when advancing the use 
of quality measure development and stratification to address healthcare 
disparities and advance health equity across our programs.
    We invite general comments on the principles and approaches 
described previously in this section of the rule, as well as additional 
thoughts about disparity measurement guidelines suitable for 
overarching consideration across CMS's QRP programs. Specifically, we 
invite comment on the following:
     Identification of Goals and Approaches for Measuring 
Healthcare Disparities and Using Measure Stratification Across CMS 
Quality Reporting Programs
    ++ The use of the within- and between-hospital disparity methods in 
LTCHs to present stratified measure results
    ++ The use of decomposition approaches to explain possible causes 
of measure performance disparities
    ++ Alternative methods to identify disparities and the drivers of 
disparities
     Guiding Principles for Selecting and Prioritizing Measures 
for Disparity Reporting
    ++ Principles to consider for prioritization of health equity 
measures and measures for disparity reporting, including prioritizing 
stratification for validated clinical quality measures, those measures 
with established disparities in care, measures that have adequate 
sample size and representation among healthcare providers and outcomes, 
and measures of appropriate access and care.
     Principles for Social Risk Factor (SRF) and Demographic 
Data Selection and Use
    ++ Principles to be considered for the selection of SRFs and 
demographic data for use in collecting disparity data including the 
importance of expanding variables used in measure stratification to 
consider a wide range of SRFs, demographic variables, and other markers 
of historic disadvantage. In the absence of patient-reported data we 
will consider use of administrative data, area-based indicators, and 
imputed variables as appropriate.
     Identification of Meaningful Performance Differences
    ++ Ways that meaningful difference in disparity results should be 
considered.
     Guiding Principles for Reporting Disparity Measures
    ++ Guiding principles for the use and application of the results of 
disparity measurement.
     Measures Related to Health Equity
    ++ The usefulness of a HESS score for LTCHs, both in terms of 
provider actionability to improve health equity, and in terms of 
whether this information would support Care Compare website users in 
making informed healthcare decisions.
    ++ The potential for a structural measure assessing an LTCH's 
commitment to health equity, the specific domains that should be 
captured, and options for reporting these data in a manner that would 
minimize burden.
    ++ Options to collect facility-level information that could be used 
to support the calculation of a structural measure of health equity.
    ++ Other options for measures that address health equity.
    While we will not be responding to specific comments submitted in 
response to this RFI in the FY 2023 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.
8. Form, Manner, and Timing of Data Submission Under the LTCH QRP
    We refer readers to the regulatory text at 42 CFR 412.560(b) for 
information regarding the current policies for reporting LTCH QRP data.
    For more details about the required reporting periods of measures 
or standardized patient assessment data during the first and subsequent 
years upon adoption, please refer to the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 24588 through 24590).
9. Policies Regarding Public Display of Measure Data for the LTCH QRP
    We are not proposing any new policies regarding the public display 
of measure data at this time.

H. Proposed Changes to the Medicare Promoting Interoperability Program

1. Statutory Authority for the Medicare Promoting Interoperability 
Program for Eligible Hospitals and CAHs
    The Health Information Technology for Economic and Clinical Health 
Act (HITECH Act) (Title IV of Division B of the American Recovery and 
Reinvestment Act of 2009 (ARRA), together with Title XIII of Division A 
of the ARRA) authorized incentive payments under Medicare and Medicaid, 
as well as downward payment adjustments under Medicare, for the 
adoption and meaningful use of certified electronic health record 
technology (CEHRT). Incentive payments under Medicare were available to 
eligible hospitals and critical access hospitals (CAHs) for certain 
payment years (as authorized under sections 1886(n) and 1814(l) of the 
Act, respectively) if they successfully demonstrated meaningful use of 
CEHRT, which included reporting on clinical quality measures using 
CEHRT. In accordance with the timeframe set forth in the statute, these 
incentive payments under Medicare are no longer available. Sections 
1886(b)(3)(B)(ix) and 1814(l)(4) of the Act authorize downward payment 
adjustments under Medicare, beginning with Federal fiscal year (FY) 
2015 (and beginning with FY 2022 for subsection (d) Puerto Rico 
hospitals), for eligible hospitals and CAHs that do not successfully 
demonstrate meaningful use of CEHRT for certain associated electronic 
health record (EHR) reporting periods.
2. EHR Reporting Period
    Under the definition of ``EHR reporting period for a payment

[[Page 28577]]

adjustment year'' at 42 CFR 495.4, for eligible hospitals and CAHs that 
are new or returning participants in the Medicare Promoting 
Interoperability Program, the EHR reporting period in calendar year 
(CY) 2023 is a minimum of any continuous 90-day period within CY 2023, 
and the EHR reporting period in CY 2024 is a minimum of any continuous 
180-day period within CY 2024. For more information, we refer readers 
to the discussion in the FY 2022 Hospital Inpatient Prospective Payment 
Systems for Acute Care Hospitals and the Long-Term Care Hospital (IPPS/
LTCH) Prospective Payment System (PPS) final rule (86 FR 45460 through 
45462).
a. CEHRT Requirements
    The Promoting Interoperability Program and the Quality Payment 
Program (QPP) require the use of CEHRT as defined at 42 CFR 495.4 and 
414.1305, respectively. Since 2019, in general, this has consisted of 
EHR technology (which could include multiple technologies) certified 
under the Office of the National Coordinator for Health Information 
Technology (ONC) Health Information Technology (IT) Certification 
Program that meets the 2015 Edition Base EHR definition (as defined at 
45 CFR 170.102) and has been certified to certain other 2015 Edition 
health IT certification criteria as specified in the definition.
    The ``21st Century Cures Act: Interoperability, Information 
Blocking, and the ONC Health IT Certification Program'' final rule 
(also referred to as the ``ONC 21st Century Cures Act final rule''), 
published in the May 1, 2020, Federal Register (85 FR 25642 through 
25961), finalized a number of updates to the 2015 Edition of health IT 
certification criteria (also referred to as the 2015 Edition Cures 
Update) and introduced new 2015 Edition certification criteria. In 
connection with these updates, ONC also finalized that health IT 
developers have 24 months from the publication date of the final rule 
(until May 2, 2022) to make technology available that is certified to 
the updated, or new criteria. In response to additional calls for 
flexibility in response to the Public Health Emergency (PHE) for COVID-
19, ONC published an interim final rule with comment period on November 
4, 2020 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'' (hereinafter the 
``ONC interim final rule'') (85 FR 70064). In this interim final rule, 
ONC finalized extended compliance dates for certain 2015 Edition 
certification criteria. Specifically, where the ONC 21st Century Cures 
Act final rule provided that developers of certified health IT have 24 
months from the publication date of the final rule to make technology 
certified to new or updated criteria available, ONC extended the 
timeline until December 31, 2022 (and until December 31, 2023, for 45 
CFR[thinsp]170.315(b)(10), ``electronic health information (EHI) 
export'').
    In the CY 2021 Physician Fee Schedule (PFS) final rule (85 FR 84815 
through 84825), we finalized that the technology used by health care 
providers to satisfy the definitions of CEHRT at 42 CFR 495.4 and 
414.1305 must be certified under the ONC Health IT Certification 
Program, in accordance with the updated 2015 Edition certification 
criteria as finalized in the ONC 21st Century Cures Act final rule (85 
FR 25642). We further finalized aligning the transition period during 
which health care providers participating in the Promoting 
Interoperability Program or QPP may use technology certified to either 
the existing or updated 2015 Edition certification criteria, with the 
December 31, 2022, date established in the ONC interim final rule for 
health IT developers to make updated certified health IT available. 
After this date, health care providers will be required to use only 
certified technology updated to the 2015 Edition Cures Update for an 
EHR reporting period or performance period in CY 2023. We are not 
proposing any changes to this final policy within this proposed rule.
    We remind readers that health care providers would not be required 
to demonstrate that they are using updated technology to meet the CEHRT 
definitions immediately upon the transition date of December 31, 2022. 
In accordance with the EHR reporting period and performance period 
established for the Promoting Interoperability Program and the Merit-
based Incentive Payment System (MIPS) Promoting Interoperability 
performance category, participants are only required to use technology 
meeting the CEHRT definitions during a self-selected EHR reporting 
period or performance period of a minimum of any consecutive 90 days in 
CY 2023, including the final 90 days of 2023 (86 FR 45460 through 45462 
and 86 FR 65466, respectively). The eligible hospital, CAH, or MIPS 
eligible clinician is not required to demonstrate meaningful use of 
technology meeting the 2015 Edition Cures Update until the EHR 
reporting period or performance period they have selected.
3. Electronic Prescribing Objective: Proposed Changes to the Query of 
Prescription Drug Monitoring Program Measure and Technical Update to 
the E-Prescribing Measure
a. Query of Prescription Drug Monitoring Program Measure Background
    We have adopted the 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 41653), the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42593 through 42595), the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58967 through 58969), and the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45462 through 45464). 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. In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45464), we 
finalized that the Query of PDMP measure will remain optional and 
increased the eligible bonus points to 10 points for CY 2022.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42593 through 
42596), FY 2021 IPPS/LTCH PPS final rule (85 FR 58967 through 58969), 
and FY 2022 IPPS/LTCH PPS final rule (86 FR 45462 through 45464), we 
described the concern expressed by stakeholders who believed it was 
premature for the Medicare Promoting Interoperability Program to 
require the Query of PDMP measure and to score it based on performance. 
We 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 EHR developers may face significant cost 
burdens if they fully develop numerator and denominator calculations 
and are then required to change the specification at a later date. 
Stakeholders stated that the costs of additional development would 
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. While we recognize that a numerator/denominator-based 
measure remains challenging, we also note (as discussed in more detail 
later in this section) that the widespread availability of PDMPs across 
the

[[Page 28578]]

country, and recent progress toward solutions for connecting PDMPs with 
provider EHR systems, has made use of PDMPs feasible through a wide 
variety of approaches.
b. Current Status of PDMP Adoption
    Today, all 50 states and several localities host PDMPs.\1389\ The 
final state to establish a PDMP, the state of Missouri, passed 
legislation to address this issue in 2021, and is currently working to 
make its PDMP operational. A 2021 American Medical Association report 
found that physicians and others used state PDMPs more than 910 million 
times in 2020.\1390\ An assessment of PDMPs conducted by the PDMP 
Training and Technical Assistance Center (TTAC) at the Institute for 
Intergovernmental Research (IIR) found an increase in the number of 
PDMPs that are integrated with Health Information Exchanges (HIEs), 
EHRs, and/or Pharmacy Dispensing Systems (PDSs), with 44 PDMPs 
integrated in 2021 reflecting an increase from 28 PDMPs with at least 
one type of integration in 2017. We refer readers to Table IX.H.-01. 
for the report's findings on the type of integration and the number of 
PDMPs that have implemented that type of integration in 2021.
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    \1389\ Prescription Drug Monitoring Program Training and 
Technical Assistance Center, PDMP Policies and Capabilities: Results 
From 2021 State Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
    \1390\ American Medical Association, 2021 Overdose Epidemic 
Report, https://www.ama-assn.org/system/files/ama-overdose-epidemic-report.pdf.
[GRAPHIC] [TIFF OMITTED] TP10MY22.213

    Moreover,  a number of enhancements to PDMPs are occurring across 
the country, including enhancements to RxCheck, which is a free, 
federally supported interstate exchange hub for PDMP data. To date, the 
prototype has been successfully tested in several states. The goal of 
the project is to allow any health care 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 that are also live on RxCheck. This solution enables health care 
providers to query PDMPs via existing connections to health information 
exchange networks. Most states use either RxCheck or Prescription 
Monitoring Program (PMP) InterConnect or both to facilitate the sharing 
of PDMP information between states, allowing providers to query other 
states' PDMP information from within their own state PDMP.\1392\
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    \1391\ PDMP Policies and Capabilities: Results From 2021 State 
Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
    \1392\ Government Accountability Office. GAO-21-22, PRESCRIPTION 
DRUG MONITORING PROGRAMS: Views on Usefulness and Challenges of 
Programs.
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    We also note that the Substance Use-Disorder Prevention that 
Promotes Opioid Recovery and Treatment (SUPPORT) for Patients and 
Communities Act (Pub. L. 115-271), enacted in 2018, has focused on ways 
to address the nation's opioid epidemic. The SUPPORT for Patients and 
Communities Act included new requirements for PDMP enhancement and 
integration, to help reduce opioid misuse and overprescribing and 
promote the effective prevention and treatment of opioid use disorder 
beginning in October of 2021. Enhanced Federal matching funds were 
available to states to support related PDMP design, development, and 
implementation activities during fiscal years 2019 and 2020.
c. Proposed Changes to the Query of PDMP Measure and Related Policies
(1) Proposal To Change the Query of PDMP Measure Description
    The description of the Query of PDMP measure provides that 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 PDMP for prescription drug history, 
except where prohibited and in accordance with applicable law (42 CFR 
495.24(e)(5)(iii)(B)). Beginning with the EHR reporting period in CY 
2023, we are proposing in section IX.H.3.c.(2) of this proposed rule to 
require the Query of PDMP measure for eligible hospitals and CAHs 
participating in the Medicare Promoting Interoperability Program. In 
section IX.H.3.c.(4). of this proposed rule, we note that should we 
finalize our proposal to require the Query of PDMP measure beginning 
with the EHR reporting period in CY 2023, we are proposing two 
exclusions beginning with the EHR reporting period in CY 2023: (1) Any 
eligible hospital or CAH that does not have an internal pharmacy that 
can accept electronic prescriptions for controlled substances that 
include drugs from Schedules II, III, and IV, and is not located within 
10 miles of any pharmacy that accepts electronic prescriptions for 
controlled substances at the start of their EHR reporting period; and 
(2) any eligible hospital or CAH that cannot report on this measure in 
accordance with applicable law. Should we finalize the proposals to 
require the Query of PDMP measure and the associated exclusions, we 
believe the inclusion of the phrase ``except where prohibited and in 
accordance with applicable law'' in the description of the Query of 
PDMP measure and the inclusion of the phrase ``in accordance with 
applicable law'' in the second proposed exclusion for the Query of PDMP 
measure would be duplicative and potentially cause confusion. 
Therefore, we are proposing to remove the phrase ``except where 
prohibited and in accordance with applicable law'' from the description 
of the Query of

[[Page 28579]]

PDMP measure should our proposals to require the Query of PDMP measure 
and the associated exclusions be finalized. We refer readers to section 
IX.H.3.c.(1) of this proposed rule for our proposed measure description 
that would reflect this proposed change and additional proposed policy 
changes for the Query of PDMP measure.
    Should our proposal at section IX.H.8. of this proposed rule to 
remove associated regulatory text related to measures and objectives 
for the Medicare Promoting Interoperability Program not be finalized, 
we are proposing to update the regulatory text to reflect these 
proposed changes at 42 CFR 495.24(e)(5). We are inviting public comment 
on these proposals.
(2) Proposal To Require the Query of PDMP Measure
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45462), we noted 
that the decision to maintain the Query of PDMP as an optional measure 
for CY 2022 considered the current efforts to improve the technical 
foundation for EHR-PDMP integration, the continued implementation of 
the SUPPORT for Patients and Communities Act, our ongoing review of 
alternative measure approaches, and stakeholder concerns about the 
current readiness across states for implementation of the existing 
measure. We also noted that this measure can play an important role in 
helping health care providers to improve clinical decision making by 
utilizing this information to identify potential opioid use disorders, 
inform the development of care plans, and develop effective 
interventions (86 FR 45463); maintaining it as an optional measure with 
bonus points signals to the hospital and vendor community that this is 
an important measure which can help spur development and innovation to 
reduce barriers and challenges (86 FR 45463); and increasing bonus 
points to 10 points is consistent with the policy finalized for MIPS 
eligible clinicians in the CY 2021 Physician Fee Schedule final rule 
(85 FR 84887 through 84888) and aligns with the MIPS Promoting 
Interoperability performance category (86 FR 45464).
    We continue to believe that PDMPs play an important role in patient 
safety by assisting in the identification of patients who have multiple 
prescriptions for controlled substances or may be misusing or overusing 
them. Querying the PDMP is important for tracking dispensed controlled 
substances and improving prescribing practices. Efforts to expand the 
use of PDMPs and integrate PMDPs with health information technology 
systems are supported by Federal stakeholders including ONC, the 
Centers for Disease Control and Prevention (CDC), the Department of 
Justice (DOJ), and the Substance Abuse and Mental Health Services 
Administration (SAMHSA). The Query of PDMP measure offers a way to 
reward health care providers who participate in current PDMP 
initiatives that are supported by Federal partners.
    While work continues to improve standardized approaches to PDMP and 
EHR interoperability, we believe that it is feasible at this time to 
require providers to report the current Query of PDMP measure requiring 
a ``yes/no'' response. Given our policies for the Query of PDMP measure 
that included increasing the eligible bonus points to reward eligible 
hospitals and CAHs that could report the measure, as well as the recent 
progress in the availability of PDMPs in all fifty states, and 
solutions which support accessibility of PDMPs to providers, we believe 
eligible hospitals and CAHs have had time to grow familiar with what 
this measure requires of them, even as technical approaches to the use 
of PDMPs continue to advance. By requiring a ``yes/no'' response the 
current measure allows providers to use a variety of technical 
solutions to conduct a query of the PDMP and receive credit for the 
measure.
    Therefore, beginning with the EHR reporting period in CY 2023, we 
are proposing to require the current Query of PDMP measure requiring a 
``yes/no'' response for eligible hospitals and CAHs participating in 
the Medicare Promoting Interoperability Program. We would maintain the 
associated points at 10 points and refer readers to section IX.H.6. of 
this proposed rule for a discussion of our scoring methodology and 
proposed concurrent changes. As a result of this proposal, the maximum 
total points available for the Electronic Prescribing Objective would 
remain at 20 points for CY 2023. Should our proposal at section IX.H.8. 
of this proposed rule to remove associated regulatory text related to 
measures and objectives for the Medicare Promoting Interoperability 
Program not be finalized, we are proposing to update the regulatory 
text to reflect these proposed changes at 42 CFR 495.24(e)(5)(iii)(B).
    We are inviting public comment on these proposals.
(3) Proposal To Change the Query of PDMP Measure To Include Schedules 
II, III, and IV
    Under 42 CFR 495.24(e)(5)(iii)(B), the Query of PDMP measure 
provides that 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 PDMP for 
prescription drug history, except where prohibited and in accordance 
with applicable law. The Query of PDMP measure was adopted in the FY 
2019 IPPS/LTCH PPS final rule as one of two measures under the 
Electronic Prescribing Objective intended to support HHS initiatives 
related to the treatment of opioid and substance use disorders by 
helping health care providers avoid inappropriate prescriptions, 
improving coordination of prescribing amongst health care providers, 
and focusing on the advanced use of CEHRT (83 FR 41648 through 41653).
    Under the Controlled Substances Act (CSA),\1393\ the Drug 
Enforcement Administration classifies drugs, substances, and certain 
chemicals used to make drugs into five distinct categories or schedules 
depending upon the drug's acceptable medical use and the drug's abuse 
or dependency potential. A drug's abuse rate is a factor used to 
determine its classification; for example, Schedule I medications have 
the highest abuse potential while medications in Schedule V have a low 
abuse potential. We refer readers to Table IX.H.-02. for information on 
each Schedule, including abuse potential, medicinal use, if any, and 
drug examples. For additional information, we refer readers to the 
listing of drugs and their schedule located at CSA Scheduling at 
https://www.deadiversion.usdoj.gov/schedules/orangebook/c_cs_alpha.pdf.\1394\
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    \1393\ Public Law 91-513, tit. II, 84 Stat. 1236, 1242-84 
(1970); codified, as amended, at 21 U.S.C. 801 et seq.
    \1394\ See also https://www.dea.gov/sites/default/files/2020-04/Drugs%20of%20Abuse%202020-Web%20Version-508%20compliant-4-24-20_0.pdf.

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[[Page 28580]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.214

    PDMPs are operated at the state level and individual state 
requirements for reporting and use differ from state to state.\1396\ 
Currently, every state collects data on schedules II, III, and 
IV.\1397\ Some states collect information about certain non-controlled 
substances that are potentially subject to abuse or on all prescription 
drugs.\1398\ While state laws vary, we note that most state PDMPs 
require physicians and dispensing pharmacists to review a patient's 
prescribing information for the past twelve months prior to prescribing 
or dispensing any Schedule II, III, and IV controlled substances.\1399\
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    \1395\ GAO-21-22, Prescription Drug Monitoring Programs: Views 
on Usefulness and Challenges of Programs; 21 U.S.C. 812, and the 
U.S. Drug Enforcement Administration.
    \1396\ For additional information, we refer readers to https://www.cdc.gov/drugoverdose/pdf/Leveraging-PDMPs-508.pdf; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605194/; and https://www.pdmpassist.org/Policies/Legislative/StatutesAndRegulations.
    \1397\ https://www.pdmpassist.org/State.
    \1398\ GAO report, GAO-21-22 Prescription Drug Monitoring 
Programs.
    \1399\ https://www.pdmpassist.org/State.
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    PDMPs play an important role in patient safety by assisting in the 
identification of patients who have multiple prescriptions for 
controlled substances or may be misusing or overusing them. We believe 
that expanding the requirements of the Query of PDMP measure to include 
Schedule II, III, and IV drugs would further support HHS initiatives 
related to the treatment of opioid and substance use disorders by 
expanding the types of drugs included in the Query of PDMP measure 
while aligning with the PDMP requirements in a majority of states. We 
also believe this expansion to include additional Scheduled drugs would 
facilitate more informed prescribing practices and improve patient 
outcomes. Therefore, beginning with the EHR reporting period in CY 
2023, we are proposing to expand the Query of PDMP measure to include 
Schedule II, III, and IV drugs.
    Proposed Measure Description: For at least one Schedule II opioid 
or Schedule III or IV drug electronically prescribed using CEHRT during 
the EHR reporting period, the eligible hospital or CAH uses data from 
CEHRT to conduct a query of a PDMP for prescription drug history.
    To align with policy for the Query of PDMP measure with regard to 
Schedule II opioids, we are proposing the query of the PDMP for 
prescription drug history must occur prior to the electronic 
transmission of an electronic prescription for a Schedule II opioid or 
Schedule III or Schedule IV drug. We also note that this measure would 
include all permissible prescriptions and dispensing of Schedule II, 
III, or IV drugs no matter how small the amount prescribed during an 
encounter in order for eligible hospitals and CAHs to identify multiple 
health care provider episodes (physician shopping), prescriptions of 
dangerous combinations of drugs, and controlled substances prescribed 
in high quantities. We also note that multiple prescriptions for 
Schedule II opioids or Schedule III and IV drugs prescribed on the same 
date by the same eligible hospital or CAH would not require multiple 
queries of the PDMP and only one query would have to be performed for 
this measure. Eligible hospitals and CAHs would have flexibility to 
query the PDMP using data from CEHRT in any manner allowed under state 
law. Should our proposal at section IX.H.8. of this proposed rule to 
remove associated regulatory text related to measures and objectives 
for the Medicare Promoting Interoperability Program not be finalized, 
we are

[[Page 28581]]

proposing to update the regulatory text to reflect these proposed 
changes at 42 CFR 495.24(e)(5)(iii)(B).
    We are inviting public comment on these proposals. We are also 
inviting public comment on whether to expand this measure to include 
Schedule V or other drugs with potential for abuse.
(4) Exclusions
    In FY 2019 IPPS/LTCH PPS final rule, we finalized exclusions for 
eligible hospitals and CAHs from reporting the Query of PDMP measure 
beginning with CY 2020 when the measure would have been required by the 
Medicare Promoting Interoperability Program (83 FR 41653). The 
finalized exclusions included: (1) Any eligible hospital or CAH that 
does not have an internal pharmacy that can accept electronic 
prescriptions for controlled substances and is not located within 10 
miles of any pharmacy that accepts electronic prescriptions for 
controlled substances at the start of their EHR reporting period; and 
(2) any eligible hospital and CAH that could not report on this measure 
in accordance with applicable law. We also finalized the policy that 
beginning in CY 2020 an eligible hospital or CAH that qualifies for the 
e-Prescribing measure exclusion is also excluded from reporting on the 
Query of PDMP measure (83 FR 41649). We also noted our intention to 
propose an additional exclusion for health care providers in states 
where integration with a statewide PDMP is not yet feasible or not yet 
widely available (83 FR 41652).
    In FY 2020 IPPS/LTCH PPS final rule (84 FR 42595), we finalized the 
removal of the exclusions associated with the Query of PDMP measure, 
noting that exclusions were not necessary because we finalized the 
Query of PDMP measure as optional for CY 2020. We also finalized the 
Query of the PDMP measure as an optional measure for CY 2021 and CY 
2022 in FY 2021 IPPS/LTCH PPS final rule (85 FR 58969) and the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45464) and did not finalize any changes 
to our exclusions policy.
    In section IX.H.3.c.(2) of this proposed rule, beginning with the 
EHR reporting period in CY 2023, we are proposing to require the Query 
of PDMP measure for eligible hospitals and CAHs participating in the 
Medicare Promoting Interoperability Program. Should we finalize our 
proposal to require the Query of PDMP measure beginning with CY 2023, 
we believe that exclusions for the measure would be needed for eligible 
hospitals and CAHs. Therefore, we have revisited the exclusions we 
established in the FY 2019 IPPS/LTCH PPS final rule and subsequently 
removed in the FY 2020 IPPS/LTCH PPS final rule because the Query of 
PDMP measure would continue to be an optional measure. We believe these 
exclusions would address circumstances when an eligible hospital or CAH 
is unable to report on the measure. Specifically, if we finalize our 
proposal to require the Query of PDMP measure in section IX.H.3.c.(2) 
of this proposed rule, we are proposing the following exclusions that 
we modified from the exclusions established in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41649 through 41653) and subsequently removed in 
the FY 2020 IPPS/LTCH PPS final rule (84 FR 42593 through 42895) to 
reflect proposed policy changes in this proposed rule and that would 
begin with the EHR reporting period in CY 2023: (1) Any eligible 
hospital or CAH that does not have an internal pharmacy that can accept 
electronic prescriptions for controlled substances that include drugs 
from Schedules II, III, and IV, and is not located within 10 miles of 
any pharmacy that accepts electronic prescriptions for controlled 
substances at the start of their EHR reporting period; and (2) any 
eligible hospital or CAH that cannot report on this measure in 
accordance with applicable law. We refer readers to section IX.H.6. of 
this proposed rule for our proposed policy to redistribute points to 
the e-Prescribing measure under the Electronic Prescribing Objective 
should an eligible hospital or CAH claim an exclusion for the Query of 
PDMP measure for an EHR reporting period. Should our proposal at 
section IX.H.8. of this proposed rule to remove associated regulatory 
text related to measures and objectives for the Medicare Promoting 
Interoperability Program not be finalized, we are proposing to update 
the regulatory text to reflect these proposed changes at 42 CFR 
495.24(e)(5).
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41652), we signaled 
our intention to propose an additional exclusion beginning in CY 2020 
for providers in states where integration with a statewide PDMP is not 
yet feasible or not yet widely available. We no longer believe this 
exclusion is needed given the flexibility of the Query PDMP measure, 
which requires a ``yes/no'' response, as well as the implementation of 
PDMPs in all 50 states and several localities and the increasing number 
of PDMPs offering some degree of integration with EHRs (from 28 PDMPs 
with at least one type of integration in 2017 to 44 PDMPs that are 
integrated with HIEs, EHRs, and/or PDSs in 2021 \1400\). We also 
believe that broadly requiring this measure across providers who may 
access PDMPs in different ways would help to continue to drive 
development of improved solutions for PDMP access. While we believe the 
Query of PDMP measure is achievable for eligible hospitals and CAHs and 
that the proposed exclusions offer significant flexibilities such that 
most providers would be able to meet the measure or claim an exclusion 
we welcome public comment on other barriers, including barriers related 
to technology solutions, cost, and workflow, that should be considered. 
We also request comment on any additional exclusions that we should 
consider for this measure and may propose in the future.
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    \1400\ PDMP Policies and Capabilities: Results From 2021 State 
Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
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    We are inviting public comment on these proposals.
d. Future Direction
    While we believe that proposing to require the Query of PDMP 
measure is feasible and appropriate at this time, we are continuing to 
work with industry and other Federal partners to advance common 
standards for exchange of information between PDMPs, EHRs, pharmacy 
information systems, and exchange networks. We believe this work will 
ultimately allow us to achieve our ideal state, under which we would 
modify the Query of PDMP measure to be numerator/denominator-based and 
require use of standardized functionality within certified health IT 
systems to support the actions associated with the measure and 
reporting of a numerator and denominator. We will continue to 
collaborate with ONC to monitor developments across the industry and 
efforts to advance relevant standards, and plan to revisit this measure 
in the future to explore further specifying health IT requirements if 
they become available and are incorporated into the ONC Health IT 
Certification Program.
    Federally supported activities continue to focus on developing and 
refining standards-based approaches to enable effective integration 
into clinical workflows; exploring emerging technical solutions to 
enhance access to 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, updates to 
certified health IT systems incorporating application programming 
interfaces

[[Page 28582]]

(APIs) based on HL7[supreg] FHIR[supreg] standard version Release 4 (85 
FR 25642) can help support future technical approaches that enable more 
seamless exchange of data between CEHRT and PDMP systems. For more 
information about current and emerging standards related to PDMP data 
capture and exchange, we refer readers to the ONC Interoperability 
Standards Advisory.\1401\
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    \1401\ https://www.healthit.gov/isa/allows-a-provider-request-a-patients-medication-history-a-state-prescription-drug-monitoring.
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e. Proposed Technical Update to the E-Prescribing Measure
    The ONC 21st Century Cures Act final rule (85 FR 25642; 85 FR 25660 
through 25661) retired the ``drug-formulary and preferred drug list 
checks'' certification criterion at 45 CFR 170.315(a)(10) which was 
associated with measures under the Electronic Prescribing Objective for 
the Medicare Promoting Interoperability Program and the MIPS Promoting 
Interoperability performance category (80 FR 62882 and 83 FR 59817). 
ONC retired this criterion after January 1, 2022 (85 FR 26661).
    In the CY 2021 PFS final rule, we finalized that the ``drug-
formulary and preferred drug list checks'' criterion will no longer be 
associated with measures under the Electronic Prescribing Objective and 
will no longer be required to meet the CEHRT definition for the 
Medicare Promoting Interoperability Program and the MIPS Promoting 
Interoperability performance category, beginning with CY 2021 EHR 
reporting and performance periods (85 FR 84815 through 84825).
    In the FY 2022 IPPS/LTCH PPS final rule, we inadvertently omitted a 
revision to Table IX.F.-02.: Objectives and Measures for the Medicare 
Promoting Interoperability Program in 2022 to reflect this change and 
included the text ``queried for a drug formulary'' in the measure 
description and in the numerator of the e-Prescribing measure (86 FR 
45484). In an effort to more clearly capture the previously established 
policy finalized in the CY 2021 PFS final rule with respect to the e-
Prescribing measure, we are proposing to revise the measure description 
in Table 56 to read ``For at least one hospital discharge, medication 
orders for permissible prescriptions (for new and changed 
prescriptions) are transmitted electronically using CEHRT'' and the 
numerator will be updated to read to indicate ``[t]he number of 
prescriptions in the denominator generated and transmitted 
electronically'' to reflect the removal of the health IT certification 
criterion ``drug-formulary and preferred drug list checks'' (86 FR 
65478).
    We are inviting public comments on this proposal.
4. Health Information Exchange (HIE) Objective: Proposed Addition of an 
Alternative Measure for Enabling Exchange Under the Trusted Exchange 
Framework and Common Agreement (TEFCA)
a. Background on the Health Information Exchange Objective
    The Health Information Exchange (HIE) Objective and its associated 
measures for eligible hospitals and CAHs hold particular importance 
because of the role they play within the care continuum. In addition, 
these measures encourage and leverage interoperability on a broader 
scale and promote health IT-based care coordination. The Health 
Information Exchange Objective currently includes three measures: 
Support Electronic Referral Loops by Sending Health Information, 
Support Electronic Referral Loops by Receiving and Reconciling Health 
Information, and Health Information Exchange Bi-Directional Exchange. 
For background on this objective and its associated measures, we refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41656 through 
41661), the FY 2020 IPPS/LTCH PPS final rule (84 FR 42596 through 
42597), the FY 2021 IPPS/LTCH PPS final rule (85 FR 58969), and the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45465 through 45470).
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized the HIE Bi-
Directional Exchange measure, under the Health Information Exchange 
Objective (86 FR 45465 through 45470). The HIE Bi-Directional Exchange 
measure is worth 40 points, the maximum number of points of the Health 
Information Exchange Objective, and was finalized as an alternative to 
reporting on the two existing Health Information Exchange Objective 
measures: The Support Electronic Referral Loops by Sending Health 
Information measure (42 CFR 495.24(e)(6)(ii)(A)) and the Support 
Electronic Referral Loops by Receiving and Reconciling Health 
Information measure (42 CFR 495.24(e)(6)(ii)(B)). To meet the measure, 
eligible hospitals and CAHs must attest to the following statements:
     Statement 1: Participating in an HIE 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.
     Statement 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.
     Statement 3: Using the functions of CEHRT to support bi-
directional exchange with an HIE.
    We stated that, by enabling bi-directional exchange of information 
between health care providers and aggregating data across health care 
providers with disparate systems, HIEs (including a wide range of 
organizations facilitating health information exchange) 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 (86 FR 45465). 
We further described how participation in HIEs can amplify health care 
providers' capacity to share information beyond what a health care 
provider can achieve through the sending and receiving actions 
described in the existing measures under the Health Information 
Exchange Objective, for instance, by facilitating information exchange 
when a health care provider is unaware of another health care 
provider's need to receive information about a patient (86 FR 45466). 
By finalizing this measure for eligible hospitals and CAHs, we sought 
to ensure that health care providers participating in the Medicare 
Promoting Interoperability Program would be rewarded for connecting to 
exchange arrangements that can enable this type of robust information 
sharing.
b. Background on TEFCA
    Section 4003(b) of the 21st Century Cures Act (Pub. L. 114-255), 
enacted in 2016, amended section 3001(c) of the Public Health Service 
Act (42 U.S.C. 300jj-11(c)), and required HHS to take steps to advance 
interoperability for the purpose of ensuring full network-to-network 
exchange of health information. Specifically, Congress directed the 
National Coordinator to ``develop or support a trusted exchange 
framework, including a common agreement among health information 
networks nationally.'' Since the enactment of the 21st Century Cures 
Act, HHS has pursued development of a Trusted Exchange Framework and 
Common

[[Page 28583]]

Agreement, or TEFCA. ONC's goals for TEFCA are: \1402\
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    \1402\ See https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
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    Goal 1: Establish a universal policy and technical floor for 
nationwide interoperability.
    Goal 2: Simplify connectivity for organizations to securely 
exchange information to improve patient care, enhance the welfare of 
populations, and generate health care value.
    Goal 3: Enable individuals to gather their health care information.
    In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20537), we 
requested comment on whether eligible hospital or CAH participation in 
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. We received comments in 
support of this concept, although some commenters disagreed indicating 
that they were concerned about adding additional burden (83 FR 41669).
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25631 through 
25634), in which we proposed the HIE Bi-Directional Exchange measure 
for eligible hospitals and CAHs, we noted that the proposed attestation 
statements for the measure did not explicitly refer to participation in 
a health information network, or partnering with a health information 
network that participates in TEFCA. However, we stated TEFCA was likely 
to be an important way for eligible hospitals and CAHs to enable bi-
directional health information exchange in the future and that we would 
continue to explore ways to provide further guidance or update this 
measure to align with the use of health information networks that 
participate in TEFCA in the future (86 FR 25634). In the final rule, we 
noted that several commenters were encouraged to see our 
acknowledgement that this measure could align with the efforts on TEFCA 
(86 FR 45468).
    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, 
important additional developments have occurred with respect to 
TEFCA.\1403\ On January 18, 2022, ONC announced a significant TEFCA 
milestone by releasing the Trusted Exchange Framework \1404\ and Common 
Agreement Version 1.\1405\ The Trusted Exchange Framework is a set of 
non-binding principles for health information exchange, and the Common 
Agreement for Nationwide Health Information Interoperability Version 1 
(also referred to as Common Agreement) is a contract that advances 
those principles. The Common Agreement and the incorporated by 
reference Qualified Health Information Network (QHIN) Technical 
Framework Version 1 (QTF) \1406\ establish the technical infrastructure 
model and governing approach for different health information networks 
and their users to securely share clinical information with each 
other--all under commonly agreed-to terms. The Common Agreement is a 
legal contract that QHINs \1407\ sign with the ONC Recognized 
Coordinating Entity (RCE),\1408\ a private-sector entity that 
implements the Common Agreement and ensures QHINs comply with its 
terms.
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    \1403\ For more information on current developments related to 
TEFCA, we refer readers to www.HealthIT.gov/TEFCA.
    \1404\ Trusted Exchange Framework (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \1405\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1406\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \1407\ The Common Agreement defines a QHIN as ``to the extent 
permitted by applicable SOP(s), a Health Information Network that is 
a U.S. Entity that has been Designated by the RCE and is a party to 
the Common Agreement countersigned by the RCE.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf
    \1408\ In August 2019, ONC awarded a cooperative agreement to 
The Sequoia Project to serve as the initial RCE. The RCE will 
operationalize and enforce the Common Agreement, oversee QHIN-
facilitated network operations, and ensure compliance by 
participating QHINs. The RCE will also engage stakeholders to create 
a roadmap for expanding interoperability over time. https://sequoiaproject.org/onc-awards-the-sequoia-project-a-cooperative-agreement-for-the-trusted-exchange-framework-and-common-agreement-to-support-advancing-nationwide-interoperability-of-electronic-health-information/.
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    The technical and policy architecture of how exchange occurs under 
TEFCA follows a network-of-networks structure, which allows for 
connections at different levels and is inclusive of many different 
types of entities at different levels, such as health information 
networks, care practices, hospitals, public health agencies, and 
Individual Access Services (IAS) \1409\ Providers.\1410\ QHINs connect 
directly to each other to facilitate nationwide interoperability, and 
each QHIN can connect Participants, which can connect 
Subparticipants.\1411\ Compared to most nationwide exchange today, the 
Common Agreement includes an expanded set of Exchange Purposes beyond 
Treatment to include Individual Access Services, Payment, Health Care 
Operations, Public Health, and Government Benefits Determination 
\1412\--all built upon common technical and policy requirements to meet 
key needs of the U.S. health care system.\1413\ This

[[Page 28584]]

flexible structure allows stakeholders to participate in the way that 
makes the most sense for them, while supporting simplified, seamless 
exchange.
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    \1409\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' See Common Agreement 
for Nationwide Health Information Interoperability Version 1, at 7 
(Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1410\ The Common Agreement defines ``IAS Provider'' as: ``Each 
QHIN, Participant, and Subparticipant that offers Individual Access 
Services.'' See Common Agreement for Nationwide Health Information 
Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1411\ For the Common Agreement definitions of QHIN, 
Participant, and Subparticipant, see Common Agreement for Nationwide 
Health Information Interoperability Version 1, at 8-12 (Jan. 2022), 
https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1412\ For the Common Agreement definitions of Payment, Health 
Care Operations, Public Health, and Government Benefits 
Determination, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6-10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1413\ Exchange Purpose(s): means the reason, as authorized by 
[the] Common Agreement including the Exchange Purposes SOP, for a 
Request, Use, Disclosure, or Response transmitted via QHIN-to-QHIN 
exchange as one step in the transmission. Authorized Exchange 
Purposes are: Treatment, Payment, Health Care Operations, Public 
Health, Government Benefits Determination, Individual Access 
Services, and any other purpose authorized as an Exchange Purpose by 
the Exchange Purposes SOP, each to the extent permitted under 
Applicable Law, under all applicable provisions of [the] Common 
Agreement, and, if applicable, under the implementation SOP for the 
applicable Exchange Purpose. Definitions for each of these exchange 
purposes can be found in the Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    The QTF,\1414\ which was developed and released by the RCE, 
describes the functional and technical requirements that a Health 
Information Network (HIN) \1415\ must fulfill to serve as a QHIN under 
the Common Agreement. The QTF specifies the technical underpinnings for 
QHIN-to-QHIN exchange and certain other responsibilities described in 
the Common Agreement. The technical and functional requirements 
described in the QTF enable information exchange modalities, including 
querying and message delivery across participating entities.
---------------------------------------------------------------------------

    \1414\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \1415\ ``Health Information Network'' under TEFCA has the 
meaning assigned to the term ``Health Information Network or Health 
Information Exchange'' in the information blocking regulations at 45 
CFR 171.102.
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    In general, the information to be exchanged within the TEFCA 
ecosystem allows for the use of the Health Level Seven (HL7[supreg]) 
Implementation Guide for Clinical Document Architecture (CDA[supreg]) 
Release 2: Consolidated CDA Templates for Clinical Notes (US Realm) 
Draft Standard for Trial Use Release 2.1 (C-CDA 2.1) document format, 
including data defined as part of U.S. Core Data for Interoperability 
(USCDI), with allowance for flexibility to further expand the content 
to support a multitude of use cases.\1416\ The Common Agreement and the 
QTF do not require HL7[supreg] Fast Healthcare Interoperability 
Resource (FHIR[supreg]) based exchange. TEFCA allows for the optional 
exchange of FHIR content using more traditional, established standards 
to enable the transport of that content. However, TEFCA can nonetheless 
be a strong catalyst for network enablement of FHIR maturation. To that 
end, the RCE released a three-year FHIR Roadmap for TEFCA Exchange, 
which lays out a deliberate strategy to add FHIR-based exchange under 
TEFCA in the near future.\1417\
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    \1416\ User's Guide to the Trusted Exchange Framework and Common 
Agreement--TEFCA (Jan 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/Common-Agreement-Users-Guide.pdf.
    \1417\ FHIR[supreg] Roadmap for TEFCA Exchange Version 1 (Jan. 
2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/FHIR-Roadmap-v1.0_updated.pdf.
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c. Proposed New Enabling Exchange Under TEFCA Measure
    In 2022, prospective QHINs are anticipated to begin signing the 
Common Agreement and applying for designation. The RCE will then begin 
onboarding and designating QHINs to share information. In 2023, HHS 
expects stakeholders across the care continuum to have increasing 
opportunities to enable exchange under TEFCA. Specifically, this would 
mean such stakeholders would be: (1) Signatories to either the Common 
Agreement or an agreement that meets the flow-down requirements of the 
Common Agreement (called a Framework Agreement \1418\ under the Common 
Agreement), (2) in good standing (that is not suspended) under that 
agreement, and (3) enabling secure, bi-directional exchange of 
information to occur, in production. TEFCA is expected to give 
individuals and entities easier, more efficient access to more health 
information. The Common Agreement will require strong privacy and 
security protections for all entities who elect to participate, 
including entities not covered by the Health Insurance Portability and 
Accountability Act (HIPAA).\1419\
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    \1418\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1419\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    By connecting to an entity that connects to a QHIN or connecting 
directly to a QHIN, an eligible hospital or CAH can share health 
information in the same manner as described in the attestation 
statements previously finalized for the HIE Bi-Directional Exchange 
measure (42 CFR 495.24(e)(6)(ii)(C)). By connecting to an entity that 
connects to a QHIN, or connecting directly to a QHIN, that supports 
sharing information on patients as part of a Framework Agreement,\1420\ 
an eligible hospital or CAH would be thereby enabling bi-directional 
exchange with other providers as described in Statement 1 of the HIE 
Bi-Directional Exchange measure. Since participation in a Framework 
Agreement as a QHIN, Participant, or Sub-participant will be open to 
all qualifying entities and will not be restricted by use of a single 
vendor, a connection via a Framework Agreement would also satisfy the 
requirements of Statement 2 of the HIE Bi-Directional Exchange measure. 
Finally, as discussed above, the technical requirements for exchanging 
information by entities through the Common Agreement and Framework 
Agreements utilize standards included in certified technology 
referenced under the CEHRT definition (see 42 CFR 495.4), including the 
ability to exchange and receive data using the C-CDA standard (see 
certification criteria at 45 CFR 170.315(b)(1) and (2)), thus providers 
participating in a Framework Agreement can use the functions of CEHRT 
to support bi-directional exchange with an HIE.
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    \1420\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    To offer health care providers more opportunities to earn credit 
for the Health Information Exchange Objective, and given the alignment 
between enabling exchange under TEFCA and the existing HIE Bi-
Directional Exchange measure, we are proposing to add an additional 
measure through which an eligible hospital or CAH could earn credit for 
the Health Information Exchange Objective by connecting to an entity 
that connects to a QHIN or connecting directly to a QHIN. Specifically, 
we are proposing to add the following new measure to the Health 
Information Exchange Objective beginning with the EHR reporting period 
in CY 2023: Enabling Exchange Under TEFCA measure. We propose eligible 
hospitals and CAHs would have three reporting options for the Health 
Information Exchange Objective: (1) Report 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, (2) report on the HIE Bi-Directional Exchange 
measure, or (3) report on the proposed Enabling Exchange Under TEFCA 
measure.
    We propose the Enabling Exchange Under TEFCA measure would be worth 
the total amount of points available for the Health Information 
Exchange Objective. Under the current scoring methodology finalized in 
the FY 2022 IPPS/LTCH PPS final rule, the Health

[[Page 28585]]

Information Exchange Objective is worth a total of 40 points (86 FR 
45466). We note in section IX.H.6. of this proposed rule, we are 
proposing changes to the scoring methodology beginning with the EHR 
reporting period in CY 2023 such that the Health Information Exchange 
Objective would be worth no more than 30 points. Therefore, under our 
proposal, the proposed Enabling Exchange Under TEFCA measure would be 
worth 30 points. We are proposing this change to the scoring 
methodology as a result of our proposal in section IX.H.3.c.(2) of this 
proposed rule to make the Query of PDMP measure required and worth 10 
points. However, should we not finalize the Query of PDMP measure 
proposal, we propose the Enabling Exchange Under TEFCA measure would be 
worth 40 points (the current total point value of the Health 
Information Exchange Objective). In no case could more than 40 points 
total be earned for the Health Information Exchange Objective. In 
section IX.H.8. of this proposed rule, we are proposing to remove text 
for the objectives and measures from paragraph (e) under 42 CFR 495.24 
beginning in CY 2023. If we do not finalize that proposal, we would 
revise 42 CFR 495.24(e) to reflect the addition of the proposed 
Enabling Exchange Under TEFCA measure.
    We believe the new measure for enabling exchange under TEFCA that 
we are proposing would incentivize eligible hospitals and CAHs to 
exchange information by connecting directly or indirectly to a QHIN and 
support health information exchange at a national level. We believe 
that fulfillment of this measure is an extremely high value action. The 
overall TEFCA goal of establishing a universal floor of 
interoperability across the country aligns with our commitment to 
promoting and prioritizing interoperability and exchange of healthcare 
data. Incentivizing providers to enable exchange under TEFCA is a 
critical component to advancing healthcare data exchange nationwide. We 
are proposing eligible hospitals and CAHs would report the Enabling 
Exchange Under TEFCA measure by attestation, and the measure would 
require a ``yes/no'' response. A ``yes'' response would enable eligible 
hospitals and CAHs to earn the proposed 30 points allotted to the 
Health Information Exchange Objective. Further, we propose this measure 
may be calculated by reviewing only the actions for patients whose 
records are maintained using CEHRT. A patient's record is maintained 
using CEHRT if sufficient data were entered in the CEHRT to allow the 
record to be saved, and not rejected due to incomplete data.
    We propose that eligible hospitals and CAHs would attest to the 
following:
     Participating as a signatory to a Framework Agreement (as 
that term is defined by the Common Agreement for Nationwide Health 
Information Interoperability as published in the Federal Register and 
on ONC's website) (in good standing that is not suspended) and enabling 
secure, bi-directional exchange of information to occur, in production, 
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.
     Using the functions of CEHRT to support bi-directional 
exchange of patient information, in production, under this Framework 
Agreement.
    Similar to the HIE Bi-Directional Exchange measure, to successfully 
attest to this measure, we propose the eligible hospital or CAH must 
use the capabilities of CEHRT to support bi-directional exchange under 
a Framework Agreement, which includes capabilities that 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 other measures under the Health Information 
Exchange Objective, which point to the use of CEHRT to support the 
exchange of the clinical data within the CCDS or the USCDI.
    We believe there are numerous certified health IT capabilities that 
can support bi-directional exchange under a Framework Agreement. For 
instance, participants may exchange information under a Framework 
Agreement by using technology certified to the criterion at 45 CFR 
170.315(b)(1), ``Care coordination--Transitions of care,'' to transmit 
C-CDAs across a network. Where supported, participants could also 
utilize API technology certified to either the criterion at 45 CFR 
170.315(g)(8), ``Design and performance--Application access--data 
category request,'' or (g)(10), ``Design and performance--Standardized 
API for patient and population services,'' as finalized in the ONC 21st 
Century Cures Act final rule (85 FR 25742), to enable exchange of data 
in the CCDS or USCDI from a participant's EHR. Additional certified 
health IT modules may also support exchange of information under a 
Framework Agreement for transitions of care, including modules 
certified to certification criteria at 45 CFR 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 45 
CFR 170.315(e)(1), ``Patient engagement--View, download, and transmit 
to 3rd party,'' which supports patient access to their information; and 
the certification criterion at 45 CFR 170.315(g)(6), ``Design and 
performance--Consolidated CDA creation performance,'' which supports 
creation of a summary of care record. We recognize that entities that 
will connect directly or indirectly to a QHIN are currently interacting 
with health care providers using certified health IT in a variety of 
ways, and, as with the Bi-directional HIE Exchange measure, believe 
that we should allow for substantial flexibility in how health care 
providers use certified health IT to exchange data under a Framework 
Agreement.
    The Enabling Exchange Under TEFCA measure could offer health care 
providers an alternative to earn credit for the Health Information 
Exchange Objective. The Enabling Exchange Under TEFCA measure would not 
require an eligible hospital or CAH to assess whether they participate 
in a health information exchange that meets the attributes of 
attestation Statement 2 under the HIE Bi-Directional Exchange measure 
regarding exchange across a broad network of unaffiliated exchange 
partners including those using disparate EHRs. These attributes are key 
to the goals of TEFCA, which aims to offer providers a uniform set of 
expectations around information sharing regardless of which network for 
information exchange they participate in.
    We are inviting public comment on these proposals.
5. Public Health and Clinical Data Exchange Objective
a. Background
    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. 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

[[Page 28586]]

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.
    There are six measures under the Public Health and Clinical Data 
Exchange Objective: Immunization Registry Reporting, Syndromic 
Surveillance Reporting, Electronic Case Reporting, Electronic 
Reportable Laboratory (ELR) Result Reporting, Public Health Registry 
Reporting, and Clinical Data Registry Reporting. For background on this 
objective and its associated measures, we refer readers to the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41665 through 41667), and the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45470 through 45479). In the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45470 through 45479), we finalized the 
requirement for eligible hospitals and CAHs to report four of the six 
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. These four measures will 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 will 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.
b. Proposed Modifications to the Reporting Requirements for the Public 
Health and Clinical Data Exchange Objective: Antimicrobial Use and 
Resistance (AUR) Surveillance Measure
    Antimicrobial-resistant (AR) infections are caused by pathogens 
that no longer respond to the drugs designed to kill them and directly 
threaten patient and population health. An effective national response 
to the threat presented by antimicrobial resistant bacteria requires 
robust systems for systematically collecting, analyzing, and using 
antimicrobial use and resistance data to direct action.
    Each year in the United States, more than three million people are 
infected by an antimicrobial-resistant pathogen or C. difficile (an 
opportunistic pathogen associated with antimicrobial use), and nearly 
50,000 people die.\1421\ As more pathogens become resistant to 
available antimicrobials, options for reliably and rapidly treating 
infections--including pneumonias, foodborne illnesses, and healthcare-
associated infections--become increasingly limited, more expensive and, 
in some cases, nonexistent. The CDC has found that one-third to one-
half of all antimicrobials used in inpatient and outpatient settings 
are either unnecessary or prescribed incorrectly.\1422\ The misuse and 
overuse of antimicrobials both facilitates the emergence of drug-
resistant pathogens and exposes patients to needless risk for adverse 
effects. AR infections can also complicate the response to and recovery 
from other serious health risks, such as COVID-19. Rates of AR 
infections have increased in healthcare settings since the beginning of 
the COVID-19 pandemic, reversing previous prevention successes such as 
declines of AR infections by as much as 30 percent prior to the 
pandemic.\1423\ Additionally, Methicillin-resistant Staphylococcus 
aureus (MRSA) infections increased five consecutive quarters from 2020 
to 2021, including some quarter over quarter increases of 39 
percent.\1424\ Strengthening of infection prevention and control and 
antibiotic stewardship is needed to address these challenges and ensure 
a solid foundation for future public health emergencies.
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    \1421\ CDC. Antibiotic Resistance Threats in the United States, 
2019. Atlanta, GA: U.S. Department of Health and Human Services, 
CDC; 2019.
    \1422\ CDC. Antibiotic Use in the United States, 2018 Update: 
Progress and Opportunities. Atlanta, GA: U.S. Department of Health 
and Human Services, CDC; 2019.
    \1423\ CDC. 2020 National and State Healthcare-Associated 
Infections Progress Report. Atlanta, GA: U.S. Department of Health 
and Human Services, CDC; 2021.
    \1424\ Weiner-Lastinger, Lindsey M., et al. ``The Impact of 
Coronavirus Disease 2019 (COVID-19) on Healthcare-Associated 
Infections in 2020: A Summary of Data Reported to the National 
Healthcare Safety Network.'' Infection Control & Hospital 
Epidemiology, vol. 43, no. 1, 2022, pp. 12-25., doi:10.1017/
ice.2021.362.
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    As outlined in the National Action Plan for Combating Antibiotic-
Resistant Bacteria (CARB), 2020-2025,\1425\ an effective national 
response to the threat presented by AR bacteria and fungi depends in 
part on slowing the emergence of new resistant threats and preventing 
the spread of existing resistant infections. Successfully meeting this 
goal, in turn, requires robust systems for collecting, analyzing, and 
using AUR data to direct action. Systematically collecting AUR data 
also helps inform the availability and potential need for new 
antibiotics to address emerging forms of resistance.
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    \1425\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE). (2020). National Action Plan for Combatting 
Antibiotic-Resistant Bacteria, 2020-2025. Available at: https://aspe.hhs.gov/reports/national-action-plan-combating-antibiotic-resistant-bacteria-2020-2025.
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    Antimicrobial use (AU) data delivered to antimicrobial stewardship 
programs (ASPs) enable stewards to develop, select, and assess 
interventions aimed at optimizing antimicrobial prescribing. These 
interventions, in turn, serve to improve antimicrobial treatment 
effectiveness, protect patients from harms caused by unnecessary 
antimicrobial exposure, and curb antimicrobial resistance associated 
with prophylactic and therapeutic excess. Studies have shown that ASPs 
can help slow the emergence of antimicrobial resistance while 
optimizing treatment and minimizing costs--all in support of safe and 
appropriate care for patients.
    Antimicrobial resistance data can aid in clinical decision making 
(hospital cumulative antibiograms) and direct transmission prevention 
and antimicrobial stewardship efforts. With timely and complete 
reporting, these data can also facilitate rapid identification and 
control of potential outbreaks, as well as longer term assessment of 
progression or improvement to guide public health response efforts. 
Currently, acute care hospitals and CAHs voluntarily report to CDC's 
National Healthcare Safety Network's (NHSN) AUR Module with 
approximately 2000 eligible hospitals and 1000 CAHS reporting on AUR 
NHSN. Compared to the hospitals that have not reported AUR data, those 
that reported were more likely to be larger and teaching hospitals.
    The extensive voluntary participation in NHSN's AUR surveillance, 
which calls for hospitals to buy or build an AUR reporting solution, 
indicates that thousands of hospitals see value in NHSN's AUR 
surveillance. However, incomplete participation in NHSN's AUR 
surveillance limits the generalizability of the AUR data: The data is 
subject to selection bias and do not provide a comprehensive national 
picture. Other comparable NHSN reporting pathways--such as those used 
to report data on blood stream infections, urinary tract infections, 
and other healthcare-associated infections--are required under CMS 
quality reporting and value-based payment programs, including the 
Hospital Value-Based Purchasing (VBP) and Hospital-Acquired Condition 
(HAC) Reduction Programs. In the Hospital VBP and HAC Reduction 
Programs, the reporting coverage and compliance with NHSN measures is 
routinely approximately 97 percent. The benefits of monitoring

[[Page 28587]]

AUR data for patient care and public health are most likely to be 
achieved when data collection and analysis are systematic, 
standardized, and achieve complete coverage across eligible facilities. 
In fact, as more hospitals participate, the system becomes better at 
detecting emerging threats as the network for data collection grows.
    We believe that requiring an AUR measure under the Medicare 
Promoting Interoperability Program would enable the development of a 
true national picture of the threat posed by antimicrobial overuse and 
resistance. Requiring AUR reporting through CDC's NHSN would produce 
inpatient AU and AR benchmarks that can be used to guide clinical and 
public health action and enable a true national picture of the threat 
posed by antimicrobial overuse and resistance. We are proposing the 
following new AUR Surveillance measure under the Public Health and 
Clinical Data Exchange Objective:
    AUR Surveillance measure: The eligible hospital or CAH is in active 
engagement with CDC's National Healthcare Safety Network (NHSN) to 
submit antimicrobial use and resistance (AUR) data for the EHR 
reporting period and receives a report from NHSN indicating their 
successful submission of AUR data for the EHR reporting period.
    We are proposing to require eligible hospitals and CAHs to report 
this measure beginning with the EHR reporting period in CY 2023. 
Eligible hospitals and CAHs that report a ``yes'' response or an 
exclusion for which they are eligible would receive credit for 
reporting the measure. Eligible hospitals and CAHs that report a ``no'' 
response or fail to report any response would not receive credit for 
reporting the measure and would fail to satisfy the Public Health and 
Clinical Data Exchange Objective. No additional points would be 
associated with the reporting of this measure, but it would be one of 
five required measures required to satisfy the Public Health and 
Clinical Data Exchange Objective. See section IX.H.6. for our proposal 
to modify the scoring of this objective.
    For purposes of this proposed measure, we are proposing eligible 
hospitals and CAHs must use technology certified to the criterion at 45 
CFR 170.315(f)(6), ``Transmission to public health agencies--
antimicrobial use and resistance reporting.'' We are also aware of an 
updated version of this specification \1426\ and will work with our 
partners at CDC and ONC to consider avenues for addressing use of this 
specification within the ONC Health IT Certification program.
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    \1426\ https://www.hl7.org/implement/standards/product_brief.cfm?product_id=426.
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    We are proposing three exclusions for the AUR Surveillance measure 
as follows: the eligible hospital or CAH: (1) Does not have any 
patients in any patient care location for which data are collected by 
NHSN during the EHR reporting period; (2) Does not have electronic 
medication administration records (eMAR)/barcoded medication 
administration (BCMA) records or an electronic admission discharge 
transfer (ADT) system during the EHR reporting period; or (3) Does not 
have an electronic laboratory information system (LIS) or electronic 
ADT system during the EHR reporting period. We anticipate reevaluating 
exclusions #2 and #3 for future EHR reporting periods. The AUR 
Surveillance measure would leverage the standards and functionality 
included in certified technology referenced under the CEHRT definition, 
including the ability to transmit to public health agencies for 
antimicrobial use and resistance reporting.
    Further, we propose this measure must be calculated by reviewing 
all patient records, not just those whose records are maintained using 
CEHRT.
    We are inviting public comment on these proposals. We also invite 
comments on the feasibility of the timeline and any additional 
exclusions that we should consider for this measure for proposal in 
future rulemaking.
c. Proposed Revisions to Active Engagement
(1) Background
    The Medicare Promoting Interoperability Program has been an 
important mechanism for encouraging data exchange between healthcare 
providers and public health agencies through the Public Health and 
Clinical Data Exchange Objective. In the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45471 through 45479), we finalized beginning with the EHR 
reporting period in CY 2022, eligible hospitals and CAHs must report on 
the four required measures to obtain points under the Public Health and 
Clinical Data Exchange Objective: (1) Syndromic Surveillance Reporting; 
(2) Immunization Registry Reporting; (3) Electronic Case Reporting; 
and, (4) Electronic Reportable Laboratory Result Reporting. We believe 
these required measures will motivate electronic health record vendors 
to implement the necessary capabilities in their products and encourage 
eligible hospitals and CAHs to engage in the reporting activities 
described in the measures.
    Despite these gains, ensuring the nation's thousands of hospitals 
implement and initiate data production for these vital public health 
capabilities remains an ongoing and important effort. The Medicare 
Promoting Interoperability Program provides an opportunity to continue 
strengthening the incentives for eligible hospitals and CAHs to engage 
in these essential reporting activities. Without adequate incentives, 
it will be difficult to attain the comprehensive data exchange needed 
to ensure fast, complete, actionable data in response to future public 
health threats.
    In the EHR Incentive Program Stage 3 final rule (80 FR 62862 
through 62864), beginning with the EHR reporting period in 2016, we 
established a definition for active engagement under the Public Health 
and Clinical Data Registry Reporting Objective. Active engagement is 
defined as when an eligible hospital or CAH is in the process of moving 
towards sending ``production data'' to a public health agency or 
clinical data registry, or is sending production data to a public 
health agency or clinical data registry. We noted that the term 
``production data'' refers to data generated through clinical processes 
involving patient care and it is used to distinguish between this data 
and ``test data'' which may be submitted for the purposes of enrolling 
in and testing electronic data transfers. We established the following 
three options for eligible hospitals and CAHs to demonstrate active 
engagement:
    Option 1--Completed registration to submit data: The eligible 
hospital or CAH registered to submit data with the PHA or, where 
applicable, the clinical data registry (CDR) to which the information 
is being submitted; registration was completed within 60 days after the 
start of the EHR reporting period; and the eligible hospital or CAH is 
awaiting an invitation from the PHA or CDR to begin testing and 
validation. Eligible hospitals or CAHs that have registered in previous 
years do not need to submit an additional registration to meet this 
requirement for each EHR reporting period.
    Option 2--Testing and validation: The eligible hospital or CAH is 
in the process of testing and validation of the electronic submission 
of data. Eligible hospitals or CAHs must respond to requests from the 
PHA or, where applicable, the CDR within 30 days; failure to respond 
twice within an EHR reporting period would result in that provider not 
meeting the measure.
    Option 3--Production: The eligible hospital or CAH has completed 
testing and validation of the electronic

[[Page 28588]]

submission and is electronically submitting production data to the PHA 
or CDR.
    For more information about the current options for active 
engagement, we refer readers to the EHR Incentive Program Stage 3 final 
rule (80 FR 62862 through 62864).
(2) Proposed Revision to Options for Active Engagement
    The three active engagement options provided flexibility for 
eligible hospitals and CAHs to meet the measures under the Public 
Health and Clinical Data Exchange Objective in a variety of ways, but 
they did not provide an incentive to move through the options and get 
to option 3, production, where there is the ongoing electronic 
submission of data. Option 1, completed registration to submit data, 
was an important option in 2016 as many PHAs and CDRs were starting to 
come online, and thus the provision of this option recognized that many 
eligible hospitals and CAHs were just beginning to engage in electronic 
data exchange with PHAs and CDRs. Now many years have passed, and we 
believe that eligible hospitals and CAHs have had ample time to 
complete option 1.
    Thus, we propose to consolidate current options 1 and 2 into one 
option beginning with the EHR reporting period in CY 2023. We are not 
proposing any substantive changes to the individual options or 
requirements for selecting the individual options; rather, we would 
combine current options 1 and 2 into a single option, as follows:
    1. Proposed Option 1. Pre-production and Validation (a combination 
of current option 1, completed registration to submit data, and current 
option 2, testing and validation);
    2. Proposed Option 2. Validated Data Production (current option 3, 
production).
    Eligible hospitals and CAHs must demonstrate their level of active 
engagement as either proposed Option 1 (pre-production and validation) 
or proposed Option 2 (validated data production) to fulfill each 
measure. We are inviting public comment on these proposed changes to 
the options for active engagement.
(3) Proposed Reporting Requirement for Level of Engagement
    Although we established the active engagement options, eligible 
hospitals and CAHs currently are not required to report their level of 
active engagement for any of the measures associated with the Public 
Health and Clinical Data Exchange Objective. During the recent COVID-19 
PHE, we recognized the importance of public health reporting (as 
discussed further in section IX.H.5. of this proposed rule), and we 
believe that knowing the level of active engagement that an eligible 
hospital or CAH selects would provide information on the types of 
registries and geographic areas with health care providers in the Pre-
production and Validation stage. Our goal is for all health care 
providers nationwide to be at the Validated Data Production stage so 
that data will be actively flowing and public health threats can be 
monitored. Therefore, for the Public Health and Clinical Data Exchange 
Objective, in addition to submitting responses for the required 
measures and any optional measures a hospital chooses to report, we 
propose to require eligible hospitals and CAHs to submit their level of 
active engagement, either Pre-production and Validation or Validated 
Data Production (as proposed in section IX.H.5.c.(2)), for each measure 
they report beginning with the EHR reporting period in CY 2023. If our 
proposal to reduce the three current options of active engagement to 
two options is not finalized, we propose to require eligible hospitals 
and CAHs to submit one of the three current options of active 
engagement for each measure they report. We believe that this 
information regarding the level of active engagement would be helpful 
as it would enable HHS to identify registries and PHAs which may be 
having difficulty onboarding eligible hospitals and CAHs and moving 
them to the Validated Data Production phase. If we can identify these 
hospitals we believe we will be able to identify the barriers that 
prevent them from moving to the Validated Data Production stage and 
work to develop solutions to overcome the barriers.
    We are inviting public comment on the proposal to require 
submission of the level of active engagement.
(4) Proposed Changes to the Duration of Active Engagement Options
    As discussed in section IX.H.5.c.(3), eligible hospitals and CAHs 
currently are not required to report their level of active engagement, 
or advance from one option to the next option within a certain period 
of time. As we are now proposing to require eligible hospitals and CAHs 
to submit their level of active engagement for each measure they 
report, we are also proposing, beginning with the EHR reporting period 
in CY 2023, that eligible hospitals and CAHs may spend only one EHR 
reporting period at the Pre-production and Validation level of active 
engagement per measure, and that they must progress to the Validated 
Data Production level for the next EHR reporting period for which they 
report a particular measure. For example, under this proposal, if an 
eligible hospital or CAH submits a level of active engagement at the 
proposed option 1 (Pre-production and Validation phase) for the 
Syndromic Surveillance Reporting measure for the EHR reporting period 
in CY 2023, the hospital must report a level of active engagement at 
the proposed option 2 (Validated Data Production phase) for the next 
EHR reporting period for which it reports the Syndromic Surveillance 
Reporting measure, or it would fail to satisfy the Public Health and 
Clinical Data Exchange Objective for its next EHR reporting period. The 
options for active engagement assume the same PHA or CDR is used by the 
hospital. In the event an eligible hospital or CAH chooses to switch 
between one or more CDRs or PHAs, we are proposing they would be 
permitted to spend an additional EHR reporting period at the Pre-
production and Validation phase to assist with onboarding to the new 
CDR or PHA. As electronic transmission of high-quality data is achieved 
at the Validated Data Production phase, we want all eligible hospitals 
and CAHs to reach this level.
    We are inviting public comments on these proposed changes to the 
duration of the active engagement options.
(5) Public Health Reporting and Information Blocking
    The ONC 21st Century Cures Act final rule (85 FR 25642) implemented 
policies related to information blocking as authorized under section 
4004 of the 21st Century Cures Act. The ONC 21st Century Cures Act 
final rule established a regulatory definition of information blocking, 
under which information blocking is, in general, a practice by a health 
IT developer of certified health IT, health information network, health 
information exchange, or health care provider (actors \1427\) that, 
except as required by law or covered by an exception in 45 CFR part 
171, subpart B or C, is likely to interfere with (as defined in 45 CFR 
171.102) access, exchange, or use of EHI.1428 1429 For a

[[Page 28589]]

health care provider (as defined in 45 CFR 171.102), information 
blocking (see 45 CFR 171.103) means a practice--except as required by 
law or covered by an exception defined in 45 CFR part 171--that is 
likely to interfere with access, exchange, or use of EHI that the 
health care provider knows is unreasonable and is likely to interfere 
with access, exchange, or use of electronic health 
information.1430 1431
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    \1427\ Actor is defined in 45 CFR 171.102 as ``health care 
provider, health IT developer of certified health IT, health 
information network or health information exchange.''
    \1428\ For purposes of the definition of information blocking, 
for the period before October 6, 2022, electronic health information 
is defined in 45 CFR 171.103(b). As of that date, electronic health 
information will be defined as it is in 45 CFR 171.102.
    \1429\ In order for a practice to be considered information 
blocking, additional requirements at 45 CFR 171.103(a)(2) or (3) 
apply, depending on the type of actor engaging in the practice.
    \1430\ For other types of actors (health IT developers of 
certified health IT and health information networks or health 
information exchanges, 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.''
    \1431\ The exceptions to the definition of information blocking 
(practices that are required by law or covered by an exception in 45 
CFR part 171, subpart B or C) described in the previous sentence 
apply to this definition as well.
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    ONC recently released an information blocking frequently asked 
question (FAQ) (IB.FAQ43.1.2022FEB) that highlights important points 
about public health reporting and information blocking.\1432\ 
Specifically, if an actor is required to comply with another law that 
relates to the access, exchange, or use of EHI, failure to comply with 
that law may implicate the information blocking regulations. As an 
example, where a law requires actors to submit EHI to public health 
authorities, an actor's failure to submit EHI to public health 
authorities could be considered an interference under the information 
blocking regulations. For example, many states legally require 
reporting of certain diseases and conditions to detect outbreaks and 
reduce the spread of disease. Should an actor that is required to 
comply with such a law fail to report, the failure could be an 
interference with access, exchange, or use of EHI under the information 
blocking regulations. Practices would be evaluated to determine whether 
the unique facts and circumstances constitute information blocking, 
consistent with additional ONC frequently asked questions.\1433\
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    \1432\ See https://www.healthit.gov/curesrule/faq/would-not-complying-another-law-implicate-information-blocking-regulations.
    \1433\ See https://www.healthit.gov/curesrule/faq/how-would-any-claim-or-report-information-blocking-be-evaluated.
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6. Proposed Changes to Scoring Methodology for the EHR Reporting Period 
in CY 2023
    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 beginning with the CY 2019 EHR reporting 
period, which included a minimum scoring threshold of a total score of 
50 points or more which eligible hospitals and CAHs must meet to 
satisfy the requirement to report on the objectives and measures of 
meaningful use under 42 CFR 495.24. In the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45491 through 45492), we increased the minimum scoring 
threshold from 50 points to 60 points beginning with the EHR reporting 
period in CY 2022. As shown in Table IX.H.-03, the points associated 
with the required measures sum to 100 points, and the optional measures 
may add additional bonus points. The scores for each of the measures 
are added together to calculate a total score of up to 105 possible 
points for each eligible hospital or CAH (83 FR 41636 through 41645).
    Table IX.H.-03 reflects the objectives and measures for the EHR 
reporting period in CY 2022 and was included in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45492).
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[[Page 28590]]


    In this proposed rule, we are making various proposals that would 
affect the scoring of the objectives and measures for the EHR reporting 
period in CY 2023. In proposing to make the Query of PDMP measure 
required, we would retain the 10 points associated with it, which are 
allocated as bonus points for the EHR reporting period in CY 2022. To 
accommodate this change if our proposal is finalized, we are proposing 
to reduce the points associated with the Health Information Exchange 
Objective measures from the current 40 points to 30 points beginning 
with the CY 2023 EHR reporting period.
    The Public Health and Clinical Data Exchange Objective, with its 
current four required measures, is currently worth only 10 points. 
Despite increasing the number of required measures from two to four to 
make the objective more effective in promoting public health data 
electronic exchange, the total number of points did not change between 
CY 2021 and CY 2022. We believe that increasing the point value of the 
Public Health and Clinical Data Exchange Objective would create a more 
meaningful incentive for eligible hospitals and CAHs to engage in the 
electronic reporting of public health information and recognize the 
importance of public health systems affirmed by the COVID-19 pandemic. 
Increasing the point value would make the Public Health and Clinical 
Data Exchange Objective a more central piece of the Promoting 
Interoperability Program and better incentivize eligible hospitals and 
CAHs to implement these essential public health data exchange 
capabilities. Without adequate incentives, there remains a risk that 
eligible hospitals and CAHs will simply not prioritize implementing 
these capabilities, which are essential to ongoing efforts to address 
COVID-19 and will be indispensable for responding to future public 
health threats and emergencies. Increasing the point value would more 
appropriately incentivize eligible hospitals and CAHs to engage in the 
electronic reporting of public health information and would align the 
value of the objective with the objective's importance and the effort 
necessary to meet the required measures.
    Thus, we are proposing to increase the points allocated to the 
Public Health and Clinical Data Exchange Objective from 10 to 25 points 
to better align with the true value of this objective beginning with 
the CY 2023 EHR reporting period. This proposal is independent of our 
proposal to add the AUR Surveillance measure to this objective and we 
may finalize the point increase in this objective regardless of whether 
the proposal to add the AUR Surveillance measure to the objective is 
finalized. We believe assigning 25 points to the objective reflects the 
importance of comprehensive, nationwide health care data exchange 
between eligible hospitals and CAHs and public health agencies. 
Nationwide health care data exchange would provide immense value to the 
public by improving the speed and effectiveness of public health 
responses, as well as to eligible hospitals and CAHs, since better 
public health response reduces pressure on hospitals, which can be 
overwhelmed in a public health crisis. To balance the increase in the 
points associated with the Public Health and Clinical Data Exchange 
Objective, we are proposing to reduce the points associated with the 
Provide Patients Electronic Access to Their Health Information measure 
from the current 40 points to 25 points beginning with the CY 2023 EHR 
reporting period. We are inviting public comment on these proposed 
changes to our scoring methodology.
    Table IX.H.-04. reflects the objectives, measures, and maximum 
points available for the EHR reporting period in CY 2023 if the 
proposals discussed in section IX.H.3.c.(2), section IX.H.4.c., and 
section IX.H.5.b. are finalized.
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    The maximum points available in Table IX.H.-04. do not include the 
points that would be redistributed in the event an exclusion is 
claimed. For ease of reference, Table IX.H.-05. shows how points would 
be redistributed among the objectives and measures for the EHR 
reporting period in CY 2023 in the event an eligible hospital or CAH 
claims an exclusion, if the proposals discussed in this section are 
finalized.

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7. Proposed Public Reporting of Medicare Promoting Interoperability 
Program Data
    Section 1886(n)(4)(B) of the Act requires the Secretary to post in 
an easily understandable format a list of the names and other relevant 
data, as determined appropriate by the Secretary, of eligible hospitals 
and CAHs who are meaningful EHR users under the Medicare FFS program, 
on a CMS website. In addition, that section requires the Secretary to 
ensure that an eligible hospital or CAH has the opportunity to review 
the other relevant data that are to be made public with respect to the 
eligible hospital or CAH prior to such data being made public. As the 
Medicare Promoting Interoperability Program has evolved over the years, 
we have continued to expand the scope of relevant data points across 
the Medicare Promoting Interoperability Program to publicly report. For 
example, we post information on a CMS website available to the public 
regarding the attestations made by eligible hospitals and CAHs 
concerning actions to limit or restrict the compatibility or 
interoperability of CEHRT under 42 CFR 495.40(b)(2)(i)(I), as 
established in the 2020 Patient Access and Interoperability final rule 
(85 FR 25578 through 25580). Additionally, in alignment with the 
Hospital IQR Program and goals to encourage data accuracy and 
transparency, we finalized proposals to begin publicly reporting eCQM 
data required under the Medicare Promoting Interoperability Program 
beginning with the eCQM data reported by eligible hospitals and CAHs 
for the CY 2021 reporting period and for subsequent years (85 FR 58975 
through 58976).
    To date, we have not publicly reported eligible hospitals' and 
CAHs' total scores for the Medicare Promoting Interoperability Program. 
We have stated that we calculate a total score of up to 100 possible 
points by adding together the points earned for each required measure 
and any optional measures reported by an eligible hospital or CAH (83 
FR 41636 through 41645). However, we are now proposing to post the 
eligible hospital's or CAH's actual score up to 105 possible points so 
that consumers can clearly see the high performing hospitals. We 
believe the addition of the bonus points will be informative for 
consumers. We believe an eligible hospital's or CAH's total score for 
the Medicare Promoting Interoperability Program measures could 
constitute other relevant data because it would help consumers make 
informed decisions regarding their health care team, such as knowing 
whether and to what extent their health care provider is involved in 
health information exchange or providing patients with electronic 
access to their health information. We believe that publicly reporting 
additional Medicare Promoting Interoperability Program data 
demonstrates our commitment to providing data to patients, consumers, 
and providers to assist them in their decision-making; promoting 
enhanced health information exchange processes across eligible 
hospitals and CAHs; and continually aligning processes and policies 
with the Hospital IQR Program and the MIPS Promoting Interoperability 
performance category. For example, for the MIPS Promoting 
Interoperability performance category, individual measure scores and 
the total performance score across all measures reported by eligible 
clinicians are posted on a CMS website available to the public.
    Therefore, in alignment with our goals to encourage 
interoperability and transparency, we are proposing to publicly report 
certain Medicare Promoting Interoperability Program data submitted by 
eligible hospitals and

[[Page 28593]]

CAHs beginning with the EHR reporting period in CY 2023. Specifically, 
as a first step, we are proposing to publish on a CMS website available 
to the public the total score of up to 105 points for each eligible 
hospital and CAH, and the CMS EHR certification ID that represents the 
CEHRT used by the eligible hospital or CAH, beginning with the total 
scores and CMS EHR certification IDs for the EHR reporting period in CY 
2023. We are not proposing to publish individual measure scores at this 
time, but we will continue to evaluate that possibility for future 
rulemaking. For example, under our proposal, if an eligible hospital 
scored a total of 75 points for the EHR reporting period in CY 2023, we 
would publish the total score of 75 points and not the number of points 
earned for each individual measure within the total score. If our 
proposal is finalized, the total score and CMS EHR certification ID 
data could be made available to the public as early as the Fall of CY 
2024 or as soon as operationally feasible. In addition, as required by 
section 1886(n)(4)(B) of the Act, we are proposing that eligible 
hospitals and CAHs would have the opportunity to review their data that 
we would publish, during a 30-day preview period before the data are 
made public. We are proposing to follow our current policy and 
operational process that eligible hospitals are already familiar with 
for the Hospital IQR Program and use the Hospital Quality Reporting 
(HQR) system (formerly, the QualityNet Secure Portal) for eligible 
hospitals and CAHs to access and review their Medicare Promoting 
Interoperability Program data during a 30-day preview period before 
publication. We are proposing to post the Medicare Promoting 
Interoperability Program data using the Compare tool hosted by Health 
and Human Services currently available at https://www.medicare.gov/care-compare.
    We are inviting public comments on these proposals. Specifically, 
we are interested in comments that provide information on how these 
proposals might affect existing incentives and burdens under the 
Medicare Promoting Interoperability Program, as well as the benefit and 
utility of such data being publicly available. We are also seeking 
comments on which Medicare Promoting Interoperability Program data 
points to publish in future years, including specific objectives or 
measure performance rates.
8. Proposed Modifications and Additions to the Regulatory Text
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through 
41668), we finalized the objectives, measures, exclusion criteria, and 
scoring methodology for eligible hospitals and CAHs attesting under the 
Medicare Promoting Interoperability Program beginning with the EHR 
reporting period in CY 2019 and codified these policies in paragraph 
(e) under 42 CFR 495.24. We have updated the regulatory text to reflect 
policy changes in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42616), 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 59026), and the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45522).
    We note that historically, the objectives, measures, exclusion 
criteria, and associated scoring methodology for the Medicare Promoting 
Interoperability Program have been included in both the preamble and 
associated regulatory text under 42 CFR part 495 (see, for example, the 
Medicare and Medicaid EHR Incentive Programs Stage 1 final rule (75 FR 
44314)). We also note that many CMS quality reporting and performance-
based programs, including, but not limited to, the Hospital VBP 
Program, Hospital IQR Program, the End-Stage Renal Disease Quality 
Incentive Program (ESRD QIP), and Quality Payment Program/MIPS, do not 
include the text of the measures (also referred to as the measure 
specifications) adopted for those programs in the Code of Federal 
Regulations. Instead, the measure specifications generally are included 
in the rulemaking preamble or maintained by measure stewards outside of 
CMS and referenced in the preamble. For example, the specifications for 
the objectives and measures for the Promoting Interoperability 
performance category of MIPS are not included in the regulatory text 
for the program under 42 CFR part 414 and instead appear in the 
preamble only (for example, see CY 2022 PFS final rule (86 FR 65466 
through 65485)).
    We believe that aligning with the approach taken by other CMS 
programs to include measures only in the preamble would simplify the 
Medicare Promoting Interoperability Program and minimize confusion by 
ensuring consistency across similar CMS programs. We also believe 
taking this approach for the Medicare Promoting Interoperability 
Program would reduce burden on regulated parties, CMS, and the general 
public both during and outside of the rulemaking process. Ensuring the 
objectives and measures are described consistently in the preamble and 
regulation text can involve significant effort in terms of time and 
resources, and inconsistency has the potential to create confusion for 
regulated parties and the general public. For these reasons, we are 
proposing to remove the text of the objectives and measures for the 
Medicare Promoting Interoperability Program from paragraph (e) under 42 
CFR 495.24 beginning in CY 2023. We note that this proposal does not 
include any changes in policy for the Medicare Promoting 
Interoperability Program, including changes to the objectives and 
measures. We refer readers to section IX.H.3., section IX.H.4., and 
section IX.H.5. of this proposed rule for proposed changes in policy 
related to the objectives and measures. We also emphasize that this 
proposal does not change our view that the objectives and measures are 
rules intended to bind regulated parties, nor does it change our 
intention to enforce the objectives and measures. Specifically, we are 
proposing to modify the introductory paragraph to 42 CFR 495.24 and 
paragraph (e) and to establish a new paragraph (f) under 42 CFR 495.24 
as described in Table IX.H.-06. In the event these proposals are not 
finalized, we would update the regulatory text to reflect any policy 
changes to the objectives and measures for the Medicare Promoting 
Interoperability Program in the final rule. We refer readers to Table 
IX.H.-06 for detailed information on these proposed changes and for 
information on the paragraphs we are proposing to modify due to the 
proposed changes to regulatory text.
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    We are inviting public comment on our proposed modifications and 
additions to the regulatory text at 42 CFR 495.24 beginning in CY 2023.
9. Overview of Objectives and Measures for the Medicare Promoting 
Interoperability Program for the EHR Reporting Period in CY 2023
    For ease of reference, Table IX.H.-07. lists the objectives and 
measures for the Medicare Promoting Interoperability Program for the 
EHR reporting period in CY 2023 as revised to reflect the proposals 
made in this proposed rule. Due to our proposed modifications to the 
regulatory text at 42 CFR 495.24(e) (described in section IX.H.8. of 
the preamble of this proposed rule), we are adding a column to Table 
IX.H.-07. indicating whether the measure may be calculated by reviewing 
only the actions for patients whose records are maintained using CEHRT 
or must be calculated by reviewing all patient records, which is 
intended to reflect the policy codified at 42 CFR 495.24(e)(3). Table 
IX.H.-08. lists the 2015 Edition certification criteria required to 
meet the objectives and measures.

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10. 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 selected by 
CMS using CEHRT (also referred to as electronic clinical quality 
measures, or eCQMs), as part of being a meaningful EHR user under the 
Medicare Promoting Interoperability Program.
    Tables IX.H.-09. through IX.H.-11. summarize the previously 
finalized eCQMs available for eligible hospitals and CAHs to report 
under the Medicare Promoting Interoperability Program for the CY 2022 
reporting period, the CY 2023 reporting period, and the CY 2024 
reporting period and subsequent years (86 FR 45496 through 45497). The 
tables include the Safe Use of Opioids--Concurrent Prescribing measure 
(NQF #3316e), which we finalized as mandatory for reporting beginning 
with the CY 2022 reporting period (84 FR 42598 through 42600).

[[Page 28608]]

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(2) Proposed eCQM Adoptions
    As we have stated previously in rulemaking (82 FR 38479), we intend 
to continue to align the eCQM reporting requirements for the Promoting 
Interoperability Program with similar requirements under the Hospital 
IQR Program to the extent feasible. Section 1886(n)(3)(B)(i)(I) of the 
Act provides in part that in selecting clinical quality measures for 
the Promoting Interoperability Program, the Secretary shall provide 
preference to such measures that have been selected for purposes of the 
Hospital IQR Program (section 1886(b)(3)(B)(viii) of the Act). In 
addition, section 1886(n)(3)(B)(iii) of the Act provides that in 
selecting clinical quality measures for the Promoting Interoperability 
Program, and in establishing the form and manner for reporting, the 
Secretary shall seek to avoid redundant or duplicative reporting with 
reporting otherwise required, including reporting under the Hospital 
IQR Program. To minimize redundant or duplicative reporting, while 
maintaining a set of meaningful clinical quality measures that continue 
to incentivize improvement in the quality of care provided to patients, 
we are proposing to adopt four new eCQMs for the Medicare Promoting 
Interoperability Program in alignment with the Hospital IQR Program, as 
further discussed in this section of the proposed rule.
    In alignment with proposals for the Hospital IQR Program eCQM 
measure set, we are proposing two new eCQMs that address factors 
contributing to maternal mortality and morbidity, beginning with the CY 
2023 reporting period. Specifically, we are proposing to add the 
following eCQMs in the Medicare Promoting Interoperability Program eCQM 
measure set beginning with the CY 2023 reporting period: (1) Severe 
Obstetric Complications eCQM (NQF NA); and (2) Cesarean Birth eCQM (NQF 
NA). Table IX.H.-10 summarizes previously finalized and proposed eCQMs 
in the Medicare Promoting Interoperability Program for the CY 2023 
reporting period and subsequent years. We also are proposing to require 
mandatory reporting of the Severe Obstetric Complications eCQM and 
Cesarean Birth eCQM for the CY 2024 reporting period and for subsequent 
years. We refer readers to the discussion of the same proposals for the 
Hospital IQR Program in sections IX.E.5.d. and IX.E.5.c. of the 
preamble of this proposed rule for more information about these 
proposed measures and our policy reasons for proposing them.
    We are inviting public comments on these proposed measures for the 
Medicare Promoting Interoperability Program.
[GRAPHIC] [TIFF OMITTED] TP10MY22.296

    We also are proposing, in alignment with proposals for the Hospital 
IQR Program eCQM measure set, to adopt two new eCQMs on which hospitals 
can self-select to report for the CY 2024 reporting period and 
subsequent years that focus on opioid-related adverse events during an 
admission to an acute care hospital and on malnutrition. Specifically, 
we are proposing to add the following eCQMs to the Medicare Promoting 
Interoperability Program eCQM measure set on which hospitals can self-
select to report beginning with the CY 2024 reporting period: Hospital 
Harm-Opioid-Related Adverse Event eCQM (NQF #3501e) and Global 
Malnutrition Composite Score eCQM (NQF #3592e). Table IX.H.-11 
summarizes previously finalized and proposed eCQMs in the Medicare 
Promoting Interoperability Program for the CY 2024 reporting period and 
subsequent years. We refer readers to the discussion of the same 
proposals for the Hospital IQR Program in sections IX.E.5.e. and 
IX.E.5.f. of the preamble of this proposed rule for more information 
about these proposed measures and our policy reasons for proposing 
them.
    We are inviting public comments on these proposed measures for the

[[Page 28610]]

Medicare Promoting Interoperability Program.
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BILLING CODE 4120-01-C
b. Proposed eCQM Reporting and Submission Requirements for the CY 2024 
Reporting Period and Subsequent Years
    Consistent with our goal to align the eCQM reporting periods and 
criteria in the Medicare Promoting Interoperability Program and the 
Hospital IQR Program, we previously finalized the requirement that 
eligible hospitals and CAHs reporting eCQMs for the Medicare Promoting 
Interoperability Program must report four calendar quarters of data 
from CY 2023 and each subsequent year for: (a) Three self-selected 
eCQMs from the set of available eCQMs for CY 2023 and each subsequent 
year, and (b) the Safe Use of Opioids-Concurrent Prescribing eCQM (NQF 
#3316e), for a total of four eCQMs (85 FR 58975). We are not proposing 
to change the data reporting and submission requirements for the CY 
2023 reporting period.
    In this proposed rule, in alignment with proposals for the Hospital 
IQR Program, we are proposing to modify the eCQM reporting and 
submission requirements under the Medicare Promoting Interoperability 
Program for eligible hospitals and CAHs beginning with the CY 2024 
reporting period such that hospitals would be required to report four 
calendar quarters of data for each required eCQM: (1) Three self-
selected eCQMs; (2) the Safe Use of Opioids--Concurrent Prescribing 
eCQM; (3) the proposed Severe Obstetric Complications eCQM; and (4) the 
proposed Cesarean Birth eCQM, for a total of six eCQMs, beginning with 
the CY 2024 reporting period and for subsequent years. We note that the 
number of calendar quarters of data required and the number of self-
selected eCQMs would remain the same, but we are proposing to increase 
the number of eCQMs that all eligible hospitals and CAHs would be 
required to report from one to three. This proposal is made in 
conjunction with our proposals discussed in sections IX.D.10.e. of the 
preamble of this proposed rule, in which we are proposing to adopt the 
Severe Obstetric Complications eCQM and Cesarean Birth eCQM, 
respectively. We believe by 2024, eligible hospitals and CAHs will have 
had sufficient experience with eCQM reporting to propose an increase in 
the number of required eCQMs from four to six eCQMs. In addition, we 
believe in light of the maternal health crisis as described in sections 
IX.E.5.d.(1) and IX.E.5.c.(1) of this proposed rule, and our commitment 
to reducing unacceptably high maternal morbidity and mortality rates, 
it is important to collect and utilize quality measure data focused on 
maternal health to incentive improved quality of care.
    As detailed in sections IX.E.10.e. of the preamble of this proposed 
rule, we are proposing that if our proposals to adopt the Severe 
Obstetric Complications eCQM and the Cesarean Birth eCQM are finalized, 
these measures would be available for eligible hospitals and CAHs to 
select as one of their three self-selected eCQMs for the CY 2023 
reporting period, and then beginning with the CY 2024 reporting period, 
all eligible hospitals and CAHs would be required to report these two 
eCQMs. We refer readers to section IX.E.10.e of the preamble of this 
proposed rule for the reporting and submission requirements associated 
with the proposal to modify the eCQM reporting requirements for the 
Hospital IQR Program. We invite public comments on these proposed eCQM 
reporting requirements.
11. Patient Access to Health Information Measure--Request for 
Information (RFI)
    Patient use of portals to access their health information has been 
tied to

[[Page 28611]]

benefits such as improvements in access, quality of care, and health 
outcomes, and reductions in healthcare expenditures.\1434\ In 
particular, access to health information has been shown to enable the 
discovery of medical errors, to improve medication adherence, and to 
promote communication between the patient and health care 
provider.\1435\ However, despite the fact that surveyed patients 
experiencing shared access to notes with health care providers has been 
largely positive,\1436\ voluntary uptake and use of patient portals has 
been low, with nearly two-thirds of hospitals having less than 25 
percent of patients activate access to the hospital's patient portal in 
2017.\1437\ Health care provider encouragement (and other facilitating 
conditions), perceived usefulness, ease of use, control of health 
information, and enhanced communication are demonstrated as 
facilitators, while concerns of privacy, security, and lack of 
awareness have been tied to barriers of use.1438 1439
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    \1434\ Ronda MC, Dijkhorst-Oei LT, Rutten GE. Reasons and 
barriers for using a patient portal: survey among patients with 
diabetes mellitus. J Med Internet Res. 2014 Nov 25;16(11):e263. doi: 
10.2196/jmir.3457. PMID: 25424228; PMCID: PMC4260081.
    \1435\ Wildenbos GA, Peute L, Jaspers M. Facilitators and 
Barriers of Electronic Health Record Patient Portal Adoption by 
Older Adults: A Literature Study. Stud Health Technol Inform. 
2017;235:308-312. PMID: 28423804.
    \1436\ Walker J, Leveille S, Bell S, Chimowitz H, Dong Z, Elmore 
JG, Fernandez L, Fossa A, Gerard M, Fitzgerald P, Harcourt K, 
Jackson S, Payne TH, Perez J, Shucard H, Stametz R, DesRoches C, 
Delbanco T. OpenNotes After 7 Years: Patient Experiences With 
Ongoing Access to Their Clinicians' Outpatient Visit Notes. J Med 
Internet Res.
    \1437\ Henry J, Barker W, Kachay L. Office of the National 
Coordinator for Health Information Technology (ONC) Data Brief No. 
45 (April 2019). Electronic Capabilities for Patient Engagement 
among U.S. Non-Federal Acute Care Hospitals: 2013-2017. Available 
at: https://www.healthit.gov/sites/default/files/page/2019-04/AHApatientengagement.pdf.
    \1438\ Powell KR. Patient-Perceived Facilitators of and Barriers 
to Electronic Portal Use: A Systematic Review. Comput Inform Nurs. 
2017 Nov;35(11):565-573. doi: 10.1097/CIN.0000000000000377. PMID: 
28723832.
    \1439\ Alaa A. Abd-alrazaq, Bridgette M. Bewick, Tracey 
Farragher, Peter Gardner, Factors that affect the use of electronic 
personal health records among patients: A systematic review, 
International Journal of Medical Informatics, Volume 126, 2019, 
Pages 164-175, ISSN 1386-5056, https://doi.org/10.1016/j.ijmedinf.2019.03.014.
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    The Health Information National Trends Survey (HINTS), a large, 
nationally representative survey operated by the National Cancer 
Institute (with support from ONC), is conducted routinely and contains 
key utilization data on consumer access and use of their online medical 
record through patient portals. The HINTS results showed the rates of 
individuals being offered and subsequently using their health 
information through a patient portal, as well as use of mobile health 
applications (apps) and the role health care providers play in 
encouraging use.\1440\ Results showed that health care providers and 
staff have a substantial role in influencing patient use of the portal.
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    \1440\ Johnson C, Richwine C, Patel V. Office of the National 
Coordinator for Health Information Technology (ONC) Data Brief, No. 
57 (September 2021). Individuals' Access and Use of Patient Portals 
and Smartphone Health Apps, 2020.
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    In the past for the Medicare Promoting Interoperability Program, we 
attempted to promote patient access to their health information through 
measuring the number of patients who actively engaged with the 
electronic health record through the View, Download, or Transmit (VDT) 
measure at 42 CFR 495.24(c)(6)(ii)(A). 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 and updated the measures within the Provider to Patient 
Exchange Objective. Specifically, we removed the standalone VDT measure 
from the Medicare Promoting Interoperability Program in response to 
stakeholder feedback, including hospitals and hospital associations 
detailing the significant challenges they faced in implementing 
measures that require patient action (83 FR 41665). These challenges 
included, but were not limited to, patients who have limited knowledge 
of, proficiency with, or access to information technology; patients 
declining to access the portals provided by the eligible hospital or 
CAH to view, download, and transmit their health information via this 
platform; as well as the lack of availability of user-friendly portals 
and the immaturity of the health IT infrastructure needed to facilitate 
useful access and use of their own health information. We also noted 
that data analysis of the VDT measure showed low percentages of 
patients taking action to view, download, and transmit their health 
information (83 FR 41665). Additionally, in the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41661 through 41663) we changed the name of the 
Provide Patient Access measure at 42 CFR 495.24(c)(5)(ii)(A) to Provide 
Patients Electronic Access to Their Health Information at 42 CFR 
495.24(e)(7)(ii) and finalized changes to the measure description. 
These measure changes included a requirement for eligible hospitals or 
CAHs to provide timely access for viewing, downloading or transmitting 
their health information for at least one unique patient discharged 
using any application of the patient's choice (83 FR 41661 through 
41663). This change emphasized timely electronic access of patient 
health information rather than requiring health care providers to be 
accountable for patient actions.
    Through the current Provide Patients Electronic Access to Their 
Health Information measure in the Provider to Patient Exchange 
Objective, we are ensuring that patients have access to their health 
information through any application of their choice that is configured 
to meet the technical specifications of the Application Programing 
Interface (API) in the CEHRT of the eligible hospital or CAH. Promoting 
the use of API-enabled applications that provide timely access to 
updated information whenever the patient needs that information is an 
integral step in enhancing patient access and use of their health 
information. These API-enabled applications should be configured using 
standardized technology and contain the information the patient needs 
to make informed decisions about their care in a way the patient 
understands, and that recognizes the community's level of access to 
devices and internet connectivity. While we removed the VDT measure 
holding eligible hospitals and CAHs responsible for patient action (83 
FR 41665), we still require that the technical capabilities be in place 
within an eligible hospital's or CAH's CEHRT through the Provide 
Patients Electronic Access to Their Health Information measure should 
patients choose to access and use their health information (83 FR 41661 
through 41663).
    We continue to believe in the importance of taking a patient-
centered approach to health information access and moving to a system 
in which patients have immediate access to their electronic health 
information and can be assured that their health information will 
follow them as they move throughout the health care system. Recognizing 
the concerns and barriers with the previous VDT measure discussed 
previously, but acknowledging the advancements made within the health 
IT industry over the past few years, this request for information is 
seeking a broad array of public comments regarding how to further 
promote equitable patient access and use of their health information 
without adding unnecessary burden on the hospital or health care 
provider. Specifically, we are seeking public comment on the following 
questions:
     Moving beyond providing the information and technical 
capabilities to

[[Page 28612]]

access their data, are there additional approaches to promote patient 
access and use of their health information? Are there examples of 
successful approaches or initiatives that have enhanced patient access 
and use of their health information?
    ++ Would allowing patients to add information to their records be 
useful in promoting patient access and utilization? Are there other 
incentives that would promote patient access?
    ++ Are there potential unintended consequences in allowing patients 
to add information to their records? What could be done to mitigate any 
potential unintended consequences?
    ++ Are there certain tools found to be useful in promoting patient 
access and use of their health information?
     Recent studies have raised concerns about the presence of 
racial bias and stigmatizing language within EHRs that could lead to 
unintended consequences if patients were to obtain disparaging notes 
regarding their medical care.\1441\ \1442\
---------------------------------------------------------------------------

    \1441\ Sun M, Oliwa T, Peek ME, Tung EL. Negative Patient 
Descriptors: Documenting Racial Bias in the Electronic Health 
Record. Health Affairs 41, No. 2 (2022): 203-211. doi:10.1377/
hlthaff.2021.01423.
    \1442\ Himmelstein G, Bates D, Zhou L. Examination of 
Stigmatizing Language in the Electronic Health Record. JAMA Netw 
Open. 2022;5(1):e2144967. doi:10.1001/jamanetworkopen.2021.44967.
---------------------------------------------------------------------------

    ++ What policy, implementation strategies, or other considerations 
are necessary to address existing racial bias or other biases and 
prevent use of stigmatizing language?
     Additional analysis of HINTS data provides insights into 
common barriers to patient portal access and use as well as 
characteristics that can help predict which individuals are more likely 
to experience certain barriers (for example, preference for in-person 
communication with their provider is one of the most prevalent barriers 
experienced more often by older adults and women).\1443\
---------------------------------------------------------------------------

    \1443\ Turner K, Clary A, Hong Y, Alishahi Tabriz A, Shea CM. 
Patient Portal Barriers and Group Differences: Cross-Sectional 
National Survey Study. J Med internet Res 2020;22(9):e18870.
---------------------------------------------------------------------------

    ++ What are the most common barriers to patient access and use of 
their health information that have been observed? Are there differences 
by populations or individual characteristics?
     Patients' health information may be found in multiple 
patient portals. How could CMS or HHS facilitate individuals' ability 
to access all their health information in one place?
    ++ If patient portals connected to a network participating in the 
recently launched TEFCA,1444 1445 would this enable more 
seamless access to individual health information across various patient 
portals?
---------------------------------------------------------------------------

    \1444\ The Trusted Exchange Framework (TEF): Principles for 
Trusted Exchange. ONC January 2022: https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \1445\ Common Agreement for Nationwide Health Information 
Interoperability V1. ONC. January 2022: https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
---------------------------------------------------------------------------

     With the advancement of HIT, EHRs and other health-related 
communication technologies, there are concerns of equity to health 
outcomes and access with populations who could receive greater benefits 
from these technologies but are less likely to adopt 
them.1446 1447 What policy, governance and implementation 
strategies or other considerations are necessary to ensure equal access 
to patient portals, equitable portal implementation, appropriate design 
and encouragement of use?
---------------------------------------------------------------------------

    \1446\ Sarkar U, Karter AJ, Liu JY, et al. The literacy divide: 
health literacy and the use of an internet-based patient portal in 
an integrated health system--results from the diabetes study of 
Northern California (DISTANCE). J Health Commun 2010; 15 (Suppl 2): 
183-96.
    \1447\ Ackerman SL, Sarkar U, Tieu L, et al. Meaningful use in 
the safety net: a rapid ethnography of patient portal implementation 
at five community health centers in California. J Am Med Inform 
Assoc 2017; 24 (5): 903-12.
---------------------------------------------------------------------------

     What challenges do eligible hospitals and CAHs face when 
addressing patient questions and requests resulting from patient access 
of patient portals or access of data through use of a mobile app? What 
can be done to mitigate potential burden?
     For patients who access their health information, how 
could CMS, HHS, and health care providers help patients manage their 
health through the use of their personal health information?
     Do you believe the API and app ecosystem is at the point 
where it would be beneficial to revisit adding a measure of patient 
access to their health information which assesses providers on the 
degree to which their patients actively access their health information 
? What should be considered when designing a measure of patient access 
of their health information through portals or apps?
    We welcome input on how we can encourage and enable patient access 
to and use of their health information to manage and improve their care 
across the care continuum.

X. Changes for Hospitals and Other Providers

A. Codification of the Costs Incurred for Qualified and Non-Qualified 
Deferred Compensation Plans

1. Background
    Currently, certain costs incurred on behalf of Deferred 
Compensation Plans may be allowable costs under Medicare to the extent 
such costs are related to the reasonable and necessary cost of 
providing patient care and represent costs actually incurred. 
Reasonable cost reimbursement is addressed in section 1861(v)(1)(A) of 
the Act. Section 1861(v)(1)(A) defines ``reasonable cost,'' in part, as 
the cost actually incurred, excluding costs found to be unnecessary in 
the efficient delivery of needed health services. Section 1861(v)(1)(A) 
does not specifically address the determination of reasonable costs, 
but authorizes the Secretary to promulgate regulations and principles 
to be applied in determining reasonable costs.
    We have issued regulations implementing this provision of the Act, 
including 42 CFR 413.9(a), which provides that the payments ``must be 
based on the reasonable cost of services covered under Medicare and 
related to the care of beneficiaries.'' In addition, Sec.  413.9(c)(2) 
states that ``[t]he provision in Medicare for payment of reasonable 
cost of services is intended to meet the actual costs.'' Further, Sec.  
413.9(c)(3) provides that ``[r]easonable cost includes all necessary 
and proper expenses incurred in furnishing services . . . .'' 
Therefore, in accordance with the statute, the regulations include two 
principles that help guide the determination of which expenses may be 
considered allowable reasonable costs that can be paid under Medicare; 
that is, such costs must be ``related'' to the care of Medicare 
beneficiaries, and such costs must actually be ``incurred.''
    Consistent with these provisions, we have issued instructions in 
sections 2140 through 2142 of the Medicare Provider Reimbursement 
Manual, Part I (PRM-I) for determining and reporting the policies that 
govern how providers of services are to determine and report the 
allowable costs of Deferred Compensation Plans. Section 2140.1 of PRM-I 
defines Deferred Compensation as ``remuneration currently earned by an 
employee but which is not received until a subsequent period, usually 
after retirement. Accordingly, a Deferred Compensation Plan defers the 
receipt of income beyond the year in which it is earned.'' The policies 
for Deferred Compensation plans that we have established in sections 
2140 through

[[Page 28613]]

2142 of PRM-I vary depending on whether a plan is funded using an 
allowable funding mechanism or unfunded, and whether a plan is a 
Defined Contribution plan or a Defined Benefit plan. The term funded 
essentially means that funds are set aside to protect payment of future 
benefits for plan participants, and not simply paid out of current 
revenues, as is the case with unfunded plans. Allowable Non-Qualified 
Deferred Compensation Plan costs that are considered unfunded are based 
on reasonable benefits that providers of services paid to participating 
employees.
    Allowable Defined Contribution plan costs are based on reasonable 
contributions made by providers of services to Defined Contribution 
accounts. Prior to August 2011, allowable funded Defined Benefit plan 
costs were based on Employee Retirement Income Security Act of 1974 
(ERISA) components of accrued pension costs (for example, Normal Cost, 
Actuarial Accrued Liability, Actuarial Value of Assets) if the 
resulting computation of costs was funded into an approved account. In 
August 2011, the FY 2012 IPPS/LTCH PPS final rule (76 FR 51693 through 
51697), established regulations for reporting costs of Qualified 
Defined Benefit plans for Medicare cost-finding purposes. Specifically, 
for cost reporting periods beginning on or after October 1, 2011, a 
provider of services cost equals the cash basis contribution deposits 
plus any carry forward contributions, subject to a limitation (Sec.  
413.100(c)(2)(vii)(D)(1)). Providers of services with current 
contributions and carry forward contributions that exceed the limit may 
request approval of excess contributions, which are reviewed by the 
contractor on a case-by-case basis (Sec.  413.100(c)(2)(vii)(D)(3)).
    At the time the FY 2012 IPPS/LTCH final rule was issued, the 
regulations at Sec. Sec.  413.24 and 413.100 specified that pension 
costs of Qualified Defined Benefit plans were reported on an accrual 
basis of accounting method. To conform this accrual requirement in the 
regulations with the cash-basis methodology for reporting pension costs 
finalized in the FY 2012 IPPS/LTCH PPS final rule, in the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53448), we amended the general cost 
reporting rules under Sec. Sec.  413.24(a)(2) and 413.100(c)(2)(vii)(D) 
to note the exception for recognizing actual contributions funded 
during the cost reporting period on a cash basis.
    We are proposing to codify and clarify additional policies relating 
to Deferred Compensation in a new section in part 413, subpart F. We 
are not proposing to change our current policies for allowable Deferred 
Compensation costs associated with Qualified and Non-Qualified Deferred 
Compensation Plans (the plans) that are included in Medicare cost 
reports. Nor are we proposing to change the way in which Deferred 
Compensation costs are to be audited by the Medicare Administrative 
Contractors (MACs).
2. Proposed Qualified and Funded Non-Qualified Deferred Compensation 
Plans (Sec.  413.99)
    In accordance with section 1861(v)(1)(A) of the Act, we are 
proposing to add a new Sec.  413.99 in subpart F of part 413 of title 
42, titled ``Qualified and Funded Non-Qualified Deferred Compensation 
Plans,'' to establish rules for allowable and non-allowable costs 
incurred for the plans, by providers of services, under the program. 
Our proposals, which we discuss in more detail throughout this section 
of this proposed rule, set forth general requirements; definitions; 
requirements for costs of the plans to be allowable under the program; 
additional requirements for payments to funded defined benefit plans; 
data and documentation requirements to support payments/contributions 
to the plans; and allowable administrative and other costs associated 
with the plans, including costs related to the Pension Benefit Guaranty 
Corporation (PBGC).
3. Proposed Statutory Basis, Scope, and Definitions (Sec.  413.99(a))
    In accordance with section 1861(v)(1)(A) of the Act, we are 
proposing to establish the ``Basis,'' ``Scope,'' and ``Definitions'' of 
these regulations that determine the allowable and non-allowable costs 
of the plans under the program at proposed new Sec.  413.99(a)(1), (2), 
and (3), respectively. Specifically, we are proposing at new Sec.  
413.99(a)(1) to specify that all payments to providers of services must 
be based on the ``reasonable cost'' of services covered under Title 
XVIII in accordance with section 1861(v) of the Act and the regulations 
in 42 CFR part 413. In addition, we are proposing at new Sec.  
413.99(a)(2) to specify that this section and Sec.  413.100(c)(2)(vii) 
will apply to Medicare's treatment of the costs incurred for Qualified 
and Non-Qualified Deferred Compensation Plans.
    CMS has previously defined certain terms related to the program's 
policies on Deferred Compensation and the plans in sections 2140 
through 2142 of PRM-I. In this proposed rule, we are proposing to 
codify these definitions, with clarifications where appropriate, at new 
Sec.  413.99(a)(3). We are also proposing to add definitions for 
several new terms to ensure clarity and consistent application. 
Specifically, we are proposing at new Sec.  413.99(a)(3) to specify 
that as used in this section the following definitions apply: Deferred 
Compensation, Employee Retirement Income Security Act of 1974 (ERISA), 
Funded Plan, Non-Qualified Deferred Compensation Plan (NQDC), Non-
Qualified Defined Benefit Plan (NQDB), Pension Benefit Guaranty 
Corporation (PBGC), Qualified Defined Benefit Plan (QDBP), Qualified 
Defined Contribution or Individual Account Plan (QDCP), and Unfunded 
plan (see the defintions in the proposed regulatory text in the 
regulations text section of this proposed rule).
4. Proposed Principle Requirements (Sec.  413.99(b))
    We propose to establish at new Sec.  413.99(b) the ``Principle 
requirements'' that must be satisfied by all Deferred Compensation 
Plans in order for costs incurred by a provider of services in 
connection with such plans to be allowable under the program. A formal 
Deferred Compensation Plan is an agreement between the provider of 
services and its participating employees, in which the agreeing parties 
can make contributions to the plan for the exclusive benefit of its 
participating employees. Proposed Sec.  413.99(b)(1) would specify that 
amounts be contributed by a provider of services, or an employee of the 
provider of services, to a Qualified or Non-Qualified Deferred 
Compensation Plan, established and maintained by the provider of 
services to provide retirement income to employees or to result in the 
deferral of income by employees for periods extending to the 
termination of covered employment or beyond. Contributions or payments 
made by a provider of services for the benefit of its employees to a 
Qualified or Non-Qualified Deferred Compensation Plan are allowable 
when, and to the extent that, such costs are actually incurred by the 
provider of services and found to be reasonable and necessary under the 
principles of reasonable cost.
    Contracts or agreements between hospital-based physicians and 
hospitals involve a variety of arrangements under which the physician 
is compensated by the hospital for the full range of services within 
the institution. We are proposing to include requirements for 
recognition of the costs incurred to fund the plans for hospital-based 
physician patient care services and guarantee arrangements for 
physician emergency room services.

[[Page 28614]]

Deferred compensation paid for physician services to hospitals and SNFs 
is part of physician compensation under Sec.  415.60(a) and is directly 
attributable to an employee's salary. Deferred compensation is salary 
earned in the current period that is not received until a subsequent 
period, usually after retirement. Defined Contribution plans and 
Defined Benefit plans generally specify contributions and benefits as a 
percentage of employee salary. Deferred compensation based on 
unallowable compensation is also unallowable. Consistent with the 
policies in PRM-I, we propose in Sec.  413.99(b)(2) to specify that 
costs incurred by a hospital or SNF to fund a Qualified or Non-
Qualified Deferred Compensation Plan for a provider-based physician 
must meet certain requirements to be allowable. These proposed 
requirements at Sec.  413.99(b)(2)(i) through (iii) would establish 
that (i) the allocation of physician compensation costs required under 
Sec.  415.60 does not attribute the provider-based physician's Deferred 
Compensation entirely to one category of service and his current 
compensation to another; (ii) contributions or payments toward the 
Qualified or Non-Qualified Deferred Compensation Plan do not include 
any cost excluded from the definition of physician compensation at 
Sec.  415.60(a); and (iii) the amount of Deferred Compensation does not 
exceed the amount specified in the agreement required by Sec.  
415.60(g).
    In situations where the provider is merely acting as the billing 
agent for the physician whose remuneration is derived from billing for 
patient care services, the Medicare program will not recognize such 
remuneration. As a result, these proposed requirements would also 
specify that an arrangement between a physician and a provider of 
services under which the physician is reimbursed for patient charges, 
but the provider of services does the billing as a Deferred 
Compensation agreement, is not allowed. We propose to codify this 
policy at Sec.  413.99(b)(2)(iv).
    We propose to codify at Sec.  413.99(b)(2)(v) that the costs 
incurred for physician guarantee arrangements for hospital emergency 
room availability services must also meet the additional requirements 
that (1) the terms of both the guarantee arrangement and the Deferred 
Compensation plan establish the amounts to be included at the beginning 
of the hospital's cost reporting period; (2) the amount of Deferred 
Compensation is included in the guaranteed amount; (3) the hospital 
contributes to the fund established under the Deferred Compensation 
Plan from its own funds; (4) the amount of Deferred Compensation that 
is allowable is limited to the amount by which the guarantee, including 
Deferred Compensation, exceeds the total billed by the hospital to all 
patients for the physician's patient care services; and (5) when the 
physician's charges to all patients equal or exceed the amount 
guaranteed by the hospital, the program does not recognize a Deferred 
Compensation contribution/payment.
5. Proposed Requirements for Non-Qualified and Qualified Deferred 
Compensation Plans (Sec.  413.99(c))
    We are proposing to codify the guidance from sections 2140 through 
2142 of PRM-I regarding the requirements that must be met in order for 
costs incurred by providers of services to be allowable for inclusion 
as Deferred Compensation in the Medicare cost report. The requirements 
vary based on the type of plan established by the provider of services. 
The plans currently recognized by the program include Deferred 
Compensation Plans, currently set forth in section 2140 of PRM-I, 
Qualified Defined Contribution Deferred Compensation Plans set forth in 
section 2141 of PRM-I, and Qualified Defined Benefit Pension Plans set 
forth in section 2142 of PRM-I. As discussed previously in section 
X.A.1 of this proposed rule, we are proposing to codify the definitions 
of these types of plans and related terms, with clarifications where 
appropriate, in proposed new Sec.  413.99(a)(3). We propose to 
establish at new Sec.  413.99(c) the plan-specific requirements that 
each type of Qualified or Non-Qualified Deferred Compensation Plan must 
meet in order for a provider of servicers contributions or payments to 
the plan to be allowable under the program.
    Employer contributions for the benefit of employees under a 
Deferred Compensation Plan are allowable when, and to the extent that, 
such costs are actually incurred by the provider or services. 
Contributions to a funded Deferred Compensation Plan are allowable 
costs when they are made to the plan, to the extent they fall under the 
computed limit. Benefits paid for an unfunded Deferred Compensation 
Plans are allowable costs only when actually paid to the participating 
employees (or their beneficiaries), and only to the extent considered 
reasonable.
    First, we propose to codify at Sec.  413.99(c)(1) the requirements 
for NQDCs, which can be funded or unfunded. Proposed Sec.  
413.99(c)(1)(i) would establish that an NQDC must meet the requirements 
for document compliance and operational compliance set forth in 
Internal Revenue Code (IRC) section 409A. Proposed paragraph (c)(1)(ii) 
would specify that a funded NDQC must meet the proposed definition of a 
Funded Plan in Sec.  413.99(a)(3) and comply with the requirements in 
proposed Sec.  413.99(c)(5) (discussed later in this section of this 
proposed rule). Proposed paragraph (c)(1)(iii) would provide that an 
unfunded NQDC must meet the definition of an Unfunded Plan as proposed 
in Sec.  413.99(a)(3), and there must be no constructive receipt of 
income for employees from the NQDC as a result of contributions made by 
a provider of services.
    Second, we propose to codify at Sec.  413.99(c)(2) the requirements 
for QDCPs. Consistent with our existing policies for Defined 
Contribution Deferred Compensation Plans found in section 2141.1 of 
PRM-I, proposed paragraph (c)(2)(i) would specify that a QDCP must meet 
the applicable requirements of ERISA, as amended, and the requirements 
set forth in IRC section 401(a), and, if applicable, section 401(k). In 
addition, proposed paragraph (c)(2)(ii) would specify that a QDCP must 
meet the proposed definition for a Funded Plan in Sec.  413.99(a)(3) 
and comply with the requirements in proposed Sec.  413.99(c)(5).
    Third, we propose to codify at Sec.  413.99(c)(3) the requirements 
for QDBPs. Specifically, proposed Sec.  413.99(c)(3)(i) would establish 
that a QDBP must meet the applicable requirements of ERISA, as amended, 
and the requirements for a QDBP under IRC section 401(a). Proposed 
paragraph (c)(3)(ii) would specify that a QDBP must meet the definition 
of a Funded Plan as proposed in Sec.  413.99(a)(3) and comply with the 
requirements in proposed Sec.  413.99(c)(5).
    Fourth, we propose to codify at Sec.  413.99(c)(4) the requirements 
for NQDBs, which may be funded or unfunded. Proposed Sec.  
413.99(c)(4)(i) would establish that an NQDB must meet the requirements 
for document compliance and operational compliance set forth in 
Internal Revenue Code (IRC) section 409A. Proposed paragraph (c)(4)(ii) 
would specify that a funded NQDB must meet the definition of a Funded 
Plan as proposed in Sec.  413.99(a)(3) and comply with the requirements 
in proposed Sec.  413.99(c)(5). Proposed paragraph (c)(4)(iii) would 
provide that an unfunded NQDB must meet the definition of an Unfunded 
Plan as proposed in Sec.  413.99(a)(3), and there must be no 
constructive receipt of income for employees from the NQDC as a result 
of contributions made by a provider of services.

[[Page 28615]]

    We are proposing to codify at Sec.  413.99(c)(5) certain 
requirements for Funded Plans. We propose to establish at paragraph 
(c)(5)(i) the types of funding mechanisms that Funded Plans must use in 
order for provider of services contributions and employee contributions 
to such plans to be included in allowable costs. Specifically, a Funded 
Plan would be required to use either to purchase an insured plan with a 
commercial insurance company, to establish a custodial bank account, or 
to establish a trust fund administered by a trustee. Proposed paragraph 
(c)(5)(ii) would codify our longstanding policy, set forth in section 
2140.3.B of PRM-I, disallowing the use of an ordinary life insurance 
contract as a funding mechanism for a Funded Plan. Specifically, 
proposed paragraph (c)(5)(ii) would specify that the purchase of an 
ordinary life insurance contract (for example, whole life, straight 
life, or other) is not a deferral of compensation and is not recognized 
as a funding mechanism, even where it is convertible at the normal 
retirement date specified in the policy to an annuity payable over the 
remaining life of the employee. Proposed paragraph (c)(5)(iii) would 
establish that, regardless of the funding mechanism utilized, all 
provider of services and employee contributions to the fund established 
under the Deferred Compensation Plan and income therefrom must be used 
for the sole benefit of the participating employees.
    The proposed requirements for a Funded Plan are based on the 
generally accepted definition of a Funded Plan, along with existing CMS 
policies on the funding of Deferred Compensation Plans found in section 
2140.3 of PRM-I.
6. Proposed Recognition of Contributions or Payments to Qualified and 
Non-Qualified Deferred Compensation Plans (Sec.  413.99(d))
    At proposed Sec.  413.99(d), we propose to codify rules and 
requirements that determine when payments or contributions by a 
provider to Qualified or Non-Qualified Deferred Compensation Plans that 
meet the applicable plan-specific requirements at proposed Sec.  
413.99(c) are recognized and included in allowable costs under the 
program. In general, the rules in proposed Sec.  413.99(d) vary 
depending on whether a plan is qualified or non-qualified. In addition, 
certain special rules apply to contributions to QDBPs and NQDBs that 
are deposited into trusts.
    First, for unfunded Deferred Compensation Plan (which include 
unfunded NQDBs), we propose to codify at proposed Sec.  
413.99(d)(1)(ii) that payments made to such plans are included in 
allowable costs only during the cost reporting period in which an 
actual payment is made to the participating employees (or their 
beneficiaries) and only to the extent considered reasonable in 
accordance with Sec.  413.100(c)(2)(vii)(A). This proposed requirement 
incorporates the existing regulatory requirement for payments to 
unfunded Deferred Compensation Plans at Sec.  413.100(c)(2)(vii)(A), to 
aid the reader in understanding related policies that appear in other 
sections of this part that affect unfunded NQDCs and unfunded NQDBs.
    Second, regarding certain funded Deferred Compensation Plans 
(specifically funded Defined Contribution Plans, but excluding QDBPs 
and funded NQDBs), we propose to include at Sec.  413.99(d)(1)(ii) a 
cross reference to Sec.  413.100(c)(2)(vii)(B), which requires that 
accrued costs related to matching or non-elective contributions to a 
funded Deferred Compensation Plan must be liquidated within 1 year 
after the end of the cost reporting period in which the liability is 
incurred. Under Sec.  413.100(c)(2)(viii)(B), an extension, not to 
exceed 3 years beyond the end of the cost reporting year in which the 
liability was incurred, may be granted for good cause if the provider 
of services, within the 1-year time limit, furnishes to the contractor 
sufficient written justification for non-payment of the liability. 
Applying this requirement to QDCPs is consistent with Sec.  
413.100(c)(2)(vii)(B) and with policies established in section 2141.2 
of PRM-I.
    Third, contributions into a protected trust for QDBPs and funded 
NQDBs are allowable. We require that these assets be protected solely 
for the plan participants and to pay reasonable plan administrative 
expenses. Contributions or payments must be made by the provider into a 
protected trust and accounted for on a cash basis. For these plans, we 
are proposing to establish at Sec.  413.99(d)(1)(iii) that 
contributions by providers must satisfy the following four requirements 
to be allowable: First, the contributions must be paid to the plan 
participants or the plan trust; second, contributions are accounted for 
on a cash basis; third, money refunded from a plan must be treated as a 
negative contribution; and fourth, the allowable cost must be computed 
in accordance with the calculation defined in Sec.  
413.100(c)(2)(vii)(D). We describe each of these proposed requirements 
in greater detail in the paragraphs that follow.
    First, we propose to establish at Sec.  413.99(d)(1)(iii)(A) that 
QDBP or funded NQDB contributions are found to have been incurred only 
if paid directly to participants or beneficiaries under the terms of 
the plan or to the QDBP or NQDB. Proposed paragraph (d)(1)(iii)(A) 
codifies our existing policy, which is described in section 2142.6.A of 
PRM-I. Section 2142.6 states that provider contributions or payments 
made to a defined benefit pension plan are allowable only to the extent 
that costs are actually incurred by the provider. Such costs are found 
to have been incurred only if paid directly to participants or 
beneficiaries under the terms of the plan or paid to a pension fund 
which meets the applicable tax qualification requirements under IRC 
section 401(a).
    Second, we propose to codify at Sec.  413.99(d)(1)(iii)(B) the 
existing regulatory requirement at Sec.  413.100(c)(2)(vii)(D) for 
contributions to a QDBP or funded NQDB. Specifically, proposed Sec.  
413.99(d)(1)(iii)(B) would require that payments to a QDBP or funded 
NQDB for a cost reporting period be measured on a cash basis. A 
contribution or payment would be deemed to occur on the date it is 
credited to the fund established for the QDBP or funded NQDB, or for 
provider of services payments made directly to a plan participant or 
beneficiary, on the date the provider of services account is debited.
    Third, we propose to clarify the treatment of pension contributions 
when a QDBP or funded NQDB is terminated at Sec.  413.99(d)(1)(iii)(C) 
as payments/contributions made to fully fund a terminating QDBP or 
funded NQDB are to be included as funding on the date they are paid. 
Excess assets withdrawn from a QDBP or funded NQDB are to be treated as 
negative contributions on the date that they are withdrawn. We believe 
our proposal to recognize negative contributions by reference to the 
date of withdrawal provides greater clarity than the standard under our 
current guidance under section 2140.3 of PRM-I, which refers to the 
``year of plan termination,'' which is less specific and subject to 
interpretation.
    Fourth, we propose to specify at Sec.  413.99(d)(1)(iii)(D) that 
QDBP and funded NQDB costs and limits are computed in accordance with 
the existing regulatory requirements at Sec.  413.100(c)(2)(vii)(D). 
For purposes of determining the QDBP or funded NQDB cost limit under 
Sec.  413.100(c)(2)(vii)(D)(2), we propose that provider of services 
contribution

[[Page 28616]]

payments for each applicable cost reporting period shall be determined 
on a cash basis in accordance with proposed Sec.  413.99(d)(1)(iii)(B), 
without regard to any limit determined for the period during which the 
contributions were made, and excluding any contributions deposited in a 
prior period and treated as carry forward contributions. We are 
proposing that the averaging period used to determine the QDBP or 
funded NQDB cost limit shall be determined without regard to a provider 
of services period of participation in the Medicare program. Periods 
that are not Medicare cost reporting periods (for example, periods 
prior to the hospital's participation in the Medicare program) shall be 
defined as consecutive twelve-month periods ending immediately prior to 
the provider of services initial Medicare cost reporting period. We are 
proposing that the averaging period used to determine the QDBP or 
funded NQDB cost limit shall exclude all periods ending prior to the 
initial effective date of the plan (or a predecessor plan in the case 
of a merger). Lastly, we are proposing that in general, the current 
period defined benefit cost and limit shall be computed and applied 
separately for each QDBP or funded NQDB offered by a provider of 
services. In the case of a plan merger, the contribution payments made 
by a provider of services to a predecessor QDBP or funded NQDB and 
reflected in the assets subsequently transferred to a successor plan 
shall be treated as contribution payments made to the successor plan.
    In the FY 2012 IPPS/LTCH PPS final rule, we established separate 
methodologies for measuring pension costs for Medicare cost-finding 
purposes (76 FR 51693 through 51697) and for purposes of updating the 
hospital wage index (76 FR 51586 through 51590). Under the methodology 
we established for the wage index, the pension costs that are to be 
included in the wage index equal a hospital's average cash 
contributions deposited to its defined benefit pension plan over a 3-
year period or, if less than a 3-year period, the number of years that 
the hospital has sponsored a defined benefit plan. The 3-year average 
was centered on the base cost reporting period for the wage index. For 
example, the FY 2013 wage index is based on Medicare cost reporting 
periods beginning during Federal FY 2009 and reflects the average 
pension contributions made in hospitals' cost reporting periods 
beginning during Federal FYs 2008, 2009, and 2010. In the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49505 through 49508), we modified the policy 
such that the 3-year average is based on pension contributions made 
during the base cost reporting period plus the prior 2 cost reporting 
years. For example, the FY 2017 wage index is based on Medicare cost 
reporting periods beginning during Federal FY 2013. Therefore, the FY 
2017 wage index reflects the average pension contributions made in 
hospitals' cost reporting periods beginning during Federal FYs 2011, 
2012, and 2013 (rather than Federal FYs 2012, 2013, and 2014 under the 
prior policy established in the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51586 through 51590)). While the QDBP cost for cost-finding purposes is 
computed using the cost period annual contributions limited by a cap 
(as codified in Sec.  413.100(c)(2)(vii)(D)), the wage index QDBP cost 
is a 3-year average of annual plan contributions without adjustment or 
cap.
7. Proposed Documentation Requirements (Sec.  413.99(e))
    We propose to codify at Sec.  413.99(e) that a provider of services 
must maintain and make available upon request documentation to 
substantiate the costs incurred for the plans included in its Medicare 
cost report. These proposed requirements for documentation are based on 
the existing regulatory requirements at Sec.  413.20, which require 
providers of services to maintain sufficient financial records and 
statistical data for proper determination of costs payable under the 
program.
    In addition, these requirements are based in part on the policy 
established when CMS revised the calculation for a QDBP and funded NQDB 
in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51693 through 51697). 
Section 2142.5.F of PRM-I states that the provider must have available 
data to show the amount(s) and date(s) of contribution payments made to 
a defined benefit pension plan during the current reporting period and 
any applicable prior periods. If the pension costs included in the cost 
report for a period differ from the pension contribution payments made 
during the reporting period (for example, as a result of carry forward 
contributions), the provider must also have data available to track and 
reconcile the difference.
    Specifically, we are proposing at Sec.  413.99(e) that 
documentation must be maintained by the provider of services in 
accordance with Sec.  413.20 to substantiate the allowability of the 
payments or contributions to Qualified or Non-Qualified Deferred 
Compensation Plans (or both) that it has included in its cost reports. 
With respect to required documentation, we are proposing to specify at 
Sec.  413.99(e)(1) that the provider of services must maintain and make 
available, upon request from the contractor or CMS, certain specified 
documentation, to substantiate the allowability of payments or 
contributions made by the provider of services to a Qualified or Non-
Qualified Deferred Compensation Plan. Under proposed Sec.  
413.99(e)(1), the following documentation would be required: 
Documentation that demonstrates that the provider of services is in 
compliance with IRC section 409A and IRC section 409A(a), and if 
applicable IRC section 457; ledger accounts/account statements for each 
plan participant noting current year deferrals, distributions, and 
loans, including any deferral election forms completed by employees, 
any change requests, and the approval of such requests; documentation 
that demonstrates the amount(s) and date(s) of actual payment/
contributions made to the Non-Qualified or Qualified Deferred 
Compensation Plan during the current cost reporting period; Schedule SB 
of Form 5500 (tri-agency form (Department of Labor (DOL), Internal 
Revenue Service (IRS), PBGC) that plans file with the DOL's ``EFAST'' 
electronic filing system. The ``Form 5500'' is the Annual Return/Report 
of Employee Benefit Plan for a QDBP for the current cost reporting 
period, or any applicable prior periods; and, in the case of a system 
wide (multiple employer) plan, the home office shall identify the 
contributions attributed to each participating provider of services. If 
the costs included in the cost report for a period differ from the 
contributions made during the reporting period (for example, as a 
result of carry forward contributions), the provider of services must 
also have data available to track and reconcile the difference.
    We are also proposing to establish at Sec.  413.99(e)(2) that the 
following additional documentation must be made available, upon request 
by the contractor or CMS, to substantiate the allowability of payments 
or contributions made by a provider of services to a Qualified or Non-
Qualified Deferred Compensation Plan: The plan document, the trust 
document and all amendments related to the current cost reporting 
period; if applicable, any Form 5330, Return of Excise Taxes Related to 
Employee Benefit Plans, for the cost reporting period; supporting 
documents for all plan assets and

[[Page 28617]]

liabilities, such as broker's statements, bank statements, insurance 
contracts, loan documents, deeds, etc., and verification of how assets 
are valued; trustee or administrator reports; ledgers; journals; 
trustee, administrator and investment committee minutes; certified 
audit report; and other financial reports for the trust. Any other 
financial reports, including receipt and disbursement statements, a 
detailed income statement and a detailed balance sheet; and, for each 
covered QDBP, documentation of the certified premium information and 
payments to the PBGC.
8. Proposed Administrative and Other Costs Associated With Qualified 
and Non-Qualified Deferred Compensation Plans (Sec.  413.99(f))
    In proposed Sec.  413.99(f), we propose to codify our current 
policies, as set forth in sections 2140, 2141, and 2142 of PRM-I, 
regarding the treatment of certain administrative and other costs 
related to Deferred Compensation Plans as allowable or non-allowable 
under the program. In the paragraphs that follow, we discuss our 
proposed treatment of various administrative costs related to Deferred 
Compensation Plans. First, we propose to establish at Sec.  413.99(f) 
that the provider of services shall file a cost report required under 
Sec. Sec.  413.20 and 413.24(f) that is consistent with the proposed 
policies set forth in proposed Sec.  413.99.
a. Trustee and Custodial Fees
    We propose to codify at Sec.  413.99(f)(1) that reasonable trustee 
or custodial fees, including PBGC premiums, paid by the provider of 
services are allowed as an administrative cost, except where the plan 
provides that such fees are paid out of the corpus or earnings of the 
fund. Fees paid out of the corpus or earnings of the fund would not be 
allowed, based on the rationale that, because contributions into the 
plan trust pay for benefits and expenses that are paid from the trust, 
that means administrative costs paid out of the plan trust have already 
been accounted for through the allowance of contributions made by the 
provider of services. This proposal would codify our current policy, 
which is set forth in section 2140.3.B.1.d of PRM-I.
b. Vested Benefits
    We propose to codify at Sec.  413.99(f)(2) that the forfeiture of 
an employee's benefits for cause (as defined in the plan) is recognized 
as an allowable cost provided that such forfeited amounts are used to 
reduce the provider of services contributions or payments to the plan 
during the cost reporting period in which the forfeiture occurs. This 
proposal would codify our policy on the effects of a forfeiture of 
vested benefits on the plan costs that are allowable under the program, 
as set forth at section 2140.3.D of PRM-I, with the added clarification 
that the reduction must occur in the cost reporting period in which the 
forfeiture occurs.
    We propose to codify at Sec.  413.99(f)(3) our existing policy on 
the effects of employees' termination of participation in a plan before 
their rights are vested in the contributions/payments to the plan that 
are allowable under the program. Specifically, proposed Sec.  
413.99(f)(3) would specify that if an employee terminates participation 
in the Deferred Compensation Plan before their rights are vested, the 
applicable non-vested contributions/payments cannot be applied to 
increase the benefits of the surviving participants. Instead, the non-
vested contributions/payments should be used to reduce the provider of 
services contributions/payments to the Deferred Compensation Plan, in 
the cost reporting period wherein the employee terminated participation 
in the Deferred Compensation Plan. Otherwise, the contributions/
payments made by the provider of services must be applied to reduce the 
subsequent contributions/payments to the Deferred Compensation Plan in 
the next cost reporting period. If subsequent provider of services 
contributions/payments to the Deferred Compensation Plan are not made, 
then provider of services costs will be reduced by the contractor to 
the extent of such non-vested funds.
c. DOL, IRS, and PBGC Penalties
    Providers of services who maintain a Deferred Compensation Plan are 
required to comply with regulatory requirements related to the plan 
that are established by the Department of Labor (DOL), the IRS and the 
PBGC. Where providers of services fail to follow these requirements, a 
penalty may be levied. For example, the IRS levies an excise tax when 
payments are not timely filed. section 1861(v)(8) of the Act sets forth 
items unrelated to patient care that are not considered reasonable 
under the program. In other words, these items are unallowable, and 
therefore cannot be included in the allowable costs of the provider of 
services. One of these items is the cost for fines and penalties 
resulting from violations of Federal, State, or local laws. 
Accordingly, we are proposing at Sec.  413.99(f)(4) to specify that if 
the provider of services is assessed an excise tax or other remedy by 
DOL or IRS or PBGC for failure to follow the DOL, IRS, or PBGC 
requirements under ERISA, or any other penalty fee or penalty interest 
applicable to its Deferred Compensation Plan, the associated cost is 
unallowable, in accordance with section 1861(v)(8)(iv) of the Act.
d. Loans Made From a Deferred Compensation Plan
    Under our current policy, as set forth in section 2140.3.C of PRM-I 
providers of services are able to make a loan to themselves out of 
either corpus or income from their Qualified or Non-Qualified Deferred 
Compensation Plan on the conditions that the fund receive adequate 
security and a reasonable rate of interest on the loan. This existing 
policy is inconsistent with ERISA section 406 (29 U.S.C. 1106(1)(B)) 
which specifically prohibits lending of money or other extension of 
credit between the plan and a party in interest, unless found to be 
excepted under 29 U.S.C. 1108. The definition of a ``party in 
interest'' includes an employer any of whose employees are covered by 
such plan. The same provision exists in the IRC at 26 U.S.C. 4975. We 
believe that the policy we codify in new Sec.  413.99 should reflect 
these provisions in ERISA and the IRS rules that are designed to 
protect Deferred Compensation Plans and the plans' participants and 
beneficiaries. Accordingly, we are proposing at Sec.  413.99(f)(5) to 
specify that a provider of services cannot make a loan to itself from a 
Deferred Compensation Plan where ERISA or IRS rules prohibit such a 
transaction, except where specifically excepted. In cases where an 
exception applies, our existing policy on allowable interest expense at 
Sec.  413.153 continues to apply.
e. Termination/Discontinuation of a Deferred Compensation Plan
    Sections 2140.3.D and 2141.3.D of PRM-I set forth CMS's policy on 
the effect of a provider of services declining to vest its outstanding 
required contributions/payments as a result of a termination, in full 
or in part, or a discontinuation of contributions or payments to a 
Deferred Compensation Plan. Under this policy, which we propose to 
codify at Sec.  413.99(f)(6), where the provider of services declines 
to vest its outstanding required contributions/payments (that is, 
matching and non-elective or both) to a Deferred Compensation Plan, as 
a result of a termination, in full or in part, or a discontinuation of 
contributions or payments to a Deferred Compensation Plan, then the 
provider of services total outstanding required contributions or 
payments to the Deferred Compensation

[[Page 28618]]

Plan during the cost reporting period wherein such termination is 
initiated cannot be included in the provider of services allowable cost 
for the cost reporting period in which the termination is initiated, 
nor any future period.
f. Required Offset Against Interest Expense
    In section 2140.3.D of PRM-I, CMS has established a policy that 
investment income earned on a fund after its termination but prior to 
liquidation of the fund's assets and distribution to the provider is 
offset against the provider's allowable interest expense. We are 
proposing to adopt the current policy in section 2140.3 of PRM-I at 
proposed Sec.  413.99(f)(7), which would state that investment income 
earned on a Deferred Compensation Plan after its termination but prior 
to liquidation of the plan's assets and distribution to the provider of 
services must be offset against the provider of services allowable 
interest expense under Sec.  413.153.
g. Treatment of Residual Assets Following Termination of a Funded Plan
    In section 2140.3.D of PRM-I, CMS has established a policy 
describing how residual assets arising from the termination of a funded 
plan are to be handled on the Medicare cost report. We are proposing to 
adopt the current policy, as it appears in section 2140.3.D of PRM-I, 
at new Sec.  413.99(f)(8). Specifically, proposed Sec.  413.99(f)(8) 
would specify that residual assets arising from the termination of a 
funded plan must be recouped in the year of the plan termination only 
against the cost center(s) in which the provider of services reported 
its plan contributions/payments, usually the administrative and general 
cost center. Residual assets exceeding the amount in the administrative 
and general (or other) cost center are not further offset in the 
current or subsequent years. The Medicare share of the reversion is 
based on the Medicare utilization rate in the year the reversion occurs 
(or the year the actuarial surplus is determined), and not Medicare's 
utilization in the years the contributions to the plan were made.
9. Proposed Treatment of Costs Associated With the Pension Benefit 
Guaranty Corporation (PBGC) (Sec.  413.99(g))
    Since 1974, the PBGC has protected retirement security and the 
retirement incomes of over 33 million American workers, retirees, and 
their families in private sector defined benefit pension plans. A 
Qualified Defined Benefit Plan (defined previously as a QDBP) provides 
a specified monthly benefit at retirement, often based on a combination 
of salary and years of service. The PBGC was created by ERISA to 
encourage the continuation and maintenance of private sector defined 
benefit pension plans, provide timely and uninterrupted payment of 
pension benefits, and keep pension insurance premiums at a minimum.
    General tax revenues do not fund the PBGC Single-Employer Program. 
The PBGC collects insurance premiums from employers that sponsor 
insured pension plans, earns money from investments, and receives funds 
from pension plans it takes over (see https://www.pbgc.gov/about/how-pbgc-operates).
    Providers of services who offer a QDBP may incur costs related to 
the PBGC premiums. The proposed regulations outlined in this section of 
this proposed rule establish which costs incurred by providers of 
services who maintain a QDBP and pay premiums for basic benefits to the 
PBGC are allowable under the program. We propose to include these 
provisions on the treatment of costs associated with the PBGC in 
paragraph (g) of proposed Sec.  413.99.
    In 29 U.S.C. 1306 the schedule for the premium rates, and the bases 
for application of those rates are set forth. Under 29 U.S.C. 1306, 
premiums are established for basic benefits, non-basic benefits, and 
reimbursement for uncollectible withdrawal liability. We are proposing 
at Sec.  413.99(g)(1) that PBGC premiums and costs paid out of the 
corpus or earnings of the trust are included in the contributions 
allowed by Sec.  413.99(d)(3)(ii), and therefore are not allowable as 
separate costs. We are also proposing at Sec.  413.99(g)(2) that the 
amount of PBGC premiums paid for basic benefits (that is, flat rate or 
variable, excluding amounts paid out of the corpus or earnings of the 
trust) by a provider of services who sponsors a QDBP are allowable 
under the program. Similar to allowance of Administrative Costs as 
stated in proposed Sec.  413.99(f)(1), while PBGC premiums are an 
allowable cost, they are not allowed if they are paid from the plan 
trust.
    In 29 CFR part 4050, the rules for PBGC's program that holds 
retirement benefits for missing participants and beneficiaries of 
terminated retirement plans and pays those benefits to participants and 
beneficiaries when found, are provided. A Missing Participant is a 
former employee of a provider of services who has a liability remaining 
with the plan but cannot be located or is unresponsive when the plan 
terminates and closes out. Transfers of funds to the PBGC by the 
provider of services to cover this liability under the PBGC Missing 
Participant Program are allowable as long as they are not paid out of 
the corpus or earnings of the trust. We are proposing at new Sec.  
413.99(g)(3) that the total amount paid to the PBGC by a provider of 
services who sponsors a QDBP (excluding amounts paid out of the corpus 
or earnings of the trust) of the benefit transfer amount (see 29 CFR 
4050.103(d)) for all missing participants or beneficiaries of the QDBP 
is allowable under the program.
    After entering into a trusteeship agreement with the employer or 
after receiving an order issued by a U.S. district court approving 
termination, the PBGC guarantees employee plan benefits will be paid up 
to a certain limit if the QDBP has insufficient assets as part of a 
Distress Termination (as described in 29 CFR part 4041) or as part of a 
PBGC-initiated termination under 29 U.S.C. 1342. We are proposing at 
Sec.  413.99(g)(4) that for terminated plans with insufficient assets 
to pay all of the plan benefits, where the PBGC guarantees the payment 
of vested benefits up to limits defined by law, only contributions to 
the QDBP made by a provider of services are allowable. Benefits paid to 
the participants and beneficiaries of the QDBP by the PBGC are 
unallowable.
    In 29 CFR part 4047, PBGC is given the authority to restore a plan 
from terminated status to ongoing. Contributions and benefits paid by 
the provider of services to the PBGC or the plan or its participants 
and beneficiaries are allowable in this situation. We are proposing at 
Sec.  413.99(g)(5) that where the PBGC issues or has issued a plan 
restoration order as described in 29 CFR part 4047, the amounts that 
the provider of services repays to the PBGC for guaranteed benefits and 
related expenses under the plan while the plan was in terminated 
status, and any administrative costs assessed by the PBGC, excluding 
penalties, are allowable.

B. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
To Report Data Elements To Address Any Future Pandemics and Epidemics 
as Determined by the Secretary

    Under sections 1866 and 1902 of the Act, providers of services 
seeking to participate in the Medicare or Medicaid program, or both, 
must enter into an agreement with the Secretary or the state Medicaid 
agency, as appropriate. Hospitals (all hospitals to which the 
requirements of 42 CFR part 482 apply,

[[Page 28619]]

including short-term acute care hospitals, LTC hospitals, 
rehabilitation hospitals, psychiatric hospitals, cancer hospitals, and 
children's hospitals) and CAHs seeking to be Medicare and Medicaid 
providers of services under 42 CFR part 485, subpart F, must be 
certified as meeting Federal participation requirements. Our conditions 
of participation (CoPs), conditions for coverage (CfCs), and 
requirements set out the patient health and safety protections 
established by the Secretary for various types of providers and 
suppliers. The specific statutory authority for hospital CoPs is set 
forth in section 1861(e) of the Act; section 1820(e) of the Act 
provides similar authority for CAHs. The hospital provision at section 
1861(e)(9) of the Act authorizes the Secretary to issue any regulations 
he or she deems necessary to protect the health and safety of patients 
receiving services in those facilities; the CAH provision at section 
1820(e)(3) of the Act authorizes the Secretary to issue such other 
criteria as he or she may require. The CoPs are codified in the 
implementing regulations at part 482 for hospitals, and at 42 CFR part 
485, subpart F, for CAHs.
    Our CoPs at Sec.  482.42 for hospitals and Sec.  485.640 for CAHs 
require that hospitals and CAHs, respectively, have active facility-
wide programs, for the surveillance, prevention, and control of 
healthcare-associated infections (HAIs) and other infectious diseases 
and for the optimization of antibiotic use through stewardship. 
Additionally, the programs must demonstrate adherence to nationally 
recognized infection prevention and control guidelines, as well as to 
best practices for improving antibiotic use where applicable, and for 
reducing the development and transmission of HAIs and antibiotic-
resistant organisms. Infection prevention and control problems and 
antibiotic use issues identified in the required hospital and CAH 
programs must also be addressed in coordination with facility-wide 
quality assessment and performance improvement (QAPI) programs.
    Infection prevention and control is a primary goal of hospitals and 
CAHs in their normal day-to-day operations, and these programs have 
been at the center of initiatives taking place in hospitals and CAHs 
during the PHE for COVID-19. Our regulations at Sec. Sec.  482.42(a)(3) 
and 485.640(a)(3) require infection prevention and control program 
policies to address any infection control issues identified by public 
health authorities. On March 4, 2020, we issued guidance \1448\ stating 
that hospitals should inform infection prevention and control services, 
local and state public health authorities, and other healthcare 
facility staff as appropriate about the presence of a person under 
investigation for COVID-19. CMS followed this guidance with an interim 
final rule with comment (IFC), published on September 2, 2020 (85 FR 
54820), that now requires hospitals and CAHs to report important data 
critical to support the fight against COVID-19. The CoP provisions 
require that hospitals and CAHs report this information in accordance 
with a frequency as specified by the Secretary on COVID-19 as well as 
in a standardized format specified by the Secretary (42 CFR 482.42(e) 
and 485.640(d), respectively). Examples of data elements that may be 
required to be reported include things such as the number of staffed 
beds in a hospital and the number of those that are occupied, 
information about its supplies, and a count of patients currently 
hospitalized who have laboratory-confirmed COVID-19. This list is not 
exhaustive of those data items that we may require hospitals and CAHs 
to submit, as specified by the Secretary (see https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf for the current list of data items 
specified). These elements are essential for planning, monitoring, and 
resource allocation during the COVID-19 Public Health Emergency (PHE). 
The rules make reporting a requirement of participation in the Medicare 
and Medicaid programs. This reporting is needed to support broader 
surveillance of, and response to, COVID-19.
---------------------------------------------------------------------------

    \1448\ https://www.cms.gov/files/document/qso-20-13-hospitalspdf.pdf-2.
---------------------------------------------------------------------------

    Following the publication of the September 2, 2020 IFC, we set 
forth a second set of reporting requirements for hospitals and CAHs in 
an IFC published on December 29, 2020 (85 FR 85866). This IFC added 
additional requirements for hospitals and CAHs to report data elements 
that must include, but not be limited to, their current inventory 
supplies of any COVID-19-related therapeutics that have been 
distributed and delivered to the hospital (or CAH) under the authority 
and direction of the Secretary as well as the hospital's (or the CAH's) 
current usage rate for these COVID-19-related therapeutics (Sec. Sec.  
482.42(e) and 485.640(d), respectively, as amended). The December 2020 
IFC also requires hospitals and CAHs to report information in 
accordance with a frequency, and in a standardized format, as specified 
by the Secretary during the PHE, for Acute Respiratory Illness 
(including, but not limited to, Seasonal Influenza Virus, Influenza-
like Illness, and Severe Acute Respiratory Infection) (Sec. Sec.  
482.42(f) and 485.640(e), respectively). As with the COVID-19 
reporting, examples of data elements that may be required to be 
reported include things such as the number of staffed beds in a 
hospital and the number of those that are occupied, information about 
its supplies, and a count of patients currently hospitalized who have 
diagnoses of Acute Respiratory Illnesses (including, but not limited 
to, Seasonal Influenza Virus, Influenza-like Illness, and Severe Acute 
Respiratory Infection). And as with the COVID-19 reporting 
requirements, we firmly believe these elements are essential for 
planning, monitoring, and resource allocation during the COVID-19 PHE, 
especially during seasonal influenza season and when hospitals and CAHs 
are likely to see an increase in the number of patients presenting with 
the signs and symptoms of a variety acute respiratory illnesses along 
with a continuing and unknown number of patients presenting with both 
suspected and confirmed COVID-19.
    The current acute respiratory illness reporting requirements, in 
tandem with those for COVID-19 reporting, by all hospitals and CAHs, 
have been, and continue to be, important in supporting surveillance of, 
and response to, the PHE for COVID-19. Similarly, they play an 
important role when considering future planning to prevent the spread 
of respiratory viruses and infections, including, but not limited to, 
COVID-19. However, current regulatory language specifically ties the 
aforementioned reporting requirements to the current PHE declaration 
for COVID-19. Consequently, these reporting requirements will no longer 
be required through the CoPs once the PHE declaration ends. 
Additionally, we are concerned that the current requirements while 
appropriately focused on the current COVID-19 pandemic, are too limited 
in scope for potential future use. Given our experience throughout the 
PHE for COVID-19, CMS, in conjunction with other Federal partners, 
particularly the CDC and ASPR, are considering ways to ensure a more 
flexible regulatory framework to ensure a nimble and informed response 
to the next potential pandemic or epidemic, so that we are able to 
immediately respond to the situation at hand. Therefore, we propose to 
revise the hospital and CAH infection prevention and control and 
antibiotic stewardship programs CoPs to

[[Page 28620]]

extend the current COVID-19 reporting requirements and to establish new 
reporting requirements for any future PHEs related to a specific 
infectious disease or pathogen. For COVID-19 reporting, these proposed 
requirements would take effect after the COVID-19 PHE declaration 
expires, but no earlier than the effective date of the final rule 
implementing these proposals. Therefore, if the COVID-19 PHE 
declaration is still in effect at the time of the final rule, it is our 
intention that these proposals would not be implemented and enforced 
until the current COVID-19 PHE declaration concludes and we issued 
guidance indicating such a transition. We welcome public comment on 
strategies to mitigate challenges and support an informed transition.
    Specifically, we propose to revise the COVID-19 and Seasonal 
Influenza reporting standards for hospitals and CAHs (at Sec. Sec.  
482.42(e)-(f) and 485.640(d)-(e), respectively) to require that, 
beginning at the conclusion of the current COVID-19 PHE declaration and 
continuing until April 30, 2024, a hospital (or a CAH) must 
electronically report information about COVID-19 and Seasonal Influenza 
in a standardized format specified by the Secretary.
    For COVID-19 reporting, the categories of data elements that this 
report would, to the extent as determined by the Secretary, include are 
as follows: Suspected and confirmed COVID-19 infections o among 
patients and staff; total COVID-19 deaths among patients and staff; 
personal protective equipment and testing supplies in the facility; 
ventilator use, capacity and supplies in the facility; total hospital 
bed and intensive care unit bed census and capacity; staffing 
shortages; COVID-19 vaccine administration data of patients and staff; 
and relevant therapeutic inventories and/or usage. For seasonal 
influenza, the categories of data elements that this report would, to 
the extent as determined by the Secretary, include are as follows: 
Confirmed influenza infections among patients and staff; total 
influenza deaths among patients and staff; and confirmed co-morbid 
influenza and COVID-19 infections among patients and staff. We note 
that the proposed categories of data elements align closely with those 
COVID-19 reporting requirements for long-term care (LTC) facilities 
that were finalized on November 9, 2021 (86 FR 62421) and are 
representative of the guidance provided to hospitals and CAHs for 
reporting. Therefore, we do not expect that these categories of data 
elements would require hospitals and CAHs to report any information 
beyond that which they have already been reporting (OMB control numbers 
0938-0328 for hospitals and 0938-1043 for CAHs). Furthermore, similar 
to the requirements for LTC facilities, this proposal would also allow 
for the scope and frequency of data collection to be reduced and 
limited responsive to the evolving clinical and epidemiological 
circumstances. These requirements would also sunset April 30, 2024, 
unless the Secretary establishes an earlier ending date. To the extent 
possible, we have sought to align the proposed sunset date in this rule 
with the sunset date finalized in the CY 2022 Home Health Prospective 
Payment System (HH PPS) final rule for nursing homes' COVID-19 
reporting requirements. However, this rule also includes a provision to 
continue influenza reporting (which has been part of the broader COVID-
19 reporting requirements, given the risk of concurrently or 
sequentially occurring influenza outbreaks and the associated 
additional pressure on hospital capacity during flu season). 
Accordingly, we did not beleive it would be appropriate to set a sunset 
date in the middle of a flu season (December 2024). Therefore, we 
elected to set the sunset date at the end of a typical flu season 
(April). And, given our preference to maximize alignment with the NH 
sunset date, we were left with the option of April 2024 or April 2025. 
We are proposing a date to sunset the requirement that we believe is in 
the interest of health and safety and avoids imposing unnecessary 
burden on providers.
    We believe that additional reporting requirements are necessary to 
protect the health and safety of hospital and CAH patients as well as 
the communities that these facilities serve. The possible resurgence in 
COVID-19 cases, the uncertain virulence of annual seasonal influenza, 
and the emergence of other infectious disease pathogens that may lead 
to future epidemics and pandemics may all pose significant risks to 
patients and communities in the future. Past experiences with 
outbreaks, epidemics, and pandemics, along with the lessons learned 
from the current COVID-19 pandemic, have demonstrated that such 
scenarios can lead to surges of inpatient admissions that often 
negatively impact hospital capacity to accept and treat patients. To 
more effectively respond to future crises, we seek to ensure timely and 
complete surveillance, on an ``as needed'' basis, through broadening 
reporting requirements beyond COVID-19 and the current PHE. 
Establishing such requirements would enable HHS and the Federal 
Government to continue to respond to hospitals and CAHs in need of 
additional support and guidance. Therefore, at Sec. Sec.  482.42(g) and 
485.640(f), for hospitals and CAHs respectively, we are proposing 
additional requirements to address future PHEs related to epidemics and 
pandemics. Specifically, when the Secretary has declared a PHE, we 
propose to require hospitals and CAHs to report specific data elements 
to the CDC's National Health Safety Network (NHSN), or other CDC-
supported surveillance systems, as determined by the Secretary. The 
proposed requirements of this section would apply to local, state, and 
national PHEs as declared by the Secretary. We note that we would 
anticipate a nominal lag time between the declaration of the PHE and 
the start of the collection to allow for CMS to notify regulated 
entities and provide guidance regarding the necessary reporting. We 
would expect the method of notification to follow a model similar to 
that which we used to inform regulated entities at the beginning of the 
COVID-19 PHE (see QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). Relevant to the declared 
PHE, the categories of data elements that this report would include are 
as follows: Suspected and confirmed infections of the relevant 
infectious disease pathogen among patients and staff; total deaths 
attributed to the relevant infectious disease pathogen among patients 
and staff; personal protective equipment and other relevant supplies in 
the facility; capacity and supplies in the facility relevant to the 
immediate and long term treatment of the relevant infectious disease 
pathogen, such as ventilator and dialysis/continuous renal replacement 
therapy capacity and supplies; total hospital bed and intensive care 
unit bed census, capacity, and capability; staffing shortages; vaccine 
administration status of patients and staff for conditions monitored 
under this section and where a specific vaccine is applicable; relevant 
therapeutic inventories and/or usage; isolation capacity, including 
airborne isolation capacity; and key co-morbidities and/or exposure 
risk factors of patients being treated for the pathogen or disease of 
interest in this section that are captured with interoperable data 
standards and elements. We acknowledge that there are uncertainties in 
planning for future emergencies, and CMS understands that there are 
lots of incentives and pathways to consider with regard to 
preparedness. Therefore, we are

[[Page 28621]]

soliciting public comment on how to best align and incentivize 
preparedness, while also reducing burden and costs on regulated 
entities, and ensuring flexibility.
    In identifying categories of data elements to propose, we 
considered the data elements that proved most informative and 
actionable over the course of the COVID-19 PHE (elements that, over 
time, supported early identification and response to stress at 
facility, system, community, state, and Federal levels) as well as 
lessons learned from preparedness for, and response to, other 
epidemiological threats that have emerged over recent decades (Ebola, 
SARS, MERS, seasonal influenza). The inclusion of vaccine 
administration data, in particular, is informed by the current 
inability of the required data elements to match patient COVID-19 
vaccination status with hospitalization or ICU admission status. In 
short, the categories proposed here provide the flexibility for CMS and 
CDC to gather actionable data that would close many of the gaps 
identified throughout the COVID-19 pandemic and answer the call for 
U.S. public health agencies to have much more timely, complete, and 
consistent data for future pathogens of concern.\1449\ We believe that 
the proposed requirements provide a regulatory framework for the 
reporting of relevant infectious disease data by hospitals and CAHs 
with regard to future pandemics and epidemics. As such, we expect these 
requirements will complement, not supplant existing Federal, state, 
local, territorial, or tribal reporting requirements. We return to, and 
expand upon, these points further later in this section.
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    \1449\ Michaels D., Emanuel EJ, Bright RA. A National Strategy 
for COVID-19: Testing, Surveillance, and Mitigation Strategies. 
JAMA. Published online January 06, 2022. doi:10.1001/
jama.2021.24168.
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    In this rule, we are also proposing at Sec. Sec.  482.42(g)(2) and 
485.640(f)(2) to require that a hospital (or a CAH) must report each 
applicable infection (confirmed and suspected) and the applicable 
vaccination data in a format that provides person-level information, to 
include medical record identifier, race, ethnicity, age, sex, 
residential county and zip code, and relevant comorbidities for 
affected patients, unless the Secretary specifies an alternative format 
by which the hospital (or CAH) would be required report these data 
elements. We are also proposing in this provision to limit any person-
level, directly or potentially individually identifiable, information 
for affected patients to items outlined in this section or otherwise 
specified by the Secretary. Lastly, Sec. Sec.  482.42(g)(3) and 
485.640(f)(3), we are proposing that a hospital (or a CAH) would 
provide the information specified on a daily basis, unless the 
Secretary specifies a lesser frequency, to the Centers for Disease 
Control and Prevention's National Healthcare Safety Network (NHSN) or 
other CDC-supported surveillance systems as determined by the 
Secretary. We note that while we have proposed a maximum reporting 
frequency of daily during PHEs, this may be reduced at the discretion 
of the Secretary contingent on the state of the PHE and ongoing risks. 
Furthermore, we do not want these collections to overlap information 
being collected elsewhere, thus, we are soliciting comment on the 
potential that this data collection may duplicate elements already 
reported elsewhere, and if so, which data elements and through what 
data collection mechanism.
    The term ``person-level data'' encompasses both ``directly 
identifiable information'' (information that identifies an individual, 
such as a record number) and ``potentially identifiable information'' 
(information that could be used with other available information to 
identify an individual but is not directly tied to one individual--for 
example, race/ethnicity). As a guiding principle, HHS would limit any 
data collection under this provision to the minimum necessary 
collection cadence and data elements, including individual data, 
necessary to protect patient health and safety. We are committed to 
ensuring the provisions proposed here incorporate lessons from, and 
correct for limitations identified during, the PHE.
    We believe that individual data elements such as race, ethnicity, 
age, sex, residential county and zip code, and relevant comorbidities 
for affected patients are necessary to address issues of health equity 
and response management. In the absence of these data, it can be 
challenging to take action to reduce disparities in disease incidence 
and severity, as well as access to, receipt of, and effectiveness of 
relevant preventive and therapeutic services (for example, vaccines) 
among vulnerable or otherwise marginalized populations (for example, 
racial/ethnic minorities; individuals with intellectual or 
developmental disabilities). An important gap raised during the COVID-
19 pandemic was the inability to follow patients with COVID-19 through 
the health care system, especially the important transfers that often 
occur between acute and long-term care facilities. A medical record 
identifier would allow tracking transfers between facilities, which 
could provide important and actionable information on COVID-19 outcomes 
and health care facility capacities. Similarly, medical record 
identifiers enable data and encounters to be connected in order to 
assess the full scope of disease burden for an individual and determine 
appropriate course of therapeutic action.
    As previously noted, CMS has proposed that hospitals would report 
any data required under this provision (Sec. Sec.  482.42(g) and 
485.640(f)) to CDC's NHSN or other CDC-supported surveillance systems 
as determined by the Secretary. Hospitals reporting to NHSN in 
fulfillment of the CMS quality reporting program requirements are 
already familiar with reporting patient-level data to NHSN, including 
medical record identifiers, gender, birthdate, and date of event. CDC 
protects those elements with strong security and privacy measures and 
tightly restricts access to these data. Access to NHSN data is 
restricted to the uses described in the NHSN Agreement to Participate 
and Consent, and all NHSN users must abide by the NHSN Rules of 
Behavior, which safeguard against unwarranted or inadvertent misuse or 
disclosure of NHSN data. CDC's Secure Data Network also requires use of 
a 128-bit encryption digital certificate for authentication into NHSN. 
The provided information obtained in this surveillance system that 
would permit identification of any individual or institution is 
collected with a guarantee that it will be held in strict confidence, 
will be used only for the purposes stated, and will not otherwise be 
disclosed or released without the consent of the individual, or the 
institution in accordance with sections 304, 306, and 308(d) of the 
Public Health Service Act (42 U.S.C. 242b, 242k, and 242m(d)).
    CMS recognizes that the health and safety benefits associated with 
any reporting requirements must be carefully weighed against the 
potential burden these impose on facility operations--particularly in 
situations, like a PHE, where staff resources are already stretched to 
provide required services. The proposal balances these imperatives by 
not specifying what and how often specific data elements would be 
required. Specifically, the proposed requirements would allow for 
reporting frequency to be adjusted in response to specific triggers and 
signals. For example, if case counts nationally are low and have been 
for some time, it may be reasonable to reduce reporting frequency--
potentially even to ``zero,'' which would effectively ``turn off'' 
reporting--for a given element or category. At the same time, if case

[[Page 28622]]

counts were increasingly rapidly, it may be necessary to increase the 
scope and frequency of data collected.
    As previously noted, CMS does not intend to supplant or duplicate 
existing requirements and mechanisms for reporting of public health 
surveillance data to other Federal, state, territorial, local, and 
tribal agencies. The health care facility reporting requirements 
proposed in this rule are distinct from and serve a different purpose 
than case surveillance of notifiable diseases and conditions that is 
conducted by state and local health departments. Specifically, this 
proposed rule aims to create a framework for hospital and CAH reporting 
that would ensure HHS and the Federal Government have the information 
necessary to identify and respond to hospitals and CAHs in need of 
additional support and guidance and to monitor and assess the capacity 
of hospitals and CAHs to provide safe care during a declared PHE 
(national, regional, or local). To that end, we propose reporting to 
CDC's NHSN because it is a vendor-neutral, federally owned system. As 
such, it can and does accept data submitted by outside vendors 
contracted either by hospitals, jurisdictions, or other Federal 
entities to submit data on behalf of hospitals and which meets data 
quality standards defined by CDC. CDC's NHSN also provides ready access 
to data to state and many local public health agencies for the 
facilities in their jurisdictions via their NHSN accounts and 
contributes aggregate data to multiple public-facing platforms, 
including HHS Protect and CMS Care Compare. This proposed rule aims to 
minimize reporting burden while maintaining transparency \1450\ and 
ensuring public health agencies, researchers, and the public have 
sufficient visibility \1451\ of overall health system capacity amid 
evolving epidemiological conditions in order to rapidly direct 
preventive and response actions. Additionally, aligning these proposed 
hospital and CAH reporting requirements with the existing reporting in 
NHSN, and other mechanisms of reporting required public health data, 
may decrease reporting burden and allow for analysis of health care 
data across these patient safety and health care facility capacity 
domains by the CDC.
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    \1450\ https://obamawhitehouse.archives.gov/the-press-office/2013/05/09/executive-order-making-open-and-machine-readable-new-default-government-.
    \1451\ https://digital.gov/open-data-policy-m-13- 13/.
---------------------------------------------------------------------------

    At the same time, we recognize the value of and support hospital 
engagement with public health authorities to report public health 
surveillance data. In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45470 
through 45479), we finalized the requirement for eligible hospitals and 
CAHs participating in the Promoting Interoperability Program to report 
four of the six 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. And elsewhere in this rule, 
we've proposed changes to the duration and level of engagement that 
will further strengthen incentives for eligible hospitals and CAHs to 
engage in these essential reporting activities. To ensure CMS has the 
necessary flexibility to take advantage of these other reporting 
streams, CMS has proposed that hospitals would report any data required 
under this provision to CDC's NHSN or other CDC-supported surveillance 
systems, as specified by the Secretary.
    Ultimately, CMS expects reporting requirements under this section 
will become increasingly automated and real-time as data systems and 
standards continue to mature and become more interoperable. Through 
resources provided by the American Rescue Plan Act and its Data 
Modernization Initiative, CDC is investing in increasing the automation 
capabilities of the surveillance systems like NHSN and its ability to 
connect with other data submission techniques, vendors, and 
systems.\1452\ Nevertheless, the glidepath to this future state may 
differ across regions, facilities, and even required data elements--
particularly those captured and reported at the person level. To 
accommodate variable reporting capabilities, the person-level reporting 
requirements under this provision would leverage established national 
standards and interoperability requirements of ONC to reduce burden and 
promote standardization, and would include minimal data elements 
necessary for public health, safety, and infection control purposes.
---------------------------------------------------------------------------

    \1452\ https://www.cdc.gov/surveillance/data-modernization/index.html.
---------------------------------------------------------------------------

    We recognize that this transition may come with certain tradeoffs 
and are soliciting comments on any challenges or unintended 
consequences that this may impose on facilities. We firmly believe that 
the proposed reporting requirements support our responsibility to 
protect and ensure the health and safety of hospital and CAH patients 
by, among other things, ensuring that these facilities follow infection 
prevention and control protocols based on recognized standards of 
practice. We believe that these proposed reporting requirements are 
necessary for CMS to monitor whether individual hospitals and CAHs are 
appropriately tracking, responding to, and mitigating the spread and 
impact of viral and bacterial pathogens and infectious diseases of 
pandemic or epidemic potential on patients, the staff who care for 
them, and the general public. We believe that this action reaffirms our 
commitment to protecting the health and safety of all patients who 
receive care at the approximately 6,200 Medicare- and Medicaid-
certified hospitals and CAHs nationwide. We welcome public comments on 
our proposal and have noted specific areas of interest for feedback 
throughout the discussion.

C. Request for Public Comments on IPPS and OPPS Payment Adjustments for 
Wholly Domestically Made NIOSH-Approved Surgical N95 Respirators

1. Introduction and Overview
    On January 20, 2021, President Biden issued Executive Order (E.O.) 
13987, titled ``Organizing and Mobilizing the United States Government 
To Provide a Unified and Effective Response To Combat COVID-19 and To 
Provide United States Leadership on Global Health and Security'' (86 FR 
7019). This order launched a whole-of-government approach to combat the 
coronavirus disease 2019 (COVID-19) and prepare for future biological 
and pandemic threats. This response has continued over the past year. 
In March 2022, President Biden released the National COVID-19 
Preparedness Plan that builds on the progress of the prior 13 months 
and lays out a roadmap to fight COVID-19 in the future.\1453\ Both the 
ongoing threat of COVID-19 and the potential for future pandemics 
necessitate significant investments in pandemic preparedness.
---------------------------------------------------------------------------

    \1453\ White House, National COVID-19 Preparedness Plan, March 
2022; https://www.whitehouse.gov/wp-content/uploads/2022/03/NAT-COVID-19-PREPAREDNESS-PLAN.pdf
---------------------------------------------------------------------------

    Availability of personal protective equipment (PPE) in the health 
care sector is a critical component of this preparedness, and one that 
displayed significant weakness in the beginning of the COVID-19 
pandemic. In spring of 2020, supply chains for PPE faced severe 
disruption due to lockdowns that limited production, and unprecedented 
demand spikes across multiple industries. Supply of surgical N95 
respirators--a specific type of filtering

[[Page 28623]]

facepiece respirator used in clinical settings--was one type of PPE 
that was strained in hospitals. So-called ``just-in-time'' supply 
chains that minimize stockpiling, in addition to reliance on overseas 
production, left U.S. hospitals unable to obtain enough surgical N95 
respirators to protect health care workers. Prices for surgical N95s 
soared, from an estimated $0.25-$0.40 range \1454\ to $5.75 \1455\ or 
even $12.00 in some cases.\1456\ Unable to obtain surgical N95s 
regulated by the National Institute for Occupational Safety and Health 
(NIOSH), hospitals had to turn to KN95s--a Chinese standard of 
respirator--and other non-NIOSH-approved disposable respirators that 
were authorized under Emergency Use Authorization (EUA). Concerns were 
raised during the COVID-19 pandemic regarding counterfeit respirators. 
NIOSH evaluates and approves surgical N95s to meet efficacy standards 
for air filtration and protection from fluid hazards present during 
medical procedures. KN95 respirators, on the other hand, are not 
regulated by NIOSH. KN95s have faced particular counterfeit and quality 
risks--with NIOSH finding that about 60% of KN95 respirators that it 
evaluated during the COVID-19 pandemic in 2020 and 2021 did not meet 
the particulate filter efficiency requirements that they intended to 
meet.\1457\ Failure to meet these requirements compromises safety of 
health care personnel and patients.
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    \1454\ Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response, Supply Chain 
Control Tower analysis.
    \1455\ Society for Healthcare Organization Procurement 
Professionals, COVID-19 PPD Cost Analysis, April 2020; http://cdn.cnn.com/cnn/2020/images/04/16/shopp.covid.ppd.costs.analysis_.pdf.
    \1456\ Washington Post, ``U.S. sent millions of face masks to 
China early this year, ignoring pandemic warning signs,'' April 
2020; https://www.washingtonpost.com/health/us-sent-millions-of-face-masks-to-china-early-this-year-ignoring-pandemic-warning-signs/2020/04/18/aaccf54a-7ff5-11ea-8013-1b6da0e4a2b7_story.html.
    \1457\ U.S. Centers for Disease Control and Prevention ``Types 
of Masks and Respirators''; https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/types-of-masks.html.
---------------------------------------------------------------------------

    Over the course of the pandemic, U.S. industry responded to the 
shortages and dramatically increased production of N95s. Today, the 
majority of surgical N95s purchased by hospitals are assembled in the 
U.S., and prices have returned to rates closer to $0.70 per 
respirator.\1458\ However, risks remain to maintain preparedness for 
COVID-19 and future pandemics. It is important to maintain this level 
of domestic production for surgical N95s, which provide the highest 
level of protection from particles when worn consistently and properly, 
protecting both health care personnel and patients from the transfer of 
microorganisms, body fluids, and particulate material--including the 
virus that causes COVID-19. Additionally, it is important to ensure 
that a sufficient share of those surgical N95s are wholly made in the 
U.S.--that is, including raw materials and components. The COVID-19 
pandemic has illustrated how overseas production shutdowns, foreign 
export restrictions, or ocean shipping delays can jeopardize 
availability of raw materials and components needed to make critical 
public health supplies. In a future pandemic or COVID-19-driven surge, 
hospitals need to be able to count on PPE manufacturers to deliver the 
equipment they need on a timely basis in order to protect health care 
workers and their patients. Sustaining a level of wholly domestic 
production of surgical N95 respirators is integral to maintaining that 
assurance.
---------------------------------------------------------------------------

    \1458\ Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response, Supply Chain 
Control Tower analysis.
---------------------------------------------------------------------------

    This policy goal--ensuring that quality PPE is available to health 
care personnel when needed by maintaining production levels of wholly 
domestically made PPE--is emphasized in the National Strategy for a 
Resilient Public Health Supply Chain, published in July 2021 as a 
deliverable of President Biden's Executive Order 14001 on ``A 
Sustainable Public Health Supply Chain.'' To help achieve this goal, 
the U.S. Government is committing to purchase wholly domestically made 
PPE in line with new requirements in section 70953 of the 
Infrastructure Investment and Jobs Act. These new contract requirements 
stipulate that PPE purchased by covered departments must be wholly 
domestically made--that is, the products as well as their materials and 
components must be grown, reprocessed, reused, or produced in the U.S.
    The Federal Government's procurement of wholly domestically made 
PPE will help achieve the above policy goal. However, the U.S. 
Government alone cannot sustain the necessary level of production. As 
outlined in the previously mentioned National Strategy for a Resilient 
Public Health Supply Chain, the U.S. Government is only one small part 
of the market for PPE. Hospitals are the primary purchasers and users 
of medical PPE including surgical N95 respirators. Sustaining a strong 
domestic industrial base for PPE--in order to be prepared for future 
pandemics or COVID-19-driven surges and protect Americans' health 
during such times--therefore, requires hospitals' support.
    Surgical N95 respirators are a particularly critical type of PPE 
needed to protect personnel and beneficiaries from the SARS-CoV-2 virus 
and future respiratory pandemic illnesses. However, wholly domestically 
made NIOSH-approved surgical N95 respirators are generally more 
expensive than foreign-made ones. Therefore, we believe a payment 
adjustment that reflects, and offsets, the additional marginal costs 
that hospitals face in procuring wholly domestically made NIOSH-
approved surgical N95 respirators might be appropriate. These marginal 
costs are due to higher prices for wholly domestically made NIOSH-
approved surgical N95s, which, in turn, primarily stem from higher 
costs of manufacturing labor in the U.S. compared to costs in countries 
such as China, where many N95 and other respirators are made. Such a 
payment adjustment might provide sustained support over the long term 
to hospitals that purchase wholly domestically made NIOSH-approved 
surgical N95 respirators, and could help safeguard personnel and 
beneficiary safety over the long term by sustaining production and 
availability of these respirators.
    For the IPPS, the Secretary could potentially make such a payment 
adjustment under section 1886(d)(5)(I) of the Social Security Act, 
which specifically authorizes the Secretary to provide by regulation 
for such other exceptions and adjustments to the payment amounts under 
section 1886(d) of the Act as the Secretary deems appropriate.
    For the OPPS, the Secretary could potentially make such a payment 
adjustment under section 1833(t)(2)(E) of the Social Security Act, 
which authorizes the Secretary to establish, in a budget neutral 
manner, other adjustments as determined to be necessary to ensure 
equitable payments.
2. Request for Public Comments on Potential Payment Adjustments Under 
the IPPS and OPPS
    As discussed earlier in this section, given the importance of 
NIOSH-approved surgical N95 respirators in protecting personnel and 
beneficiaries from the SARS-CoV-2 virus and future respiratory pandemic 
illnesses, we are considering whether it might be appropriate to 
provide payment adjustments to hospitals to recognize the additional 
resource costs they incur to acquire NIOSH-approved surgical N95 
respirators that are wholly domestically made. NIOSH-approved surgical 
N95 respirators, which faced

[[Page 28624]]

severe shortage at the onset of the COVID-19 pandemic, are essential 
for the protection of patients and hospital personnel that interface 
with patients. The Department of Health and Human Services (HHS) 
recognizes that procurement of NIOSH-approved surgical N95 respirators 
that are wholly domestically made, while critical to pandemic 
preparedness and protecting health care workers and patients, can 
result in additional resource costs for hospitals.
    We are interested in feedback and comments on the appropriateness 
of payment adjustments that would account for these additional resource 
costs. We believe such payment adjustments could help achieve a 
strategic policy goal, namely, sustaining a level of supply resilience 
for NIOSH-approved surgical N95 respirators that is critical to protect 
the health and safety of personnel and patients in a public health 
emergency. We are considering such payment adjustments to apply to 2023 
and potentially subsequent years. This rule outlines for feedback and 
comments two possible frameworks to do so.
    One potential framework for payment adjustments might be to provide 
biweekly interim lump-sum payments to hospitals that would be 
reconciled at cost report \1459\ settlement. Under this framework, a 
hospital would separately report on its cost report the aggregate cost 
and total quantity of NIOSH-approved surgical N95 respirators it 
purchased that were wholly domestically made and those that were not--
for cost reporting periods beginning on or after January 1, 2023. This 
information, along with existing information already collected on the 
cost report, could be used to calculate a Medicare payment for the 
estimated cost differential, specific to each hospital, incurred due to 
the purchase of NIOSH-approved surgical N95 respirators that are wholly 
domestically made vs. those that are foreign-assembled or include 
foreign-sourced components. In accordance with the principles of 
reasonable cost as set forth in section 1861(v)(1)(A) of the Act and in 
42 CFR 413.1 and 413.9, Medicare could make a lump-sum payment for 
Medicare's share of these additional inpatient and outpatient costs at 
cost report settlement.
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    \1459\ Medicare-certified providers, such as Medicare-certified 
hospitals, are required to submit an annual cost report (CMS-2552-10 
(OMB control number 0938-0050)) to their Medicare Administrative 
Contractor (MAC). The Medicare cost report contains provider 
information such as facility characteristics, cost and charges by 
cost center, in total and for Medicare, Medicare settlement data, 
and financial statement data. CMS will provide the opportunity for 
the public to comment on any information collection associated with 
a future proposal.
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    Alternatively, a second potential framework on which we seek 
comment is the development of a claims-based approach wherein Medicare 
could establish a MS-DRG add-on payment that could be applied to each 
applicable Medicare IPPS discharge. Under this alternative, hospitals 
would have to meet or exceed a ``domestic sourcing threshold'' of 50 
percent for wholly domestically sourced surgical N95 respirators 
purchased by or for the hospital in 2023. We could establish a unique 
billing code that eligible hospitals would append to their claim 
attesting to the fact that they met or exceeded the domestic sourcing 
threshold for the year. If we were to adopt a claims-based approach for 
IPPS, we believe it would be appropriate to adopt a similar claims-
based approach for face-to-face Medicare encounters under the OPPS. 
Similar to the MS-DRG add-on payment approach, for OPPS, Medicare could 
establish an Ambulatory Payment Classification (APC) add-on payment for 
each non-telehealth OPPS service.
    There are several considerations for either a potential framework 
of lump-sum interim biweekly periodic payments reconciled at cost 
report settlement; or a potential framework of claims-based payment 
adjustments for IPPS and OPPS. Accordingly, we seek comment on the 
following questions.
     Which of the potential frameworks would be a more 
appropriate approach to provide payment adjustments for purchased 
wholly domestically made NIOSH-approved surgical N95 respirators? 
Please explain why.
     How can hospitals determine if the surgical N95 
respirators they purchase are wholly domestically made NIOSH-approved 
surgical N95 respirators and eligible for these payment adjustments?
     For the lump-sum payment framework, what would be the most 
appropriate methodology to determine Medicare's share of costs for 
purchased wholly domestically made NIOSH-approved surgical N95 
respirators? One potential methodology could use the ratio of Medicare 
inpatient cases to total inpatient hospital cases for all payers 
reported on the Medicare cost report.
     For the lump-sum payment framework, a hospital might use 
only wholly domestically made NIOSH-approved surgical N95 respirators. 
Such a hospital would not have any cost information to report for 
NIOSH-approved surgical N95 respirators that were not wholly 
domestically made. Strictly for purposes of calculating a cost 
differential in such situations, should a national minimum cost be 
established for a NIOSH-approved surgical N95 respirator that is not 
wholly domestically made?
     For the claims-based payment framework, how should 
Medicare calculate the per claim add-on amount prospectively given the 
varying costs of NIOSH-approved surgical N95 respirators, and how 
should it be updated given year-by-year cost changes for NIOSH-approved 
surgical N95 respirators?
     For the claims-based payment framework, what are 
reasonable usage assumptions upon which to base the payment 
adjustments? For example, for OPPS, should the payment adjustments be 
based on assumption of one wholly domestically made NIOSH-approved 
surgical N95 respirator worn per face-to-face, in-person encounter? 
What assumptions should be made for IPPS? Should the claims-based 
payment adjustment differ by MS-DRG and by APC?
     Given that the OPPS authority that would potentially be 
used for an OPPS payment adjustment is required by law to be budget 
neutral, should the IPPS payment adjustment also be budget neutral or 
should it be applied in a non-budget neutral manner?
     What program integrity safeguards should Medicare 
institute in effectuating this policy? What documentation should 
hospitals be required to maintain? \1460\ How can the policy mitigate 
price increases for wholly domestically made NIOSH-approved surgical 
N95 respirators and preserve incentives for hospitals to negotiate fair 
prices with N95 mask suppliers?
---------------------------------------------------------------------------

    \1460\ We note if a hospital does not maintain adequate 
documentation regarding its wholly domestically made NIOSH-approved 
surgical N95 respirators for its cost report under the lump-sum 
payment framework or its domestic sourcing threshold attestation 
under the claims-based payment framework, CMS could recoup any 
additional payments.
---------------------------------------------------------------------------

     For hospitals that meet the domestic sourcing threshold, 
should the submission of the claim be deemed sufficient for attestation 
of compliance with meeting or exceeding the domestic sourcing threshold 
or is a separate attestation process necessary? For what time period 
should a hospital be attesting that it met the domestic sourcing 
threshold?
     Do special considerations for certain hospitals exist, 
such as hospitals with low-volume of Medicare patients or those in a 
rural or urban safety net setting?

[[Page 28625]]

     For Group Purchasing Organizations (GPOs) that purchase 
wholly domestically made NIOSH-approved surgical N95 respirators on 
behalf of health systems, what considerations, if any, are needed to 
inform a payment adjustment policy?
     Other than information obtained from hospital cost reports 
or claims, what additional data sources should CMS consider to inform 
future adjustments?
     What data or circumstances should be taken into 
consideration to determine continuation of these payments beyond 2023?
     Are there other types of respiratory devices and PPE that 
should be considered for payment adjustments?
    We realize there may be different ways a payment adjustment to 
recognize the additional resource costs hospitals incur when purchasing 
wholly domestically made NIOSH-approved surgical N95 respirators could 
be implemented and seek comment on these or other frameworks.

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 2022 ``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 2023 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 https://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 this proposed rule, we are 
proposing to use the FY 2021 data for FY 2023 ratesetting, with certain 
proposed modifications to our relative weight and outlier 
methodologies. As discussed in section I.F. of the preamble of this 
proposed rule, we are also considering, as an alternative to our 
proposed approach, the use of the FY 2021 MedPAR claims for purposes of 
FY 2023 ratesetting but without these proposed modifications to our 
usual methodologies. In order to facilitate comments on this 
alternative approach, which we may consider finalizing for FY 2023 
based on consideration of comments received, we are making available 
supplemental information, including the relative weights calculated 
both with and without COVID-19 cases as described in section I.F. of 
the preamble of this proposed rule as well as other proposed rule 
supporting data files including the IPPS and LTCH PPS Impact Files, 
supporting MS-DRG files (such as the AOR/BOR File, the Case Mix Index 
File, and the Standardizing File) and a file that contains Operating 
and Capital National Standardized Amounts as well as other factors 
(such as budget neutrality factors and the fixed-loss outlier 
threshold), determined under the alternatives considered for this 
proposed rule. 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.
    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 2019 Medicare cost reports used to create 
the proposed FY 2023 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 2023 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 2023 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 2023 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 2023.
5. FY 2023 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).
    Media: Internet at https://www.cms.gov/Medicare/Medicare-Fee-for-
Service-Payment/AcuteInpatientPPS/Index.html (on the navigation panel 
on the left side of the page, click on the FY 2023 proposed rule home 
page or the FY 2023 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
    Period Available: FY 2023 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

[[Page 28626]]

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-Fee-for-Service-Payment/ProspMedicareFeeSvcPmtGen/psf_text.
    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-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/
Medicare/Medicare-Fee-for-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 1985 through FY 2023.
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-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/
Medicare/Medicare-Fee-for-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 the fiscal year final 
rule home page desired).
    Periods Available: FY 2005 through FY 2023 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-Fee-for-Service-Payment/AcuteInpatientPPS/Historical-Impact-Files-for-FY-1994-through-Present, or for the more recent data files, https://
www.cms.gov/Medicare/Medicare-Fee-for-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 2023 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-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html, or for the more recent data files, https://www.cms.gov/
Medicare/Medicare-Fee-for-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 2005 through FY 2023 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 Core-Based Statistical Area (CBSA). The file supports the 
rulemaking.
    Media: Internet at https://www.cms.gov/Medicare/Medicare-Fee-for-
Service-Payment/AcuteInpatientPPS/Index.html (on the navigation panel 
on the left side of the page, click on the FY 2023 proposed rule home 
page or the FY 2023 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
    Period Available: FY 2023 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-Fee-for-
Service-Payment/AcuteInpatientPPS/Index.html (on the navigation panel 
on the left side of the page, click on the FY 2023 proposed rule home 
page or the FY 2023 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
    Period Available: FY 2023 IPPS Update.
14. Hospital Readmissions Reduction Program Supplemental File
    The Hospital Readmissions Reduction Program Supplemental File is 
only available and updated for the final rule, when the most recent 
data is available. Therefore, we refer readers to the FY 2022 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 2023 IPPS/LTCH PPS proposed rule 
supplemental file.
    Media: Internet at https://www.cms.gov/Medicare/Medicare-Fee-for-
Service-Payment/AcuteInpatientPPS/Index.html (on the navigation

[[Page 28627]]

panel on the left side of the page, click on the FY 2023 proposed rule 
home page or the FY 2023 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
    Period Available: FY 2023 IPPS Update.
15. Medicare Disproportionate Share Hospital (DSH) Supplemental File
    This file contains information on the calculation of the 
uncompensated care payments for FY 2023. 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-Fee-for-
Service-Payment/AcuteInpatientPPS/Index.html (on the navigation panel 
on the left side of the page, click on the FY 2023 proposed rule home 
page or the FY 2023 final rule home page) or https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download.html.
    Period Available: FY 2023 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-Fee-for-
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-Inpatient-Files-for-Download.html.
    Periods Available: For FY 2023 and FY 2024 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 for the Hospital Wage Index for Acute Care Hospitals
    Section III.E.1. of the preamble of this proposed rule, use of 2019 
Medicare wage index occupational mix survey for the FY 2023 wage index, 
references the information collection request currently approved under 
0938-0907. There are no proposed changes to the currently approved 
information collection request associated with this rulemaking; 
however, we note that the information collection expires September 30, 
2022.
    Section III.I.2.a. of the preamble of this proposed rule, FY 2023 
Reclassification Application Requirements and Approvals, references the 
information collection request 0938-0573 which expired on January 31, 
2021. A reinstatement of the information collection request is 
currently being developed. The public will have an opportunity to 
review and submit comments regarding the reinstatement of this PRA 
package through a public notice and comment period separate from this 
rulemaking.
3. ICRs for Payments for Low-Volume Hospitals
    As discussed in section V.C. of this proposed rule, in accordance 
with section 1886(d)(12) of the Act, beginning with FY 2023, the low-
volume hospital definition and payment adjustment methodology will 
revert back to the statutory requirements that were in effect prior to 
the amendments made by the Affordable Care Act and subsequent 
legislation. Therefore, effective for FY 2023 and subsequent years, 
under current policy at Sec.  412.101(b), in order to qualify as a low-
volume hospital, a subsection (d) hospital must be more than 25 road 
miles from another subsection (d) hospital and have less than 200 
discharges during the fiscal year. In that section we also discuss the 
process for requesting and obtaining the low-volume hospital payment 
adjustment under Sec.  412.101. Specifically, a hospital makes a 
written request to its MAC that contains sufficient documentation to 
establish that the hospital meets the applicable statutory mileage and 
discharge criteria. While this information collection requirement would 
normally be subject to the PRA, we believe in this instance it is 
exempt. Based on historical data, we estimate there are fewer than 5 
hospitals among all subsection (d) hospitals that will meet the 
applicable mileage and discharge criteria for FY 2023. In accordance 
with the implementing regulations of the PRA at 5 CFR 1320.3(c)(4), the 
proposed requirement would be exempt as it affects less than 10 
entities in a 12-month period.
4. 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 1,572,810 hours of burden and 
approximately $65 million under OMB control number 0938-1022 
(expiration date December 31, 2022), accounting for information 
collection burden experienced by approximately 3,300 IPPS hospitals and 
1,100 non-IPPS hospitals for the FY 2024 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.

[[Page 28628]]

    For more detailed information on our proposed policies for the 
Hospital IQR Program, we refer readers to section IX.E. of the preamble 
of this proposed rule. We are proposing the adoption of four measures 
that we expect to affect our collection of information burden 
estimates: (1) The Hospital Commitment to Health Equity structural 
measure, beginning with the CY 2023 reporting period/FY 2025 payment 
determination and for subsequent years; (2) the Screening for Social 
Drivers of Health measure, beginning with voluntary reporting for the 
CY 2023 reporting period and mandatory reporting beginning with the CY 
2024 reporting period/FY 2026 payment determination; (3) the Screen 
Positive Rate for Social Drivers of Health measure, beginning with 
voluntary reporting for the CY 2023 reporting period and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination; and (4) the Hospital-level THA/TKA PRO-PM, beginning 
with voluntary reporting across two periods, followed by mandatory 
reporting of the measure for the reporting period which runs from July 
1, 2025 through June 30, 2026, impacting the FY 2028 payment 
determination. We are also proposing a modification to our eCQM 
reporting and submission requirements whereby we would increase the 
total number of eCQMs to be reported from four to six eCQMs beginning 
with the CY 2024 reporting period/FY 2026 payment determination, which 
would additionally affect our collection of information burden. The 
estimated collection of burden associated with these proposals is 
discussed in this section of this proposed rule.
    We are also proposing policies which would not affect the 
information collection burden associated with the Hospital IQR Program. 
As discussed in section IX.E. of the preamble of this proposed rule, we 
are proposing to adopt four eCQMs: (1) Cesarean Birth electronic 
clinical quality measure (eCQM), beginning with the CY 2023 reporting 
period/FY 2025 payment determination, followed by mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (2) Severe Obstetric Complications eCQM, beginning with 
the CY 2023 reporting period/FY 2025 payment determination, followed by 
mandatory reporting beginning with the CY 2024 reporting period/FY 2026 
payment determination; (3) Hospital-Harm--Opioid-Related Adverse Events 
eCQM, beginning with the CY 2024 reporting period/FY 2026 payment 
determination; and (4) Global Malnutrition Composite Score eCQM, 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination. We are also proposing the adoption of two claims-based 
measures beginning with the FY 2024 payment determination: (1) MSPB 
Hospital; and (2) the Hospital-Level RSCR Following Elective Primary 
THA/TKA. We are proposing refinements to current Hospital IQR Program 
claims-based measures beginning with the FY 2024 payment determination: 
(1) Hospital-Level, Risk-Standardized Payment Associated with an 
Episode of Care for Primary Elective THA/TKA; and (2) The Acute 
Myocardial Infarction (AMI) Excess Days in Acute Care (EDAC). Lastly, 
we are proposing to: (1) Establish a hospital designation related to 
patient care to be publicly-reported on a public-facing website 
beginning in Fall 2023; (2) modify our case threshold exemptions and 
zero denominator declaration policies for hybrid measures as we believe 
they are not applicable for this measure type beginning with the FY 
2026 payment determination; and (3) modify our eCQM validation policy 
to increase the reporting of medical requests from 75 percent of 
records to 100 percent of records, beginning with the validation of CY 
2022 eCQM data affecting the FY 2025 payment determination.
    The most recent data from the Bureau of Labor Statistics reflects a 
median hourly wage of $21.20 per hour for a medical records and health 
information technician professional.\1461\ 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 ($21.20 x 2 = $42.40) to estimate total cost is a 
reasonably accurate estimation method. Accordingly, unless otherwise 
specified, we will calculate cost burden to hospitals using a wage plus 
benefits estimate of $42.40 per hour throughout the discussion in this 
section of this rule for the Hospital IQR Program.
---------------------------------------------------------------------------

    \1461\ U.S. Bureau of Labor Statistics. Occupational Outlook 
Handbook, Medical Records and Health Information Technicians. 
Accessed on January 13, 2022; available at: https://www.bls.gov/oes/current/oes292098.htm.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45507), our burden 
estimates were based on an assumption of approximately 3,300 IPPS 
hospitals. For this proposed rule, we are updating our assumption to 
3,150 IPPS hospitals based on recent data from the FY 2022 Hospital IQR 
Program payment determination which reflects a closer approximation of 
the total number of hospitals reporting data to the Hospital IQR 
Program.
b. Information Collection Burden Estimate for the Hospital Commitment 
to Health Equity Structural Measure Beginning With the CY 2023 
Reporting Period/FY 2025 Payment Determination
    In section IX.E.5.a. of the preamble of this proposed rule, we are 
proposing the adoption of the Hospital Commitment to Health Equity 
structural measure beginning with the CY 2023 reporting period/FY 2025 
payment determination. Hospitals would report data through the Hospital 
Quality Reporting (HQR) System.
    We are proposing to require hospitals 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, on average across all 3,150 IPPS hospitals, no more than 10 minutes 
per hospital per year, as it involves attesting to as many as five 
questions one time per year for a given reporting period. While we 
understand some hospitals may require more than 10 minutes to research 
the information needed to respond, we believe that the majority of 
hospitals will have the information readily available to respond to the 
questions listed in section IX.E.5.a. of the preamble of this proposed 
rule and will require less than 10 minutes. In addition, we believe 
that many hospitals would be able to submit similar responses in future 
years, thereby reducing the actual time to respond in subsequent 
reporting periods. Using the estimate of 10 minutes (or 0.167 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 525 hours across all participating IPPS hospitals 
(0.167 hours x 3,150 IPPS hospitals) at a cost of $22,260 (525 hours x 
$42.40). With respect to any costs/burdens unrelated to data 
submission, we refer readers to the Regulatory Impact Analysis (section 
I.K. of Appendix A of this proposed rule).

[[Page 28629]]

c. Information Collection Burden Estimate for the Screening for Social 
Drivers of Health Measure Beginning With Voluntary Reporting in the CY 
2023 Reporting Period and Mandatory Reporting in the CY 2024 Reporting 
Period/FY 2026 Payment Determination
    In section IX.E.5.b.(1). of the preamble of this proposed rule, we 
are proposing the adoption of the Screening for Social Drivers of 
Health measure beginning with voluntary reporting in the CY 2023 
reporting period and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination. Hospitals would report 
data through the HQR System.
    As discussed in the preamble of this proposed rule, hospitals would 
be able to collect data and report the measure via multiple methods. We 
believe that most hospitals would likely collect data through a 
screening tool incorporated into their electronic health record (EHR) 
or other patient intake process.
    We believe the Outcome and Assessment Information Set (OASIS), 
which is currently used in the Home Health Quality Reporting Program, 
is a reasonable comparison for estimating the information collection 
burden for the Screening for Social Drivers of Health measure due to 
analogous assessment of patient-level need. The OASIS is a core 
standard assessment data set home health agencies integrate into their 
own patient-specific, comprehensive assessment to identify each 
patient's need for home care that meets the patient's medical, nursing, 
rehabilitative, social, and discharge planning needs. For OASIS, the 
currently approved information collection burden under OMB 0938-1279 
(expiration date November 30, 2024) is estimated to be 0.3 minutes per 
data element (18 seconds). For the five HRSN domains screened for by 
the proposed Social Drivers of Health measure under the Hospital IQR 
Program, we estimate a total of 2 minutes (0.033 hours) per patient to 
conduct this screening. The most recent data from the Bureau of Labor 
Statistics reflects an Average Hourly Earnings of $31.31.\1462\ Based 
on information collected by the American Hospital Association,\1463\ we 
estimate approximately 21,000,000 patients (34,251,159 total admissions 
in U.S. community hospitals x 3,150 IPPS hospitals / 5,198 total U.S. 
community hospitals) will be screened annually across all participating 
IPPS hospitals. For the purposes of calculating burden, we estimate 
that during the voluntary period, 50 percent of hospitals will survey 
50 percent of patients. We estimate during the mandatory period, 
hospitals would submit for 100 percent of patients. For the CY 2023 
voluntary reporting period, we estimate a total burden of 175,000 hours 
(21,000,000 respondents x 50 percent of patients x 50 hospitals of 
hospitals x 0.033 hours) at a cost of $5,479,250 (175,000 hours x 
$31.31) across all participating IPPS hospitals. For the CY 2024 
reporting period and subsequent years, we estimate a total annual 
burden of 700,000 hours (21,000,000 respondents x 0.033 hours) at a 
cost of $21,917,000 (700,000 hours x $31.31) across all participating 
IPPS hospitals.
---------------------------------------------------------------------------

    \1462\ U.S. Bureau of Labor Statistics. Economy at a Glance, 
Average Hourly Earnings. Accessed on January 24, 2022; available at: 
https://www.bls.gov/eag/eag.us.htm.
    \1463\ https://www.aha.org/system/files/media/file/2020/01/2020-aha-hospital-fast-facts-new-Jan-2020.pdf.
---------------------------------------------------------------------------

    Measure data would be submitted via the HQR System annually. 
Similar to the currently approved data submission and reporting burden 
estimate for eCQMs in the Hospital IQR Program and web-based measures 
for the Ambulatory Surgical Center Quality Reporting (ASCQR) Program 
(OMB control number 0938-1270; expiration date July 31, 2024) reported 
via the HQR System, we estimate a burden of 10 minutes per hospital 
response to transmit the measure data. Therefore, we estimate that each 
participating facility will spend 10 minutes (0.1667 hours) annually to 
collect and submit the data via this portal. For the purposes of 
calculating burden, we estimate that during the voluntary period, 50 
percent of hospitals will submit data. For the CY 2023 voluntary 
reporting period, we estimate a total burden of 263 hours (0.1667 hours 
x 3,150 hospitals x 50 percent of hospitals) at a cost of $11,151 (263 
hours x $42.40) across all participating IPPS hospitals. For the CY 
2024 reporting period and subsequent years, we estimate a total annual 
burden for all participating IPPS hospitals of 525 hours (0.1667 hours 
x 3,150 hospitals) at a cost of $22,260 (525 hours x $42.40).
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this proposed rule).
d. Information Collection Burden Estimate for the Screen Positive Rate 
for Social Drivers of Health Process Measure Beginning With Voluntary 
Reporting in the CY 2023 Reporting Period and Mandatory Reporting 
Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination
    In section IX.E.5.b.(2). of the preamble of this proposed rule, we 
are proposing the adoption of the Screen Positive Rate for Social 
Drivers of Health measure beginning with voluntary reporting in the CY 
2023 reporting period and mandatory reporting beginning with the CY 
2024 reporting period/FY 2026 payment determination. Hospitals would 
report data through the HQR System. For this measure, hospitals would 
be required to report on an annual basis the number of patients who 
screen positive for one or more of the five domains (reported as five 
separate rates) divided by the total number of patients screened.
    We previously included the burden associated with screening 
patients in our discussion of the Screening for Social Drivers of 
Health measure. For this measure, we estimate only the additional 
burden for a hospital reporting via the HQR System since patients would 
not need to provide any additional information for this measure. We 
estimate that each participating facility will spend 10 minutes (0.1667 
hours) annually to collect and submit the data. For the purposes of 
calculating burden, we estimate that during the voluntary period, 50 
percent of hospitals would submit data. For the CY 2023 voluntary 
reporting period, we estimate a total burden of 263 hours (0.1667 hours 
x 3,150 hospitals x 50 percent of hospitals) at a cost of $11,130 (263 
hours x $42.40) across all participating IPPS hospitals. For the CY 
2024 reporting period and subsequent years, we estimate a total annual 
burden estimate for all IPPS hospitals of 525 hours (0.1667 hours x 
3,150 hospitals) at a cost of $22,260 (525 hours x $42.40).

[[Page 28630]]

e. Information Collection Burden Estimate for the Hospital-Level, Risk 
Standardized Patient-Reported Outcomes Performance Measure (PRO-PM) 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) Beginning With Two Voluntary Reporting Periods 
Followed by Mandatory Reporting for Eligible Elective Procedures 
Occurring July 1, 2025 Through June 30, 2026, Impacting the FY 2028 
Payment Determination, and for Subsequent Years
    In section IX.E.5.g. of the preamble of this proposed rule, we are 
proposing the adoption of the THA/TKA PRO-PM beginning with voluntary 
reporting across two periods (July 1, 2023 through June 30, 2024 and 
July 1, 2024 through June 30, 2025), followed by mandatory reporting of 
the measure beginning with the reporting period which runs from July 1, 
2025 through June 30, 2026, impacting the FY 2028 payment 
determination.
    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. We estimate 
no additional burden associated with claims data, Medicare enrollment 
and beneficiary data, and U.S. Census Bureau survey data as these data 
are already collected via other mechanisms.
    Many hospitals have already incorporated patient-reported outcome 
(PRO) data collection into their workflows. While we are not proposing 
to require how hospitals collect data, hospitals new to collecting PRO 
data have multiple options for when and how they would collect this 
data so they can best determine the mode and timing of collection that 
works best for their patient population. The possible patient 
touchpoints for pre-operative PRO data collection include the doctor's 
office, pre-surgical steps such as education classes, or medical 
evaluations that can occur in an office or at the hospital. The modes 
of PRO data collection can include completion of the pre-operative 
surveys using electronic devices (such as an iPad or tablet), pen and 
paper, mail, phone call, or through the patient's portal. Post-
operative PRO data collection modes are similar to pre-operative modes. 
The possible patient touchpoints for post-operative data collection can 
occur before the follow-up appointment, at the doctor's office, or 
after the follow-up appointment. The potential modes of PRO data 
collection for post-operative data are the same as for pre-operative 
data. If the patient does not or cannot attend a follow-up appointment, 
the modes of collection can include completion of the post-operative 
survey using email, mail, phone, or through the patient portal. Use of 
multiple modes would increase response rates as it allows for different 
patient preferences.
    For the THA/TKA PRO-PM data, we are proposing that hospitals would 
be able to submit data during two voluntary periods, followed by 
mandatory reporting for eligible elective procedures occurring July 1, 
2025 through June 30, 2026, impacting the FY 2028 payment determination 
and for subsequent years. Hospitals would need to submit data twice 
(pre-operative data and post-operative data). For the purposes of 
calculating burden, we estimate that during the voluntary periods, 50 
percent of hospitals that perform at least one THA/TKA procedure would 
submit data, and would do so for 50 percent of THA/TKA patients. We 
estimate during the mandatory period, hospitals would submit for 100 
percent of patients. While we are proposing that hospitals would be 
required to submit, at minimum, 50 percent of eligible, complete pre-
operative data with matching eligible, complete post-operative data, we 
are conservative in our estimate for the mandatory period in case 
hospitals exceed this currently proposed threshold.
    Under OMB control number 0938-0981 (expiration date September 30, 
2024), the currently approved burden per respondent to complete the 
Hospital Consumer Assessment of Healthcare Providers and Systems 
(HCAHPS) Survey measure is 7.25 minutes (0.120833 hours). We estimate 
that the time to complete both the preoperative and post-operative 
surveys is analogous to completing the HCAHPS Survey once. The most 
recent data from the Bureau of Labor Statistics reflects an Average 
Hourly Earnings of $31.31.\1464\ For burden estimating purposes, we 
assume that most hospitals will likely undertake PRO data collection 
through a screening tool incorporated into their EHR or other patient 
intake process. We estimate that approximately 330,000 THA/TKA 
procedures occur in the inpatient setting each year, and that many 
patients could complete both the pre-operative and postoperative 
questionnaires, although from our experience with using this measure in 
the Comprehensive Joint Replacement model, we are also aware that not 
all patients who complete the pre-operative questionnaire would 
complete the post-operative questionnaire. Due to the performance 
period for the first voluntary reporting period being 6 months, we 
assume 41,250 patients will complete the survey (165,000 patients x 
0.50 x 0.50 of hospitals) for a total of 4,984 hours annually (41,250 
respondents x 0.120833 hours) at a cost of $156,049 (4,984 hours x 
$31.31) across all IPPS hospitals. For the second voluntary reporting 
periods, we assume 82,500 patients will complete the survey (330,000 
patients x 0.50 x 0.50 hospitals) for a total of 9,969 hours annually 
(82,500 respondents x 0.120833 hours) at a cost of $312,122 (9,969 
hours x $31.31) across all IPPS hospitals. Beginning with mandatory 
reporting for the FY 2028 payment determination, we estimate a total of 
39,875 hours (330,000 patients x 0.120833 hours) at a cost of 
$1,248,486 (39,875 hours x $31.31) across all IPPS hospitals.
---------------------------------------------------------------------------

    \1464\ U.S. Bureau of Labor Statistics. Economy at a Glance, 
Average Hourly Earnings. Accessed on January 24, 2022; available at: 
https://www.bls.gov/eag/eag.us.htm.
---------------------------------------------------------------------------

    For the data submission, which would be reported via the HQR 
System, we estimate a burden of 10 minutes per response. For each of 
the two voluntary reporting periods, we estimate that each hospital 
will spend 20 minutes (0.33 hours) annually (10 minutes x 2 surveys) to 
collect and submit the data via this tool. We estimate a resulting 
burden for all participating IPPS hospitals of 525 hours (0.33 hours x 
3,150 hospitals x 50 percent) at a cost of $22,260 (525 hours x 
$42.40). Beginning with mandatory reporting for the FY 2028 payment 
determination, we estimate a total of 1,050 hours (0.33 hours x 3,150 
hospitals) at a cost of $44,520 (1,050 hours x $42.40).
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this proposed rule).
f. Information Collection Burden Estimate for the Modification of the 
eCQM Reporting and Submission Requirements Beginning With the CY 2024 
Reporting Period/FY 2026 Payment Determination
    In section IX.E.10.e. of the preamble of this proposed rule, we are 
proposing a modification to our eCQM reporting and submission 
requirements whereby we are increasing the total number of eCQMs to be 
reported from four to six eCQMs beginning with the CY 2024 reporting 
period/FY 2026 payment determination.
    We previously finalized in the FY 2020 IPPS/LTCH PPS final rule 
that, for the CY 2021 reporting period/FY 2023

[[Page 28631]]

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 in the FY 2021 IPPS/LTCH PPS final rule to 
require hospitals to submit four quarters of eCQM data beginning in the 
CY 2023 reporting period/FY 2025 payment determination (85 FR 59008 
through 59009). We continue to estimate the information collection 
burden associated with the eCQM reporting and submission requirements 
to be 10 minutes per measure per quarter. For the increase in 
submission from four to six eCQMs, we estimate a total of 20 minutes or 
0.33 hours (10 minutes x 2 eCQMs) per hospital per quarter. We estimate 
a total burden increase of 1,050 hours across all participating IPPS 
hospitals (0.33 hour x 3,150 IPPS hospitals) for each quarter of eCQM 
data or 4,200 hours annually (1,050 hours x 4 quarters) at a cost of 
$178,080 (4,200 hours x $42.40).
g. Information Collection Burden Estimate for the Adoption of Four 
eCQMs: Two Perinatal eCQMs Beginning With the CY 2023 Reporting Period/
FY 2025 Payment Determination; One Opioid-Related Hospital-Harm eCQM 
and One Malnutrition eCQM Beginning With the CY 2024 Reporting Period/
FY 2026 Payment Determination
    In sections IX.E.5.c. and IX.E.5.d. of the preamble of this 
proposed rule, we are proposing to adopt two perinatal eCQMs--Cesarean 
Birth and Severe Obstetric Complications--beginning with the CY 2023 
reporting period/FY 2025 payment determination, followed by mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years. Also, in sections IX.E.5.e. and 
IX.E.5.f. of the preamble of this proposed rule, we are proposing to 
adopt the Hospital-Harm--Opioid-Related Adverse Events eCQM and the 
Global Malnutrition Composite Score eCQM, respectively, beginning with 
the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years.
    We do not believe that these proposals to add four eCQMs will 
affect the information collection burden of submitting eCQMs under the 
Hospital IQR Program. Current Hospital IQR Program policy requires 
hospitals to select four eCQMs from the eCQM measure set on which to 
report (84 FR 42503 through 4250). In other words, while these 
provisions will result in new eCQMs being added to 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) or six eCQMs, if the 
proposal discussed in section IX.E.10.e. of the preamble of this 
proposed rule is finalized. In the previous section XII.B.4.f. (of the 
Collection of Information section of this proposed rule), we account 
for the burden of reporting six eCQMs.
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this proposed rule).
h. Information Collection Burden Estimate for the Adoption or 
Refinement of Four Claims-Based Measures
    In sections IX.E.5.h., IX.E.5.i., IX.E.6.a., and IX.E.6.b. of the 
preamble of this proposed rule, we are proposing to adopt two claims-
based measures--MSPB Hospital and Hospital-Level RSCR Following 
Elective Primary THA/TKA--and refine two claims-based measures 
currently in the Hospital IQR Program measure set--Hospital-Level, 
Risk-Standardized Payment Associated with an Episode of Care for 
Primary Elective THA/TKA and AMI EDAC. We are proposing to adopt the 
Hospital MSPB measure and the Hospital-Level RSCR Following Elective 
Primary THA/TKA beginning with the FY 2024 payment determination and 
are proposing refinements to the other two measures beginning with the 
FY 2024 payment determination and for subsequent years. Because these 
measures are calculated using data that are already reported to the 
Medicare program for payment purposes, adopting and refining these 
measures will not result in a change to the burden estimates provided 
in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45507 through 45512).
i. Information Collection Burden Estimate for Addition of the Publicly-
Reported Hospital Designation To Capture Hospital Commitment to the 
Quality and Safety of Maternal Health Beginning Fall 2023
    In section IX.E.8. of the preamble of this proposed rule, we are 
proposing to establish the publicly-reported hospital designation to 
capture hospital commitment to the quality and safety of maternity care 
on a CMS website, for hospitals who qualify for the designation, 
beginning in Fall 2023. In the FY 2022 IPPS/LTCH PPS final rule, we 
finalized adoption of the Maternal Morbidity Structural measure (86 FR 
45365) and accounted for that burden under OMB control number 0938-1022 
(expiration date December 31, 2022). We expect that our policy will not 
yield a change in burden as it does not require any additional 
information collection nor affect the requirements for data submission 
for hospitals.
j. Information Collection Burden Estimate for the Modification of the 
Case Threshold Exemptions and Zero Denominator Declaration Policies for 
Hybrid Measures Beginning With the FY 2026 Payment Determination
    In section IX.E.10.f.(4). of the preamble of this proposed rule, we 
are proposing to modify our case threshold exemptions and zero 
denominator declaration policies for hybrid measures as we believe they 
are not applicable for those measure types, beginning with the FY 2026 
payment determination and for subsequent years.
    In the FY 2020 IPPS/LTCH PPS final rule, we finalized the adoption 
of the Hybrid Hospital-Wide Readmission Measure with Claims and 
Electronic Health Record Data (Hybrid HWR) (84 FR 42505 through 42508) 
and in the FY 2022 IPPS/LTCH PPS final rule, we finalized the Hybrid 
Hospital-Wide Mortality Measure with Claims and Electronic Health 
Record Data (Hybrid HWM) (86 FR 45508). For each hybrid measure, all 
IPPS hospitals are required to submit one of three things: Data via 
QRDA I file, a zero denominator declaration, or a case threshold 
exemption. Of these three options, submission of data via QRDA I file 
is the most burden-intensive. For both hybrid measures, our currently 
approved burden estimates assume data submission via QRDA I file for 
all IPPS hospitals; therefore, we do not believe this proposal will 
result in an increase in burden.
k. Information Collection Burden Estimate for the Modification of the 
eCQM Validation Policy Medical Record Requests Beginning With the FY 
2025 Payment Determination
    In section IX.E.11.b. of the preamble of this proposed rule, we are 
proposing to modify our eCQM validation policy to increase the 
reporting of medical requests from at least 75 percent of records to 
100 percent of records beginning with the FY 2025 payment determination 
and for subsequent years.
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized to require 
submission of at least 75 percent of sampled eCQM medical records in a 
timely and complete manner (81 FR 57181). While we adopted a policy to 
require

[[Page 28632]]

submission of at least 75 percent of sampled records, we estimated the 
burden associated with this finalized policy with the assumption that 
hospitals would submit 100 percent of sampled eCQM medical records (81 
FR 57261). Based on this estimate, we believe the currently approved 
burden already encompasses burden associated with our proposed policy.
l. Information Collection Burden Estimate To Add Reporting and 
Submission Requirements for PRO-PMs Beginning With the FY 2026 Payment 
Determination
    In section IX.E.10.k. of the preamble of this proposed rule, we are 
proposing reporting and submission requirements for PRO-PMs beginning 
with the FY 2026 payment determination. We expect that our policy will 
not yield a change in burden beyond that which is discussed in section 
X.B.6.e. of the preamble of this proposed rule for the THA/TKA PRO-PM.
m. Summary of Information Collection Burden Estimates for the Hospital 
IQR Program
    In summary, under OMB control number 0938-1022 (expiration date 
December 31, 2022), we estimate that the policies promulgated in this 
proposed rule will result in a total increase of 746,300 hours annually 
for 3,150 IPPS hospitals from the CY 2023 reporting period/FY 2025 
payment determination through the CY 2026 reporting period/FY 2028 
payment determination. The total cost increase related to this 
information collection is approximately $23,437,906. The subsequent 
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 2028 payment 
determination reflects the total burden change associated with all 
proposals). For the THA/TKA PRO-PM, only one survey would be 
administered during the CY 2023 reporting period due to the start of 
reporting occurring in 3Q and the beginning of mandatory reporting 
would take place in 3Q of the CY 2025 reporting period. We will submit 
the revised information collection estimates to OMB for approval under 
OMB control number 0938-1022 which expires December 31, 2022.
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5. ICRs for PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program
    OMB has currently approved 0 hours of burden under OMB control 
number 0938-1175 (expiration date January 31, 2025), accounting for the 
information collection requirements for 11 PCHs for the FY 2024 program 
year.
    For more detailed information on our proposed policies for the 
PCHQR Program, we refer readers to section IX.F. of the preamble of 
this proposed rule. We are proposing to: (1) Adopt and codify a patient 
safety exemption for the measure removal policy; (2) begin public 
display of the End-of-Life (EOL) measures beginning with FY 2024 
program year data; and (3) begin public display of the 30-Day Unplanned 
Readmissions for Cancer Patients measure beginning with FY 2024 program 
year data. We do not expect that any of these proposals will impact our 
currently approved information collection burden estimates.
6. ICRs for the Hospital Value-Based Purchasing (VBP) Program
    In section V.I. 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 to suppress the Hospital Consumer Assessment of Healthcare 
Providers and Systems (HCAHPS) Survey and the five healthcare-
associated infection (HAI) measures for the FY 2023 program year. We 
are also proposing to continue requiring hospitals to report data for 
all measures, including measures we are proposing to suppress for FY 
2023. Because the 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.
7. ICRs Relating to 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.\1465\ The HAC

[[Page 28636]]

Reduction Program has previously adopted six measures: The CMS PSI 90 
measure and five CDC NHSN HAI measures. We do not believe that the 
claims-based CMS PSI 90 measure in the HAC Reduction Program creates 
additional burden for hospitals because the measure is calculated using 
the Medicare FFS claims that hospitals have submitted to the Medicare 
program for payment purposes. Accordingly, we do not believe that our 
proposed policies in sections V.J.3.c.(1). and V.J.2.b.(2). to increase 
the minimum volume threshold and suppress the CMS PSI 90 measure from 
the FY 2023 HAC Reduction program change any information collection 
burden for hospitals.
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    \1465\ Burden associated with the validation procedures in the 
HAC Reduction Program are accounted for under OMB Control Number 
0938-1352.
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    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 CDC's NHSN system is captured 
under a separate OMB control number, 0920-0666 (expiration January 1, 
2025). As discussed in sections V.J.2.b.(2). and V.J.2.b.(3). of the 
preamble of this proposed rule, we are proposing to suppress the five 
NHSN measures, in addition to the claims-based CMS PSI 90 measure, from 
the FY 2023 HAC Reduction Program. We propose to suppress CY 2021 CDC 
NHSN HAI data from the FY 2024 program year. Because hospitals would 
continue to report data for the HAI measures, this proposal would not 
change information collection burden for hospitals as accounted for 
under CDC's OMB control number 0920-1066.
    In section V.J.7. of the preamble of this proposed rule, we clarify 
the removal of the No Mapped Locations (NML) policy beginning in FY 
2023. Hospitals will be required to appropriately submit data to the 
NHSN or, if hospitals do not have the applicable locations for the 
CLABSI and CAUTI measures, the hospital must submit an IPPS Measure 
Exception Form to be exempt from CLABSI and CAUTI reporting for CMS 
programs. The burden for all hospitals to submit data to the NHSN is 
already accounted for under OMB control number 0920-0666, therefore 
there is no increase in burden for hospitals which submit data as a 
result of this clarification. In addition, the burden associated with 
completion of forms (including the IPPS Measure Exception Form) is 
already accounted for under OMB control number 0938-1022, therefore 
there is no increase in burden for hospitals which elect to submit this 
form as a result of this clarification. We are currently assessing 
whether this clarification will necessitate changes to the IPPS Measure 
Exception Form, however we believe that if changes are necessary, the 
change in burden will be negligible and our currently approved burden 
estimates under OMB control number 0938-1022 are conservative enough to 
accommodate the change. If the IPPS Measure Exception Form is revised, 
we will submit the new version for approval under OMB control number 
0938-1022.
8. ICRs Relating to the Hospital Readmissions Reduction Program
    In section V.H. 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 2023. 
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.
9. ICRs for the Promoting Interoperability Program
a. Historical Background
    In section IX.H. of the preamble of this proposed rule, we 
discussed several proposals for the Medicare Promoting Interoperability 
Program. An information collection request under OMB control number 
0938-1278 (expiration date March 31, 2022) reflecting program policies 
finalized in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45514) is 
pending approval, which includes an estimated total burden of 21,450 
hours and $879,450, accounting for information collection burden 
experienced by approximately 3,300 eligible hospitals that attest to 
CMS under the Medicare Promoting Interoperability Program. We will be 
submitting an updated information collection request under OMB control 
number 0938-1278 in connection with the proposals in this FY 2023 IPPS/
LTCH PPS proposed rule that will reflect the inclusion of CAHs and 
additional new information pertinent to the collection requirements. 
The collection of information burden analysis in this proposed rule 
focuses on all eligible hospitals and CAHs that could participate in 
the Medicare Promoting Interoperability Program and attest to the 
objectives and measures, and report eCQMs, under the Medicare Promoting 
Interoperability Program for the EHR reporting periods in CY 2023, CY 
2024, and CY 2025.
    For more detailed information on our proposed policies for the 
Medicare Promoting Interoperability Program, we refer readers to 
section IX.H. of the preamble of this proposed rule. We are proposing 
the following changes for eligible hospitals and CAHs that attest to 
CMS under the Medicare Promoting Interoperability Program that we 
expect to affect our collection of information burden estimates: (1) To 
require the Electronic Prescribing Objective's Query of Prescription 
Drug Monitoring Program (PDMP) measure beginning in the CY 2023 
electronic health record (EHR) reporting period while maintaining its 
associated points at 10 points and adding exclusions; (2) to adopt a 
new Antimicrobial Use and Resistance (AUR) Surveillance measure that 
would be required for eligible hospitals and CAHs under the Medicare 
Promoting Interoperability Program's Public Health and Clinical Data 
Exchange Objective with associated exclusions beginning with the CY 
2023 EHR reporting period and (3) to require eligible hospitals and 
CAHs to submit their level of active engagement in addition to 
submitting responses for the Public Health and Clinical Data Exchange 
Objective required measures and the optional measures beginning with 
the CY 2023 EHR reporting period. We are also proposing a modification 
to our eCQM reporting and submission requirements whereby we are 
increasing the total number of eCQMs to be reported from four to six 
eCQMs beginning with the CY 2024 reporting period. 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 policies which would not affect the 
information collection burden associated with the Medicare Promoting 
Interoperability Program. As discussed in section IX.H.10.a.(2) of the 
preamble to this proposed rule, we are proposing to adopt four eCQMs: 
(1) Severe Obstetric Complications eCQM beginning with the CY 2023 
reporting period, followed by mandatory reporting beginning with the CY 
2024 reporting period; (2) Cesarean Birth (ePC-02) eCQM beginning with 
the CY 2023 reporting period, followed by mandatory reporting beginning 
with the CY 2024 reporting period; (3) Hospital-Harm--

[[Page 28637]]

Opioid-Related Adverse Events eCQM beginning with the CY 2024 reporting 
period; and (4) Global Malnutrition Composite Score eCQM beginning with 
the CY 2024 reporting period. We are also proposing: (1) To expand the 
Query of PDMP measure to include Schedule II, III, and IV drugs 
beginning with the CY 2023 EHR reporting period; (2) to add the 
Enabling Exchange Under TEFCA measure to the Health Information 
Exchange Objective as an optional alternative to the three existing 
measures and to update the scoring methodology for the Health 
Information Exchange Objective beginning in the CY 2023 EHR reporting 
period; (3) to reduce the active engagement options for the Public 
Health and Clinical Data Exchange Objective from three to two options 
beginning with the CY 2023 EHR reporting period; (4) to modify the 
scoring methodology for the Medicare Promoting Interoperability Program 
beginning in the CY 2023 EHR reporting period; (5) to institute public 
reporting of certain Medicare Promoting Interoperability Program data 
beginning with data from the CY 2023 EHR reporting period; and (6) to 
remove regulation text for the objectives and measures under 42 CFR 
495.24(e) and add new paragraph (f) beginning in CY 2023.
    The most recent data from the Bureau of Labor Statistics reflects a 
median hourly wage of $21.20 per hour for a medical records and health 
information technician professional.\1466\ 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 publicly available literature. Nonetheless, we believe that 
doubling the hourly wage rate ($21.20 x 2 = $42.40) to estimate total 
cost is a reasonably accurate estimation method and is consistent with 
OMB guidance. Accordingly, we will calculate cost burden to hospitals 
using a wage plus benefits estimate of $42.40 per hour throughout the 
discussion in this section of this rule for the Medicare Promoting 
Interoperability Program.
---------------------------------------------------------------------------

    \1466\ U.S. Bureau of Labor Statistics. Occupational Outlook 
Handbook, Medical Records and Health Information Technicians. 
Accessed on January 13, 2022; available at: https://www.bls.gov/oes/current/oes292098.htm.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45514), our burden 
estimates were based on an assumption of 3,300 eligible hospitals and 
CAHs. We have determined that our assumption was in error as we 
inadvertently omitted the number of CAHs in our estimate. For this 
proposed rule, we are updating our assumption to 3,150 eligible 
hospitals and 1,350 CAHs based on data from the CY 2020 EHR reporting 
period, for a total number of 4,500 respondents. These estimates differ 
from those of the information collection request under OMB control 
number 0938-1278 as they are based on updated data from the CY 2020 EHR 
reporting period and reflect the addition of the number of CAHs. As 
indicated earlier, an updated information collection request will be 
submitted with updated numbers inclusive of CAHs. We are making this 
adjustment to reflect the total number of potential eligible hospitals 
and CAHs that could report under the Medicare Promoting 
Interoperability Program.
b. Information Collection Burden Estimate for the Electronic 
Prescribing Objective's Query of PDMP Measure Beginning With the CY 
2023 EHR Reporting Period
    In section IX.H.3.c.(2) of the preamble of this proposed rule, we 
are proposing to require the Query of PDMP measure for eligible 
hospitals and CAHs participating in the Medicare Promoting 
Interoperability Program beginning in CY 2023 and maintain the 
associated points at 10 points.
    In the FY 2020 IPPS/LTCH PPS final rule, we estimated the burden 
associated with reporting the Electronic Prescribing Objective and 
associated measures to be 10 minutes (84 FR 42608) coinciding with the 
finalized change to the Query of PDMP measure to require a ``yes/no'' 
response instead of a numerator/denominator calculation. However, the 
burden associated with the Query of PDMP measure was not accounted for 
in the burden estimate of 10 minutes for the Electronic Prescribing 
Objective in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42608 through 
42609), the FY 2021 IPPS/LTCH PPS final rule (85 FR 59014), or the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45516). In the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45464), we finalized that the Query of PDMP 
measure will remain optional. As a result of the proposal to require 
the Query of PDMP measure beginning with the EHR reporting period in CY 
2023, and considering the burden estimate of 30 seconds (0.5 minutes) 
for similar ``yes/no'' response measures for the Public Health and 
Clinical Data Exchange Objective as reflected in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45515), we are updating our burden estimate for 
the Electronic Prescribing Objective to 10.5 minutes to reflect the 
additional burden of reporting the Query of PDMP measure. Therefore, we 
estimate a total increase in burden of 38 hours across all eligible 
hospitals and CAHs (0.5 minutes x 4,500 eligible hospitals and CAHs) 
annually at a cost of $1,590 (38 hours x $42.40).
    In addition, in section IX.H.3.c.(3) of the preamble of this 
proposed rule, we are proposing expanding the Query of PDMP measure to 
include Schedule II, III, and IV drugs beginning with the CY 2023 EHR 
reporting period. We expect that our policy will not yield a change in 
burden as it does not affect the requirements for data submission for 
eligible hospitals or CAHs as we continue to assume all eligible 
hospitals and CAHs would report this measure once per year.
c. Information Collection Burden Estimate for the Antimicrobial Use and 
Resistance (AUR) Surveillance Measure Beginning With the CY 2023 EHR 
Reporting Period
    In section IX.H.5.b. of the preamble of this proposed rule, we are 
proposing to require new Antimicrobial Use and Resistance (AUR) 
Surveillance measure for eligible hospitals and CAHs under the Medicare 
Promoting Interoperability Program's Public Health and Clinical Data 
Exchange Objective beginning with the CY 2023 EHR reporting period. 
Eligible hospitals and CAHs would be required to attest to active 
engagement with CDC's National Healthcare Safety Network (NHSN) to 
submit AUR data and receive a report from NHSN indicating their 
successful submission of AUR data for the EHR reporting period.
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized that eligible 
hospitals and CAHs are required to report four measures for the Public 
Health and Clinical Data Exchange Objective with a total estimated 
burden of 2 minutes annually (30 seconds x 4 measures) (86 FR 45516). 
Therefore, we estimate the burden associated with this new measure to 
be 30 seconds or 0.5 minutes per eligible hospital or CAH annually. We 
estimate a total increase in burden of 38 hours across all eligible 
hospitals and CAHs (0.5 minutes x 4,500 eligible hospitals and CAHs) 
annually at a cost of $1,611 (38 hours x $42.40).
    While the burden associated with attesting to active engagement 
with NHSN to submit data will be accounted for under OMB control number 
0938-1278 (expiration date March 31, 2022), the burden associated with 
the actual submission of AUR data to NHSN is accounted for under OMB 
control

[[Page 28638]]

number 0920-0666 (expiration date January 31, 2025).
d. Information Collection Burden Estimate for the Proposal To Require 
Eligible Hospitals and CAHs To Submit Their Level of Active Engagement 
for the Public Health and Clinical Data Exchange Objective Beginning 
With the CY 2023 EHR Reporting Period
    In section IX.H.5.c.(3) of the preamble of this proposed rule, we 
are proposing to require eligible hospitals and CAHs to submit their 
level of engagement for the measures under the Public Health and 
Clinical Data Exchange Objective, either Pre-production and Validation 
or Validated Data Production. This requirement would be in addition to 
submitting responses for the required measures and the optional 
measures, if applicable.
    We believe the burden associated with this requirement is similar 
to the burden associated with the attestation that eligible hospitals 
and CAHs must complete for the four previously finalized measures under 
this objective and the proposed AUR Surveillance measure. Therefore, we 
estimate the burden associated with this new requirement to be 30 
seconds or 0.5 minutes per eligible hospital or CAH annually. We 
estimate a total increase in burden of 38 hours across all eligible 
hospitals and CAHs (0.5 minutes/hospital x 4,500 eligible hospitals and 
CAHs) annually at a cost of $1,611 (38 hours x $42.40).
    In addition, in section IX.H.c.(2) of the preamble of this proposed 
rule, we are proposing to reduce the active engagement options for the 
Public Health and Clinical Data Exchange Objective from three to two 
options beginning with the CY 2023 EHR reporting period and require 
eligible hospitals and CAHs to spend only one EHR reporting period at 
the pre-production and validation phase. We expect that our policy will 
not yield a change in burden as it does not affect the requirements for 
data submission for eligible hospitals or CAHs but instead will 
motivate EHR vendors to implement these capabilities in their products 
and encourage healthcare organizations to engage in these reporting 
activities.
e. Information Collection Burden Estimate for the Modification of the 
eCQM Reporting and Submission Requirements Beginning With the CY 2024 
Reporting Period
    In section IX.H.10.b of the preamble of this proposed rule, we are 
proposing a modification to our eCQM reporting and submission 
requirements whereby we would increase the total number of eCQMs to be 
reported from four to six eCQMs beginning with the CY 2024 reporting 
period. We are also proposing that the six eCQMs must be comprised of: 
(1) Three self-selected eCQMs; (2) the Safe Use of Opioids--Concurrent 
Prescribing eCQM; (3) the proposed Severe Obstetric Complications eCQM; 
and (4) the proposed Cesarean Birth eCQM, for a total of six eCQMs.
    We previously finalized in the FY 2021 IPPS/LTCH PPS final rule 
that, for the CY 2023 reporting period, eligible hospitals and CAHs are 
required to submit data for three self-selected eCQMs each year and the 
Safe Use of Opioids-Concurrent Prescribing eCQM for a total of four 
eCQMs (85 FR 58975). We also finalized in the FY 2021 IPPS/LTCH PPS 
final rule to require eligible hospitals and CAHs to submit four 
quarters of eCQM data beginning in the CY 2023 reporting period (85 FR 
58975). We continue to estimate the information collection burden 
associated with the eCQM reporting and submission requirements to be 10 
minutes per measure per quarter. As discussed in the section IX.E.4.f. 
of the preamble of this proposed rule, we already account for the 
burden associated with the reporting of eCQM measures for eligible 
hospitals as part of the Hospital Inpatient Quality Reporting program, 
therefore the burden for the 3,150 eligible hospitals is included 
there. For the submission of six eCQM measures for CAHs, we estimate a 
total of 1 hour (0.167 hours/eCQM x 6 eCQMs) per CAH per quarter. We 
estimate a total burden of 1,350 hours across all CAHs (1 hour x 1,350 
CAHs) for each quarter of eCQM data or 5,400 hours annually (1,350 
hours x 4 quarters) at a cost of $228,960 (5,400 hours x $42.40).
f. Information Collection Burden Estimate for the Adoption of Two eCQMs 
Beginning With the CY 2023 Reporting Period and Two eCQMs Beginning 
With the CY 2024 Reporting Period
    In section IX.H.10.a. of the preamble of this proposed rule, we are 
proposing to adopt four eCQMs: (1) Severe Obstetric Complications eCQM 
beginning with the CY 2023 reporting period, followed by mandatory 
reporting beginning with the CY 2024 reporting period; (2) Cesarean 
Birth (ePC-02) eCQM beginning with the CY 2023 reporting period, 
followed by mandatory reporting beginning with the CY 2024 reporting 
period; (3) Hospital-Harm--Opioid-Related Adverse Events eCQM beginning 
with the CY 2024 reporting period; and (4) Global Malnutrition 
Composite Score eCQM beginning with the CY 2024 reporting period.
    We do not believe that these proposals to add four eCQMs would 
affect the information collection burden of submitting eCQMs under the 
Medicare Promoting Interoperability Program beyond the burden described 
in section IX.B.4.f. of the preamble of this proposed rule. Current 
Medicare Promoting Interoperability Program policy requires hospitals 
to submit data for three self-selected eCQMs each year and the Safe Use 
of Opioids--Concurrent Prescribing eCQM for a total of four eCQMs (85 
FR 58975). In other words, while these proposals would result in new 
eCQMs being added to the eCQM measure set, hospitals would not be 
required to report more than a total of four eCQMs as is currently 
required (84 FR 42603) or six eCQMs if the proposal discussed in 
section IX.10. of the preamble of this proposed rule is finalized.
    With respect to any costs unrelated to data submission, we refer 
readers to section I.K. of Appendix A of this proposed rule.
g. Information Collection Burden Estimate for the Proposal To Add the 
Enabling Exchange Under TEFCA Measure to the Health Information 
Exchange Objective Beginning With the CY 2023 EHR Reporting Period
    In section IX.H.4.c. of the preamble of this proposed rule, we are 
proposing to add the Enabling Exchange Under TEFCA measure to the 
Health Information Exchange Objective as an optional alternative to the 
three existing measures (Support Electronic Referral Loops by Sending 
Health Information measure, Support Electronic Referral Loops by 
Receiving and Reconciling Health Information measure, and the HIE Bi-
Directional Exchange measure) and to update the scoring methodology for 
the Health Information Exchange Objective beginning with the CY 2023 
EHR reporting period. We expect that our policy will not yield a change 
in burden as eligible hospitals and CAHs may choose to report the two 
Support Electronic Referral Loop measures, or may choose to report the 
HIE Bi-Directional Exchange measure, or may choose to report the 
proposed new Enabling Exchange Under TEFCA measure.

[[Page 28639]]

h. Information Collection Burden Estimate for the Proposal To Modify 
the Scoring Methodology for the Medicare Promoting Interoperability 
Program Beginning With the CY 2023 EHR Reporting Period
    In section IX.H.6. of the preamble of this proposed rule, we are 
proposing the following changes to the scoring methodology:
     Increasing the points allocated to the Public Health and 
Clinical Data Exchange Objective from 10 points to 25 points.
     Increasing the points allocated to the Electronic 
Prescribing Objective from 10 points to 20 points.
     Decreasing the points allocated to the Health Information 
Exchange Objective from 40 points to 30 points.
     Decreasing the points allocated to the Provide to Patient 
Exchange Objective from 40 points to 25 points.
    We expect that our policy will not yield a change in burden as it 
does not affect the requirements for data submission for eligible 
hospitals or CAHs but only changes the scoring methodology.
i. Information Collection Burden Estimate for the Proposal To Institute 
Public Reporting of Medicare Promoting Interoperability Program Data 
Beginning With Data From the CY 2023 EHR Reporting Period
    In section IX.H.7. of the preamble of this proposed rule, we are 
proposing to publicly report certain Medicare Promoting 
Interoperability Program data submitted by eligible hospitals and CAHs 
beginning with CY 2023 EHR reporting period. Specifically, we are 
proposing to publish eligible hospitals' and CAHs' final scores and the 
CMS EHR certification ID, beginning with data submitted for the CY 2023 
EHR reporting period. We expect that our policy will not yield a change 
in burden as it does not affect the requirements for data submission 
for eligible hospitals or CAHs.
j. Information Collection Burden Estimate for Proposed Modifications to 
Regulatory Text
    In section IX.H.8. of the preamble of this proposed rule, we are 
proposing remove references to objectives and measures and to make 
modifications to regulatory text at 42 CFR 495.24 beginning in CY 2023. 
We expect that our policy will not yield a change in burden as it does 
not affect the requirements for data submission for eligible hospitals 
or CAHs since the changes only seek to modify regulatory text.
k. Summary of Estimates Used To Calculate the Collection of Information 
Burden
    In summary, under OMB control number 0938-1278 (expiration date 
March 31, 2022), we estimate that the policies proposed in this 
proposed rule will result in a total increase in burden of 5,513 hours 
through the CY 2024 EHR reporting period. The total cost increase 
related to this information collection is approximately $233,730 (5,513 
hours x $42.40) across 4,500 eligible hospitals and CAHs. The tables 
summarize the total burden changes for CY 2023 and for CY 2024 EHR 
reporting periods compared to our currently approved information 
collection burden estimates (the table for the CY 2024 EHR reporting 
period reflects the total burden change associated with all proposals).
    In the FY 2022 IPPS/LTCH PPS final rule, we estimated each eligible 
hospital and CAH would require 6.5 hours annually to participate in the 
Medicare Promoting Interoperability Program (86 FR 45517). As a result 
of the policies in this proposed rule, we estimate the new total annual 
burden to be 6.6 hours per eligible hospital and CAH as well as an 
additional 4 hours annually for CAHs to report eCQMs. Therefore, we 
estimate the adjustment in the number of eligible hospitals and CAHs 
from 3,300 to 4,500 results in an increase of approximately +13,290 
hours ((6.6 hours x -150 eligible hospitals) + (10.6 hours x 1,350 
CAHs)) at a cost of +$563,496 (+13,290 hours x $42.40).
    We will submit the revised information collection estimates to OMB 
for approval under OMB control number 0938-1278 (expiration date March 
31, 2022).
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BILLING CODE 4120-01-C
10. ICRs for the Proposed Codification of the Costs Incurred for 
Qualified and Non-Qualified Deferred Compensation Plans
    As discussed in section X.A. of the preamble of this proposed rule, 
we are proposing to codify and clarify certain policies relating to 
Deferred Compensation. This proposal would not change our current 
policies for allowable Deferred Compensation costs associated with 
Qualified and Non-Qualified Deferred Compensation Plans that are 
included in Medicare cost reports. The proposed documentation 
requirements would require that a provider of services must maintain 
and make available to its contractor and CMS, documentation to 
substantiate the costs incurred for the plans included in its Medicare 
cost report. These proposed documentation requirements are based on the 
recordkeeping requirements at current Sec.  413.20, which require 
providers of services to maintain sufficient financial records and 
statistical data for proper determination of costs payable under 
Medicare. The OMB control number for this information collection 
request is 0938-0050, which expired on March 31, 2022. A reinstatement 
of the information collection request is currently being developed. The 
public will have an opportunity to review and submit comments on the 
reinstatement through a public notice and comment period separate from 
this rulemaking.
11. ICRs for Condition of Participation (CoP) Requirements for 
Hospitals and CAHs To Report Data Elements To Address Any Future 
Pandemics and Epidemics as Determined by the Secretary
a. Continued COVID-19 and Seasonal Influenza-Related Reporting
    We are proposing to revise the regulations by adding provisions to 
the CoPs (Sec.  482.42 for hospitals and Sec.  485.640 for CAHs) 
requiring hospitals and CAHs, after the conclusion of the current 
COVID-19 PHE, to continue COVID-19 and seasonal influenza-related 
reporting. The proposed revisions would continue to apply upon 
conclusion of the COVID-19 Public Health Emergency (PHE) and would 
continue until April 30, 2024, unless the Secretary establishes an 
earlier ending date. The proposed data elements align closely with 
those COVID-19 reporting requirements for long-term care (LTC) 
facilities that were finalized on November 9, 2021 (86 FR 62421) and 
are representative of the guidance provided to hospitals and CAHs for 
reporting. Therefore, we do not expect that these categories of data 
elements would require hospitals and CAHs to report any information 
beyond that which they have already been reporting. Furthermore, 
similar to the requirements for LTC facilities, this proposal would 
also allow for the scope and frequency of data collection to be reduced 
and limited responsive to the evolving clinical and epidemiological 
circumstances.
    For purposes of burden estimates, we do not differentiate among 
hospitals and CAHs as they all would complete the same data collection.
    For the estimated costs contained in the analysis below, we used 
data from the U.S. Bureau of Labor Statistics (BLS) to determine the 
mean hourly wage for

[[Page 28642]]

the staff member responsible for reporting the required information for 
a hospital (or a CAH).\1467\ Based on our experience with hospitals and 
CAHs and the current COVID-19 and related reporting requirements, we 
believe that this will primarily be the responsibility of a registered 
nurse and we have used this position in this analysis at an average 
hourly salary of $39.27. For the total hourly cost, we doubled the mean 
hourly wage for a 100 percent increase to cover overhead and fringe 
benefits, according to standard HHS estimating procedures. If the total 
cost after doubling resulted in 0.50 or more, the cost was rounded up 
to the next dollar. If it was 0.49 or below, the total cost was rounded 
down to the next dollar. Therefore, we estimated the total hourly cost 
for a registered nurse to perform these duties would be $79.
---------------------------------------------------------------------------

    \1467\ BLS. May 2020 National Occupational Employment and Wage 
Estimates United States. United States Department of Labor. Accessed 
at https://www.bls.gov/oes/current/oes_nat.htm. Accessed on August 
25, 2021.
---------------------------------------------------------------------------

    According to the most recent COVID-19 hospital reporting guidance 
(available at https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf), 
hospitals are reporting COVID-19 and influenza-related data on a daily 
basis, with backdating permitted for weekends and holidays, except 
psychiatric and rehabilitation hospitals who report weekly. Some data 
element reporting fields are inactive for data collection, and 
therefore, hospitals can optionally report data for these fields. The 
inactive fields and active fields together reflect what is listed in 
this proposed rule for continued COVID-19 and influenza-related 
reporting as well as future reporting in the event of a declared PHE, 
which we discuss next. We do not expect, nor have we proposed, 
continued daily reporting for COVID-19 or influenza outside of a 
declared PHE. If we were to assume a weekly reporting frequency, we 
would anticipate that there are reduced cases and fewer data elements 
(with no line level patient data) being reported. Based on these 
assumptions, we estimate that total annual burden hours for all 
participating hospitals and CAHs to comply with these requirements 
would be 483,600 hours based on weekly reporting of the required 
information by approximately 6,200 hospitals and CAHs x 52 weeks per 
year and at an average weekly response time of 1.5 hours for a 
registered nurse with an average hourly salary of $79. Therefore, the 
estimate for total annual costs for all hospitals and CAHs to comply 
with the required reporting provisions weekly would be $38,204,400 or 
approximately $6,162 per facility annually. We acknowledge that the 
data elements and reporting frequency could increase or decrease over 
the next two years, and those changes would impact this burden 
estimate.
    We note that this estimate is assumed to be a one-day snapshot of 
reporting information as opposed to a cumulative weekly report 
accounting for information based on each day of that week. If we 
assumed a cumulative weekly account, we can assume reduced burden 
related to the actual reporting time, but anticipate that the estimate 
would be slightly higher to account for the need to track closely to 
daily reporting. We also acknowledge that respondents may have to track 
and invest in infrastructure in order to timely and accurately report 
on the specified frequency. Thus, respondents may face ongoing burdens 
associated with this collection even in the case of reduced frequency 
of submissions. We solicit comment on this potentiality.
    Furthermore, we note that this estimate likely overestimates the 
costs associated with reporting because it assumes that all hospitals 
and CAHs will report manually. Efforts are underway to automate 
hospital and CAH reporting that have the potential to significantly 
decrease reporting burden and improve reliability. Our preliminary 
estimates for these reporting activities (OMB control numbers 0938-0328 
for hospitals and 0938-1043 for CAHs) can be found in the tables that 
follow.
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[GRAPHIC] [TIFF OMITTED] TP10MY22.239

b. Future Reporting in the Event of a PHE Declaration
    In addition, we are proposing to establish reporting requirements 
for future PHEs related to epidemics and pandemics by requiring 
hospitals and CAHS to electronically report information on Acute 
Respiratory Illness (including, but not limited to, Seasonal Influenza 
Virus, Influenza-like Illness, and Severe Acute Respiratory Infection), 
SARS-CoV-2/COVID-19, and other viral and bacterial pathogens or 
infectious diseases of pandemic or epidemic potential only when the 
Secretary has declared a PHE directly related to such specific 
pathogens and

[[Page 28643]]

infectious diseases. Specifically, when the Secretary has declared a 
PHE, we propose to require hospitals and CAHs to report specific data 
elements to the CDC's National Health Safety Network (NHSN), or other 
CDC-supported surveillance systems, as determined by the Secretary. The 
proposed requirements of this section would apply to local, state, and 
national PHEs as declared by the Secretary. Relevant to the declared 
PHE, the categories of data elements that this report would include are 
as follows: Suspected and confirmed infections of the relevant 
infectious disease pathogen among patients and staff; total deaths 
attributed to the relevant infectious disease pathogen among patients 
and staff; personal protective equipment and other relevant supplies in 
the facility; capacity and supplies in the facility relevant to the 
immediate and long term treatment of the relevant infectious disease 
pathogen, such as ventilator and dialysis/continuous renal replacement 
therapy capacity and supplies; total hospital bed and intensive care 
unit bed census, capacity, and capability; staffing shortages; vaccine 
administration status of patients and staff for conditions monitored 
under this section and where a specific vaccine is applicable; relevant 
therapeutic inventories and/or usage; isolation capacity, including 
airborne isolation capacity; and key co-morbidities and/or exposure 
risk factors of patients being treated for the pathogen or disease of 
interest in this section that are captured with interoperable data 
standards and elements.
    We are also proposing to require that, unless the Secretary 
specifies an alternative format by which a hospital (or a CAH) must 
report each applicable infection (confirmed and suspected) and the 
applicable vaccination data in a format that provides person-level 
information, to include medical record identifier, race, ethnicity, 
age, sex, residential county and zip code, and relevant comorbidities 
for affected patients, unless the Secretary specifies an alternative 
format by which the hospital (or CAH) would be required report these 
data elements. We are also proposing in this provision to limit any 
person-level, directly or potentially individually identifiable, 
information for affected patients and staff to items outlined in this 
section or otherwise specified by the Secretary. We note that the 
provided information obtained in this surveillance system that would 
permit identification of any individual or institution is collected 
with a guarantee that it will be held in strict confidence, will be 
used only for the purposes stated, and will not otherwise be disclosed 
or released without the consent of the individual, or the institution 
in accordance with Section 304, 306, and 308(d) of the Public Health 
Service Act (42 U.S.C. 242b, 242k, and 242m(d)). Lastly, we are 
proposing that a hospital (or a CAH) would provide the information 
specified on a daily basis, unless the Secretary specifies a lesser 
frequency, to the Centers for Disease Control and Prevention's National 
Healthcare Safety Network (NHSN) or other CDC-supported surveillance 
systems as determined by the Secretary.
    For purposes of this burden collection, we acknowledge the unknown 
and the ongoing burdens that may exist even if CMS is not collecting 
information outside of a declared PHE. We recognize that considerations 
such as building and maintaining the infrastructure to support 
readiness are necessary to ensure compliance with this requirement. 
Therefore, we are soliciting comment on the burden associated with 
these proposed requirements given the intended flexibility provided in 
reducing or limiting the scope and frequency of reporting based on the 
state of the PHE and ongoing circumstances. We are specifically asking 
for comment on the potential burden associated with the proposed 
reporting requirements as they might relate to any differences in the 
public health response to one specific pathogen or infectious disease 
versus another that would be directly related to the declared PHE. We 
are also interested in public comments addressing burden estimates (and 
the potential differences in those estimates) for variations in the 
required reporting response for a local PHE versus a regional PHE 
versus a national PHE that might be declared by the Secretary based on 
the specific circumstances at the time of the declaration.
    CMS will pursue an emergency collection of information in the case 
of a declared PHE and use such burden estimate to inform its approach 
at that time. CMS will also publish an accompanying Federal Register 
Notice concurrent with its submission of a request to collect 
information, in addition to all other actions consistent with 5 CFR 
1320.13. CMS commits to ensuring that respondents are well aware in 
advance of the intention to collect such information and solicits 
comment on the appropriate timeline and notification process for such 
actions.
12. Summary of All Burden in This Proposed Rule
    The following chart reflects the total burden and associated costs 
for the ICRs presented in this section of this proposed rule.
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[[Page 28645]]

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 proposed 
rule, and, when we proceed with a subsequent document(s), we will 
respond to those comments in the preamble to that document.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on April 8, 2022.

List of Subjects

42 CFR Part 412

    Administrative practice and procedure, Health facilities, Medicare, 
Puerto Rico, Reporting and recordkeeping requirements.

42 CFR Part 413

    Diseases, Health facilities, Medicare, Puerto Rico, Reporting and 
recordkeeping requirements.

42 CFR Part 482

    Grant programs--health, Hospitals, Medicaid, Medicare, Reporting 
and recordkeeping requirements.

42 CFR Part 485

    Grant programs--health, Health facilities, Medicaid, Privacy, 
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, Reporting and recordkeeping 
requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
and Medicaid Services proposes to amend 42 CFR chapter IV as set forth 
below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 
SERVICES

0
1. The authority citation for part 412 continues to read as follows:

    Authority: 42 U.S.C. 1302 and 1395hh.

0
2. Section 412.24 is amended by adding paragraph (d)(3)(iii) to read as 
follows:


Sec.  412.24  Requirements under the PPS-Exempt Cancer Hospital Quality 
Reporting (PCHQR) Program.

* * * * *
    (d) * * *
    (3) * * *
    (iii) Patient safety exception. Upon a determination by CMS that 
the continued requirement for PCHs to submit data on a measure raises 
specific patient safety concerns, CMS may elect to immediately remove 
the measure from the PCHQR measure set. CMS will, upon removal of the 
measure--
    (A) Provide notice to PCHs and the public at the time CMS removes 
the measure, along with a statement of the specific patient safety 
concerns that would be raised if PCHs continued to submit data on the 
measure; and
    (B) Provide notice of the removal in the Federal Register.
* * * * *
0
3. Section 412.60 is amended by revising paragraph (b) to read as 
follows:


Sec.  412.60  DRG classification and weighting factors.

* * * * *
    (b) DRG weighting factors. CMS assigns, for each DRG, an 
appropriate weighting factor that reflects the estimated relative cost 
of hospital resources used with respect to discharges classified within 
that group compared to discharges classified within other groups, 
subject to a maximum ten percent reduction to the weighting factor for 
a DRG as compared to the weighting factor for the same DRG for the 
prior fiscal year.
* * * * *
0
4. Section 412.64 is amended by adding paragraph (h)(7) to read as 
follows:


Sec.  412.64  Federal rates for inpatient operating costs for Federal 
fiscal year 2005 and subsequent fiscal years.

* * * * *
    (h) * * *
    (7) Beginning with fiscal year 2023, if CMS determines that a 
hospital's wage index value for a fiscal year would decrease by more 
than 5 percent as compared to the hospital's wage index value for the 
prior fiscal year, CMS limits the decrease to 5 percent for the fiscal 
year.
* * * * *
0
5. Section 412.103 is amended by adding paragraph (a)(8) to read as 
follows:


Sec.  412.103  Special treatment: Hospitals located in urban areas and 
that apply for reclassification as rural.

    (a) * * *
    (8) For a hospital with a main campus and one or more remote 
locations under a single provider agreement where services are provided 
and billed under the inpatient hospital prospective payment system and 
that meets the provider-based criteria at Sec.  413.65 of this chapter 
as a main campus and a remote location of a hospital, approved rural 
reclassification status applies to the main campus and any remote 
location located in an urban area (as defined in Sec.  412.64(b) and 
including a main campus or any remote location deemed urban under 
section 1886(d)(8)(B) of the Act).
* * * * *
0
6. Section 412.106 is amended by--
0
a. Revising paragraphs (b)(4) introducotry text and (b)(4)(i) and (ii);
0
b. Redesignating paragraphs (b)(4)(iii) and (iv) as paragraphs 
(b)(4)(iv) and (v), respectively;
0
c. Adding a new paragraph (b)(4)(iii);
0
d. Revising paragraph (g)(1)(ii);
0
e. In paragraph (g)(1)(iii)(C)(8), removing the phrase ``For each 
subsequent fiscal year,'' and adding in its place the phrase ``For 
fiscal year 2022,'';
0
f. Adding paragraphs (g)(1)(iii)(C)(10) and (11);
0
g. Redesignating paragraph (h) as paragraph (i); and
0
h. Adding a new paragraph (h).
    The revisions and additions read as follows:


Sec.  412.106  Special treatment: Hospitals that serve a 
disproportionate share of low-income patients.

* * * * *
    (b) * * *
    (4) Second computation. The fiscal intermediary determines, for the 
same cost reporting period used for the first computation, the number 
of the hospital's patient days of service for patients who were not 
entitled to Medicare Part A, but who were eligible for Medicaid on such 
days as described in paragraph (b)(4)(i) of this section or who were 
regarded as eligible for Medicaid on such days and the Secretary has 
determined to include such patient days in this computation as 
described in paragraph (b)(4)(ii)(A) or (B) of this section, and 
divides that number by the total number of patient days in the same 
period. For purposes of this second computation, the following 
requirements apply:
    (i) For purposes of this computation, a patient is eligible for 
Medicaid on a given day if the patient is eligible for inpatient 
hospital services under a State Medicaid plan approved under Title XIX 
of the Act on that day, regardless of whether particular items or 
services were covered or paid for on that day under the State plan.
    (ii) For purposes of this computation, a patient is regarded as 
eligible for Medicaid on a given day if the patient

[[Page 28646]]

receives on that day health insurance authorized by a demonstration 
approved by the Secretary under section 1115(a)(2) of the Act where the 
cost of such health insurance may be counted as expenditures under 
section 1903 of the Act, or the patient has on that day health 
insurance purchased using premium assistance received through a 
demonstration approved by the Secretary under section 1115(a)(2) of the 
Act where the premium assistance covers all or substantially all of the 
cost of the health insurance and the cost of the premium assistance may 
be counted as expenditures under section 1903 of the Act. Of these 
patients regarded as eligible for Medicaid on a given day, only the 
days of patients meeting the following criteria on that day may be 
counted in this second computation:
    (A) Patients who are provided by a demonstration authorized under 
section 1115(a)(2) of the Act health insurance that provides essential 
health benefits (EHB) as set forth in subpart C of part 440 of this 
chapter for an Alternative Benefit Plan; or
    (B) Patients who have health insurance that provides EHB as set 
forth in subpart C of part 440 of this chapter for an Alternative 
Benefit Plan purchased using premium assistance provided by a 
demonstration authorized under section 1115(a)(2) of the Act and the 
premium assistance accounts for at least 90 percent of the cost of the 
health insurance.
    (iii) Patients whose health care costs, including inpatient 
hospital care costs, for a given day are claimed for payment by a 
provider from an uncompensated, undercompensated, or other type of 
funding pool authorized under section 1115(a) of the Act to fund 
providers' uncompensated care costs are not regarded as eligible for 
Medicaid for purposes of paragraph (b)(4)(ii) of this section on that 
day and the days of such patients may not be included in this second 
computation.
* * * * *
    (g) * * *
    (1) * * *
    (ii) Factor 2. (A) For each of fiscal years 2014, 2015, 2016, and 
2017, a factor equal to 1 minus the percent change in the percent of 
individuals under the age of 65 who are uninsured (and subtracting from 
the factor 0.1 percentage point for fiscal year 2014 and 0.2 percentage 
point for each of fiscal years 2015, 2016, and 2017), as determined by 
comparing--
    (1) 18 percent, the percent of such individuals who are uninsured 
in 2013, based on the March 20, 2010, estimate of the ``Insured Share 
of the Nonelderly Population Including All Residents'' by the 
Congressional Budget Office.
    (2) The percent of such individuals who are uninsured in the 
applicable fiscal year, based on the most recent estimate of the 
``Insured Share of the Nonelderly Population Including All Residents'' 
by the Congressional Budget Office available at the time of development 
of the annual final rule for the hospital inpatient prospective payment 
system.
    (B) For FY 2018 and subsequent fiscal years, a factor equal to 1 
minus the percent change in the percent of individuals who are 
uninsured (and subtracting from the factor 0.2 percentage point for 
each of fiscal years 2018 and 2019), as determined by comparing the 
percent of individuals who are uninsured in--
    (1) 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 the CMS); and
    (2) The most recent period for which data is available (as so 
estimated and certified).
    (iii) * * *
    (C) * * *
    (10) For fiscal year 2023, for all eligible hospitals, 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 two most recent cost reporting years for which audits have 
been conducted. If a hospital is a new hospital (that is, a hospital 
that began participation in the Medicare program after the two most 
recent cost reporting years for which audits have been conducted) or if 
the hospital is treated as a new hospital for purposes of Factor 3, the 
Medicare Administrative Contractor (MAC) will determine Factor 3 as the 
ratio of the hospital's uncompensated care costs from its FY 2023 cost 
report to the sum of uncompensated care costs for all DSH-eligible 
hospitals as estimated by CMS from the most recent cost reporting year 
for which audits have been conducted.
    (11) For fiscal year 2024 and subsequent fiscal years, for all 
eligible hospitals, 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 three most recent 
cost reporting years for which audits have been conducted. If a 
hospital is a new hospital (that is, a hospital that began 
participation in the Medicare program after the three most recent cost 
reporting years for which audits have been conducted) or if the 
hospital is treated as a new hospital for purposes of Factor 3 in this 
paragraph (g)(1)(iii), the MAC will determine Factor 3 as the ratio of 
the hospital's uncompensated care costs from its cost report for the 
applicable fiscal year to the sum of uncompensated care costs for all 
disproportionate share hospital (DSH)-eligible hospitals as estimated 
by CMS from the most recent cost reporting year for which audits have 
been conducted.
    (h) Supplemental payment for Indian Health Service and Tribal 
hospitals and Puerto Rico hospitals. (1) For fiscal year 2023 and each 
subsequent fiscal year, Indian Health Service and Tribal Hospitals and 
Puerto Rico hospitals that qualify for an additional payment for 
uncompensated care under paragraph (g) of this section for the 
applicable fiscal year may also qualify to receive a supplemental 
payment.
    (2) Indian Health Service and Tribal Hospitals and Puerto Rico 
hospitals that do not have a Factor 3 amount for fiscal year 2022 
determined under paragraph (g)(1)(iii)(C)(9) of this section are not 
eligible to receive a supplemental payment under this paragraph (h).
    (3) The amount of the supplemental payment for a fiscal year is 
determined as the difference between the following:
    (i) A base year amount defined as the FY 2022 uncompensated care 
payment determined for the hospital, in accordance with paragraph 
(g)(1) of this section, adjusted by 1 plus the percent change in the 
aggregate amount of uncompensated care payments as estimated by CMS in 
accordance with paragraphs (g)(1)(i) and (ii) of this section between 
fiscal year 2022 and the applicable fiscal year. If the hospital did 
not qualify for an additional payment for uncompensated care under 
paragraph (g) of this section for fiscal year 2022, CMS uses the Factor 
3 determined for the hospital under paragraph (g)(1)(iii)(C)(9) of this 
section to estimate the amount of the additional payment for 
uncompensated care that the hospital would have received in fiscal year 
2022 if the hospital had qualified for an additional payment for 
uncompensated care under paragraph (g)(1) of this section for that 
fiscal year.
    (ii) The additional payment for uncompensated care determined for 
the hospital for the applicable fiscal year, in accordance with 
paragraph (g)(1) of this section.
    (4) If the base year amount under paragraph (h)(3)(i) of this 
section is equal to or lower than the additional

[[Page 28647]]

payment for uncompensated care determined for the hospital for the 
applicable fiscal year in accordance with paragraph (g)(1) of this 
section, the hospital will not receive a supplemental payment under 
paragraph (h) of this section for that fiscal year.
* * * * *


Sec.  412.140  [Amended]

0
7. Section 412.140 is amended in paragraph (d)(2)(ii) by removing the 
phrase ``at least 75 percent'' and adding in its place the phrase ``100 
percent''.
0
8. Section 412.168 is amended by--
0
a. Revising the section heading;
0
b. In paragraph (a), removing the phrase ``for the fiscal year 2022'' 
and adding in its place ``for each of fiscal years 2022 and 2023''; and
0
c. By adding paragraphs (g) through (k).
    The revision and additions read as follows:


Sec.  412.168  Special rules for FY 2022 and FY 2023.

* * * * *
    (g) CMS calculates a measure rate for all measures selected under 
Sec.  412.164(a) for fiscal year 2023 but only applies Sec.  412.165(a) 
to the measures included in the Clinical Outcomes Domain and the 
Efficiency and Cost Reduction 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).
    (7) Medicare Spending Per Beneficiary (MSPB)--Hospital.
    (h) CMS calculates--
    (1) A Clinical Outcomes Domain score for fiscal year 2023 for 
hospitals that report the minimum number of cases and measures with 
respect to the measures described in paragraphs (g)(1) through (6) of 
this section; and
    (2) An Efficiency and Cost Reduction Domain score for fiscal year 
2023 for hospitals that report the minimum number of cases with respect 
to the measure described in paragraph (g)(7) of this section.
    (i) CMS does not award a Total Performance Score to any hospital 
for fiscal year 2023.
    (j) The total amount available for value-based incentive payments 
for fiscal year 2023 is equal to the total amount of base-operating DRG 
payment reductions for that fiscal year, as estimated by the Secretary.
    (k) CMS awards a value-based incentive payment percentage (as 
defined in Sec.  412.160) for fiscal year 2023 to all hospitals to 
ensure that each hospital receives a value-based incentive payment 
amount equal to the amount of the reduction made to its base-operating 
DRG payment amounts.
0
9. Section 412.273 is amended by revising paragraphs (d)(2) and (e) to 
read as follows:


Sec.  412.273  Withdrawing an application, terminating an approved 3-
year reclassification, or canceling a previous withdrawal or 
termination.

* * * * *
    (d) * * *
    (2) Timing and process of cancellation request. Cancellation 
requests must be submitted in writing to the MGCRB according to the 
method prescribed by the MGCRB no later than the deadline for 
submitting reclassification applications for the following fiscal year, 
as specified in Sec.  412.256(a)(2).
* * * * *
    (e) Written request only. (1) A request to withdraw an application 
must be submitted in writing to the MGCRB according to the method 
prescribed by the MGCRB by all hospitals that are party to the 
application.
    (2) A request to terminate an approved reclassification must be 
submitted in writing to the MGCRB according to the method prescribed by 
the MGCRB by an individual hospital or by an individual hospital that 
is party to a group classification.
* * * * *
0
10. Section 412.515 is revised to read as follows:


Sec.  412.515  LTC-DRG weighting factors.

    (a) For each LTC-DRG, CMS assigns an appropriate weight that 
reflects the estimated relative cost of hospital resources used within 
that group compared to discharges classified within other groups.
    (b)(1) Beginning FY 2023, each LTC-DRG weight is subject to a 
maximum 10 percent reduction as compared to the weight for the same 
LTC-DRG for the prior fiscal year, except as provided in paragraph 
(b)(2) of this section.
    (2) The limitation described in paragraph (b)(1) of this section 
does not apply to no-volume LTC-DRGs.
0
11. Section 412.525 is amended by revising paragraph (c)(1) to read as 
follows:


Sec.  412.525  Adjustments to the Federal prospective payment.

* * * * *
    (c) * * *
    (1) The labor portion of a long-term care hospital's Federal 
prospective payment is adjusted to account for geographical differences 
in the area wage levels using an appropriate wage index (established by 
CMS), which reflects the relative level of hospital wages and wage-
related costs in the geographic area (that is, urban or rural area as 
determined in accordance with the definitions set forth in Sec.  
412.503) of the hospital compared to the national average level of 
hospital wages and wage-related costs.
    (i)(A) The appropriate wage index that is established by CMS is 
updated annually.
    (B) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
wage index value for a fiscal year would decrease by more than 5 
percent as compared to the LTCH's wage index value for the prior fiscal 
year, CMS limits the decrease to 5 percent for the fiscal year.
    (ii) The labor portion of a long-term care hospital's Federal 
prospective payment is established by CMS and is updated annually.
* * * * *
0
12. Section 412.529 is amended by revising paragraphs (d)(4)(ii)(B) and 
(d)(4)(iii)(B) to read as follows:


Sec.  412.529  Special payment provision for short-stay outliers.

* * * * *
    (d) * * *
    (4) * * *
    (ii) * * *
    (B)(1) Is adjusted for different area wage levels based on the 
geographic classifications set forth at Sec.  412.503 and the 
applicable hospital inpatient prospective payment system (IPPS) labor-
related share, using the applicable hospital inpatient prospective 
payment system wage index value for nonreclassified hospitals (an 
LTCH's applicable IPPS wage index).
    (2) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
applicable IPPS wage index value for a fiscal year would decrease by 
more than

[[Page 28648]]

5 percent as compared to the LTCH's applicable IPPS wage index value 
for the prior fiscal year, CMS limits the decrease to 5 percent for the 
fiscal year.
    (3) For LTCHs located in Alaska and Hawaii, the amount specified in 
paragraph (d)(4)(ii) of this section is also adjusted by the applicable 
hospital inpatient prospective payment system cost of living adjustment 
factors.
* * * * *
    (iii) * * *
    (B)(1) Is adjusted for the applicable geographic adjustment 
factors, including local cost variation based on the geographic 
classifications set forth at Sec.  412.503 and the applicable full 
hospital inpatient prospective payment system (IPPS) wage index value 
for nonreclassified hospitals (an LTCH's applicable IPPS wage index) 
and applicable cost of living adjustment factors for LTCHs in Alaska 
and Hawaii.
    (2) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
applicable IPPS wage index value for a fiscal year would decrease by 
more than 5 percent as compared to the LTCH's applicable IPPS wage 
index value for the prior fiscal year, CMS limits the decrease to 5 
percent for the fiscal year.
* * * * *

PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR 
END-STAGE RENAL DISEASE SERVICES; PROSPECTIVELY DETERMINED PAYMENT 
RATES FOR SKILLED NURSING FACILITIES; PAYMENT FOR ACUTE KIDNEY 
INJURY DIALYSIS

0
13. 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
14. Section 413.75 is amended in paragraph (b) by adding in 
alphabetical order the definitions of ``Rural track Medicare GME 
affiliated group'' and ``Rural track Medicare GME affiliation 
agreement'' to read as follows:


Sec.  413.75  Direct GME payments: General requirements.

* * * * *
    (b) * * *
    Rural track Medicare GME affiliated group means an urban hospital 
and a rural hospital that--
    (i) Participate in a rural track program defined in this paragraph 
(b);
    (ii) Have rural track FTE limitations in effect prior to October 1, 
2022; and
    (iii) Comply with the regulations at Sec.  413.79(f)(1) through (6) 
for Medicare GME affiliated groups.
    Rural track Medicare GME affiliation agreement means a written, 
signed, and dated agreement by responsible representatives of each 
respective hospital in a rural track Medicare GME affiliated group, as 
defined in this paragraph (b), that specifies all of the following:
    (i) A statement attesting that each participating hospital's FTE 
counts and rural track FTE limitations in the agreement do not reflect 
FTE residents nor FTE caps associated with programs other than the 
rural track program.
    (ii) The term of the rural track Medicare GME affiliation agreement 
(which, at a minimum is 1 year), beginning on July 1 of a year.
    (iii) Each participating hospital's direct and indirect GME rural 
track FTE limitations in effect prior to the rural track Medicare GME 
affiliation.
    (iv) The total adjustment to each hospital's rural track FTE 
limitations in each year that the rural track Medicare GME affiliation 
agreement is in effect, for both direct GME and indirect medical 
education (IME), that reflects a positive adjustment to one hospital's 
direct and indirect rural track FTE limitations that is offset by a 
negative adjustment to the other hospital's (or hospitals') direct and 
indirect rural track FTE limitations of at least the same amount.
    (v) The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
rural track Medicare GME affiliated group for each year the Medicare 
GME affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's rural track FTE limitations (in 
accordance with paragraph (iii) of this definition).
* * * * *
0
15. Section 413.79 is amended by revising paragraph (c)(2)(iii) to read 
as follows:


Sec.  413.79  Direct GME payments: Determination of the weighted number 
of FTE residents.

* * * * *
    (c) * * *
    (2) * * *
    (iii) Effective for cost reporting periods beginning on or after 
October 1, 2001, if the hospital's unweighted number of FTE residents 
exceeds the limit described in this section, and the number of weighted 
FTE residents in accordance with paragraph (b) of this section also 
exceeds that limit, the respective primary care and obstetrics and 
gynecology weighted FTE counts and other weighted FTE counts are 
adjusted to make the total weighted FTE count equal the limit. If the 
number of FTE residents weighted in accordance with paragraph (b) of 
this section does not exceed that limit, then the allowable weighted 
FTE count is the actual weighted FTE count.
* * * * *
0
16. Add Sec.  413.99 to read as follows:


Sec.  413.99  Qualified and Non-Qualified Deferred Compensation Plans.

    (a) Statutory basis, scope, and definitions--(1) Basis. All 
payments to providers of services must be based on the reasonable cost 
of services covered under Title XVIII in accordance with section 
1861(v) of the Act and the regulations in this part.
    (2) Scope. This section and Sec.  413.100(c)(2)(vii) apply to 
Medicare's treatment of the costs incurred for Qualified and Non-
Qualified Deferred Compensation Plans.
    (3) Definitions. As used in this section the following definitions 
apply:
    Deferred Compensation means remuneration currently earned by an 
employee that is not received until a subsequent period, usually after 
retirement.
    Employee Retirement Income Security Act of 1974 (ERISA) is a 
Federal law that sets standards of protection for individuals in most 
voluntarily established, private-sector retirement plans. The law is 
set forth in Title 29, Chapter 18 of the U.S. Code.
    Funded Plan means a plan in which assets have been irrevocably and 
unconditionally set aside with a third party for the payment of plan 
benefits (for example, in a trust or escrow account), and those assets 
are beyond the reach of the employer or its general creditors.
    Non-Qualified Deferred Compensation Plan (NQDC) means an elective 
or non-elective plan, agreement, method, or arrangement between an 
employer and an employee to pay the employee compensation in the 
future. In comparison with qualified plans, nonqualified plans do not 
provide employers and employees with the tax benefits associated with 
qualified plans because NQDC plans do not satisfy all the requirements 
of 26 U.S.C. 401(a).
    Non-Qualified Defined Benefit Plan (NQDB) means a type of NQDC that 
is established and maintained by the employer primarily to provide 
definitely determinable benefits to its employees usually over a period 
of years, or for life,

[[Page 28649]]

after retirement. Such benefits are generally measured by, and based 
on, such factors as age of employees, years of service, and 
compensation received by the employees.
    Pension Benefit Guaranty Corporation (PBGC) is a Federal agency 
created by ERISA to protect benefits in private-sector QDBP plans 
described in section 3(35) of ERISA.
    Qualified Defined Benefit Plan (QDBP) means a type of Qualified 
Deferred Compensation Plan that is established and maintained by the 
employer primarily to provide definitely determinable benefits to its 
employees usually over a period of years, or for life, after 
retirement. Such benefits are generally measured by, and based on, such 
factors as age of employees, years of service, and compensation 
received by the employees. A QDBP meets the applicable requirements of 
ERISA, as amended, and the requirements for a QDBP under 26 U.S.C. 
401(a). Under a qualified plan, employers are entitled to deduct 
expenses in the year the employer makes contributions even though 
employees will not recognize income until the receipt of distributions.
    Qualified Defined Contribution or Individual Account Plan (QDCP) 
means a type of Deferred Compensation Plan in which the employee, the 
employer, or both, contribute to an employee's individual account under 
the plan. The amount in the account at distribution includes the 
contributions and investment gains or losses, minus any investment and 
administrative fees. The value of the account changes based on 
contributions and the value and performance of the investments. A QDCP 
meets the applicable requirements of ERISA, as amended, and the 
requirements set forth in 26 U.S.C. 401(a), and, if applicable 26 
U.S.C. 401(k).
    Unfunded Plan means a plan in which benefits are supported by 
assets that have not been set aside (that is, a ``pay as you go'' 
plan), or by assets that have been set aside, but remain subject to the 
claims of the employer's general creditors.
    (b) Principle requirements--(1) General. Deferred Compensation 
contributions or payments must be made by a provider of services, or an 
employee of the provider of services, to a Qualified or Non-Qualified 
Deferred Compensation Plan, established and maintained by the provider 
of services to provide retirement income to employees or to result in 
the deferral of income by employees for periods extending to the 
termination of covered employment or beyond. Contributions or payments 
made by a provider of services for the benefit of its employees to a 
Qualified or Non-Qualified Deferred Compensation Plan are allowable, 
when, and to the extent that, such costs are actually incurred by the 
provider of services and found to be reasonable and necessary under the 
principles of reasonable cost.
    (2) Deferred Compensation for provider-based physicians services in 
a hospital or SNF. Costs incurred by a hospital or SNF to fund a 
Qualified or Non-Qualified Deferred Compensation Plan for a provider-
based physician must meet the following requirements to be allowable 
under the program:
    (i) The allocation of physician compensation costs required under 
Sec.  415.60 does not attribute the provider-based physician's Deferred 
Compensation entirely to one category of service and his current 
compensation to another.
    (ii) Contributions or payments toward the Qualified or Non-
Qualified Deferred Compensation Plan do not include any cost excluded 
from the definition of physician compensation at Sec.  415.60(a) of 
this chapter.
    (iii) The amount of Deferred Compensation does not exceed the 
amount specified in the agreement required by Sec.  415.60(g) of this 
chapter.
    (iv) An arrangement between a physician and a provider of services 
under which the physician is reimbursed for patient charges, but the 
provider of services does the billing as a Deferred Compensation 
agreement, is not allowed.
    (v) The costs incurred for physician guaranteed arrangements for 
hospital emergency room availability services, must meet the following 
additional requirements:
    (A) The terms of both the guarantee arrangements and the Deferred 
Compensation Plan establish the amounts to be included at the beginning 
of the hospital's cost reporting period.
    (B) The amount of Deferred Compensation is included in the 
guaranteed amount.
    (C) The hospital contributes to the Deferred Compensation Plan from 
its own funds.
    (D) The amount of Deferred Compensation that is allowable is 
limited to the amount by which the guarantee, including Deferred 
Compensation, exceeds the total billed by the hospital to all patients 
for the physician's patient care services.
    (E) When the physician's charges to all patients equal or exceed 
the amount guaranteed by the hospital, the program does not recognize a 
Deferred Compensation contribution/payment.
    (c) Requirements for Non-Qualified and Qualified Deferred 
Compensation Plans--(1) NQDC requirements. In order for contributions 
or payments by a provider of services to an NQDC as defined at 
paragraph (a)(3) of this section to be allowable under the program, the 
NQDC must meet the general requirements at paragraph (c)(1)(i) of this 
section, and it must either meet the requirements for a funded NQDC at 
paragraph (c)(1)(ii) of this section or the requirements for an 
unfunded NQDC at paragraph (c)(1)(iii) of this section, as applicable.
    (i) General requirements. An NQDC must satisfy the requirements for 
document compliance and operational compliance set forth in 26 U.S.C. 
409A.
    (ii) Funded NQDCs. A funded NQDC must meet the definition of a 
Funded Plan in paragraph (a)(3) of this section and comply with the 
requirements in paragraph (c)(5) of this section.
    (iii) Unfunded NQDCs. An NQDC that is unfunded must meet the 
definition of an Unfunded Plan in paragraph (a)(3) of this section, and 
there must be no constructive receipt of income for employees from a 
NQDC as a result of contributions made by a provider of services.
    (2) QDCP requirements. A QDCP must meet the applicable requirements 
of ERISA, as amended, and the requirements set forth in 26 U.S.C. 
401(a), and if applicable 26 U.S.C. 401(k). A QDCP must meet the 
definition of a Funded Plan in paragraph (a)(3) of this section and 
comply with the requirements in paragraph (c)(5) of this section.
    (3) QDBP requirements. A QDBP must meet the applicable requirements 
of ERISA, as amended, and the requirements for a defined benefit plan 
under 26 U.S.C. 401(a). A QDBP must meet the definition of a Funded 
Plan in paragraph (a)(3) of this section and comply with the 
requirements in paragraph (c)(5) of this section.
    (4) NQDB requirements. In order for contributions or payments by a 
provider of services to an NQDB as defined at paragraph (a)(3) of this 
section to be allowable under the program, the NQDB must meet the 
general requirements at paragraph (c)(4)(i) of this section, and it 
must either meet the requirements for a funded NQDB at paragraph 
(c)(4)(ii) of this section or the requirements for an unfunded NQDB at 
paragraph (c)(4)(iii) of this section, as applicable.
    (i) General requirements. An NQDB must satisfy the requirements for 
document compliance set forth in 26 U.S.C. 409A and operational 
compliance set forth in 26 U.S.C. 409A(a).

[[Page 28650]]

    (ii) Funded NQDBs. An NQDB that is funded must meet the definition 
of a Funded Plan in paragraph (a)(3) of this section and comply with 
the requirements in paragraph (c)(5) of this section.
    (iii) Unfunded NQDBs. An NQDB that is unfunded must meet the 
definition of an Unfunded Plan in paragraph (a)(3) of this section, and 
there must be no constructive receipt of income for employees from a 
NQDB as a result of contributions made by a provider of services.
    (5) Funded Plan requirements--(i) Acceptable funding mechanism. 
Both provider of services contributions and employee contributions must 
be used either to purchase an insured plan with a commercial insurance 
company, to establish a custodial bank account, or to establish a trust 
fund administered by a trustee.
    (ii) Life insurance contracts. The purchase of an ordinary life 
insurance contract (for example, whole life, straight life, or other) 
is not a deferral of compensation and is not recognized as a funding 
mechanism, even where it is convertible at the normal retirement date 
specified in the policy to an annuity payable over the remaining life 
of the employee.
    (iii) Sole benefit of participating employees. Regardless of the 
funding mechanism utilized, all provider of services and employee 
contributions to the fund established under the Deferred Compensation 
Plan and income therefrom must be used for the sole benefit of the 
participating employees.
    (d) Recognition of contributions or payments to Qualified and Non-
Qualified Deferred Compensation Plans--(1) General rule. Except as 
provided for in paragraph (c)(1)(iii) with respect to QDBPs and funded 
NQDBs, contributions to Qualified Deferred Compensation Plans or 
payments to plan participants from Non-Qualified Deferred Compensation 
Plans are recognized as allowable costs in accordance with paragraph 
(c)(1)(i) of this section (in the case of Unfunded Plans) and paragraph 
(c)(1)(ii) of this section (in the case of Funded Plans).
    (i) Unfunded Plans. Contributions or payments made to an unfunded 
Deferred Compensation Plans (including unfunded NQDBs) by a provider of 
services on behalf of its employees are included in allowable costs 
only during the cost reporting period in which an actual payment is 
made to the participating employees (or their beneficiaries) and only 
to the extent considered reasonable, in accordance with Sec.  
413.100(c)(2)(vii)(A).
    (ii) Funded Plans. Reasonable provider of services payments made 
under funded Deferred Compensation Plans (specifically, funded Defined 
Contribution Plans, but excluding QDBPs and funded NQDBs) are included 
in allowable costs in accordance with Sec.  413.100(c)(2)(vii)(B).
    (iii) Exception for QDBPs and funded NQDBs. (A) QDBP and NQDB 
contributions are found to have been incurred only if paid directly to 
participants or beneficiaries under the terms of the plan or to the 
QDBP or NQDB.
    (B) Payments to a QDBP or funded NQDB for a cost reporting period 
must be measured on a cash basis. A contribution or payment is deemed 
to occur on the date it is credited to the fund established for the 
QDBP or funded NQDB, or for provider of services payments made directly 
to a plan participant or beneficiary, on the date the provider of 
services account is debited.
    (C) Payments or contributions made to fully fund a terminating QDBP 
or funded NQDB are to be included as funding on the date they are paid. 
Excess assets withdrawn from a QDBP or funded NQDB are to be treated as 
negative contributions on the date that they are withdrawn.
    (D) QDBP and funded NQDB annual allowable costs are computed as 
follows:
    (1) QDBP and funded NQDB costs and limits are computed in 
accordance with Sec.  413.100(c)(2)(vii)(D).
    (2) For purposes of determining the QDBP or funded NQDB cost limit 
under Sec.  413.100(c)(2)(vii)(D)(2), provider of services contribution 
payments for each applicable cost reporting period must be determined 
on a cash basis without regard to any limit determined for the period 
during which the contributions were made, and excluding any 
contributions deposited in a prior period and treated as carry forward 
contributions.
    (3) The averaging period used to determine the QDBP or funded NQDB 
cost limit must be determined without regard to a provider of services 
period of participation in the Medicare program. Periods that are not 
Medicare cost reporting periods (for example, periods prior to the 
hospital's participation in the Medicare program) must be defined as 
consecutive 12-month periods ending immediately prior to the provider 
of services initial Medicare cost reporting period.
    (4) The averaging period used to determine the QDBP or funded NQDB 
cost limit must exclude all periods ending prior to the initial 
effective date of the plan (or a predecessor plan in the case of a 
merger).
    (5) In general, the current period defined benefit cost and limit 
is computed and applied separately for each QDBP or funded NQDB offered 
by a provider of services. In the case of a plan merger, the 
contributions or payments made by a provider of services to a 
predecessor QDBP or funded NQDB and reflected in the assets 
subsequently transferred to a successor plan are treated as 
contribution payments made to the successor plan.
    (2) [Reserved]
    (e) Documentation requirements. Documentation must be maintained by 
the provider of services in accordance with Sec.  413.20 to 
substantiate the allowability of contributions or payments to Qualified 
and Non-Qualified Deferred Compensation Plan(s) that it has included in 
its cost reports.
    (1) Required documentation. The provider of services must maintain 
and make available, upon request by the contractor or CMS, certain 
specified documentation, to substantiate the allowability of the 
contributions or payments to its Qualified or Non-Qualified Deferred 
Compensation Plan(s), or both:
    (i) Documentation that demonstrates that the provider of services 
is in compliance with 26 U.S.C. 409A and 409A(a), and, if applicable, 
26 U.S.C. 457.
    (ii) Ledger accounts/account statements for each plan participant 
noting current year deferrals, distributions and loans, including any 
deferral election forms completed by employees, any change requests, 
and the approval of such requests.
    (iii) Documentation that demonstrates the amount(s) and date(s) of 
actual contributions or payments made to the Qualified or Non-Qualified 
Deferred Compensation Plan during the current cost reporting period.
    (iv) Schedule SB of Form 5500 (tri-agency form (Department of Labor 
(DOL), Internal Reveue Service (IRS), and PBGC) that plans file with 
the DOL's ``EFAST'' electronic filing system) for a QDBP for the 
current cost reporting period, or any applicable prior periods.
    (v) In the case of a system-wide (multiple employer) plan, the home 
office shall identify the contributions attributed to each 
participating provider of services. If the costs included in the cost 
report for a period differ from the contributions made during the 
reporting period (that is, as a result of carry forward contributions), 
the provider of

[[Page 28651]]

services must also have data available to track and reconcile the 
difference.
    (2) Additional documentation. The following additional 
documentation must be made available, upon request by the contractor or 
CMS, to substantiate the allowability of the payments/contributions by 
a provider of services to a Qualified or Non-Qualified Deferred 
Compensation Plan:
    (i) The plan document, the trust document and all amendments 
related to the current cost reporting period.
    (ii) If applicable, any Form 5330, Return of Excise Taxes Related 
to Employee Benefit Plans, for the cost reporting period.
    (iii)(A) Supporting documents for all plan assets and liabilities, 
such as broker's statements, bank statements, insurance contracts, loan 
documents, deeds, etc.
    (B) Verification of how assets are valued.
    (iv)(A) Trustee or administrator reports.
    (B) Ledgers.
    (C) Journals.
    (D) Trustee, administrator, and investment committee minutes.
    (E) Certified audit report and other financial reports for the 
trust.
    (F) Any other financial reports, including receipt and disbursement 
statements, a detailed income statement, and a detailed balance sheet.
    (v) For each covered QDBP, documentation of the certified premium 
information and payments to the PBGC.
    (f) Administrative and other costs associated with Deferred 
Compensation Plans. The provider of services shall file a cost report 
required under Sec. Sec.  413.20 and 413.24(f) that is consistent with 
the policies set forth in this section.
    (1) Trustee and custodial fees. Reasonable trustee or custodial 
fees, including PBGC premiums, paid by the provider of services are 
allowed as an administrative cost except where the plan provides that 
such fees are paid out of the corpus or earnings of the fund.
    (2) Vested benefits. The forfeiture of an employee's benefits for 
cause (as defined in the plan) is recognized as an allowable cost 
provided that such forfeited amounts are used to reduce the provider of 
services contributions or payments to the plan during the cost 
reporting period in which the forfeiture occurs.
    (3) Benefits to be paid. If an employee terminates participation in 
the Deferred Compensation Plan before their rights are vested, the 
applicable non-vested contributions/payments cannot be applied to 
increase the benefits of the surviving participants. Instead the non-
vested contributions or payments should be used to reduce the provider 
of services contributions or payments to the Deferred Compensation 
Plan, in the cost reporting period in which the employee terminated 
participation in the Deferred Compensation Plan. Otherwise, the 
contributions/payments made by the provider of services must be applied 
to reduce the subsequent contributions or payments to the Deferred 
Compensation Plan in the next cost reporting period. If subsequent 
provider of services contributions/payments to the Deferred 
Compensation Plan are not made, then the provider of services costs are 
reduced by the contractor to the extent of such non-vested funds.
    (4) DOL, IRS, or PBGC penalties. If the provider of services is 
assessed an excise tax or other remedy by the DOL, IRS, or PBGC for 
failure to follow DOL, IRS, or PBGC requirements under ERISA or any 
other penalty fee or penalty interest applicable to its Deferred 
Compensation Plan, the cost is unallowable in accordance with section 
1861(v)(8) of the Act.
    (5) Loans made from a Deferred Compensation Plan. A provider of 
services cannot make a loan to itself from a Deferred Compensation Plan 
where ERISA or IRS rules prohibit such a transaction, except where 
specifically excepted.
    (6) Termination/discontinuation of a Deferred Compensation Plan. If 
the provider of services declines to vest its outstanding required 
contributions or payments (that is, matching or non-elective) to a 
Deferred Compensation Plan as a result of a termination in full or in 
part or a discontinuation of contributions or payments to a Deferred 
Compensation Plan, then the provider of services total outstanding 
required contributions or payments to the Deferred Compensation Plan 
during the cost reporting period wherein such termination is initiated 
cannot be included in the provider of services allowable cost for the 
cost reporting period in which the termination is initiated, nor any 
future period.
    (7) Required offset against interest expense. Investment income 
earned on a Deferred Compensation Plan after its termination but prior 
to liquidation of the plan's assets and distribution to the provider of 
services must be offset against the provider of services allowable 
interest expense under Sec.  413.153.
    (8) Treatment of residual assets following termination of a Funded 
Plan. (i) Residual assets arising from the termination of a funded 
Deferred Compensation Plan must be recouped in the year of the plan 
termination only against the cost center(s) in which the provider of 
services reported its plan contributions or payments, usually the 
administrative and general cost center.
    (ii) Residual assets exceeding the amount in the administrative and 
general (or other) cost center are not further offset in the current or 
subsequent years.
    (iii) The Medicare share of the reversion is based on the Medicare 
utilization rate in the year the reversion occurs (or the year the 
actuarial surplus is determined), and not Medicare's utilization in the 
years the contributions to the plan were made.
    (g) Treatment of costs associated with the PBGC. Costs associated 
with the requirements set forth in ERISA and by the PBGC and incurred 
by a provider of services who sponsors a QDBP are allowable or 
unallowable under the program as provided for in this paragraph (g).
    (1) Costs paid out of the plan trust. PBGC premiums and costs paid 
out of the corpus or earnings of the trust are included in the 
contributions allowed under paragraph (d)(3)(ii) of this section, and 
are not allowable as separate costs.
    (2) Premium payments for single- and multi-employer plans. The 
amount of PBGC premiums paid for basic benefits (flat rate or variable, 
excluding amounts paid out of the corpus or earnings of the trust) by a 
provider of services who sponsors a QDBP are allowable under the 
program.
    (3) Liability for missing participants or beneficiaries. The total 
amount paid to the PBGC by a provider of services who sponsors a QDBP 
(excluding amounts paid out of the corpus or earnings of the trust) of 
the benefit transfer amount (as described in 29 CFR 4050.103(d)) for 
all missing participants or beneficiaries of the QDBP, is allowable 
under the program.
    (4) Plan termination due to distress. For a defined benefit plan 
that terminated with insufficient assets to pay all of the plan 
benefits, which resulted in the PBGC making payment of vested benefits 
up to limits defined by law in accordance with 29 CFR part 4022, such 
amounts contributed to the QDBP by the provider of services who 
sponsors the QDBP are allowable. Benefits paid to the participants and 
beneficiaries of the QDBP by the PBGC are unallowable.
    (5) Restored plan payments. If the PBGC issues or has issued a plan 
restoration order as described in 29 CFR part 4047, the amounts that 
the provider of services repays to the PBGC for guaranteed benefits and 
related expenses under the plan while the plan

[[Page 28652]]

was in terminated status, and any administrative costs assessed by the 
PBGC, excluding penalties, are allowable.

PART 482--CONDITIONS OF PARTICIPATION FOR HOSPITALS

0
17. The authority citation for part 482 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1395hh, and 1395rr, unless otherwise 
noted.

0
18. Section 482.42 is amended by--
0
a. Revising paragraph (e).
0
b. Redesignating paragraph (g) as paragraph (h).
0
c. Adding a new paragraph (g).
    The revision and addition read as follows:


Sec.  482.42  Condition of participation: Infection prevention and 
control and antibiotic stewardship programs.

* * * * *
    (e) COVID-19 and seasonal influenza reporting. Beginning at the 
conclusion of the COVID-19 Public Health Emergency, as defined in Sec.  
400.200 of this chapter, and continuing until April 30, 2024, except 
when the Secretary specifies an earlier end date for the requirements 
of this paragraph (e), the hospital must electronically report 
information about COVID-19 and seasonal influenza in a standardized 
format specified by the Secretary.
    (1) Related to COVID-19, to the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Suspected and confirmed COVID-19 infections among patients and 
staff.
    (ii) Total COVID-19 deaths among patients and staff.
    (iii) Personal protective equipment and testing supplies.
    (iv) Ventilator use, capacity, and supplies.
    (v) Total bed and intensive care unit bed census and capacity.
    (vi) Staffing shortages.
    (vii) COVID-19 vaccine administration data of patients and staff.
    (viii) Relevant therapeutic inventories or usage, or both.
    (2) Related to seasonal influenza, to the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Confirmed influenza infections among patients and staff.
    (ii) Total influenza deaths among patients and staff.
    (iii) Confirmed co-morbid influenza and COVID-19 infections among 
patients and staff.
* * * * *
    (g) Standard: Reporting of data related to viral and bacterial 
pathogens and infectious diseases of pandemic or epidemic potential. 
The hospital must electronically report information on Acute 
Respiratory Illness (including, but not limited to, Seasonal Influenza 
Virus, Influenza-like Illness, and Severe Acute Respiratory Infection), 
SARS-CoV-2/COVID-19, and other viral and bacterial pathogens and 
infectious diseases of pandemic or epidemic potential only when the 
Secretary has declared a Public Health Emergency (PHE), as defined in 
Sec.  400.200 of this chapter, directly related to such specific 
pathogens and infectious diseases. The requirements of this paragraph 
(g) will be applicable to local, state, regional, or national PHEs as 
declared by the Secretary.
    (1) The hospital must electronically report information about the 
infectious disease pathogen, relevant to the declared PHE, in a 
standardized format specified by the Secretary. To the extent as 
required by the Secretary, this report must include, the following:
    (i) Suspected and confirmed infections of the relevant infectious 
disease pathogen among patients and staff.
    (ii) Total deaths attributed to the relevant infectious disease 
pathogen among patients and staff.
    (iii) Personal protective equipment and other relevant supplies in 
the hospital.
    (iv) Capacity and supplies in the hospital relevant to the 
immediate and long term treatment of the relevant infectious disease 
pathogen, such as ventilator and dialysis/continuous renal replacement 
therapy capacity and supplies.
    (v) Total hospital bed and intensive care unit bed census, 
capacity, and capability.
    (vi) Staffing shortages.
    (vii) Vaccine administration data of patients and staff for 
conditions monitored under this section and where a specific vaccine is 
applicable.
    (viii) Relevant therapeutic inventories or usage, or both.
    (ix) Isolation capacity, including airborne isolation capacity.
    (x) Key co-morbidities or exposure risk factors, or both, of 
patients being treated for the pathogen or disease of interest in this 
section that are captured with interoperable data standards and 
elements.
    (2) Unless the Secretary specifies an alternative format by which 
the hospital must report these data elements, the hospital must report 
the applicable infection (confirmed and suspected) and vaccination data 
in a format that provides person-level information, which must include 
medical record identifier, race, ethnicity, age, sex, residential 
county and zip code, and relevant comorbidities for affected patients. 
Facilities must not report any directly or potentially individually-
identifiable information for affected patients (for example, name, 
social security number) that is not set out in this section or 
otherwise specified by the Secretary.
    (3) The hospital must provide the information specified in this 
paragraph (g) on a daily basis, unless the Secretary specifies a lesser 
frequency, to the Centers for Disease Control and Prevention's (CDC) 
National Healthcare Safety Network or other CDC-supported surveillance 
systems as determined by the Secretary.
* * * * *

PART 485--CONDITIONS OF PARTICIPATION: SPECIALIZED PROVIDERS

0
19. The authority citation for part 485 is revised to read as follows:

    Authority: 42 U.S.C. 1302 and 1395(hh).

0
20. Section 485.640 is amended by--
0
a. Revising paragraph (d).
0
b. Redesignating paragraph (f) as paragraph (g).
0
c. Adding a new paragraph (f).
    The revision and addition read as follows:


Sec.  485.640  Condition of participation: Infection prevention and 
control and antibiotic stewardship programs.

* * * * *
    (d) COVID-19 and seasonal influenza reporting. Beginning at the 
conclusion of the COVID-19 Public Health Emergency, as defined in Sec.  
400.200 of this chapter, and continuing until April 30, 2024, except 
when the Secretary specifies an earlier end date for the requirements 
of this paragraph (d), the CAH must electronically report information 
about COVID-19 and seasonal influenza in a standardized format 
specified by the Secretary.
    (1) Related to COVID-19, to the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Suspected and confirmed COVID-19 infections among patients and 
staff.
    (ii) Total COVID-19 deaths among patients and staff.
    (iii) Personal protective equipment and testing supplies.
    (iv) Ventilator use, capacity, and supplies.
    (v) Total bed and intensive care unit bed census and capacity.
    (vi) Staffing shortages.
    (vii) COVID-19 vaccine administration data of patients and staff.

[[Page 28653]]

    (viii) Relevant therapeutic inventories or usage, or both.
    (2) Related to seasonal influenza, to the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Confirmed influenza infections among patients and staff.
    (ii) Total influenza deaths among patients and staff.
    (iii) Confirmed co-morbid influenza and COVID-19 infections among 
patients and staff.
* * * * *
    (f) Standard: Reporting of data related to viral and bacterial 
pathogens and infectious diseases of pandemic or epidemic potential. 
The CAH must electronically report information on Acute Respiratory 
Illness (including, but not limited to, Seasonal Influenza Virus, 
Influenza-like Illness, and Severe Acute Respiratory Infection), SARS-
CoV-2/COVID-19, and other viral and bacterial pathogens and infectious 
diseases of pandemic or epidemic potential only when the Secretary has 
declared a Public Health Emergency (PHE), as defined in Sec.  400.200 
of this chapter, directly related to such specific pathogens and 
infectious diseases. The requirements of this paragraph (f) will be 
applicable to local, state, regional, or national PHEs as declared by 
the Secretary.
    (1) The CAH must electronically report information about the 
relevant infectious disease pathogen in a standardized format specified 
by the Secretary. To the extent as required by the Secretary, this 
report must include the following:
    (i) Suspected and confirmed infections of the relevant infectious 
disease pathogen among patients and staff.
    (ii) Total deaths attributed to the relevant infectious disease 
pathogen among patients and staff.
    (iii) Personal protective equipment and other relevant supplies in 
the CAH.
    (iv) Capacity and supplies in the CAH relevant to the immediate and 
long-term treatment of the relevant infectious disease pathogen, such 
as ventilator and dialysis/continuous renal replacement therapy 
capacity and supplies.
    (v) Total CAH bed and intensive care unit bed census, capacity, and 
capability.
    (vi) Staffing shortages.
    (vii) Vaccine administration data of patients and staff for 
conditions monitored under this section and where a specific vaccine is 
applicable.
    (viii) Relevant therapeutic inventories or usage, or both.
    (ix) Isolation capacity, including airborne isolation capacity.
    (x) Key co-morbidities or exposure risk factors of patients being 
treated for the pathogen or disease of interest in this section that 
are captured with interoperable data standards and elements.
    (2) Unless the Secretary specifies an alternative format by which 
the CAH must report these data elements, the CAH must report the 
applicable infection (confirmed and suspected) and vaccination data in 
a format that provides person-level information, which must include 
race, ethnicity, age, sex, residential county and zip code, and 
relevant comorbidities for affected patients. Facilities must not 
report any directly or personally individually-identifiable information 
for affected patients (for example, name, social security number) that 
is not set out in this section or otherwise specified by the Secretary.
    (3) The CAH must provide the information specified in this 
paragraph (f) on a daily basis, unless the Secretary specifies a lesser 
frequency, to the Centers for Disease Control and Prevention's (CDC) 
National Healthcare Safety Network or other CDC-supported surveillance 
systems as determined by the Secretary.
* * * * *

PART 495--STANDARDS FOR THE ELECTRONIC HEALTH RECORD TECHNOLOGY 
INCENTIVE PROGRAM

0
21. The authority citation for part 495 continues to read as follows:

    Authority: 42 U.S.C. 1302 and 1395hh.

0
22. Section 495.24 is amended by--
0
a. In the introductory text:
0
i. In the last sentence, removing the phrase ``for 2019 and subsequent 
years'' and adding in its place ``for 2019 through 2022''; and
0
ii. Adding a sentence at the end of the paragraph;
0
b. In paragraph (e) heading, removing the phrase ``for 2019 and 
subsequent years'' and adding in its place the phrase ``for 2019 
through 2022'';
0
c. In paragraph (e)(1)(i)(C), removing the phrase ``In 2022 and 
subsequent years, earn'' and adding in its place the phrase ``In 2022, 
earn'';
0
d. In paragraph (e)(4)(ii), removing the phrase ``In 2022 and 
subsequent years'' and adding in its place the phrase ``In 2022'';
0
e. In paragraph (e)(5)(ii)(B) introductory text, removing the phrase 
``In 2020 and subsequent years'' and adding in its place the phrase 
``In 2020 through 2022'';
0
f. In paragraph (e)(5)(iii)(A), removing the phrase ``in CY 2019 and 
subsequent years'' and adding in its place ``in CY 2019 through CY 
2022'';
0
g. In paragraph (e)(5)(v), removing the phrase ``Beginning with the EHR 
reporting period in CY 2019'' and adding in its place ``For the EHR 
reporting periods in CY 2019 through CY 2022'';
0
h. In paragraph (e)(7)(ii) introductory text, removing the phrase 
``beginning in CY 2019'' and adding in its place the phrase ``for CY 
2019 through CY 2022'';
0
i. In paragraph (e)(8)(ii) introducotry text, removing the phrase ``For 
CY 2022 and subsequent years'' and adding in its place ``For CY 2022'';
0
j. In paragraph (e)(8)(ii)(A), removing the phrase ``For CY 2022 and 
subsequent years'' and adding in its place ``For CY 2022'';
0
k. In paragraphs (e)(8)(iii) introductory text, removing the phrase 
``For CY 2022 and subsequent years'' and adding in its place ``For CY 
2022'';
0
l. In paragraph (e)(8)(iii)(A)(2), removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022'';
0
m. In paragraph (e)(8)(iii)(D)(2), removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022'';
0
n. In paragraph (e)(8)(iii)(E)(2), removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022''; and
0
o. Adding paragraph (f).
    The 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.

    * * * The criteria specified in paragraph (f) of this section are 
applicable for eligible hospitals and CAHs attesting to CMS for 2023 
and subsequent years.
* * * * *
    (f) Stage 3 objectives and measures for eligible hospitals and CAHs 
attesting to CMS for 2023 and subsequent years--(1) General rule. (i) 
Except as specified in paragraph (f)(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 selected by CMS 
under section 1886(n)(3) of the Act for an EHR reporting period.
    (B) In 2023 and subsequent years, earn a total score of at least 60 
points.
    (ii) The numerator and denominator of the measures increment based 
on actions occurring during the EHR reporting period selected by the 
eligible hospital or CAH, unless otherwise indicated.

[[Page 28654]]

    (2) Exclusion for nonapplicable measures--(i) Exclusion of a 
particular measure. An eligible hospital or CAH may exclude a 
particular measure that includes an option for exclusion if the 
eligible hospital or CAH meets the following requirements:
    (A) Meets the criteria in the applicable measure that would permit 
the exclusion.
    (B) Attests to the exclusion.
    (ii) Distribution of points for nonapplicable measures. For 
eligible hospitals or CAHs that claim such exclusion, the points 
assigned to the excluded measure are distributed to other measures as 
specified by CMS for an EHR reporting period.

    Dated: April 13, 2022.
Xavier Becerra,
Secretary, Department of Health and Human Services.

    Note: The following Addendum and Appendixes will not appear in 
the Code of Federal Regulations.

Table of Contents

Addendum--Schedule of Standardized Amounts, Update Factors, and Rate-
of-Increase Percentages Effective With Cost Reporting Periods Beginning 
on or After October 1, 2022 and Payment Rates for LTCHs Effective for 
Discharges Occurring on or After October 1, 2022

I. Summary and Background
II. Proposed Changes to Prospective Payment Rates for Hospital 
Inpatient Operating Costs for Acute Care Hospitals for FY 2023
    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 2023
    A. Determination of the Proposed Federal Hospital Inpatient 
Capital-Related Prospective Payment Rate Update for FY 2023
    B. Calculation of the Proposed Inpatient Capital-Related 
Prospective Payments for FY 2023
    C. Capital Input Price Index
IV. Proposed Changes to Payment Rates for Excluded Hospitals: Rate-
of-Increase Percentages for FY 2023
V. Proposed Changes to the Payment Rates for the LTCH PPS for FY 
2023
    A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2023
    B. Proposed Adjustment for Area Wage Levels Under the LTCH PPS 
for FY 2023
    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 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 2023
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 Analysis
VI. Executive Order 13132
VII. Executive Order 13175
VIII. 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 2023
    A. Proposed FY 2023 Inpatient Hospital Update
    B. Proposed Update for SCHs for FY 2023
    C. Proposed FY 2023 Puerto Rico Hospital Update
    D. Proposed Update for Hospitals Excluded From the IPPS for FY 
2023
    E. Proposed Update for LTCHs for FY 2023
III. Secretary's Recommendations
IV. MedPAC Recommendation for Assessing Payment Adequacy and 
Updating Payments in Traditional Medicare

Addendum--Schedule of Standardized Amounts, Update Factors, Rate-of-
Increase Percentages Effective With Cost Reporting Periods Beginning on 
or After October 1, 2022, and Payment Rates for LTCHs Effective for 
Discharges Occurring on or After October 1, 2022

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 2023 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 
2023. 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, 2022.
    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 2023.
    In general, except for SCHs, for FY 2023, 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. Under current law, the MDH program is 
effective for discharges on or before September 30, 2022. Therefore, 
under current law, the MDH program will expire at the end of FY 2022.
    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

[[Page 28655]]

updated hospital-specific rate based on FY 2006 costs per discharge.
    As discussed in section V.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 
2023. 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 2023. 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 2023. 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 2023. 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 2023

    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 
2023.
    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 2023, 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 2023 
inpatient hospital update. The table that follows shows these four 
scenarios:
[GRAPHIC] [TIFF OMITTED] TP10MY22.241

    We note that section 1886(b)(3)(B)(viii) of the Act, which 
specifies the adjustment to the applicable percentage increase for 
``subsection (d)'' hospitals that do not submit quality data under the 
rules established by the Secretary, is not applicable to hospitals 
located in Puerto Rico.
    In addition, section 602 of Public Law 114-113 amended section 
1886(n)(6)(B) of the Act to specify that Puerto Rico hospitals are 
eligible for incentive payments for the meaningful use of certified EHR 
technology, effective beginning FY 2016, and also to apply the 
adjustments to the applicable percentage increase under section 
1886(b)(3)(B)(ix) of the Act to subsection (d) Puerto Rico hospitals 
that are not meaningful EHR users, effective beginning FY 2022. 
Accordingly, for FY 2022, section 1886(b)(3)(B)(ix) of the Act in 
conjunction with section 602(d) of Public Law 114-113 requires that any 
subsection (d) Puerto Rico hospital that is not a meaningful EHR user 
(as defined in section 1886(n)(3) of the Act) and not subject to an 
exception under section 1886(b)(3)(B)(ix) of the Act will have ``three-
quarters'' of the applicable percentage increase (prior to the 
application of other statutory adjustments), or three-quarters of the 
applicable market basket update, reduced by 33\1/3\ percent. The 
reduction

[[Page 28656]]

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). 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 2023 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 the standardized amount to ensure budget 
neutrality for our proposed permanent 10-percent cap on the reduction 
in a MS-DRG's relative weight in a given fiscal year beginning FY 2023, 
as discussed in section II.E.2.d. of the preamble of this proposed 
rule, consistent with our current methodology for implementing DRG 
recalibration and reclassification budget neutrality 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 2022 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 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 the standardized amount to implement in a 
budget neutral manner our proposal of a permanent wage index cap 
policy, consistent with our proposal in section III. N of the preamble 
of this proposed rule.
     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 Pub. L. 111-148; 
section 15003 of Pub. L. 114-255; and Division CC, section 128 of Pub. 
L. 116-260, which extended the program), are budget neutral, as 
required under section 410A(c)(2) of Pub. L. 108-173.
     An adjustment to remove the FY 2022 outlier offset and 
apply an offset for FY 2023, as provided for in section 1886(d)(3)(B) 
of the Act.
    For FY 2023, 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 2023 wage index for the rural floor.
    For FY 2023, we are proposing to continue to not remove the 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 and 59033). When cost report data regarding reasonable cost of 
acquisition become available, we intend to consider using that 
reasonable cost data in future rulemaking for budget neutrality.

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 2023, we are proposing to continue to use the national 
labor-related and nonlabor-related shares (which are based on the 2018-
based IPPS market basket) that were used in FY 2022. 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 2023, as discussed 
in section III.M. of the preamble of the 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 2023 national average 
standardized amount irrespective of whether a hospital is located in an 
urban or rural location.

[[Page 28657]]

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 2018-based 
IPPS operating and capital market baskets for FY 2023. 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 2023 applicable 
percentage increase (which for this proposed rule is based on IGI's 
fourth quarter 2021 forecast of the 2018-based IPPS market basket) by 
the productivity adjustment, as discussed elsewhere in this proposed 
rule.
    Based on IGI's fourth quarter 2021 forecast (as discussed in 
Appendix B of this proposed rule), the forecast of the IPPS market 
basket increase for FY 2023 for this proposed rule is 3.1 percent. As 
discussed earlier, for FY 2023, 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 V.B. of the preamble of this 
proposed rule for a complete discussion on the FY 2023 inpatient 
hospital update to the standardized amount. We also refer readers to 
the previous table for the four 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 2023 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 
2023 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
    The methodology we used to calculate the proposed FY 2023 
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 2023 
standardized amount to remove the effects of the FY 2022 geographic 
reclassifications and outlier payments before applying the FY 2023 
updates. We then applied budget neutrality offsets for outliers and 
geographic reclassifications to the standardized amount based on 
proposed FY 2023 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 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 2023, we are continuing to remove allogeneic 
hematopoietic stem cell acquisition charges from the covered charge 
field for budget neutrality adjustments. As discussed in

[[Page 28658]]

the FY 2021 IPPS/LTCH PPS final rule, payment for allogeneic 
hematopoietic stem cell acquisition costs is made on a reasonable cost 
basis for cost reporting periods beginning on or after October 1, 2020 
(85 FR 58835 through 58842).
     The participation of hospitals under the BPCI (Bundled 
Payments for Care Improvement) Advanced model started on October 1, 
2018. The BPCI Advanced model, tested under the authority of section 
3021 of the Affordable Care Act (codified at section 1115A of the Act), 
is comprised of a single payment and risk track, which bundles payments 
for multiple services beneficiaries receive during a Clinical Episode. 
Acute care hospitals may participate in the BPCI Advanced model in one 
of two capacities: As a model Participant or as a downstream Episode 
Initiator. Regardless of the capacity in which they participate in the 
BPCI Advanced model, participating acute care hospitals 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 2023, 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 2023, we are proposing to continue to apply a proposed 
proxy based on the prior fiscal year hospital readmissions payment 
adjustment (for FY 2023 this would be FY 2022 final adjustment factors 
from Table 15 of the FY 2022 IPPS/LTCH PPS final rule) and a proposed 
proxy based on the prior fiscal year hospital VBP payment adjustment 
(for FY 2023, this proposed proxy would be an adjustment factor of 1 to 
reflect our policy for the FY 2022 program year to suppress measures 
and award each hospital a value-based payment amount that matches the 
reduction to the base operating DRG payment amount) 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 
from the prior final rule 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 2023 (as we did for the last 9 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.
     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 2023. Similar to FY 2022, 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 2023.
     In our determination of all budget neutrality factors 
described in section

[[Page 28659]]

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. of the preamble of the FY 2020 IPPS/LTCH PPS final rule (84 FR 
45239 through 42342).
    We note that prior to FY 2020, the Rural Community Hospital (RCH) 
Demonstration budget neutrality factor was typically applied to the 
standardized amount after all wage index and other budget neutrality 
factors were applied. In the past we completed all the wage index 
budget neutrality factors and then applied the RCH Demonstration budget 
neutrality factor. Beginning with FY 2020, we finalized and implemented 
additional policies in a budget neutral manner such as the increase in 
the wage index values for hospitals with a wage index value below the 
25th percentile wage index value across all hospitals and the 
transitional wage indexes. When these new policies were implemented 
beginning with FY 2020, the associated budget neutrality adjustments 
were applied to the standardized amount after the RCH Demonstration 
budget neutrality factor was applied. Taking into consideration that we 
are proposing to place a permanent cap on wage index decreases 
beginning FY 2023, we believe the RCH Demonstration budget neutrality 
factor should revert to the order prior to FY 2020 and be applied after 
all wage index and other budget neutrality adjustments. Therefore, 
beginning in FY 2023, we are proposing to change the ordering of budget 
neutrality factors with the proposed RCH Demonstration budget 
neutrality factor applied after all wage index and other budget 
neutrality factors. We believe this re-ordering of applying the RCH 
Demonstration budget neutrality factor after all wage index and other 
budget neutrality factors will have a minimal impact and minor 
interactive affects.
a. Proposed Reclassification and Recalibration of MS-DRG Relative 
Weights Before Proposed Cap
    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.E of 
this proposed rule, we are proposing to determine the MS DRG relative 
weights for FY 2023 by averaging the relative weights as calculated 
with and without COVID-19 cases in the FY 2021 data. We refer the 
reader to section II.E.2.c for complete details. As discussed in 
section II.E. of the preamble of this proposed rule, we normalized the 
recalibrated MS-DRG relative weights by an adjustment factor so that 
the average case relative weight after recalibration is equal to the 
average case relative weight prior to recalibration. However, equating 
the average case relative weight after recalibration to the average 
case relative weight before recalibration does not necessarily achieve 
budget neutrality with respect to aggregate payments to hospitals 
because payments to hospitals are affected by factors other than 
average case relative weight. Therefore, as we have done in past years, 
we are 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 2023 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 2021 discharge data to simulate payments and compared 
the following:
     Aggregate payments using the FY 2022 labor-related share 
percentages, the FY 2022 relative weights, and the FY 2022 pre-
reclassified wage data, and applied the estimated FY 2023 hospital 
readmissions payment adjustments and estimated FY 2023 hospital VBP 
payment adjustments; and
     Aggregate payments using the FY 2022 labor-related share 
percentages, the proposed FY 2023 relative weights before applying the 
proposed 10-percent cap, and the FY 2022 pre-reclassified wage data, 
and applied the estimated FY 2023 hospital readmissions payment 
adjustments and estimated FY 2023 hospital VBP payment adjustments 
applied previously.
    Because this payment simulation uses the proposed FY 2023 relative 
weights (before application of the proposed 10-percent cap), 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 2023 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 2023 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, 2022. Please see the table 
later in this section setting forth each of the proposed FY 2023 budget 
neutrality factors.
b. Proposed Budget Neutrality Adjustment for Reclassification and 
Recalibration of MS-DRG Relative Weights With Proposed Cap
    As discussed in section II.E.2.d of this proposed rule, we are 
proposing a permanent 10-percent cap on the reduction in a MS-DRG's 
relative weight in a given fiscal year, beginning in FY 2023. As 
discussed in section II.E.2.d of this proposed rule, and consistent 
with our current methodology for implementing budget neutrality for MS-
DRG reclassification and recalibration of the relative weights under 
section 1886(d)(4)(C)(iii) of the Act, we are proposing to apply a 
budget neutrality adjustment to the standardized amount for all 
hospitals so that this proposed 10-percent cap on relative weight 
reductions does not increase estimated aggregate Medicare payments 
beyond the payments that would be made had we never applied this cap. 
We refer the reader to section II.E.2.d of this proposed rule for 
further discussion on our proposed permanent 10-percent cap on the 
reduction in a MS-DRG's relative weight in a given fiscal year, 
including the proposed budget neutrality adjustment to the standardized 
amount.
    To calculate this proposed budget neutrality adjustment factor for 
FY 2023, we used FY 2021 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the FY 2022 labor-related share 
percentages, the FY 2023 relative weights before applying the proposed 
10-percent cap, and the FY 2022 pre-reclassified wage data, and applied 
the estimated FY 2023 hospital readmissions payment adjustments and 
estimated FY 2023 hospital VBP payment adjustments; and

[[Page 28660]]

     Aggregate payments using the FY 2022 labor-related share 
percentages, the proposed FY 2023 relative weights with the proposed 
10-percent cap, and the FY 2022 pre-reclassified wage data, and applied 
the estimated FY 2023 hospital readmissions payment adjustments and 
estimated FY 2023 hospital VBP payment adjustments applied previously.
    Because this payment simulation uses the FY 2023 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 2023 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 2023 relative weights 
to account for certain cases that group to MS-DRG 018.
    In addition, we applied the proposed MS-DRG reclassification and 
recalibration budget neutrality adjustment factor before the proposed 
cap (derived in the first step) to the payment rates that were used to 
simulate payments for this comparison of aggregate payments from FY 
2022 to FY 2023. 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 this budget neutrality factor to the hospital-
specific rates that are effective for cost reporting periods beginning 
on or after October 1, 2022. Please see the table later in this section 
setting forth each of the proposed FY 2023 budget neutrality factors.
c. 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 2023, 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 2021 
discharge data to simulate payments and compared the following:
     Aggregate payments using the proposed FY 2023 relative 
weights and the FY 2022 pre-reclassified wage indexes, applied the FY 
2022 labor-related share of 67.6 percent to all hospitals (regardless 
of whether the hospital's wage index was above or below 1.0000), and 
applied the proposed FY 2023 hospital readmissions payment adjustment 
and the estimated FY 2023 hospital VBP payment adjustment; and
     Aggregate payments using the proposed FY 2023 relative 
weights and the proposed FY 2023 pre-reclassified wage indexes, applied 
the proposed labor-related share for FY 2023 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 2023 hospital 
readmissions payment adjustments and estimated FY 2023 hospital VBP 
payment adjustments applied previously.
    In addition, we applied the proposed MS-DRG reclassification and 
recalibration budget neutrality adjustment factor before the proposed 
cap (derived in the first step) and the proposed 10-percent cap on 
relative weight reductions adjustment factor (derived from the second 
step) to the payment rates that were used to simulate payments for this 
comparison of aggregate payments from FY 2022 to FY 2023. 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 2023 proposed budget neutrality factors.
d. 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 2023, we used FY 2021 discharge data to 
simulate payments and compared the following:

[[Page 28661]]

     Aggregate payments using the proposed FY 2023 labor-
related share percentage, the proposed FY 2023 relative weights, and 
the proposed FY 2023 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 2023 hospital readmissions payment adjustments and the 
estimated FY 2023 hospital VBP payment adjustments; and
     Aggregate payments using the proposed FY 2023 labor-
related share percentage, the proposed FY 2023 relative weights, and 
the proposed FY 2023 wage data after such reclassifications, and 
applied the same estimated FY 2023 hospital readmissions payment 
adjustments and the estimated FY 2023 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 2023, and applies the proposed 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 2023 budget neutrality factors.
    The proposed FY 2023 budget neutrality adjustment factor was 
applied to the proposed standardized amount after removing the effects 
of the FY 2022 budget neutrality adjustment factor. We note that the 
proposed FY 2023 budget neutrality adjustment reflects FY 2023 wage 
index reclassifications approved by the MGCRB or the Administrator at 
the time of development of this proposed rule.
e. 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 2023 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 2023, 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 2023 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 
2023 rural Puerto Rico wage index is calculated based on the average of 
the proposed FY 2023 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 2021 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 2023 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 applying the imputed floor after the application of the rural floor 
and applying 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. We refer the 
reader to section III.G.2. of the preamble of this proposed rule for a 
complete discussion regarding the imputed floor.
f. Proposed 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 proposing to continue for FY 2023 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 2023, we used FY 2021 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the proposed FY 2023 labor-
related share percentage, the proposed FY 2023 relative weights, and 
the proposed FY 2023 wage index for each hospital before adjusting the 
wage indexes under

[[Page 28662]]

the low wage index hospital policy, and applied the estimated FY 2023 
hospital readmissions payment adjustments and the estimated FY 2023 
hospital VBP payment adjustments, and the operating outlier 
reconciliation adjusted outlier percentage discussed later in this 
section; and
     Aggregate payments using the proposed FY 2023 labor-
related share percentage, the proposed FY 2023 relative weights, and 
the proposed FY 2023 wage index for each hospital after adjusting the 
wage indexes under the low wage index hospital policy, and applied the 
same estimated FY 2023 hospital readmissions payment adjustments and 
the estimated FY 2023 hospital VBP payment adjustments applied 
previously, and the operating outlier reconciliation adjusted outlier 
percentage discussed later in this section.
    This proposed FY 2023 budget neutrality adjustment factor was 
applied to the standardized amount.
g. Proposed Permanent Cap Policy for the Wage Index--Proposed Budget 
Neutrality Adjustment
    As noted previously, in section III.N. of the preamble to this 
proposed rule, for FY 2023 and subsequent years, we are proposing to 
apply a 5-percent cap on any decrease to a hospital's wage index from 
its wage index in the prior FY, regardless of the circumstances causing 
the decline. That is, we are proposing that a hospital's wage index for 
FY 2023 would not be less than 95 percent of its final wage index for 
FY 2022, and that for subsequent years, a hospital's wage index would 
not be less than 95 percent of its final wage index for the prior FY. 
In section III.N.2. of this proposed rule, we are also proposing to 
apply this proposed wage index cap policy in a budget neutral manner 
through an adjustment to the standardized amount to ensure that 
estimated aggregate payments under our proposed wage index cap policy 
for hospitals that would have a decrease in their wage indexes for the 
upcoming fiscal year of more than 5 percent would equal what estimated 
aggregate payments would have been without the proposed wage index cap 
policy. We refer readers to sections III.N.1 and III.N.2 of the 
preamble of this proposed rule for a complete discussion regarding this 
proposed policy.
    To calculate a proposed wage index cap budget neutrality adjustment 
factor for FY 2023, we used FY 2021 discharge data to simulate payments 
and compared the following:
     Aggregate payments without the proposed 5-percent cap 
using the proposed FY 2023 labor-related share percentages, the 
proposed FY 2023 relative weights, the proposed FY 2023 wage index for 
each hospital after adjusting the wage indexes under the low wage index 
hospital policy with the associated budget neutrality adjustment to the 
standardized amount, and applied the estimated FY 2023 hospital 
readmissions payment adjustments and the estimated FY 2023 hospital VBP 
payment adjustments, and the operating outlier reconciliation adjusted 
outlier percentage discussed later in this section; and
     Aggregate payments with the proposed 5-percent cap using 
the proposed FY 2023 labor-related share percentages, the proposed FY 
2023 relative weights, the proposed FY 2023 wage index for each 
hospital after adjusting the wage indexes under the low wage index 
hospital policy with the associated budget neutrality adjustment to the 
standardized amount, and applied the same estimated FY 2023 hospital 
readmissions payment adjustments and the estimated FY 2023 hospital VBP 
payment adjustments applied previously, and the operating outlier 
reconciliation adjusted outlier percentage discussed later in this 
section.
    We note, Table 2 associated with this proposed rule contains the 
wage index by provider before and after applying the low wage index 
hospital policy and the proposed cap.
h. Proposed Rural Community Hospital Demonstration Program Adjustment
    In section V.K. of the preamble of this proposed rule, we discuss 
the Rural Community Hospital (RCH) 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). 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 make an adjustment to the standardized amount to ensure 
the effects of the RCH Demonstration program are budget neutral as 
required under section 410A(c)(2) of Public Law 108-173. We refer 
readers to section V.K. 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 2023, based on 
the latest data for this proposed rule, the total amount that we would 
apply to make an adjustment to the standardized amounts to ensure the 
effects of the Rural Community Hospital Demonstration program are 
budget neutral is $107,945,638. Accordingly, using the most recent data 
available to account for the estimated costs of the demonstration 
program, for FY 2023, 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 2023 budget neutrality factors. We 
refer readers to section V.K. of the preamble of this proposed rule on 
complete details regarding the calculation of the amount we would apply 
to make an adjustment to the standardized amounts.
    The following table is a summary of the proposed FY 2023 budget 
neutrality factors, as discussed in the previous sections.

[[Page 28663]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.242

    As discussed in section II.A. of this proposed rule, we are 
proposing to use the FY 2021 data for FY 2023 ratesetting, with certain 
proposed modifications to our relative weight and outlier 
methodologies. As discussed elsewhere in this proposed rule and in this 
Addendum, we are soliciting comments on, as an alternative to our 
proposed approach, the use of the FY 2021 MedPAR claims for purposes of 
FY 2023 ratesetting without these proposed modifications to our usual 
methodologies. In order to facilitate comments on this alternative 
approach, we are making available budget neutrality and other 
ratesetting adjustments calculated under this alternative approach, 
which can be found on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We refer the 
reader to section I.O. of Appendix A of this proposed rule for further 
discussion of the files that we are making available with regard to our 
alternative approach.
i. Proposed Adjustment for FY 2023 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 2023, we are proposing to implement the 
required +0.5 percent adjustment to the standardized amount. This is a 
permanent adjustment to the payment rates.
j. 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.'' (As discussed later in this section, we are also 
proposing to include the proposed supplemental payment for eligible 
IHS/Tribal hospitals and Puerto Rico hospitals in the computation of 
the proposed outlier fixed-loss cost threshold beginning in FY 2023.) 
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 2023 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 2023, 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 https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/outlier.html.
(1) Proposed Methodology To Incorporate an Estimate of Outlier 
Reconciliation in the FY 2023 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

[[Page 28664]]

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 2023 Outlier Threshold Calculation
    Based on the methodology finalized in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42623 through 42625), for FY 2023, we are proposing 
to continue to incorporate outlier reconciliation in the FY 2023 
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 FYs 2021 and 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) and 
the FY 2016 cost reports (cost reports with a begin date on or after 
October 1, 2015, and on or before September 30, 2016), respectively.
    Similar to the FY 2022 methodology, in this proposed rule, we are 
proposing to determine a projection of outlier payment reconciliations 
for the FY 2023 outlier threshold calculation, by advancing the 
methodology by 1 year. Specifically, we are proposing to use FY 2017 
cost reports (cost reports with a begin date on or after October 1, 
2016, and on or before September 30, 2017).
    For FY 2023, we are proposing to use the same methodology from FY 
2020 to incorporate a projection of operating outlier payment 
reconciliations for the FY 2023 outlier threshold calculation. The 
following steps are the same as those finalized in the FY 2020 final 
rule but with updated data for FY 2023:
    Step 1.--Use the Federal FY 2017 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 2017 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total Federal operating 
payments using the Federal FY 2017 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 2017. This percentage amount would be used to 
adjust the outlier target for FY 2023 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 2017 cost reports based 
on the December 2021 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 2023 under 
our proposed methodology.
    For this FY 2023 proposed rule, we used the December 2021 HCRIS 
extract of the cost report data to calculate the proposed percentage 
adjustment for outlier reconciliation. For the FY 2023 final rule, we 
propose to use the latest quarterly HCRIS extract that is publicly 
available at the time of the development of that rule which, for FY 
2023, would be the March 2022 extract. Similar to the FY 2022 final 
rule, we may also

[[Page 28665]]

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 2023 outlier threshold.
    For this FY 2023 proposed rule, based on the December 2021 HCRIS, 
10 hospitals had an outlier reconciliation amount recorded on Worksheet 
E, Part A, Line 2.01 for total operating outlier reconciliation dollars 
of negative $11,939,505 (Step 2). The total Federal operating payments 
based on the December 2021 HCRIS was $88,388,722,611 (Step 3). The 
ratio (Step 4) is a negative -0.013508 percent, which, when rounded to 
the second digit, is -0.01 percent. Therefore, for FY 2023, 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 2023 outlier threshold as 
calculated 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 2023 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 2023 by incorporating the projection of negative 
outlier reconciliation. That is, under this proposal, total estimated 
outlier payments for FY 2023 would be the sum of the estimated FY 2023 
outlier payments based on the claims data from the outlier model and 
the estimated FY 2023 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 2023 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 
2023 outlier payments (which include the proposed estimated recoupment 
percentage for FY 2023 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 2023.
(b) Proposed Reduction to the FY 2023 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 2023 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 2023, we are proposing to use the same methodology from FY 
2020 to adjust the FY 2023 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 2023 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 2023 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 2023 outlier threshold calculation.
    Step 1.--Use the Federal FY 2017 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 2021 HCRIS 
extract for this proposed rule and expect to use the March 2022 HCRIS 
extract for the FY 2023 final rule. Similar to the FY 2022 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 2023 adjustment 
to the FY 2023 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 2017 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total capital Federal 
payments using the Federal FY 2017

[[Page 28666]]

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 2017. This percentage amount would be used to adjust 
the estimate of capital outlier payments for FY 2023 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 2023 
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 2023 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 2023 proposed rule, we used the December 
2021 HCRIS extract of the cost report data to calculate the proposed 
percentage adjustment for outlier reconciliation. For the FY 2023 final 
rule, we are proposing to use the latest quarterly HCRIS extract that 
is publicly available at the time of the development of that rule 
which, for FY 2023, would be the March 2022 extract. As previously 
noted, 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 2023 adjustment 
to the FY 2023 capital standard Federal rate.
    For this FY 2023 proposed rule, the estimated percentage of FY 2023 
capital outlier payments otherwise determined using the shared outlier 
threshold is 5.56 percent (estimated capital outlier payments of 
$394,593,407 divided by (estimated capital outlier payments of 
$394,593,407 plus the estimated total capital Federal payment of 
$6,707,033,365)). Based on the December 2021 HCRIS, # hospitals had an 
outlier reconciliation amount recorded on Worksheet E, Part A, Line 93 
for total capital outlier reconciliation dollars of negative $759,945 
(Step 2). The total Federal capital payments based on the December 2021 
HCRIS was $7,992,953,494 (Step 3) which results in a ratio (Step 4) of 
-0.01 percent. Therefore, for FY 2023, taking into account projected 
capital outlier reconciliation payments under our proposed methodology 
would decrease the estimated percentage of FY 2023 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 2023.
    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 
2023 capital outlier payments for purposes of determining the capital 
outlier adjustment factor.
(2) Proposed FY 2023 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 2023 
outlier threshold, we simulated payments by applying proposed FY 2023 
payment rates and policies using cases from the FY 2021 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 2023 outlier threshold, we 
inflated the charges on the MedPAR claims by 2 years, from FY 2021 to 
FY 2023. 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 2023:
     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.

[[Page 28667]]

     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 2023 
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 2023 
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.
    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 FY 2023, under our policy of computing the charge inflation 
factor using the publicly available Federal fiscal year period, we 
would ordinarily use charge data from the MedPAR files for Federal 
fiscal years 2020 and 2021 to compute the 1-year average annual rate-
of-change in charges per case. Specifically, for this proposed rule, we 
would ordinarily use the December 2020 MedPAR file of FY 2020 (October 
1, 2019, through September 30, 2020) charge data and the December 2021 
MedPAR file of FY 2021 (October 1, 2021, through September 30, 2021) 
charge data to compute the proposed charge inflation factor. However, 
based on our analysis, the charge inflation factors calculated using 
these two most recently available years of MedPAR claims data (FY 2020 
and FY 2021) are abnormally high as compared to recent historical 
levels prior to the COVID-19 PHE period. Specifically, we calculated a 
1-year average annual rate-of-change in charges per case of 
approximately 10 percent based on the FY 2020 and FY 2021 MedPAR claims 
data, as compared to approximately 6 percent based on the FY 2018 and 
2019 MedPAR claims data for the two most recent Federal fiscal year 
time periods prior to the PHE. We believe this abnormally high charge 
inflation as compared to historical levels was partially due to the 
high number of COVID-19 cases with higher charges that were treated in 
IPPS hospitals in FY 2021. As discussed in section I.F of the preamble 
of this proposed rule, we believe there will be fewer COVID-19 cases in 
FY 2023 than in FY 2021. Therefore, we do not believe it is reasonable 
to assume charges will continue to increase at these abnormally high 
rates.
    Therefore, for FY 2023, we are proposing to use the same 
methodology as FY 2020, with a proposed modification to use the most 
recent 1-year average annual rate-of-change in charges per case for the 
period prior to the COVID-19 PHE, 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. We further note that this is the same 
data used to determine the charge inflation factor for the FY 2022 
IPPS/LTCH PPS rulemaking. Specifically, for FY 2023, 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 are 
proposing to use 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 2023 IPPS/LTCH PPS final 
rule, we would continue to use the charge inflation estimate from the 
FY 2021 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 2023, we compared the average covered charge per case of 
$61,578.82 ($584,618,863,834/9,493,830 cases) from October 1, 2017, 
through September 31, 2018, to the average covered charge per case of 
$65,522.10 ($604,209,834,327/9,221,466 cases) from October 1, 2018, 
through September 31, 2019. This rate-of-change was 6.4 percent 
(1.06404) or 13.2 percent over two years (1.13218). Because we are 
proposing to use the FY 2021 MedPAR for the FY 2023 ratesetting, we 
applied a factor of 13.2 percent over 2 years. The billed charges are 
obtained from the claim from the MedPAR file and inflated by the 
inflation factor specified previously.
    We are also soliciting comments on the alternative approach of 
using the data we would ordinarily use to determine the charge 
inflation factor for purposes of this FY 2023 rule (that is, charge 
data from FYs 2020 and 2021 to compute the 1-year average annual rate 
of change in charges per case), and note that under this alternative 
approach, if finalized, we would anticipate using more recently updated 
data from FYs 2020 and 2021 for purposes of the FY 2023 IPPS/LTCH PPS 
final rule. As previously noted, in order to facilitate comments on our 
alternative approach of using the FY 2021 MedPAR claims for purposes of 
FY 2023 ratesetting but without the proposed modifications to our usual 
methodologies, including use of the same data that we would

[[Page 28668]]

ordinarily use for purposes of determining the charge inflation factor 
for this FY 2023 rulemaking, and which we may consider finalizing for 
FY 2023 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, an impact file 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.
    In this proposed rule, we are proposing to establish the FY 2023 
outlier threshold using hospital CCRs from the December 2021 update to 
the Provider-Specific File (PSF), the most recent available data at the 
time of developing this proposed rule. 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 2023, we are also proposing to continue to apply an 
adjustment factor to the CCRs to account for cost and charge inflation 
(as explained further 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 apply a proposed 
adjustment factor to adjust the CCRs from the December 2021 update of 
the PSF by comparing the percentage change in the national average 
case-weighted operating CCR and capital CCR from the December 2020 
update of the PSF to the national average case-weighted operating CCR 
and capital CCR from the December 2021 update of the PSF. However, the 
operating and capital CCR adjustment factors based on the data we 
ordinarily would use are above 1.0. Since the implementation of our new 
methodology to adjust the CCRs in the FY 2014 IPPS/LTCH PPS final rule 
(78 FR 50979), the operating and capital CCR adjustment factors have 
typically been below 1.0 (for example, operating and capital CCR 
adjustment factors of approximately 1.03 and 1.03, respectively, based 
on the December 2020 and December 2021 updates to the PSF as compared 
to operating and capital CCR adjustment factors of approximately 0.97 
and 0.96, respectively, based on the March 2019 and March 2020 updates 
to the PSF). As stated in section I.F. of the preamble to this proposed 
rule, we believe this abnormally high CCR adjustment factor as compared 
to historical levels is partially due to the high number of COVID-19 
cases with higher charges that were treated in IPPS hospitals in FY 
2021. As we previously stated, we believe there will be fewer COVID-19 
cases in FY 2023 than in FY 2021. Therefore, we do not believe it is 
reasonable to assume CCRs will continue to increase at these abnormally 
high rates. Therefore, we are proposing to adjust the CCRs from the 
December 2021 update of the PSF by comparing the percentage change in 
the national average case-weighted operating CCR and capital CCR from 
the March 2019 update of the PSF to the national average case-weighted 
operating CCR and capital CCR from the March 2020 update of the PSF, 
which is the last update of the PSF prior to the PHE. We note that this 
is the same data used to adjust the CCRs for the FY 2022 IPPS/LTCH PPS 
rulemaking. We believe using these data for the latest available period 
prior to the PHE, for which the percentage change in the national 
average case weighted operating CCR and capital CCR is below 1.0, is 
appropriate in light of our expectation that the CCRs will not continue 
to increase at these abnormally high rates for FY 2023. 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 March 2019 operating national average case-weighted CCR of 
0.254027 and a March 2020 operating national average case-weighted CCR 
of 0.247548. We then calculated the percentage change between the two 
national operating case-weighted CCRs by subtracting the March 2019 
operating national average case-weighted CCR from the March 2020 
operating national average case-weighted CCR and then dividing the 
result by the March 2019 national operating average case-weighted CCR. 
This resulted in a proposed one-year national operating CCR adjustment 
factor of 0.974495. Because we are proposing to use CCRs from the 
December 2021 update of the PSF for FY 2023, we are applying a one-year 
proposed national operating CCR adjustment.
    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 proposed one-year national capital CCR adjustment 
factor of 0.96165. Because we are proposing to use CCRs from the 
December 2021 update of the PSF for FY 2023, we are applying a one-year 
proposed national capital CCR adjustment.
    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 data that we would ordinarily use 
for purposes of adjusting the CCRs for this FY 2023 rulemaking, which 
we may consider finalizing for FY 2023 based on consideration of 
comments received. As previously noted, in order to facilitate comments 
on our alternative approach of using the FY 2021 MedPAR claims for 
purposes of FY 2023 ratesetting but

[[Page 28669]]

without the proposed modifications to our usual methodologies, we are 
making available supplemental data files, including 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 
2023, we used a wage index that reflects the policies discussed in the 
proposed rule. This includes all of the following:
     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.
     Incorporating the proposed FY 2023 low wage index hospital 
policy (described in section III. G. 4 of the preamble of this proposed 
rule) 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.
     Incorporating our proposed policy (described in section 
III. N of the preamble of this proposed rule) to apply a 5-percent cap 
on any decrease to a hospital's wage index from its wage index in the 
prior FY, regardless of the circumstances causing the decline.
    If we did not take the aforementioned into account, our estimate of 
total FY 2023 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).
    As described in sections V.K. and V.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 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 2023, 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 2023, we are proposing to include estimated FY 2023 
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.
    In addition, as discussed in section IV.E. of the preamble of the 
proposed rule, we are proposing to establish a supplemental payment for 
eligible IHS/Tribal hospitals and Puerto Rico hospitals, beginning in 
FY 2023. We are proposing to make interim payments of this proposed new 
supplement payment on a per-discharge basis. Consistent with the policy 
of including estimated uncompensated care payments in the computation 
of the proposed outlier fixed-loss cost threshold, as previously 
summarized, we are proposing to use our authority under section 
1886(d)(5)(I) of the Act to include the estimated supplemental payments 
in the computation of the proposed outlier fixed-loss cost threshold. 
Specifically, we are proposing to use the estimated per-discharge 
supplemental payments to hospitals eligible for the supplemental 
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 2023 outlier reconciliation in the methodology for 
determining the outlier threshold. As noted previously, for this FY 
2023 proposed rule, the ratio of outlier reconciliation dollars to 
total Federal Payments (Step 4) is a negative 0.013508 percent, which, 
when rounded to the second digit, is -0.01 percent. Therefore, for FY 
2023, 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 $43,214 and calculated total outlier payments 
of $4,709,906,314 and total operating Federal payments of 
$88,837,735,468. 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

[[Page 28670]]

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 
$43,292. We are proposing an outlier fixed-loss cost threshold for FY 
2023 equal to the prospective payment rate for the MS-DRG, plus any 
IME, empirically justified Medicare DSH payments, estimated 
uncompensated care payment, proposed estimated supplemental payment for 
eligible IHS/Tribal hospitals and Puerto Rico hospitals, and any add-on 
payments for new technology, plus $43,214.
    As previously noted, and as discussed further in section I.O of the 
Appendix A of this proposed rule, we are also considering an 
alternative approach of using the FY 2021 MedPAR claims for purposes of 
FY 2023 ratesetting but without the proposed modifications to our usual 
methodologies, including use of the same data we would ordinarily use 
for purposes of this FY 2023 rulemaking to compute the charge inflation 
factors and CCR adjustment factors in determining the FY 2023 outlier 
fixed-loss amount for IPPS cases. Under this alternative approach, we 
estimate an outlier threshold of $58,798 rather than the proposed 
threshold of $43,214 above.
(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 2023 (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 
5.55 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 2023 
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 2023 outlier threshold are as follows:
[GRAPHIC] [TIFF OMITTED] TP10MY22.243

    We are proposing to apply the outlier adjustment factors to the FY 
2023 payment rates after removing the effects of the FY 2022 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 1.222 or capital CCRs greater than 0.141 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, 2022, 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 2023 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.
    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 2021 Outlier Payments
    Our current estimate, using available FY 2021 claims data, is that 
actual outlier payments for FY 2021 were approximately 5.62 percent of 
actual total MS-DRG payments. Therefore, the data indicate that, for FY 
2021, the percentage of actual outlier payments relative to actual 
total payments is

[[Page 28671]]

higher than we projected for FY 2021. 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 2021 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 2022 
period would not be available until after September 30, 2022, we are 
unable to provide an estimate of actual outlier payments for FY 2022 
based on FY 2022 claims data in this proposed rule. We will provide an 
estimate of actual FY 2022 outlier payments in the FY 2024 IPPS/LTCH 
PPS proposed rule.
5. Proposed FY 2023 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 2023. 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 
2023.
    The proposed labor-related and nonlabor-related portions of the 
national average standardized amounts for Puerto Rico hospitals for FY 
2023 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 2022 
national standardized amounts to the proposed FY 2023 national 
standardized amounts. The second through fifth columns display the 
changes from the FY 2022 standardized amounts for each proposed 
applicable FY 2023 standardized amount. The first row of the table 
shows the updated (through FY 2022) average standardized amount after 
restoring the FY 2022 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 (that is, we have not restored the offsets). Accordingly, 
those FY 2022 adjustment factors have not been removed from the base 
rate in the following table. Additionally, for FY 2023 we have applied 
the budget neutrality factors for the lowest quartile hospital policy, 
described previously.
BILLING CODE 4910-59-P

[[Page 28672]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.244

BILLING CODE 4910-59-C

[[Page 28673]]

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 2023. 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 2023, 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 2023 wage 
index.
2. Adjustment for Cost-of-Living in Alaska and Hawaii
    Section 1886(d)(5)(H) of the Act provides discretionary authority 
to the Secretary to make adjustments as the Secretary deems appropriate 
to take into account the unique circumstances of hospitals located in 
Alaska and Hawaii. Higher labor-related costs for these two States are 
taken into account in the adjustment for area wages described 
previously. To account for higher non-labor 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.
    In the FY 2013 IPPS/LTCH PPS final rule, we established a 
methodology to update the COLA factors for Alaska and Hawaii that were 
published by the U.S. Office of Personnel Management (OPM) every 4 
years (at the same time as the update to the labor related share of the 
IPPS market basket), beginning in FY 2014. We refer readers to the FY 
2013 IPPS/LTCH PPS proposed and final rules for additional background 
and a detailed description of this methodology (77 FR 28145 through 
28146 and 77 FR 53700 through 53701, respectively). For FY 2022, in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45546 through 45547), we 
updated 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. Based on the policy finalized in the FY 2013 
IPPS/LTCH PPS final rule, we are continuing to use the same COLA 
factors in FY 2023 that were used in FY 2022 to adjust the nonlabor-
related portion of the standardized amount for hospitals located in 
Alaska and Hawaii. The following table lists the COLA factors for FY 
2023.
[GRAPHIC] [TIFF OMITTED] TP10MY22.245

    Lastly, as we finalized in the FY 2013 IPPS/LTCH PPS final rule (77 
FR 53700 and 53701), we intend to update the COLA factors based on our 
methodology every 4 years, at the same time as the update to the labor-
related share of the IPPS market basket.

C. Calculation of the Proposed Prospective Payment Rates

1. General Formula for Calculation of the Prospective Payment Rates for 
FY 2023
    In general, the operating prospective payment rate for all 
hospitals (including hospitals in Puerto Rico) paid under the IPPS, 
except SCHs, for FY 2023 equals the Federal rate (which includes 
uncompensated care payments). Under current law, the MDH program is 
effective for discharges on or before September 30, 2022. Therefore, 
under current law, the MDH program will expire at the end of FY 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-

[[Page 28674]]

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.
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). We note 
that the formula specified below reflects our proposal to include the 
proposed estimated supplemental payment for eligible IHS/Tribal 
hospitals and Puerto Rico hospitals in the computation of the outlier 
fixed-loss cost threshold.
    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 + Proposed Supplemental Payment for IHS/Tribal hospitals and 
Puerto Rico hospitals + 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. In addition, we add the uncompensated care payment to the total 
claim payment amount. As noted in the previous formula, we take 
uncompensated care payments and new technology add-on payments into 
consideration when calculating outlier payments. Finally, as previously 
discussed, we are also proposing, beginning in FY 2023, to take into 
consideration the proposed supplemental payment for eligible IHS/Tribal 
hospitals and Puerto Rico hospitals 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. (We note, under current law, the 
MDH program is effective for discharges on or before September 30, 
2022. Therefore, under current law, the MDH program will expire at the 
end of FY 2022.)
    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 2023
    Section 1886(b)(3)(B)(iv) of the Act provides that the applicable 
percentage increase applicable to the hospital-specific rates for SCHs 
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 equal to the update factor for all other IPPS 
hospitals, the update to the hospital-specific rates for SCHs 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 are the following:

[[Page 28675]]

[GRAPHIC] [TIFF OMITTED] TP10MY22.246

    For a complete discussion of the applicable percentage increase 
applied to the hospital-specific rates for SCHs, we refer readers to 
section V.B. of the preamble of this proposed rule.
    In addition, because SCHs use the same MS-DRGs as other hospitals 
when they are paid based 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 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. 
In addition, as discussed in section II.E.2.d of this proposed rule and 
above, we are proposing a permanent 10-percent cap on the reduction in 
a MS-DRG's relative weight in a given fiscal year, beginning in FY 
2023. As discussed in section II.E.2.d of this proposed rule, and 
consistent with our current methodology for implementing budget 
neutrality for DRG reclassification and recalibration of the relative 
weights, we are proposing to apply a budget neutrality adjustment to 
the standardized amount for all hospitals so that this proposed 10-
percent cap on relative weight reductions does not increase estimated 
aggregate Medicare payments beyond the payments that would be made had 
we never applied this cap. As mentioned previously, SCHs use the same 
MS-DRGs as other hospitals when they are paid based on the hospital-
specific rate. Therefore, we are proposing that the hospital specific-
rate for an SCH would be adjusted by the proposed MS-DRG 10-percent cap 
budget neutrality factor. The resulting rate is used in determining the 
payment rate that an SCH would receive for its discharges beginning on 
or after October 1, 2022. We note that, in this proposed rule, for FY 
2023, 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.
    We note, as mentioned previously, under current law, the MDH 
program is effective for discharges on or before September 30, 2022. 
Therefore, under current law, the MDH program will expire at the end of 
FY 2022. However, if the MDH program were to be extended by Congress 
for FY 2023, we would propose to apply the MS-DRG reclassification and 
recalibration budget neutrality factor and the proposed cap policy MS-
DRG budget neutrality factor to the hospital specific rate for MDHs.

III. Proposed Changes to Payment Rates for Acute Care Hospital 
Inpatient Capital-Related Costs for FY 2023

    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 
2023, which would be effective for discharges occurring on or after 
October 1, 2022.
    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 2023

    In the discussion that follows, we explain the factors that we are 
proposing to use to determine the capital Federal rate for FY 2023. In 
particular, we explain why the proposed FY 2023 capital Federal rate 
would increase approximately 1.63 percent, compared to the FY 2022 
capital Federal rate. As discussed in the impact analysis in Appendix A 
to this proposed rule, we

[[Page 28676]]

estimate that capital payments per discharge would decrease 
approximately 0.4 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.
    In section I.F. of the preamble to this proposed rule, we discuss 
our proposal to use FY 2021 data for purposes of FY 2023 IPPS 
ratesetting. Consistent with this proposal, for this proposed rule we 
are proposing to use claims from the December 2021 update of the FY 
2021 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, we 
also discuss in section I.F of the preamble to this proposed rule 
certain modifications we propose to make to our usual methodologies to 
account for the anticipated decline in COVID-19 hospitalizations of 
Medicare beneficiaries at IPPS hospitals in FY 2023 as compared to FY 
2021. First, we are proposing to modify the calculation of the FY 2023 
MS-DRG relative weights by first calculating two sets of weights, one 
including and one excluding COVID-19 claims in the FY 2021 data, and 
then averaging the two sets of relative weights to determine the 
proposed FY 2023 MS-DRG relative weight values (as described in greater 
detail in section II.E. of the preamble to this proposed rule). Second, 
we are proposing to modify our methodologies for determining the FY 
2023 outlier fixed-loss amount for IPPS cases by using charge inflation 
factors and CCR adjustment factors based on the last 1-year period 
prior to the COVID-19 PHE (as discussed in greater detail in section 
II.A.4. of the Addendum to this proposed rule). In section I.O. of 
Appendix A of this proposed rule, we are also considering as an 
alternative to this proposal, to use the FY 2021 data for purposes of 
FY 2023 IPPS ratesetting without these proposed modifications to our 
usual methodologies for the calculation of the FY 2023 MS-DRG relative 
weights or the usual methodologies used to determine the FY 2023 
outlier fixed-loss amount for IPPS cases. 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.
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 2023 under that framework is 1.7 percent based on 
a projected 1.7 percent increase in the 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 0.0 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 2023 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 2023.
    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 2023, we are projecting a 1.0 percent total increase in the 
case-mix index. We estimated that the real case-mix increase would 
equal 1.0 percent for FY 2023. 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 2023 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, 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 proposed rule, we have the FY 2021 MedPAR claims data 
available to evaluate the effects of the FY 2021 DRG reclassification 
and recalibration as part of our update for FY 2023. We assume for 
purposes of this adjustment, that the estimate of FY 2021 DRG 
reclassification and recalibration would result in no change in the 
case-mix when compared with the case mix index that would have resulted 
if we had not made the reclassification and recalibration changes to 
the DRGs. Therefore, we are proposing to make a 0.0 percentage point 
adjustment for reclassification and recalibration in the update 
framework for FY 2023.
    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 
greater than 0.25 percentage point in absolute terms. 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

[[Page 28677]]

under this framework. A forecast error of -0.1 percentage point was 
calculated for the FY 2021 update, for which there are historical data. 
That is, current historical data indicated that the forecasted FY 2021 
CIPI (1.1 percent) used in calculating the FY 2021 update factor is 0.1 
percentage point higher than actual realized price increases (1.0 
percent). As this does not exceed the 0.25 percentage point threshold, 
we are not proposing an adjustment for forecast error in the update for 
FY 2023.
    Under the capital IPPS update framework, we also make an adjustment 
for changes in intensity. Historically, we calculate this adjustment 
using the same methodology and data that were used in the past under 
the framework for operating IPPS. The intensity factor for the 
operating update framework reflects how hospital services are utilized 
to produce the final product, that is, the discharge. This component 
accounts for changes in the use of quality-enhancing services, for 
changes within DRG severity, and for expected modification of practice 
patterns to remove noncost-effective services. Our intensity measure is 
based on a 5-year average.
    We calculate case-mix constant intensity as the change in total 
cost per discharge, adjusted for price level changes (the CPI for 
hospital and related services) and changes in real case-mix. Without 
reliable estimates of the proportions of the overall annual intensity 
changes that are due, respectively, to ineffective practice patterns 
and the combination of quality-enhancing new technologies and 
complexity within the DRG system, we assume that one-half of the annual 
change is due to each of these factors. Thus, the capital update 
framework provides an add-on to the input price index rate of increase 
of one-half of the estimated annual increase in intensity, to allow for 
increases within DRG severity and the adoption of quality-enhancing 
technology.
    In this 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 2023 (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 2023, 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 
2016 and extending through FY 2020. Based on these data, we estimated 
that case-mix constant intensity declined during FYs 2016 through 2020. 
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 2023. 
Therefore, we are proposing to make a 0.0 percentage point adjustment 
for intensity in the update for FY 2023.
    Earlier, we described the basis of the components we used to 
develop the proposed 1.7 percent capital update factor under the 
capital update framework for FY 2023, as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.247

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 2023, we are proposing to 
incorporate the estimated outlier reconciliation payment amounts into 
the outlier threshold model, as we did for FY 2022. (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 2022, we estimated that outlier payments for capital-related 
PPS payments would equal 5.29 percent of inpatient capital-related 
payments based on the capital Federal rate in FY 2022. 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 5.56 
percent for inpatient capital-related payments based on the proposed 
capital Federal rate in FY 2023. 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 2023 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 5.55 percent (5.56 percent-0.01 percent) of 
inpatient capital-related payments based on the capital Federal rate in 
FY 2023. Accordingly, we are proposing to apply an outlier adjustment 
factor of 0.9445 in determining the capital Federal rate for FY 2023. 
Thus, we estimate that the percentage of capital outlier payments to 
total capital Federal rate payments for

[[Page 28678]]

FY 2023 would be higher than the percentage for FY 2022.
    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 2023 outlier 
adjustment of 0.9445 is a -0.27 percent change from the FY 2022 outlier 
adjustment of 0.9471. Therefore, the proposed net change in the outlier 
adjustment to the capital Federal rate for FY 2023 is 0.9973 (0.9445/
0.9471) so that the proposed outlier adjustment would decrease the FY 
2023 capital Federal rate by approximately -0.27 percent compared to 
the FY 2022 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, 2021 and 2022, and will continue to apply in FY 2023. In 
addition, in FYs 2020 and 2021, we 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)). In FY 2022, we finalized a policy that for 
hospitals that received the transition in FY 2021 (that is hospitals 
that received a 5 percent cap on their FY 2021 wage index), we 
continued a wage index transition for FY 2022 under which we applied a 
5 percent cap on any decrease in the hospital's wage index compared to 
its wage index for FY 2021 (86 FR 45164 through 45165). Beginning in FY 
2023, as discussed in section III.N. of the preamble to this proposed 
rule, we are proposing a permanent cap on wage index decreases, 
limiting the overall reductions in a hospital's wage index value for 
the upcoming FY to be no greater than 5 percent of its wage index value 
for the current FY. That is, under this proposed policy a hospital's 
wage index value would not be less than 95 percent of its prior year 
value.
    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. 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 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. We further note that in this section, we refer to the 
proposed permanent cap on wage index decreases beginning in FY 2023 as 
the proposed 5 percent cap on wage index decreases policy.
    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 the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45552), we finalized our proposal to 
not 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. Accordingly 
and consistent with this approach, prior to calculating the proposed 
GAF budget neutrality factors for FY 2023, we removed from the capital 
Federal rate the budget neutrality factor applied in FY 2022 for the 
lowest quartile hospital wage index adjustment and the 5 percent cap on 
wage index decreases. Specifically, we divided the capital Federal rate 
by the FY 2022 budget neutrality factor of 0.9974 (86 FR 45552). We 
refer the reader to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45552) 
for additional discussion on our policy of removing the prior year 
budget neutrality factor for the lowest quartile hospital wage index 
adjustment and the 5 percent cap on wage index decreases from the 
capital Federal rate.
    In light of the proposed changes to the wage index and other 
proposed wage index policies for FY 2023 discussed previously, which 
directly affect the GAF, we are proposing to continue to compute a 
budget neutrality adjustment for changes in the GAFs in two steps. We 
discuss our proposed 2-step calculation of the proposed GAF budget 
neutrality factors for FY 2023 as follows.
    To determine the GAF budget neutrality factors for FY 2023, we 
first compared estimated aggregate capital Federal rate payments based 
on the FY 2022 MS-DRG classifications and relative weights and the FY 
2022 GAFs to estimated aggregate capital Federal rate payments based on 
the FY 2022 MS-DRG classifications and relative weights and the 
proposed FY 2023 GAFs without incorporating the lowest quartile 
hospital wage index adjustment and the proposed 5 percent cap on wage 
index decreases policy. To achieve budget neutrality for these proposed 
changes in the GAFs, we calculated an incremental GAF budget neutrality 
adjustment factor of 1.0019 for FY 2023. Next, we compared estimated 
aggregate capital Federal rate payments based on the proposed FY 2023 
GAFs with and without the lowest quartile hospital wage index 
adjustment and the proposed 5 percent cap on wage index decreases 
policy. For this calculation, estimated aggregate capital Federal rate 
payments were calculated using the proposed FY 2023 MS-DRG 
classifications and relative weights (after application of the proposed 
10 percent cap discussed later in this section) and the proposed FY 
2023 GAFs (both with and without the lowest quartile hospital wage 
index adjustment and the proposed 5 percent cap on wage index decreases 
policy). (We note, for this calculation the proposed GAFs included the 
imputed floor, out-migration and Frontier state adjustments.) To 
achieve budget

[[Page 28679]]

neutrality for the effects of the lowest quartile hospital wage index 
adjustment and the proposed 5 percent cap on wage index decreases 
policy on the proposed FY 2023 GAFs, we calculated an incremental GAF 
budget neutrality adjustment factor of 0.9971. As discussed earlier in 
this section, the budget neutrality factor for the lowest quartile 
hospital wage index adjustment factor and the 5 percent cap on wage 
index decreases is not permanently built into the capital Federal rate. 
Consistent with this, we present the proposed budget neutrality factor 
for the lowest quartile hospital wage index adjustment and the proposed 
5 percent cap on wage index decreases calculated under the second step 
of this 2-step methodology separately from the other proposed budget 
neutrality factors in the discussion that follows, and this proposed 
factor is not included in the calculation of the proposed combined GAF/
DRG adjustment factor described later in this section.
    In section II.E.2. of the preamble to this proposed rule, we 
discuss our proposal to apply a permanent 10 percent cap on the 
reduction in a MS-DRG's relative weight in a given year. Consistent 
with our current methodology for adjusting the capital standard Federal 
rate to ensure that the effects of the annual DRG reclassification and 
the recalibration of DRG weights are budget neutral under Sec.  
412.308(c)(4)(ii), we are proposing to apply an additional budget 
neutrality factor to the capital standard Federal rate so that the 
proposed 10 percent cap on decreases in an MS-DRG's relative weight is 
implemented in a budget neutral manner. Specifically, in light of this 
proposal, we are proposing to augment our historical methodology for 
computing the budget neutrality factor for the annual DRG 
reclassification and recalibration by computing a budget neutrality 
adjustment for the annual DRG reclassification and recalibration in two 
steps. We are proposing to first calculate a budget neutrality factor 
to account for the annual DRG reclassification and recalibration prior 
to the application of the 10 percent cap on MS-DRG relative weight 
decreases. We then are proposing to calculate an additional budget 
neutrality factor to account for the application of the 10 percent cap 
on MS-DRG relative weight decreases.
    To determine the proposed DRG budget neutrality factors for FY 
2023, we first compared estimated aggregate capital Federal rate 
payments based on the FY 2022 MS-DRG classifications and relative 
weights to estimated aggregate capital Federal rate payments based on 
the proposed FY 2023 MS-DRG classifications and relative weights prior 
to the application of the proposed 10 percent cap. For these 
calculations, estimated aggregate capital Federal rate payments were 
calculated using the proposed FY 2023 GAFs without the lowest quartile 
hospital wage index adjustment and the proposed 5 percent cap on wage 
index decreases. The proposed incremental adjustment factor for DRG 
classifications and changes in relative weights prior to the 
application of the proposed 10 percent cap is 1.0006. Next, we compared 
estimated aggregate capital Federal rate payments based on the proposed 
FY 2023 MS-DRG classifications and relative weights prior to the 
application of the 10 percent cap to estimated aggregate capital 
Federal rate payments based on the proposed FY 2023 MS-DRG 
classifications and relative weights after the application of the 
proposed 10 percent cap. For these calculations, estimated aggregate 
capital Federal rate payments were also calculated using the proposed 
FY 2023 GAFs without the lowest quartile hospital wage index adjustment 
and the proposed 5 percent cap on wage index decreases. The proposed 
incremental adjustment factor for the proposed application of the 
proposed 10 percent cap on relative weight decreases is 0.9998. 
Therefore, to achieve budget neutrality for the proposed FY 2023 MS-DRG 
reclassification and recalibration (including the proposed 10 percent 
cap), based on the proposed calculations described previously, we are 
proposing to apply an incremental budget neutrality adjustment factor 
of 1.0003 (1.0006 x 0.9998) for FY 2023 to the capital Federal rate. We 
note that all the values are calculated with unrounded numbers.
    The proposed incremental adjustment factor for the proposed FY 2023 
MS-DRG reclassification and recalibration (1.0003) and for proposed 
changes in the FY 2023 GAFs due to the proposed update to the wage 
data, wage index reclassifications and redesignations, and application 
of the rural floor policy (1.0019) is 1.0023 (1.0003 x 1.0019). This 
incremental adjustment factor is built permanently into the capital 
Federal rates. To achieve budget neutrality for the effects of the 
lowest quartile hospital wage index adjustment and the proposed 5 
percent cap on wage index decreases policy on the FY 2023 GAFs, as 
described previously, we calculated a proposed budget neutrality 
adjustment factor of 0.9971 for FY 2023. We refer to this budget 
neutrality factor for the remainder of this section as the lowest 
quartile/cap adjustment factor.
    We applied the budget neutrality adjustment factors described 
previously to the capital Federal rate. This follows the requirement 
under Sec.  412.308(c)(4)(ii) that estimated aggregate payments each 
year be no more or less than they would have been in the absence of the 
annual DRG reclassification and recalibration and changes in the GAFs.
    The methodology used to determine the recalibration and geographic 
adjustment factor (GAF/DRG) budget neutrality adjustment is similar to 
the methodology used in establishing budget neutrality adjustments 
under the IPPS for operating costs. One difference is that, under the 
operating IPPS, the budget neutrality adjustments for the effect of 
updates to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy are 
determined separately. Under the capital IPPS, there is a single budget 
neutrality adjustment factor for changes in the GAF that result from 
updates to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy. In addition, 
there is no adjustment for the effects that geographic 
reclassification, the lowest quartile hospital wage index adjustment, 
or the proposed 5 percent cap on wage index decreases policy described 
previously have on the other payment parameters, such as the payments 
for DSH or IME.
    The proposed incremental GAF/DRG adjustment factor of 1.0023 
accounts for the proposed MS-DRG reclassifications and recalibration 
(including application of the proposed 10 percent cap on relative 
weight decreases) and for proposed changes in the GAFs that result from 
proposed updates to the wage data, the effects on the GAFs of FY 2023 
geographic reclassification decisions made by the MGCRB compared to FY 
2022 decisions, and the application of the rural floor policy. The 
proposed lowest quartile/cap adjustment factor of 0.9971 accounts for 
changes in the GAFs that result from our policy to increase the wage 
index values for hospitals with a wage index value below the 25th 
percentile wage index and the proposed 5 percent cap on wage index 
decreases policy. However, these factors do not account for changes in 
payments due to changes in the DSH and IME adjustment factors.
4. Proposed Capital Federal Rate for FY 2023
    For FY 2022, we established a capital Federal rate of $472.59 (86 
FR 45553, as corrected in 86 FR 58026). We are

[[Page 28680]]

proposing to establish an update of 1.7 percent in determining the FY 
2023 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 $480.29 for FY 2023. The proposed national capital Federal rate for 
FY 2023 was calculated as follows:
     The proposed FY 2023 update factor is 1.017; that is, the 
proposed update is 1.7 percent.
     The proposed FY 2023 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 (including 
application of the proposed 10 percent cap on relative weight 
decreases) 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 1.0023.
     The proposed FY 2023 lowest quartile/cap 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 and the proposed 5 percent cap on wage index 
decreases policy is 0.9971.
     The proposed FY 2023 outlier adjustment factor is 0.9445.
    We are providing the following chart that shows how each of the 
proposed factors and adjustments for FY 2023 affects the computation of 
the proposed FY 2023 national capital Federal rate in comparison to the 
FY 2022 national capital Federal rate. The proposed FY 2023 update 
factor has the effect of increasing the capital Federal rate by 1.7 
percent compared to the FY 2022 capital Federal rate. The proposed GAF/
DRG budget neutrality adjustment factor has the effect of increasing 
the capital Federal rate by 0.23 percent. The proposed FY 2023 lowest 
quartile/cap budget neutrality adjustment factor has the effect of 
decreasing the capital Federal rate by 0.03 percent compared to the FY 
2022 capital Federal rate. The proposed FY 2023 outlier adjustment 
factor has the effect of decreasing the capital Federal rate by 0.27 
percent compared to the FY 2022 capital Federal rate. The combined 
effect of all the proposed changes would increase the national capital 
Federal rate by approximately 1.63 percent, compared to the FY 2022 
national capital Federal rate.
[GRAPHIC] [TIFF OMITTED] TP10MY22.248

B. Calculation of the Proposed Inpatient Capital-Related Prospective 
Payments for FY 2023

    For purposes of calculating payments for each discharge during FY 
2023, 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 2023 is in section II.A. of this 
Addendum. For FY 2023, a case will qualify as a cost outlier if the 
cost for the case is greater than the prospective payment rates for the 
MS-DRG plus IME and DSH payments (including the empirically justified 
Medicare DSH payment and the estimated uncompensated care payment), any 
add-on payments for new technology, and, as we are proposing beginning 
in FY 2023, the proposed estimated supplemental payment for eligible 
IHS/Tribal hospitals and Puerto Rico hospitals (as discussed in section 
IV.E. of the preamble of this proposed rule), plus the proposed fixed-
loss amount of $43,214.
    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

[[Page 28681]]

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 proposed rule, we are 
proposing to use the IPPS operating and capital market baskets that 
reflect a 2018 base year. For a complete discussion of this rebasing, 
we refer readers to section IV. of the preamble of the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45194 through 45213).
2. Forecast of the CIPI for FY 2023
    Based on IHS Global Inc.'s fourth quarter 2021 forecast, for this 
proposed rule, we are forecasting the 2018-based CIPI to increase 1.7 
percent in FY 2023. This reflects a projected 2.3 percent increase in 
vintage-weighted depreciation prices (building and fixed equipment, and 
movable equipment), and a projected 4.3 percent increase in other 
capital expense prices in FY 2023, partially offset by a projected 2.7 
percent decline in vintage-weighted interest expense prices in FY 2023. 
The weighted average of these three factors produces the forecasted 1.7 
percent increase for the 2018-based CIPI in FY 2023. 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 2023 increase in the 
2018-based CIPI for the final rule.

IV. Proposed Changes to Payment Rates for Excluded Hospitals: Rate-of-
Increase Percentages for FY 2023

    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.)
    For this FY 2023 IPPS/LTCH PPS proposed rule, based on IGI's 2021 
fourth quarter forecast, we estimated that the 2018-based IPPS 
operating market basket update for FY 2023 is 3.1 percent (that is, the 
estimate of the market basket rate-of-increase). Based on this 
estimate, the FY 2023 rate-of-increase percentage that will be applied 
to the FY 2022 target amounts in order to calculate the FY 2023 target 
amounts for children's hospitals, the 11 cancer hospitals, RNCHIs, 
short-term acute care hospitals located in the U.S. Virgin Islands, 
Guam, the Northern Mariana Islands, and American Samoa, and extended 
neoplastic disease care hospitals will be 3.1 percent, in accordance 
with the applicable regulations at 42 CFR 413.40. However, we are 
proposing that if more recent data subsequently become available (for 
example, a more recent estimate of the market basket update), we would 
use such data, if appropriate, to calculate the IPPS operating market 
basket update for FY 2023.
    IRFs and rehabilitation distinct part units, IPFs and psychiatric 
units, and LTCHs are excluded from the IPPS and paid under their 
respective PPSs. The IRF PPS, the IPF PPS, and the LTCH PPS are updated 
annually. We refer readers to section VIII. of the preamble of this 
proposed rule and section V. of the Addendum to this proposed rule for 
the changes to the Federal payment rates for LTCHs under the LTCH PPS 
for FY 2023. 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 2023

A. Proposed LTCH PPS Standard Federal Payment Rate for FY 2023

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 2023.
    Under Sec.  412.523(c)(3) of the regulations, for FY 2012 and 
subsequent years, we updated the standard Federal payment rate by the 
most recent estimate of the LTCH PPS market basket at that time, 
including additional statutory adjustments required by sections 
1886(m)(3) (citing sections 1886(b)(3)(B)(xi)(II) and 1886(m)(4) of the 
Act as set forth in the regulations at Sec.  412.523(c)(3)(viii) 
through (xvii)). (For a summary of the payment rate development prior 
to FY 2012, we refer readers to the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38310 through 38312) and references therein.)
    Section 1886(m)(3)(A) of the Act specifies that, for rate year 2012 
and each subsequent rate year, any annual update to the standard 
Federal payment rate shall be reduced by the productivity adjustment 
described in section 1886(b)(3)(B)(xi)(II) of the Act as discussed in 
section VIII.C.2 of the preamble of this 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 2023 LTCH PPS Standard Federal 
Payment Rate
    Consistent with our historical practice and Sec.  
412.523(c)(3)(xvii), for FY 2023 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 2023, we also are proposing to make certain 
regulatory adjustments, consistent with past practices. Specifically, 
in determining the proposed FY 2023 LTCH PPS

[[Page 28682]]

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 2.7 percent 
(that is, the most recent estimate of the LTCH PPS market basket 
increase of 3.1 percent less the proposed productivity adjustment of 
0.4 percentage point). Therefore, in accordance with Sec.  
412.523(c)(3)(xvii), we are proposing to apply an update factor of 
1.027 to the FY 2022 LTCH PPS standard Federal payment rate of 
$44,713.67 to determine the proposed FY 2023 LTCH PPS standard Federal 
payment rate. Also, in accordance with Sec.  412.523(c)(3)(xvii) and 
(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 2023 as 
required under the LTCH QRP. Therefore, we are proposing to establish 
an annual update to the LTCH PPS standard Federal payment rate of 0.7 
percent (that is, an update factor of 1.007) for FY 2023 for LTCHs that 
fail to submit the required quality reporting data for FY 2023 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 2023 LTCH PPS standard Federal payment rate of 1.000691, 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 (including application of the proposed 5-
percent cap on wage index decreases, discussed later in this section), 
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 $45,952.67 (calculated as $44,713.67 x 
1.027 x 1.000691) for FY 2023. For LTCHs that fail to submit quality 
reporting data for FY 2023, 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 $45,057.78 
(calculated as $44,713.67 x 1.007 x 1.000691) for FY 2023.

B. Proposed Adjustment for Area Wage Levels Under the LTCH PPS for FY 
2023

1. Background
    Under the authority of section 123 of the BBRA, as amended by 
section 307(b) of the BIPA, we established an adjustment to the LTCH 
PPS standard Federal payment rate to account for differences in LTCH 
area wage levels under Sec.  412.525(c). The labor-related share of the 
LTCH PPS standard Federal payment rate is adjusted to account for 
geographic differences in area wage levels by applying the applicable 
LTCH PPS wage index. The applicable LTCH PPS wage index is computed 
using wage data from inpatient acute care hospitals without regard to 
reclassification under section 1886(d)(8) or section 1886(d)(10) of the 
Act.
    The proposed FY 2023 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, 2022, through 
September 30, 2023, 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/wp-content/uploads/legacy_drupal_files/omb/bulletins/2017/b-17-01.pdf.
    On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which 
superseded the August 15, 2017 OMB Bulletin No. 17-01. On September 14, 
2018, OMB issued OMB Bulletin No. 18-04, which superseded the April 10, 
2018 OMB Bulletin No. 18-03. Historically OMB bulletins issued between 
decennial censuses have only contained minor modifications to CBSA 
delineations based on changes in population counts. However, OMB's 2010 
Standards for Delineating Metropolitan and Micropolitan Standards 
created a larger mid-decade redelineation that takes into account 
commuting data from the American Commuting Survey. As a

[[Page 28683]]

result, the September 14, 2018 OMB Bulletin No. 18-04 included more 
modifications to the CBSAs than are typical for OMB bulletins issued 
between decennial censuses. We adopted the updates set forth in OMB 
Bulletin No. 18-04 in the FY 2021 IPPS/LTCH PPS final rule (85 FR 59050 
through 59051). A copy of the September 14, 2018 OMB Bulletin No. 18-
04, may be obtained at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04, which was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018. (For a copy of this bulletin, we refer readers to the 
following website: https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf.) In OMB Bulletin No. 20-01, OMB announced one 
new Micropolitan Statistical Area and one new component of an existing 
Combined Statistical Area. After reviewing OMB Bulletin No. 20-01, we 
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. Therefore, we adopted the updates 
set forth in OMB Bulletin No. 20-01 in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45556 through 45557) consistent with our general policy of 
adopting OMB delineation updates; however, the LTCH PPS area wage level 
adjustment was not altered as a result of adopting the updates because 
the CBSA-based labor market area delineations were 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 FR59050 through 
59051).
    We believe the CBSA-based labor market area delineations, as 
established in OMB Bulletin 20-01, 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, for FY 2023, we are not proposing any changes to 
the CBSA-based labor market area delineations as established in OMB 
Bulletin 20-01 and adopted in the FY 2022 IPPS/LTCH final rule.
    CBSAs are made up of one or more constituent counties. Each CBSA 
and constituent county has its own unique identifying codes. The Census 
Bureau maintains a complete list of changes to counties or county 
equivalent entities on their 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 to properly crosswalk LTCHs from a county to a CBSA 
for purposes of the wage indexes used under the LTCH PPS. Based on the 
latest information included in the Census Bureau's website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.2010.html, the Census Bureau has made the following 
updates to the Federal Information Processing Series (FIPS) codes for 
counties or county equivalent entities:
     Chugach Census Area, AK (FIPS State County Code 02-063) 
and Copper River Census Area, AK (FIPS State County Code 02-066) were 
created from former Valdez-Cordova Census Area (02-261) which was 
located in CBSA 02. The CBSA code for these two new county equivalents 
remains 02.
    We believe using the latest FIPS codes allows us to maintain a more 
accurate and up-to-date payment system that reflects population shifts 
and labor market conditions. Therefore, we are proposing to implement 
these FIPS code updates listed previously, effective October 1, 2022. 
We note that while the county update changes listed previously changed 
the county names, the CBSAs to which these counties map did not change 
from the prior counties. We also note that there are currently no LTCHs 
located in these counties. However, if an LTCH were to open in one of 
these counties, there would be no impact or change to the LTCH for 
purposes of the LTCH PPS wage indexes as a result of our implementation 
of these FIPS code updates. We are publishing as a supplemental file to 
this proposed rule an updated county-to-CBSA crosswalk that reflects 
this proposal.
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 is adjusted by the applicable wage index 
for the labor market area in which the LTCH is located. The LTCH PPS 
labor-related share currently represents the sum of the labor-related 
portion of operating costs and a labor-related portion of capital costs 
using the applicable LTCH market basket. Additional background 
information on the historical development of the labor-related share 
under the LTCH PPS can be found in the RY 2007 LTCH PPS final rule (71 
FR 27810 through 27817 and 27829 through 27830) and the FY 2012 IPPS/
LTCH PPS final rule (76 FR 51766 through 51769 and 51808).
    For FY 2013, we rebased and revised the market basket used under 
the LTCH PPS by adopting a 2009-based LTCH market basket. In addition, 
for FY 2013 through FY 2016, we determined the labor-related share 
annually as the sum of the relative importance of each labor-related 
cost category of the 2009-based LTCH market basket for the respective 
fiscal year based on the best available data. (For more details, we 
refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53477 
through 53479).) For FY 2017, we rebased and revised the 2009-based 
LTCH market basket to reflect a 2013 base year. In addition, for FY 
2017 through FY 2020, we determined the labor-related share annually as 
the sum of the relative importance of each labor-related cost category 
of the 2013-based LTCH market basket for the respective fiscal year 
based on the best available data. (For more details, we refer readers 
to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57085 through 57096).) 
Then, effective for FY 2021, we rebased and revised the 2013-based LTCH 
market basket to reflect a 2017 base year and determined the labor-
related share annually as the sum of the relative importance of each 
labor-related cost category in the 2017-based LTCH market basket using 
the most recent available data. (For more details, we refer readers to 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58909 through 58926).)
    In this proposed rule, consistent with our historical practice, we 
are proposing that the LTCH PPS labor-related share for FY 2023 is the 
sum of the FY 2023 relative importance of each labor-related cost 
category in the LTCH market basket using the most recent available 
data. Specifically, we are proposing that the labor-related share for 
FY 2023 would continue to include the sum of the labor-related portion 
of operating costs from the 2017-based LTCH market basket (that is, the 
sum of the FY 2023 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

[[Page 28684]]

market basket. The relative importance reflects the different rates of 
price change for these cost categories between the base year (2017) and 
FY 2023. Based on IHS Global Inc.'s fourth quarter 2021 forecast of the 
2017-based LTCH market basket, the sum of the FY 2023 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 64.0 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 2023 relative importance 
for capital-related costs is 9.2 percent based on IHS Global Inc.'s 
fourth quarter 2021 forecast of the 2017-based LTCH market basket, we 
took 46 percent of 9.2 percent to determine the labor-related share of 
capital-related costs for FY 2023 of 4.2 percent. Therefore, we are 
proposing a total labor-related share for FY 2023 of 68.2 percent (the 
sum of 64.0 percent for the operating costs and 4.2 percent for the 
labor-related share of capital-related costs). We are also proposing 
that if more recent data become available after the publication of this 
proposed rule and before the publication of the final rule (for 
example, a more recent estimate of the relative importance of each 
labor-related cost category of the 2017-based LTCH market basket), we 
would use such data, if appropriate, to determine the FY 2023 LTCH PPS 
labor-related share.
4. Proposed Wage Index for FY 2023 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. 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 employ a 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 2023 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 2023 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 2019) because these data are the most recent 
complete data available.
    In addition, we are proposing to compute the FY 2023 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 2023 
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 2019 IPPS wage data that we are proposing to use to 
determine the proposed FY 2023 LTCH PPS 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 2023 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.
    Based on the FY 2019 IPPS wage data that we are proposing to use to 
determine the proposed FY 2023 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 wage index 
value for rural areas with no IPPS wage data for FY 2023. 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 Permanent Cap on Wage Index Decreases
a. Proposed Permanent Cap on LTCH PPS Wage Index Decreases
    In the past, we have proposed and finalized temporary transition 
policies to mitigate significant changes to payments due to changes to 
the LTCH PPS wage index, particularly when adopting changes that have 
large negative impacts on an LTCH's payments. In the FY 2021 IPPS/LTCH 
final rule (85 FR 59052), we implemented 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 the hospital's final wage index for FY 2021 would not be 
less than 95 percent of its final wage index for FY 2020. We 
implemented this policy to mitigate potential negative consequences of 
finalizing the adoption of revised CBSA delineations announced in OMB 
Bulletin 18-04 for FY 2021. In particular, we acknowledged that a 
significant portion of Medicare LTCH PPS payments are adjusted by the 
wage index and that some changes in OMB delineations destabilized 
payments to LTCHs. We stated our belief that applying the 5 percent cap 
to all wage index decreases for FY 2021 provided an adequate safeguard 
against significant payment reductions related to the adoption of the 
revised CBSAs and that it would improve stability and predictability in 
payment levels to LTCHs. We applied a budget neutrality adjustment to 
the FY 2021 standard Federal payment rate to achieve budget neutrality 
for this policy (85 FR 59053).
    Although we did not propose or implement a cap on wage index 
decreases for LTCH's in FY 2022, we acknowledged that some commenters 
requested that we extend the FY 2021 transition policy, citing the 
continuing impact of changes related to the OMB updates and the 
unprecedented nature

[[Page 28685]]

of the ongoing COVID-19 PHE. In response to those comments, we 
reiterated that our policy principles with regard to the wage index 
include generally using the most current data and information available 
and providing that data and information, as well as addressing 
significant effects on Medicare payments resulting from potential 
scenarios in notice and comment rulemaking.
    For FY 2023, we have further considered comments received during 
the FY 2022 rulemaking, including requests for a broader, permanent 
wage index policy to mitigate unpredictable changes in payments to 
LTCHs resulting from large wage index decreases. We recognize that 
changes to the wage index have the potential to create instability and 
significant negative impacts on certain providers even when we have not 
adopted specific changes to wage index policy. That is, year to year 
fluctuations in an area's wage index can occur due to external factors 
that can be difficult for an LTCH to predict and are often outside an 
LTCH's ability to directly control, such as the COVID-19 PHE. We 
recognize that predictability in Medicare payments is important to 
enable hospitals to budget and plan their operations. For LTCHs, in 
particular, we further recognize that a significant portion of Medicare 
LTCH PPS payments are adjusted by the wage index and that a large 
decrease from one year to the next can have significant implications 
for LTCH payments.
    For these reasons, under the broad authority of section 123 of the 
BBRA, as amended by section 307(b) of the BIPA, we are proposing, 
beginning with FY 2023, to apply a permanent 5 percent cap on any 
decrease to an LTCH's wage index from its wage index in the prior year. 
We believe that a 5 percent reduction is an appropriate threshold to 
mitigate large negative financial impacts on hospitals and limit the 
magnitude of the associated proposed budget neutrality adjustment 
(discussed later in this section). Typical year-to-year variations in 
the LTCH wage index has historically been within 5 percent, and we 
expect this will continue to be the case in future years. Because 
providers typically experience some level of wage index fluctuation, we 
believe applying a 5 percent cap on all wage index decreases each year, 
regardless of the reason for the decrease, would effectively mitigate 
instability and increase predictability in LTCH PPS payments due to any 
significant wage index decreases.
    We believe this proposed policy to provide a permanent cap to wage 
index decreases would provide greater predictability to LTCHs. That is, 
the policy would smooth year-to-year changes in LTCHs' wage indexes and 
provide for increased predictability in their wage index and thus their 
LTCH PPS payments. We also believe our proposed permanent policy would 
mitigate significant payment reductions due to changes in wage index 
policy, such as the adoption of the revised CBSAs in FY 2021, thereby 
eliminating the need for one-off temporary transition adjustments to 
wage index levels in the future. Because applying a 5 percent cap on 
all wage index decreases would generally represent a small overall 
impact on the adjustment for area wage levels, we believe the 5 percent 
cap would not distort the integrity of the wage index as a relative 
measure of the value of labor in a labor market area. We also note that 
this proposal is similar to our proposal to establish a permanent 5 
percent cap on annual wage index decreases for IPPS hospitals, as 
discussed in section III.N. of the preamble to this proposed rule.
    Furthermore, consistent with the requirement at Sec.  412.525(c)(2) 
that changes to area wage level adjustments are made in a budget 
neutral manner, we propose that the 5 percent cap on the decrease on an 
LTCH's wage index should not result in any change in estimated 
aggregate LTCH PPS payments by including the application of this policy 
in the determination of the area wage level budget neutrality factor 
that is applied to the standard Federal payment rate, as is discussed 
later in section V.B.6. of the addendum to the proposed rule.
    We are proposing that an LTCH's wage index cap adjustment would be 
determined based on the wage index value applicable to the LTCH on the 
last day of the prior Federal fiscal year. We are proposing that new 
LTCHs that became operational during the prior Federal fiscal year 
would be subject to the LTCH PPS wage index cap. For example, if an 
LTCH begins operations on July 1, 2022 and is paid its area wage index 
of 0.9000 for the remainder of FY 2022, its FY 2023 wage index would be 
capped at 95 percent of that value and could not be lower than 0.8550 
(0.95 x 0.9000). However, for newly opened LTCHs that become 
operational on or after the first day of the fiscal year to which this 
proposed rule would apply, we propose that these LTCHs would not be 
subject to the LTCH PPS wage index cap since they were not paid under 
the LTCH PPS in the prior year. These LTCHs would receive the 
calculated wage index for the area in which they are geographically 
located, even if other LTCHs in the same geographic area are receiving 
a wage cap. For example, a hospital that opens on December 1, 2022 
would not be eligible for a capped wage index in FY 2023, as it was not 
paid a wage index during FY 2022.
    For each LTCH we identify in our rulemaking data, we are including 
in a supplemental data file the wage index values from both fiscal 
years used in determining its capped wage index. This will include the 
LTCH's final prior year wage index value, the LTCH's uncapped current 
year wage index value, and the LTCH's capped current year wage index 
value. Due to the lag in rulemaking data, a new LTCH may not be listed 
in this supplemental file for a few years. For this reason, a newly 
opened LTCH could contact their MAC to ensure that its wage index value 
is not less than 95 percent of the value paid to it for the prior 
Federal fiscal year. This supplemental data file for public use will be 
posted on the CMS website for this proposed rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    In summary, we are proposing a permanent wage index cap policy that 
limits the reductions in an LTCH's LTCH PPS wage index value for the 
upcoming FY to 5 percent of the LTCH's wage index value for the current 
FY. We are also proposing that this wage index cap policy would be 
implemented in a budget neutral manner by including the application of 
this policy in the area wage level budget neutrality factor that is 
applied to the standard Federal payment rate. We believe that this 
proposed policy appropriately mitigates instability and significant 
negative impacts to LTCHS resulting from significant changes to the 
wage index and increases predictability of LTCH payments. We are 
proposing to reflect the proposed permanent cap on wage index decreases 
at Sec.  412.525(c)(1) by adding paragraphs (c)(1)(i) and (ii) to 
specify that CMS updates the wage index for LTCHs annually and that, 
beginning in FY 2023, if CMS determines that an LTCH's wage index value 
for a fiscal year would decrease by more than 5 percent as compared to 
the LTCH's wage index value for the prior year, we would limit the 
decrease to 5 percent for the fiscal year.
b. Proposed Permanent Cap on IPPS Comparable Wage Index Decreases
    Determining LTCH PPS payments for short-stay-outlier cases 
(reflected in Sec.  412.529) and site neutral payment rate cases 
(reflected in Sec.  412.522(c)) requires calculating an ``IPPS 
comparable amount.'' For information on this ``IPPS comparable amount'' 
calculation, we

[[Page 28686]]

refer the reader to the FY 2016 IPPS/LTCH PPS final rule (FR 80 49608 
through 49610). Determining LTCH PPS payments for LTCHs that do not 
meet the applicable discharge payment percentage (reflected in Sec.  
412.522(d)) requires calculating an ``IPPS equivalent amount.'' For 
information this ``IPPS equivalent amount'' calculation, we refer the 
reader to the FY 2020 IPPS/LTCH PPS final rule (FR 84 49608 through 
49610).
    Calculating both the ``IPPS comparable amount'' and the ``IPPS 
equivalent amount'' requires adjusting the IPPS operating and capital 
standardized amounts by the applicable IPPS wage index for 
nonreclassified IPPS hospitals. That is, the standardized amounts are 
adjusted by the IPPS wage index for nonreclassified IPPS hospitals 
located in the same geographic area as the LTCH. Consistent with our 
proposed policy to apply a 5 percent cap on decreases in the LTCH PPS 
wage index and under the broad authority of section 123 of the BBRA, as 
amended by section 307(b) of the BIPA, we are proposing, beginning with 
FY 2023 to apply a permanent 5 percent cap on decreases in an LTCH's 
applicable IPPS comparable wage index from its applicable IPPS 
comparable wage index in the prior year. As with our proposed policy to 
apply a cap on decreases in the LTCH PPS wage index each year, we 
believe a permanent cap on applicable IPPS comparable wage index 
decreases would provide greater predictability to LTCHs by mitigating 
instability and significant negative impacts to LTCHs resulting from 
significant changes to the wage index and increase predictability of 
LTCH payments. Historically, we have not budget neutralized changes to 
LTCH PPS payments that result from the annual update of the IPPS wage 
index for nonreclassified IPPS hospitals. Consistent with this 
approach, we are proposing that the cap on decreases in an LTCH's 
applicable IPPS comparable wage index not be applied in a budget 
neutral manner.
    We are proposing that an LTCH's applicable IPPS comparable wage 
index cap adjustment would be determined based on the wage index value 
assigned to the LTCH on the last day of the prior Federal fiscal year. 
We are proposing that new LTCHs that became operational during the 
prior Federal fiscal year be subject to the applicable IPPS comparable 
wage index cap. However, for newly opened LTCHs that become operational 
on or after the first day of the fiscal year to which this proposed 
rule applies, we propose that these LTCHs would not be subject to the 
applicable IPPS comparable wage index cap since they were not paid 
under the LTCH PPS in the prior year. Similar to the information we are 
making available for the proposed cap on the LTCH PPS wage index values 
(described previously), for each LTCH we identify in our rulemaking 
data, we are including in a supplemental data file the wage index 
values from both fiscal years used in determining its capped applicable 
IPPS comparable wage index. Due to the lag in rulemaking data, a new 
LTCH may not be listed in this supplemental file for a few years. For 
this reason, a newly opened LTCH could contact its MAC to ensure that 
its applicable IPPS comparable wage index value is not less than 95 
percent of the value paid to them for the prior Federal fiscal year. 
This supplemental data file for public use will be posted on the CMS 
website for this proposed rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We 
propose to reflect the proposed permanent cap on IPPS comparable wage 
index decreases at Sec.  412.529(d)(4)(ii)(B) to state that, beginning 
in FY 2023, an LTCH's applicable IPPS wage index used to adjust the 
IPPS operating standardized amount is subject to a 5 percent cap on 
decreases to an LTCH's applicable IPPS wage index value from the prior 
fiscal year. We also propose to reflect the proposed permanent cap on 
IPPS comparable wage index decreases at Sec.  412.529(d)(4)(iii)(B) to 
state that, beginning in FY 2023, an LTCH's applicable IPPS wage index 
used to adjust the IPPS capital Federal rate is subject to a 5 percent 
cap on decreases to an LTCH's applicable IPPS wage index value from the 
prior fiscal year. In addition, we are taking this opportunity to 
propose to remove the reference in Sec.  412.529(d)(4)(iii)(B) related 
to the applicable large urban location adjustment because this policy 
is no longer applicable under the IPPS effective with discharges 
occurring on or after October 1, 2007 (72 FR 47400).
6. 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 2023, in accordance with Sec.  412.523(d)(4), we are 
proposing to apply an area wage level budget neutrality factor to 
adjust the LTCH PPS standard Federal payment rate to account for the 
estimated effect of the adjustments or updates to the area wage level 
adjustment under Sec.  412.525(c)(1) on estimated aggregate LTCH PPS 
payments, consistent with the methodology we established in the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51773). As discussed in section V.B.5. 
of the Addendum to this proposed rule, we are proposing, for each year, 
beginning with FY 2023, to limit a hospital's LTCH PPS wage index value 
for the coming year by capping it at 95 percent of its prior year 
value. As also discussed previously, we are proposing to apply the 
proposed 5 percent cap on wage index decreases, consistent with Sec.  
412.525(c)(2), in a budget neutral manner.
    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 2023 
using the following methodology, which would incorporate our proposed 5 
percent cap on decreases in a hospital's wage index:
    Step 1--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the FY 2022 wage index values and the FY 
2022 labor-related share of 67.9 percent.
    Step 2--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the proposed FY 2023 wage index values 
(including application of the proposed 5 percent

[[Page 28687]]

cap on wage index decreases) and the proposed FY 2023 labor-related 
share of 68.2 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 2022 area 
wage level adjustments (calculated in Step 1) by the estimated total 
LTCH PPS standard Federal payment rate payments using the proposed FY 
2023 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 2023 LTCH PPS standard Federal 
payment rate payments.
    Step 4--Apply the proposed FY 2023 updates to the area wage level 
adjustment budget neutrality factor from Step 3 to determine the 
proposed FY 2023 LTCH PPS standard Federal payment rate after the 
application of the proposed FY 2023 annual update.
    In section I.F. of the preamble to this proposed rule, we discuss 
our proposal to use FY 2021 claims data for the FY 2023 LTCH PPS 
ratesetting. We also state our belief that it is reasonable to assume 
that there will be fewer COVID-19 hospitalizations among Medicare 
beneficiaries at LTCHs in FY 2023 than there were in FY 2021. For this 
reason, we are proposing modifications in our determination of the FY 
2023 MS-LTC-DRG relative weights and outlier fixed-loss amount for LTCH 
PPS standard Federal payment rate cases. We believe that these 
modifications will account for an anticipated decline in, but not 
elimination of, COVID-19 hospitalizations at LTCHs in FY 2023. However, 
when modeling payments for determining the area wage level adjustment 
budget neutrality factor, we are proposing to use the full set of LTCH 
PPS standard Federal payment rate cases (including all COVID-19 cases) 
identified in the FY 2021 claims data. In the absence of a set of 
MedPAR claims that reflect our expectation that there will be fewer 
(but not zero) COVID-19 cases in FY 2023 as compared to the COVID-19 
cases in the FY 2021 claims data, we believe this is the best data 
available for determining the budget neutrality factors. We note this 
is consistent with the proposed calculation of the budget neutrality 
factors for proposed changes to the MS-LTC-DRG classifications and 
relative weights (including the proposed 10 percent cap) discussed in 
section VIII.B.4.b. (Step 11) of the preamble of this proposed rule. We 
also note this is consistent with the approach being proposed under the 
IPPS as discussed in section II.A.4. of the Addendum of this proposed 
rule. We are also soliciting feedback from commenters on alternative 
ways to use the FY 2021 claims data for purposes of calculating the FY 
2023 budget neutrality factors.
    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 
2023 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 2023 
LTCH PPS standard Federal payment rate area wage level adjustment 
budget neutrality factor of 1.000691. Accordingly, in section V.A. of 
the Addendum to this proposed rule, we applied the proposed area wage 
level adjustment budget neutrality factor of 1.000691 to determine the 
proposed FY 2023 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) and we last updated the COLA factors for Alaska and 
Hawaii published by OPM for 2009 in FY 2022 (86 FR 45559 through 
45560).
    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. Therefore, in this proposed rule, for FY 2023, 
under the broad authority conferred upon the Secretary by section 123 
of the BBRA, as amended by section 307(b) of the BIPA, to determine 
appropriate payment adjustments under the LTCH PPS, we are proposing to 
continue to use the COLA factors based on the 2009 OPM COLA factors 
updated through 2020 by the comparison of the growth in the CPIs for 
Anchorage, Alaska, and Honolulu, Hawaii, relative to the growth in the 
CPI for the average U.S. city as established in the FY 2022 IPPS/LTCH 
PPS final rule. (For additional details on our current methodology for 
updating the COLA factors for Alaska and Hawaii and for a discussion on 
the FY 2022 COLA factors, we refer readers to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45559 through 45560).)

[[Page 28688]]

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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.
    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, previously 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.

[[Page 28689]]

b. Proposed LTCH Total CCR Ceiling
    Consistent with our historical practice, we are proposing to use 
the best available data to determine the LTCH total CCR ceiling for FY 
2023 in this proposed rule. Specifically, in this proposed rule, we are 
proposing to use our established methodology for determining the LTCH 
total CCR ceiling based on IPPS total CCR data from the December 2021 
update of the Provider Specific File (PSF), which is the most recent 
data available. Accordingly, we are proposing an LTCH total CCR ceiling 
of 1.321 under the LTCH PPS for FY 2023 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 2023 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.)
    Consistent with our historical practice of using the best available 
data, in this proposed rule, we are proposing to use our established 
methodology for determining the LTCH statewide average CCRs, based on 
the most recent complete IPPS ``total CCR'' data from the December 2021 
update of the PSF. We are proposing LTCH PPS statewide average total 
CCRs for urban and rural hospitals that would be effective for 
discharges occurring on or after October 1, 2022, through September 30, 
2023, 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 2023 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 December 2021. 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 1.205. Because this is much higher than the statewide urban 
average (0.480) and furthermore implies costs greater than 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 2023
    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

[[Page 28690]]

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 an LTCH PPS standard Federal payment 
rate case if the statutory changes had been in effect at the time of 
the discharge) using claims data from the MedPAR files. In accordance 
with Sec.  412.525(a)(2)(ii), the applicable fixed-loss amount for LTCH 
PPS standard Federal payment rate cases results in estimated total 
outlier payments being projected to be equal to 7.975 percent of 
projected total LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45562-45566), we 
finalized a number of technical changes to the methodology for 
determining the charge inflation factor and the CCR used when 
calculating the fixed-loss amount, 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. First, we 
finalized a technical change to the methodology for determining the 
charge inflation factor applied to the charges on the MedPAR claims 
when calculating the fixed-loss amount for each FY. Second, we 
finalized a technical change to the methodology for determining the 
CCRs used when calculating the fixed-loss amount for each FY. These 
methodologies are described in greater detail later in this section.
(1) Proposed Charge Inflation Factor for Use in Determining the 
Proposed Fixed-Loss Amount for LTCH PPS Standard Federal Payment Rate 
Cases for FY 2023
    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.
    For greater accuracy in calculating the fixed-loss amount, in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45562-45566), we finalized 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), our methodology determines 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. In this section we describe our charge 
inflation factor methodology using the most recently available data. 
However, as discussed in further detail later in this section, we are 
proposing to not use the charge inflation factor derived from the most 
recently available data. Rather, we are proposing to use the charge 
inflation factor used in the FY 2022 IPPS/LTCH PPS final rule that was 
based on the growth in charges that occurred between FY 2018 and FY 
2019.

Step 1--Identify LTCH PPS Standard Federal Payment Rate Cases

    The first step in our 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 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 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.
    Following the methodology described previously, we computed a 
charge inflation factor based on the most recently available data. 
Specifically, we used the December 2021 update of the FY 2021 MedPAR 
file and the December 2020 update of the FY 2020 MedPAR as the basis of 
the LTCH PPS standard Federal payment rate cases for the two most 
recently available Federal fiscal year time periods, as described 
previously in our methodology. Therefore, we trimmed the December 2021 
update of the FY 2021 MedPAR file and the December 2020 update of the 
FY 2020 MedPAR file as described in steps 1 and 2 of our methodology. 
To compute the 1-year average annual rate-of-change in charges per 
case, we compared the average covered charge per case of $239,245 
($14,013,531,722/58,574 cases) from FY 2020 to the average covered 
charge per case of $266,358 ($13,426,298,925/50,407 cases) from FY 
2021. This rate-of-change was 11.3327 percent, which results in a 1-
year charge inflation factor of 1.113327, and a 2-year charge inflation 
factor of 1.239497 (calculated by squaring the 1-year factor).
    We recognize that the LTCH charge inflation factor calculated 
previously is abnormally high compared to recent historical levels 
prior to the COVID-19 PHE. As discussed in section I.F. of the preamble 
to this proposed rule, we believe this abnormally high charge inflation 
factor is partially due to the high number of COVID-19 cases that were 
treated in LTCHs in FY 2021. We also believe there will be fewer COVID-
19 cases in FY 2023 than in FY 2021 and therefore do not believe it is 
reasonable to assume charges will continue to increase at this 
abnormally high rate. Consequently, when determining the proposed 
fixed-loss amount for LTCH PPS standard Federal payment rate cases for 
FY 2023, we are not proposing to use this charge inflation factor, 
which was based on the growth in charges that occurred between FY 2020 
and FY 2021. Rather, as discussed in section I.F. of the preamble to 
this proposed rule, we are proposing to use the charge inflation factor

[[Page 28691]]

determined in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45565), which 
was based on the growth in charges that occurred between FY 2018 and FY 
2019 (the last 1-year period prior to the COVID-19 PHE).
    The rate of LTCH charge growth determined in the FY 2022 IPPS/LTCH 
PPS final rule, based on the growth in charges that occurred between FY 
2018 and FY 2019, was 6.0723 percent. This results in a 1-year charge 
inflation factor of 1.060723, and a 2-year charge inflation factor of 
1.125133 (calculated by squaring the 1-year factor). Therefore, we 
propose to inflate the billed charges obtained from the FY 2021 MedPAR 
file by this 2-year charge inflation factor of 1.125133 when 
determining the proposed fixed-loss amount for LTCH PPS standard 
Federal payment rate cases for FY 2023.
(2) Proposed CCRs for Use in Determining the Proposed Fixed-Loss Amount 
for LTCH PPS Standard Federal Payment Rate Cases for FY 2023
    For greater accuracy in calculating the fixed-loss amount, in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45562-45566), we finalized a 
technical change to our 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), our methodology adjusts 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 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 our CCR adjustment factor methodology using the 
most recently available data. However, as discussed in further detail 
later in this section, we are not proposing to use the CCR adjustment 
factor derived from the most recently available data. Rather, we are 
proposing to use the CCR adjustment factor that was derived in the FY 
2022 IPPS/LTCH PPS final rule, which is based on the change in CCRs 
that occurred between the March 2019 PSF and the March 2020 PSF.

Step 1--Assign Providers Their Historical CCRs

    The first step in our 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 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 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 a CCR Adjustment Factor

    The final step in our methodology is to calculate, across all 
remaining providers after application of Step 3, an 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.
    Following the methodology described previously, we computed a CCR 
adjustment factor based on the most recently available data. 
Specifically, we used the December 2021 PSF as the most recently 
available PSF and the December 2020 PSF as the PSF that was made 
available one year prior to the most recently available PSF, as 
described in our methodology. In addition, we used claims from the 
December 2021 update of the FY 2021 MedPAR file in our calculation of 
average case-weighted CCRs described in Step 4 of our methodology. 
Specifically, following the methodology described previously and, for 
providers with LTCH PPS standard Federal payment rate cases in the 
December 2021 update of the FY 2021 MedPAR file, we identified their 
CCRs from both the December 2020 PSF and December 2021 PSF. After 
performing the trims outlined in our methodology, we used the LTCH PPS 
standard Federal payment rate case counts from the FY 2021 MedPAR file 
(classified using proposed Version 40 of the GROUPER) to calculate 
case-weighted average CCRs. Based on this data, we calculated a 
December 2020 national average case-weighted CCR of 0.244856 and a 
December 2021 national average case-weighted CCR of 0.234409. We then 
calculated a national CCR adjustment factor by dividing the December 
2021 national average case-weighted CCR by the December 2020 national 
average case-weighted CCR. This results in a 1-year national CCR 
adjustment factor of 0.957334.
    Unlike the charge inflation factor calculated using the most 
recently available data, the CCR adjustment factor calculated 
previously is not significantly different from historical levels. 
However, consistent with our proposal to derive our proposed charge 
inflation factor for FY 2023 based on data from the last 1-year period 
prior to the COVID-19 PHE, we are proposing to use the CCR adjustment 
factor determined in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45565), which was based on the change in CCRs that occurred between the 
March 2019 PSF and the March 2020 PSF (the last 1-year period prior to 
the COVID-19 PHE).
    We note that the CCR adjustment factor of 0.961554 determined in 
the FY 2022 IPPS/LTCH PPS final rule is close to the CCR adjustment 
factor we calculated previously using the most recently available data. 
We note this

[[Page 28692]]

proposal is consistent with the approach being proposed under the IPPS 
as discussed in section II.A.4.h.(2). of the Addendum of this proposed 
rule.
    When calculating the proposed fixed-loss amount for FY 2023, we 
assigned the statewide average CCR for the upcoming fiscal year to all 
providers who were assigned the statewide average in the December 2021 
PSF or whose CCR was missing in the December 2021 PSF. For all other 
providers, we multiplied their CCR from the December 2021 PSF by the 
proposed 1-year national CCR adjustment factor of 0.961554.
(3) Proposed Fixed-Loss Amount for LTCH PPS Standard Federal Payment 
Rate Cases for FY 2023
    In section in of the preamble to this proposed rule, we discuss our 
proposal to use FY 2021 claims data for the FY 2023 LTCH PPS 
ratesetting. We also state our belief that it is reasonable to assume 
that there will be fewer COVID-19 hospitalizations among Medicare 
beneficiaries at LTCHs in FY 2023 than there were in FY 2021. For this 
reason, as discussed previously, we are proposing modifications to the 
charge inflation and CCR adjustment factors used in determining the 
outlier fixed-loss amount for LTCH PPS standard Federal payment rate 
cases. However, when modeling payments for the outlier fixed-loss 
amount for LTCH PPS standard Federal payment rate cases, we are 
proposing to use the full set of LTCH PPS standard Federal payment rate 
cases (including all COVID-19 cases) identified in the FY 2021 claims 
data. In the absence of a set of MedPAR claims that reflect our 
expectation that there will be fewer (but not zero) COVID-19 cases in 
FY 2023 as compared to the COVID-19 cases in the FY 2021 claims data, 
we believe this is the best data available for determining the outlier 
fixed-loss amount for LTCH PPS standard Federal payment rate cases. We 
note that this is consistent with the approach being proposed for 
determining the budget neutrality adjustments for the annual update to 
the MS-LTC-DRG classifications and relative weights (as discussed in 
section B.4.b. of the preamble to this proposed rule) and changes to 
the area wage level adjustment (as discussed in section V.B.6. of the 
addendum to this proposed rule.) We also note this is consistent with 
the approach being proposed under the IPPS as discussed in section 
II.A.4.h.(2). of the Addendum of this proposed rule. We are also 
soliciting feedback from commenters on alternative ways to use the FY 
2021 claims data for purposes of calculating the FY 2023 outlier fixed-
loss amount for LTCH PPS standard Federal payment rate cases.
    In this proposed rule, for FY 2023, 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). Therefore, based on LTCH claims data 
from the December 2021 update of the FY 2021 MedPAR file adjusted for 
charge inflation and adjusted CCRs from the December 2021 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 2023 of $44,182 
that would result in estimated outlier payments projected to be equal 
to 7.975 percent of estimated FY 2023 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 $44,182).
    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 2023 in the final rule. In section I.O. of Appendix A 
of this proposed rule, we are also considering as an alternative to 
this proposal, to use the FY 2021 data without any of our proposed 
methodological changes that account for an anticipated decline in 
COVID-19 cases in FY 2023. We note, under this alternative, the fixed-
loss amount for LTCH PPS standard Federal payment rate cases would be 
$61,842.
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 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 2022, 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 2022, 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

[[Page 28693]]

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 2022 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 2022. In particular, in FY 
2022, we established the fixed-loss amount for site neutral payment 
rate cases as the FY 2021 IPPS fixed-loss amount of $30,988 (86 FR 
45567).
    As discussed in section I.F. of the preamble of this proposed rule, 
we are proposing to use FY 2021 data in the FY 2023 LTCH PPS 
ratesetting. Section 3711(b)(2) of the CARES Act, which provided a 
waiver of the application of the site neutral payment rate for LTCH 
cases admitted during the COVID-19 PHE period, was in effect for the 
entirety of FY 2021. Therefore, all LTCH PPS cases in FY 2021 were paid 
the LTCH PPS standard Federal rate regardless of whether the discharge 
met the statutory patient criteria. Because not all FY 2021 claims in 
the data used for this proposed rule were subject to the site neutral 
payment rate, we continue to rely on the same considerations and 
actuarial projections used in FYs 2016 through 2022 when developing a 
fixed-loss amount for site neutral payment rate cases for FY 2023. Our 
actuaries continue to project that the costs and resource use for FY 
2023 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 2021 LTCH claims data used in the development of this 
proposed rule, if the provisions of the CARES Act had not been in 
effect, approximately 72 percent of LTCH cases would have been paid the 
LTCH PPS standard Federal payment rate and approximately 28 percent of 
LTCH cases would have been paid the site neutral payment rate for 
discharges occurring in FY 2021.)
    For these reasons, we continue to believe that the most appropriate 
fixed-loss amount for site neutral payment rate cases for FY 2023 is 
the IPPS fixed-loss amount for FY 2023. 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 
$43,214, which is the same proposed FY 2023 IPPS fixed-loss amount 
discussed in section II.A.4.j.(1). of the Addendum to this proposed 
rule. Accordingly, for FY 2023, 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 $43,214).
    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 2023 would not result in any increase in 
estimated aggregate FY 2023 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 
2023. Consistent with our historical practice, 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 2023 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 2023 would 
not result in any increase in estimated aggregate FY 2023 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 2023. To achieve this, for FY 2023, 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 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

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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 2023, 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 
65.71 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 2023. 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 49.28 percent (the 
product of 75 percent and 65.71 percent) and the resulting amount is 
used to calculate the uncompensated care payments to eligible 
hospitals. As a result, for FY 2023, 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 
74.28 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 + 49.28 percent = 74.28 
percent).
    Therefore, for FY 2023, 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 74.28 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 2023

    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 proposed FY 2023 values are shown in Tables 12A through 
12B listed in section VI. of the Addendum to this proposed rule and are 
available via the internet on the CMS website). The LTCH PPS standard 
Federal payment rate is also adjusted to account for the higher costs 
of LTCHs located in Alaska and Hawaii by the applicable COLA factors 
(the proposed FY 2023 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 2023 of $45,952.67, 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 2023 
in the following example:
Example:

    During FY 2023, 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 2023 LTCH PPS wage index value of 
1.0505 (as shown in Table 12A listed in section VI. of the Addendum to 
this proposed rule). The Medicare patient case is classified into 
proposed MS-LTC-DRG 189 (Pulmonary Edema & Respiratory Failure), which 
has a proposed relative weight for FY 2023 of 0.9562 (as shown in Table 
11 listed in section VI. of the Addendum to this proposed rule). The 
LTCH submitted quality reporting data for FY 2023 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 2023, we computed the 
wage-adjusted Federal prospective payment amount by multiplying the 
unadjusted proposed FY 2023 LTCH PPS standard Federal payment rate 
($45,952.67) by the proposed labor-related share (0.682 percent) and 
the proposed wage index value (1.0505). This wage-adjusted amount was 
then added to the proposed nonlabor-related portion of the unadjusted 
proposed LTCH PPS standard Federal payment rate (0.318 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 (0.9562) to 
calculate the total adjusted proposed LTCH PPS standard Federal 
prospective payment for FY 2023 ($45,453.28). 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 
2022, for the FY 2023 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 2022 IPPS/LTCH PPS final rule (86 FR 45569 through 
45571).
    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 2023 HAC Reduction Program 
will be made publicly available once it has undergone the review and 
corrections process.
    We note, Tables 7A and 7B historically contained the Medicare 
prospective payment system selected percentile lengths of stay for the 
MS-DRGs for the prior year and upcoming fiscal year. As discussed in 
section II.E of this proposed rule, we are proposing to determine the 
MS DRG relative weights for FY 2023 by averaging the relative weights 
as calculated with and without COVID-19 cases in the FY 2021 data. 
Because we are using MS-DRG weights based on an average of the relative 
weights, the percentile lengths of stay, which are based on separate 
sets of MS-DRG relative weights prior to averaging are not applicable 
to the proposed averaged MS-DRG relative weights for FY 2023. The 
separate percentile lengths of stay statistics are only applicable to 
the relative weights as calculated with and without COVID-19 cases. 
Additionally, we note that unlike the other files listed as tables in 
this section that typically contain information/variables relating to a 
hospital's IPPS claim for payment, Tables 7A and 7B are informational 
files containing percentile lengths of stay that are not used for claim 
payment. Therefore, beginning with this FY 2023 IPPS/LTCH PPS proposed 
rule, we are proposing to instead provide the percentile length of stay 
information previously included in Tables 7A and 7B in the supplemental 
AOR/BOR data file, as described in section XII.A. of this proposed 
rule, which contains additional data relevant to the MS-DRG relative 
weights. For FY 2023, because we are proposing to average the relative 
weights, we are providing an AOR/BOR file for the relative weights 
calculated with COVID-19 cases in the December 2021 update of the FY 
2021 MedPAR file and an AOR/BOR file for the relative weights 
calculated without COVID-19 cases in the December 2021 update of the FY 
2021 MedPAR file. Therefore, instead of including the percentile 
lengths of stay that are typically in Tables 7A and 7B (that is, for 
this proposed rule, the selected percentile lengths of stay based on 
the MedPAR data and MS-DRGs for the prior year and upcoming fiscal year 
(for FY 2023, this would be the proposed version 40 GROUPER and version 
39 GROUPER)) we are including this statistical information in the AOR/
BOR File for the relative weights as calculated with and without COVID-
19 cases. The AOR/BOR files can be found on the FY 2023 IPPS proposed 
rule home page on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    As was the case for the FY 2022 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 hospital1specific data. After hospitals have 
been given an opportunity to review and correct their calculations for 
FY 2023, we will post Table 15 (which will be available via the 
internet on the CMS website) to display the final FY 2023 readmissions 
payment adjustment factors that will be applicable to discharges 
occurring on or after October 1, 2022. We expect Table 15 will be 
posted on the CMS website in the fall of 2022.
    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 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 2023 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 we are making available based on the use of the 
FY 2021 data without the proposed modifications to our usual 
methodologies for the calculation of the FY 2023 MS-DRG and MS-LTC-DRG 
relative weights or our usual methodologies for the determination of 
the FY 2023 outlier fixed-loss amount for IPPS cases and LTCH PPS 
standard Federal payment rate cases for this FY 2023 ratesetting, which 
we are also making available on the CMS website.

Table 2.--Proposed Case-Mix Index and Wage Index Table by CCN--FY 2023 
Proposed Rule
Table 3.--Proposed Wage Index Table by CBSA--FY 2023 Proposed Rule

[[Page 28696]]

Table 4A.--Proposed List of Counties Eligible for the Out-Migration 
Adjustment under Section 1886(d)(13) of the Act--FY 2023 Proposed Rule
Table 4B.--Counties Redesignated under Section 1886(d)(8)(B) of the Act 
(LUGAR Counties)--FY 2023 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 2023
Table 6A.--New Diagnosis Codes--FY 2023
Table 6B.--New Procedure Codes--FY 2023
Table 6C.--Invalid Diagnosis Codes--FY 2023
Table 6E.--Revised Diagnosis Code Titles--FY 2023
Table 6G.1.--Proposed Secondary Diagnosis Order Additions to the CC 
Exclusions List--FY 2023
Table 6G.2.--Proposed Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2023
Table 6H.1.--Proposed Secondary Diagnosis Order Deletions to the CC 
Exclusions List--FY 2023
Table 6H.2.--Proposed Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2023
Table 6I.1.--Proposed Additions to the MCC List--FY 2023
Table 6I.2.--Proposed Deletions to the MCC List--FY 2023
Table 6J.1.--Proposed Additions to the CC List--FY 2023
Table 6J.2.--Proposed Deletions to the CC List--FY 2023
Table 6P.--ICD-10-CM and ICD-10-PCS Codes for Proposed MS-DRG and 
Medicare Code Editor (MCE) Changes--FY 2023 (Table 6P contains multiple 
tables, 6P.1a. through 6P.6c that include the ICD-10-CM and ICD-10-PCS 
code lists relating to specific proposed MS-DRG and MCE changes. These 
tables are referred to throughout section II.D. of the preamble of this 
proposed rule.)
Table 8A.--Proposed FY 2023 Statewide Average Operating Cost-to-Charge 
Ratios (CCRs) for Acute Care Hospitals (Urban and Rural)
Table 8B.--Proposed FY 2023 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 2023 If Our Proposals to 
Revise the Scoring and Payment Methodology For That Program Year Are 
Not Finalized
Table 18.--Proposed FY 2023 Medicare DSH Uncompensated Care Payment 
Factor 3

    The following LTCH PPS tables for this FY 2023 proposed rule are 
available through the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the list item for Regulation 
Number CMS-1771-P:

Table 8C.--Proposed FY 2023 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, 2022, through September 30, 2023
Table 12A.--Proposed LTCH PPS Wage Index for Urban Areas for Discharges 
Occurring from October 1, 2022, through September 30, 2023
Table 12B.--Proposed LTCH PPS Wage Index for Rural Areas for Discharges 
Occurring from October 1, 2022, through September 30, 2023
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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 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.

1. Acute Care Hospital Inpatient Prospective Payment System (IPPS)

a. Proposed Update to the IPPS Payment Rates

    In accordance with section 1886(b)(3)(B) of the Act and as 
described in section V.A. of the preamble to this proposed rule, we 
are proposing to update the national standardized amount for 
inpatient hospital operating costs by the proposed applicable 
percentage increase of 2.7 percent (that is, a 3.1 percent market 
basket update with a proposed reduction of 0.4 percentage point for 
the productivity adjustment) and by a proposed 0.5 percentage point 
adjustment required under section 414 of the MACRA. We are also 
proposing to apply the proposed applicable percentage increase 
(including the market basket update and the proposed productivity 
adjustment) to the hospital-specific rates.
    Subsection (d) 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 1.925 percent. 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 0.375 percent.
    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 -0.4 percent, which 
reflects a one-quarter percent reduction of the market basket update 
for failure to submit quality data and a three-quarter percent 
reduction of the market basket update for being identified as not a 
meaningful EHR user.

b. Proposed Use of FY 2021 Data in the FY 2023 IPPS and LTCH PPS 
Ratesetting

    As discussed in section I.A of this proposed rule, we believe 
that it is reasonable to assume that some Medicare beneficiaries 
will continue to be hospitalized with COVID-19 at IPPS hospitals and 
LTCHs in FY 2023. Accordingly, we believe it is appropriate to use 
FY 2021 data, specifically

[[Page 28698]]

the FY 2021 MedPAR claims file and the FY 2020 HCRIS dataset (which 
contains data from many cost reports ending in FY 2021 based on each 
hospital's cost reporting period) as the most recent available data 
during the period of the COVID-19 PHE, for purposes of the FY 2023 
IPPS and LTCH PPS ratesetting. However, we also believe it is 
reasonable to assume based on the information available at this time 
that there will be fewer COVID 19 hospitalizations in FY 2023 than 
in FY 2021 given the more recent trends in the CDC hospitalization 
data since the Omicron variant peak in January, 2022. Accordingly, 
because we anticipate Medicare inpatient hospitalizations for COVID-
19 will continue in FY 2023 but at a lower level, we are proposing 
to use FY 2021 data for purposes of the FY 2023 IPPS and LTCH PPS 
ratesetting but with modifications to our usual ratesetting 
methodologies to account for the anticipated decline in COVID-19 
hospitalizations of Medicare beneficiaries at IPPS hospitals and 
LTCHs as compared to FY 2021.
    First, we are proposing to modify the calculation of the FY 2023 
MS-DRG and MS LTC DRG relative weights. The proposal for modifying 
the methodology for determining the FY 2023 IPPS MS-DRG relative 
weights is discussed in section II.E. of the preamble of this 
proposed rule. The proposal for modifying the methodology for 
determining the FY 2023 LTCH PPS MS-LTC-DRG relative weights is 
discussed in greater detail in section VIII.B. of the preamble of 
this proposed rule.
    Second, we also are proposing to modify our methodologies for 
determining the FY 2023 outlier fixed-loss amount for IPPS cases and 
LTCH PPS standard Federal payment rate cases. The proposal for 
modifying the methodology for determining the FY 2023 outlier fixed-
loss amounts for IPPS cases is discussed in section II.A.4. of the 
addendum to this proposed rule. The proposal for modifying the 
methodology for determining the FY 2023 outlier fixed loss amounts 
for LTCH PPS standard Federal payment rate cases is discussed in 
section V.D.3. of the addendum to this proposed rule.
    In section I.O. of Appendix A of this proposed rule, we are also 
considering as an alternative to this proposal, to use the FY 2021 
data without any modifications to our usual methodologies for the 
calculation of the FY 2023 MS-DRG and MS-LTC-DRG relative weights or 
the usual methodologies used to determine the FY 2023 outlier fixed-
loss amount for IPPS cases and LTCH PPS standard Federal payment 
rate cases, which we may consider finalizing based on consideration 
of comments received.

c. Proposed Cap on Reductions in Medicare Severity Diagnosis-Related 
Group (MS-DRG) Relative Weights

    As described in section II.E.2. of the preamble of this proposed 
rule, we have further considered requests made by commenters that we 
address year-to-year fluctuations in relative weights, particularly 
for low volume MS-DRGs, and to mitigate the financial impacts of 
significant fluctuations. Consistent with our statutory authority 
under section 1886(d)(4)(B) and (C) of the Act to assign and update 
appropriate weighting factors, beginning in FY 2023, we are 
proposing a permanent 10-percent cap on the reduction in a MS-DRG's 
relative weight in a given fiscal year. This proposal is consistent 
with our general authority to assign and update appropriate 
weighting factors as part of our annual reclassifications of the MS-
DRGs and recalibration of the relative weights under sections 
1886(d)(4)(B) and (C)(i) of the Act, as well as the requirements of 
section 1886(d)(4)(C)(iii) of the Act, which specifies that the 
annual DRG reclassification and recalibration of the relative 
weights be made in a manner that ensures that aggregate payments to 
hospitals are not affected. In addition, we have authority to 
implement this proposed cap and the associated budget neutrality 
adjustment under our special exceptions and adjustments authority at 
section 1886(d)(5)(I)(i) of the Act, which similarly gives the 
Secretary broad authority to provide by regulation for such other 
exceptions and adjustments to the payment amounts under section 
1886(d) of the Act as the Secretary deems appropriate.

d. Add-On Payments for New Services and Technologies

    Consistent with sections 1886(d)(5)(K) and (L) of the Act, CMS 
reviews applications for new technology add-on payments based on the 
eligibility criteria at 42 CFR 412.87. As set forth in 42 CFR 
12.87(e)(1), CMS considers whether a technology meets the criteria 
for the new technology add-on payment and announces the results as 
part of its annual updates and changes to the IPPS.

(1) Proposal To Use National Drug Codes (NDCs) for Identification of 
Certain Therapeutic Agents Approved for New Technology Add-On Payment

    CMS has received comments from stakeholders opposing the 
continued creation of new ICD-10-PCS (for example, Section X) 
procedure codes for the purpose of administering the new technology 
add-on payment for drugs and biologics. Specifically, public 
comments from the ICD-10 Coordination and Maintenance Committee 
Meetings have stated that the ICD-10-PCS classification system was 
not intended to represent unique drugs/therapeutic agents and is not 
an appropriate code set for this purpose.
    In addition, the current process of requesting, proposing, 
finalizing and assigning new ICD-10-PCS procedure codes to identify 
and describe the administration of drugs involves several steps 
(described further in section II.F.8. of this proposed rule), and 
frequently results in a number of procedure codes that are created 
unnecessarily when the drug/therapeutic agents do not receive 
approval for the new technology add-on payments, as the 
administration of drugs/therapeutic agents is not typically coded in 
the inpatient hospital setting.
    In section II.F.8. of this proposed rule, we are proposing to 
use National Drug Codes (NDCs) to identify cases involving use of 
therapeutic agents approved for new technology add-on payments. We 
also note that we have previously established the use of NDCs as an 
alternative code set for the purposes of administering the new 
technology add-on payment in circumstances where an ICD-10-PCS code 
was not available to uniquely identify the use of the technology.
    Therefore, we are proposing for FY 2024 to instead use NDCs to 
identify cases involving the use of therapeutic agents approved for 
the new technology add-on payment. We believe that this proposal 
would address concerns raised by commenters regarding the use of the 
ICD-10-PCS classification system to identify these agents and reduce 
the need for applicants to seek a unique ICD-10-PCS code through the 
ICD-10-PCS Section X code request process in advance of a 
determination on their new technology add-on payment applications. 
We also expect this proposed change would address concerns regarding 
the creation of duplicative codes within the ICD-10-PCS procedure 
coding system and reduce efforts associated with determining the 
disposition of procedure codes describing therapeutic agents that 
have reached the end of their three-year new technology add-on 
payment timeframe.

(2) Proposal To Publicly Post Applications for New Technology Add-On 
Payments

    As discussed in II.F.9. of this proposed rule, beginning with 
the FY 2024 application cycle for new technology add-on payments, we 
are proposing to post online the full contents of the applications, 
including updated application information submitted subsequent to 
the initial application submission, with the exception of certain 
cost and volume information and application attachments. CMS has 
received requests from the public to access and review the new 
technology add-on payment applications to further facilitate comment 
on whether a technology meets the new technology add-on payment 
criteria. Making this information publicly available may also foster 
greater input from experts in the stakeholder community based on 
their review of the original application materials.
    Additionally, we believe that posting the applications online 
would reduce the risk that we may inadvertently omit or misrepresent 
relevant information submitted by applicants, or are perceived as 
misrepresenting such information, in our summaries in the rules. It 
also would streamline our evaluation process, including the 
identification of critical questions in the proposed rule, 
particularly as the number and complexity of the applications have 
been increasing over time. That is, by making the applications 
available to the public online, we would afford more time for CMS to 
process and analyze the supporting data and evidence rather than 
reiterate parts of the application in the rule.

e. Proposed Permanent Cap on Wage Index Decreases

    Consistent with section 1886(d)(3)(E) of the Act, we adjust the 
IPPS 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 and update the 
wage index annually based on a survey of wages

[[Page 28699]]

and wage-related costs of short-term, acute care hospitals. As 
described in section III.N. of the preamble of this proposed rule, 
we have further considered the comments we received during the FY 
2022 rulemaking recommending a permanent 5 percent cap policy to 
prevent large year-to-year variations in wage index values as a 
means to reduce overall volatility for hospitals. Under the 
authority at sections 1886(d)(3)(E) and 1886(d)(5)(I)(i) of the Act, 
we are proposing a permanent cap on wage index decreases, limiting 
overall reductions in a hospital's wage index value for the upcoming 
FY to be no greater than 5 percent of its wage index value for the 
current FY. That is, under this proposed policy, a hospital's wage 
index value would not be less than 95 percent of its prior year 
value. We are also proposing to apply this proposed permanent cap 
policy in a budget neutral manner through a national adjustment to 
the standardized amount under our authority in sections 
1886(d)(3)(E) and 1886(d)(5)(I)(i) of the Act.

f. Continuation of the Low Wage Index Hospital Policy

    To help mitigate wage index disparities between high wage and 
low wage hospitals, in the FY 2020 IPPS/LTCH PPS rule (84 FR 42326 
through 42332), we adopted a policy to increase the wage index 
values for certain hospitals with low wage index values (the low 
wage index hospital policy). This policy was adopted in a budget 
neutral manner through an adjustment applied to the standardized 
amounts for all hospitals. We also indicated that this policy 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, as discussed in section III.G.4. of the preamble of this 
proposed rule, for FY 2023, 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.

g. Payment Adjustment for Medicare Disproportionate Share Hospitals 
(DSHs)

    In this proposed rule, as required by section 1886(r)(2) of the 
Act, we are proposing to update our estimates of the three factors 
used to determine uncompensated care payments for FY 2023. We are 
proposing to adopt a multiyear averaging methodology to determine 
Factor 3 of the uncompensated care methodology, which will help to 
mitigate against large fluctuations in uncompensated care payments 
from year to year. Specifically, we are proposing to use a two-year 
average of audited data on uncompensated care costs from Worksheet 
S-10 from the FY 2018 and FY 2019 cost reports to calculate Factor 3 
for the FY 2023 for all eligible hospitals, including Indian Health 
Service (IHS) and Tribal hospitals and hospitals located in Puerto 
Rico. In addition, for FY 2024 and subsequent fiscal years, we are 
proposing to use a three-year average of the data on uncompensated 
care costs from Worksheet S-10 for the three most recent fiscal 
years for which audited data are available.
    We recognize that our proposal to discontinue the use of the 
low-income insured days proxy to calculate Factor 3 in the 
uncompensated care payment methodology for IHS and Tribal hospitals 
and Puerto Rico hospitals could result in a significant financial 
disruption for these hospitals. Accordingly, we are proposing to use 
our authority under section 1886(d)(5)(I) of the Act to establish a 
new supplemental payment for these hospitals for FY 2023 and 
subsequent fiscal years.
    Additionally, as discussed in section IV.F. of the preamble of 
this proposed rule, we are proposing to revise our regulation 
governing the calculation of the Medicaid fraction of the DSH 
calculation. Under this proposal, we would revise our regulation to 
explicitly reflect our interpretation of the language ``regarded 
as'' ``eligible for medical assistance under a State plan approved 
under title XIX'' in section 1886(d)(5)(F)(vi) of the Act to mean 
patients who receive health insurance through a section 1115 
demonstration itself or purchase such insurance with the use of 
premium assistance provided by a section 1115 demonstration. 
Moreover, of the groups we ``regard'' as Medicaid eligible, we 
propose that only the days of those individuals that obtain 
insurance coverage that provides essential health benefits (EHB) 
(defined as meeting the EHB requirements set forth in 42 CFR part 
440, subpart C, for an Alternative Benefit Plan), and if bought with 
premium assistance, for which the premium assistance is equal to or 
greater than 90 percent of the cost of the coverage, would be 
included in the Medicaid fraction of the DSH calculation, provided 
the patient is not also entitled to Medicare Part A.

h. Effects of Implementation of the Rural Community Hospital 
Demonstration Program in FY 2023

    The Rural Community Hospital Demonstration (RCHD) was authorized 
originally 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 it was extended for another 5-year period by 
section 3123 and 10313 of the Affordable Care Act (Pub. L. 111-148). 
Section 15003 of the 21st Century Cures Act (Cures Act) (Pub. L. 
114-255) extended the demonstration for an additional 5-year period, 
and section 128 of the Consolidated Appropriations Act of 2021 (Pub. 
L. 116-159) included an additional 5-year re-authorization through 
2028. CMS has conducted the demonstration since 2004, which allows 
enhanced, cost-based payment for Medicare inpatient services for up 
to 30 small rural hospitals.
    The authorizing legislation imposes a strict budget neutrality 
requirement. In this proposed rule, we summarize the status of the 
demonstration program, and the ongoing methodologies for 
implementation and budget neutrality.

2. Payments for Graduate Medical Education (GME)

    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME 
payments to teaching hospitals when those hospitals' weighted full-
time equivalent (FTE) counts exceed their direct GME FTE cap. In 
Milton S. Hershey Medical Center, et al. v. Becerra, the court 
ordered CMS to recalculate reimbursement owed, holding that CMS's 
regulation impermissibly modified the statutory weighting factors.
    After reviewing the statutory language regarding the direct GME 
FTE cap and the court's opinion in Milton S. Hershey Medical Center, 
et al. v. Becerra, we are proposing, as described in greater detail 
in section V.F.2. of the preamble of this proposed rule, a modified 
policy to be applied retroactively and prospectively for all 
teaching hospitals. Specifically, effective for cost reporting 
periods beginning on or after October 1, 2001 that are open or 
reopenable, we are proposing that if the hospital's unweighted 
number of FTE residents exceeds the FTE cap, and the number of 
weighted FTE residents also exceeds that FTE cap, the respective 
primary care and obstetrics and gynecology weighted FTE counts and 
other weighted FTE counts are adjusted to make the total weighted 
FTE count equal the FTE cap. If the number of weighted FTE residents 
does not exceed that FTE cap, then the allowable weighted FTE count 
for direct GME payment is the actual weighted FTE count. We estimate 
the impact of this modified policy to be $170 million for FY 2023.

3. Frontier Community Health Integration Project (FCHIP) Demonstration

    The Frontier Community Health Integration Project (FCHIP) 
demonstration was authorized under 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 (ACA) of 
2010 (Pub. L. 114-158), and most recently re-authorized and extended 
by the Consolidated Appropriations Act of 2021 (Pub. L. 116-159). 
The legislation authorized a demonstration project to allow eligible 
entities to develop and test new models for the delivery of health 
care 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 certain rural areas. The FCHIP 
demonstration initial period was conducted in 10 critical access 
hospitals (CAHs) from August 1, 2016, to July 31, 2019, and the 
demonstration ``extension period'' began on January 1, 2022, and run 
through June 30, 2027.
    The authorizing legislation requires the FCHIP demonstration to 
be budget neutral. In this proposed rule, we propose to continue 
with the budget neutrality approach used in the demonstration 
initial period for the demonstration extension period--to offset 
payments across CAHs nationally--should the demonstration incur 
costs to Medicare.

4. Proposed Update to the LTCH PPS Payment Rates

    As described in section VIII.C.2. of the preamble of this 
proposed rule, in order to update payments to LTCHs using the best 
available data, we are proposing to update the LTCH PPS standard 
Federal payment rate by 2.7 percent (that is, a 3.1 percent market 
basket update with a proposed reduction of 0.4 percentage point for 
the productivity adjustment, as required by section

[[Page 28700]]

1886(m)(3)(A)(i) of the Act). LTCHs that failed to submit quality 
data, as required by 1886(m)(5)(A)(i) of the Act and described in 
section VIII.C.2. of the preamble of this proposed rule, would 
receive a proposed update of 0.7 percent, which reflects a 2.0 
percentage points reduction for failure to submit quality data.

5. Hospital Quality Programs

    Section 1886(b)(3)(B)(viii) of the Act requires subsection (d) 
hospitals to report data in accordance with the requirements of the 
Hospital IQR Program for purposes of measuring and making publicly 
available information on health care quality, and links the quality 
data submission to the annual applicable percentage increase. 
Sections 1886(b)(3)(B)(ix), 1886(n), and 1814(l) of the Act require 
eligible hospitals and CAHs to demonstrate they are meaningful users 
of certified EHR technology for purposes of electronic exchange of 
health information to improve the quality of health care, and links 
the submission of information demonstrating meaningful use to the 
annual applicable percentage increase for eligible hospitals and the 
applicable percent for CAHs. Section 1886(m)(5) of the Act requires 
each LTCH to submit quality measure data in accordance with the 
requirements of the LTCH QRP for purposes of measuring and making 
publicly available information on health care quality, and in order 
to avoid a 2-percentage point reduction. Section 1886(o) of the Act 
requires the Secretary to establish a value-based purchasing program 
under which value-based incentive payments are made in a fiscal year 
to hospitals that meet the performance standards established on an 
announced set of quality and efficiency measures for the fiscal 
year. The purposes of the Hospital VBP Program include measuring the 
quality of hospital inpatient care, linking hospital measure 
performance to payment, and making publicly available information on 
hospital quality of care. Section 1886(p) of the Act requires a 
reduction in payment for subsection (d) hospitals that rank in the 
worst-performing 25 percent with respect to measures of hospital-
acquired conditions under the HAC Reduction Program for the purpose 
of measuring, linking measure performance to payment, and making 
publicly available information on health care quality. Section 
1886(q) of the Act requires a reduction in payment for subsection 
(d) hospitals for excess readmissions based on measures for 
applicable conditions under the Hospital Readmissions Reduction 
Program for the purpose of measuring, linking measure performance to 
payment, and making publicly available information on health care 
quality. Section 1866(k) of the Act applies to hospitals described 
in section 1886(d)(1)(B)(v) of the Act (referred to as ``PPS-Exempt 
Cancer Hospitals'' or ``PCHs'') and requires PCHs to report data in 
accordance with the requirements of the PCHQR Program for purposes 
of measuring and making publicly available information on the 
quality of care furnished by PCHs, however, there is no reduction in 
payment to a PCH that does not report data.

6. Other Proposed Provisions

a. Codification of the Costs Incurred for Qualified and Non-Qualified 
Deferred Compensation Plans

    As discussed in section X.A. of the preamble of this proposed 
rule, we are proposing to clarify general requirements; definitions; 
requirements for costs of the plans to be allowable under the 
program; additional requirements for payments to funded defined 
benefit plans; data and documentation requirements to support 
payments/contributions to the plans; and allowable administrative 
and other costs associated with the plans, including costs related 
to the Pension Benefit Guarantee Corporation.

b. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
To Report Data Elements To Address Any Future Pandemics and Epidemics 
as Determined by the Secretary

    Section X.B. of the preamble of this proposed rule would revise 
the hospital and CAH infection prevention and control CoP 
requirements that would require hospitals and CAHs, after the 
conclusion of the current COVID-19 PHE, to continue COVID-19 and 
seasonal influenza related reporting. The proposed revisions would 
continue to apply upon conclusion of the COVID-19 Public Health 
Emergency (PHE) and would continue until April 30, 2024, unless the 
Secretary establishes an earlier ending date. In addition, the rule 
proposes to establish reporting requirements for future PHEs related 
to epidemics and pandemics by requiring hospitals and CAHs to 
electronically report information on Acute Respiratory Illness 
(including, but not limited to, Seasonal Influenza Virus, Influenza-
like Illness, and Severe Acute Respiratory Infection), SARS-CoV-2/
COVID-19, and other viral and bacterial pathogens or infectious 
diseases. This collection would only occur when the Secretary has 
declared a Public Health Emergency (PHE), as defined in Sec.  
400.200, directly related to such specific pathogens and infectious 
diseases. Specifically, when the Secretary has declared a PHE, we 
propose to require hospitals and CAHs to report specific data 
elements to the CDC's National Health Safety Network (NHSN), or 
other CDC-supported surveillance systems, as determined by the 
Secretary. The proposed requirements of this section would apply to 
local, state, and national PHEs as declared by the Secretary. 
Relevant to the declared PHE, the categories of data elements that 
this report would include are as follows: Suspected and confirmed 
infections of the relevant infectious disease pathogen among 
patients and staff; total deaths attributed to the relevant 
infectious disease pathogen among patients and staff; personal 
protective equipment and other relevant supplies in the facility; 
capacity and supplies in the facility relevant to the immediate and 
long term treatment of the relevant infectious disease pathogen, 
such as ventilator and dialysis/continuous renal replacement therapy 
capacity and supplies; total hospital bed and intensive care unit 
bed census, capacity, and capability; staffing shortages; vaccine 
administration status of patients and staff for conditions monitored 
under this section and where a specific vaccine is applicable; 
relevant therapeutic inventories and/or usage; isolation capacity, 
including airborne isolation capacity; and key co-morbidities and/or 
exposure risk factors of patients being treated for the pathogen or 
disease of interest in this section that are captured with 
interoperable data standards and elements.
    In this proposed rule, we would also require that, unless the 
Secretary specifies an alternative format by which a hospital (or a 
CAH) must report each applicable infection (confirmed and suspected) 
and the applicable vaccination data in a format that provides 
person-level information, to include medical record identifier, 
race, ethnicity, age, sex, residential county and zip code, and 
relevant comorbidities for affected patients. We are also proposing 
in this provision to limit any person-level, directly or potentially 
individually identifiable, information for affected patients to 
items outlined in this section or otherwise specified by the 
Secretary. Lastly, we are proposing that a hospital (or a CAH) would 
provide the information specified on a daily basis, unless the 
Secretary specifies a lesser frequency. For purposes of burden 
estimates, we do not differentiate among hospitals and CAHs as they 
all would complete the same data collection.
    In regards to these proposals, we note that reporting frequency 
and requirements would be communicated to hospitals, stakeholders, 
and the public following a model similar to that which we used to 
inform regulated entities at the beginning of the COVID-19 PHE (see 
QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0).
    As detailed in the Collection of Information section of the 
preamble of this proposed rule, our current estimate of the cost for 
all hospitals and CAHs to comply with the continued COVID-19 and 
influenza-related reporting requirements would be a total of 
$38,204,400 (approximately $6,162 per facility) annually, based on 
weekly reporting. These estimates are likely overestimates of the 
costs associated with reporting because it assumes that all 
hospitals and CAHs will report manually. Efforts are underway to 
automate hospital and CAH reporting that have the potential to 
significantly decrease reporting burden and improve reliability. For 
proposed reporting requirements associated with a future PHE 
declaration, we acknowledge that there are uncertainties in planning 
for future emergencies, and CMS understands that there are lots of 
incentives and pathways to consider with regard to preparedness. 
Therefore, we are soliciting public comment on how to best align and 
incentivize preparedness, while also reducing burden and costs on 
regulated entities, and ensuring flexibility to quickly be informed 
and respond during emergencies. We are soliciting comment on the 
burden impacts related to reporting for a specified infectious 
disease when a future PHE is declared.

B. Overall Impact

    We have examined the impacts of this proposed rule as required 
by Executive Order

[[Page 28701]]

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 Social Security 
Act, section 202 of the Unfunded Mandates Reform Act of 1995 (March 
22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism 
(August 4, 1999), and the Congressional Review Act (5 U.S.C. 
804(2)).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that 
maximize net benefits (including potential economic, environmental, 
public health and safety effects, distributive impacts, and equity). 
Section 3(f) of Executive Order 12866 defines a ``significant 
regulatory action'' as an action that is likely to result in a rule: 
(1) Having an annual effect on the economy of $100 million or more 
in any 1 year, or adversely and materially affecting a sector of the 
economy, productivity, competition, jobs, the environment, public 
health or safety, or state, local or tribal governments or 
communities (also referred to as ``economically significant''); (2) 
creating a serious inconsistency or otherwise interfering with an 
action taken or planned by another agency; (3) materially altering 
the budgetary impacts of entitlement grants, user fees, or loan 
programs or the rights and obligations of recipients thereof; or (4) 
raising novel legal or policy issues arising out of legal mandates, 
the President's priorities, or the principles set forth in the 
Executive order.
    A regulatory impact analysis (RIA) must be prepared for major 
rules with significant regulatory action/s and/or with economically 
significant effects ($100 million or more in any 1 year). Based on 
our estimates, OMB's Office of Information and Regulatory Affairs 
has determined this rulemaking is ``economically significant'' as 
measured by the $100 million threshold, and hence also a major rule 
under Subtitle E of the Small Business Regulatory Enforcement 
Fairness Act of 1996 (also known as the Congressional Review Act). 
Accordingly, we have prepared a Regulatory Impact Analysis that to 
the best of our ability presents the costs and benefits of the 
rulemaking. OMB has reviewed these proposed regulations, and the 
Departments have provided the following assessment of their impact.
    We estimate that the proposed changes for FY 2023 acute care 
hospital operating and capital payments would redistribute amounts 
in excess of $100 million to acute care hospitals. 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 $0.3 billion decrease in 
FY 2023 payments, primarily driven by: (a) A combined $0.6 billion 
increase in FY 2023 operating payments, including uncompensated care 
payments and proposed supplemental payments, and (b) a combined 
decrease of $1.02 billion resulting from estimated changes in new 
technology add-on payments, the proposed change to the GME weighting 
methodology, the expiration of the low-volume payment adjustment, 
and FY 2023 capital payments. These proposed changes are relative to 
payments made in FY 2022. 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 $25 million in 
FY 2023 relative to FY 2022.
    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 2.7 percent 
hospital update to the standardized amount (which includes the 
estimated 3.1 percent market basket update reduced by the proposed 
0.4 percentage point for the productivity adjustment). The estimates 
of IPPS operating payments to acute care hospitals do not reflect 
any changes in hospital admissions or real case-mix intensity, which 
will also affect overall payment changes.
    The analysis in this Appendix, in conjunction with the remainder 
of this document, demonstrates that this 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 some hospitals may be significant. 
Finally, in accordance with the provisions of Executive Order 12866, 
the 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 2023, 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 of March 2022, there were 3,141 IPPS acute care hospitals 
included in our analysis. This represents approximately 53 percent 
of all Medicare-participating hospitals. The majority of this impact 
analysis focuses on this set of hospitals. There also are 
approximately 1,422 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 2023 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 91 
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 14 RNHCIs being paid on a reasonable

[[Page 28702]]

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 2023 
percentage increase in the 2018-based IPPS operating market basket, 
consistent with section 1886(b)(3)(B)(ii) of the Act, and Sec. Sec.  
403.752(a) and 413.40 of the regulations. Consistent with current 
law, based on IGI's 2021 fourth quarter forecast of the 2018-based 
IPPS market basket increase, we are estimating the proposed FY 2023 
update to be 3.1 percent (that is, the estimate of the market basket 
rate-of-increase), as discussed in section V.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 2023. However, the Affordable Care Act requires a 
productivity adjustment (proposed 0.4 percentage point reduction for 
FY 2023), resulting in a proposed 2.7 percent applicable percentage 
increase for IPPS hospitals that submit quality data and are 
meaningful EHR users, as discussed in section V.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 2018-based IPPS operating market basket for FY 2023, 
estimated at 3.1 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 2023 for operating 
costs of acute care hospitals. The proposed FY 2023 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 2023 operating payments would increase by 1.4 percent, 
compared to FY 2022. In addition to the proposed applicable 
percentage increase, this amount reflects the proposed +0.5 
percentage point permanent adjustment to the standardized amount 
required under section 414 of MACRA. The impacts do not reflect 
changes in the number of hospital admissions or real case-mix 
intensity, which 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 2021 
claims data is the best available data for purposes of the proposed 
FY 2023 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 2021 MedPAR file, as discussed previously in this 
proposed rule, and the most current Provider-Specific File (PSF) 
that is used for payment purposes. 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, as also discussed previously in this proposed 
rule. Our analysis has several qualifications. First, in this 
analysis, we do not adjust 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 2021 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 2023 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 2.7 percent (that is, a 3.1 
percent market basket update with a proposed reduction of 0.4 
percentage point for the 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 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 2019, compared to the FY 2018 
wage data, to calculate the proposed FY 2023 wage index.
     The effects of the geographic reclassifications by the 
MGCRB (as of publication of this proposed rule) that will be 
effective for FY 2023.
     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 imputed floor wage index 
adjustment. This provision is not budget neutral.
     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 2023. This provision is not budget neutral.
     The effects of the expiration of the special payment 
status for MDHs at the end of FY 2022 under current law as a result 
of

[[Page 28703]]

which MDHs that currently receive the higher of payments made based 
on the Federal rate or the payments made based on the Federal rate 
plus 75 percent of the difference between payments based on the 
Federal rate and the hospital-specific rate will be paid based on 
the Federal rate starting in FY 2023.
     The total estimated change in payments based on the 
proposed FY 2023 policies relative to payments based on FY 2022 
policies.
    To illustrate the impact of the proposed FY 2023 changes, our 
analysis begins with a FY 2022 baseline simulation model using: The 
FY 2022 applicable percentage increase of 2.0 percent; the 0.5 
percentage point adjustment required under section 414 of the MACRA 
applied to the IPPS standardized amount; the FY 2022 MS-DRG GROUPER 
(Version 39); the FY 2022 CBSA designations for hospitals based on 
the OMB definitions from the 2010 Census; the FY 2022 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 1.925 
percent. At the time this impact was prepared, 25 hospitals are 
estimated to not receive the full market basket rate-of-increase for 
FY 2023 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 2023 using a reduced update for 
these hospitals.
    For FY 2023, 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 0.375 percent. At the time this impact 
analysis was prepared, 158 hospitals are estimated to not receive 
the full market basket rate-of-increase for FY 2023 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 2023 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 -0.4 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, 19 hospitals are 
estimated to not receive the full market basket rate-of-increase for 
FY 2023 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 2023 
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 2022 to FY 2023. 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 2023 using a proposed applicable 
percentage increase of 2.7 percent. This includes the FY 2023 
forecasted IPPS operating hospital market basket increase of 3.1 
percent with a proposed 0.4 percentage point reduction for the 
productivity adjustment. Hospitals that fail to comply with the 
quality data submission requirements and are meaningful EHR users 
would receive a proposed update of 1.925 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 0.375 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 -0.4 percent. Under section 
1886(b)(3)(B)(iv) of the Act, the update to the hospital-specific 
amounts for SCHs is also equal to the applicable percentage 
increase, or 2.7 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 2022 to FY 2023 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 2022 that are no longer reclassified in FY 2023. 
Conversely, payments may increase for hospitals not reclassified in 
FY 2022 that are reclassified in FY 2023.

2. Analysis of Table I

    Table I displays the results of our analysis of the proposed 
changes for FY 2023. 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 3,141 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 
2,419 hospitals located in urban areas and 722 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 2023 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 1,867, and 1,274, 
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 1,939 nonteaching hospitals in our 
analysis, 932 teaching hospitals with fewer than 100 residents, and 
270 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 six rows examine the impacts of the proposed changes on 
rural hospitals by special payment groups (SCHs and RRCs) and 
reclassification status from urban to rural in accordance with 
section 1886(d)(8)(E) of the Act. Of the hospitals that are not 
reclassified from urban to rural, there are 161 RRCs, 256 SCHs, and 
120 hospitals that are both SCHs and RRCs. Of the hospitals that are 
reclassified from urban to rural, there are 460 RRCs, 47 SCHs, and 
37 hospitals that are both SCHs and RRCs.
    The next series of groupings are based on the type of ownership 
and the hospital's Medicare and Medicaid utilization expressed as a 
percent of total inpatient days. These data were taken from the most 
recent available Medicare cost reports.
    The next grouping is based on hospitals' reporting of diagnosis 
codes describing patients experiencing homelessness. This row 
reflects hospitals whose claims indicate

[[Page 28704]]

that at least 5 percent of their IPPS cases involve these patients 
based on the reporting of ICD-10-CM diagnosis code Z59.0 
(Homelessness). We note that hospitals are not required to identify 
these patients on their claims, and reporting this information on 
the claim does not currently impact Medicare payment. There may be 
other hospitals with at least 5 percent of their IPPS cases 
involving these patients, however we are unable to identify these 
hospitals. As discussed in section II.D.13.b. of the preamble to 
this proposed rule, we are soliciting public comments on how the 
reporting of ICD-10-CM diagnosis codes in categories Z55-Z65 
(Persons with potential health hazards related to socioeconomic and 
psychosocial circumstances) that describe the social determinants of 
health may improve our ability to recognize severity of illness, 
complexity of illness, and/or utilization of resources under the MS-
DRGs. Consistent with the Administration's goal of advancing health 
equity for all, we are also interested in receiving feedback on how 
we might otherwise foster the documentation and reporting of the 
diagnosis codes describing social and economic circumstances to more 
accurately reflect each health care encounter and improve the 
reliability and validity of the coded data including in support of 
efforts to advance health equity. As also noted in that section, 
stakeholders have shared several reasons for reduced documentation 
of social determinants of health in the inpatient setting. While 
homelessness was one of the more frequently reported codes that 
describe social determinants of health prior to FY 2022, we seek 
comment on whether including groupings of hospitals that report 
other social determinants of health in diagnosis codes categories 
Z55-Z65 could be informative.
    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 2023 or not, respectively. The fourth subgrouping 
displays hospitals that reclassified from urban to rural in 
accordance with section 1886(d)(8)(E) of the Act. The fifth 
subgrouping displays hospitals deemed urban in accordance with 
section 1886(d)(8)(B) of the Act.
BILLING CODE 4120-01-P

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BILLING CODE 4120-01-C

[[Page 28708]]

a. Effects of the Proposed Hospital Update and Other Proposed 
Adjustments (Column 1)

    As discussed in section V.A. of the preamble of this proposed 
rule, this column includes the proposed hospital update, including 
the proposed 3.1 percent market basket update reduced by the 
proposed 0.4 percentage point for the productivity adjustment. In 
addition, as discussed in section II.D. of the preamble of this 
proposed rule, this column includes the FY 2023 +0.5 percentage 
point adjustment required under section 414 of the MACRA. As a 
result, we are proposing to make a 3.2 percent update to the 
national standardized amount. This column also includes the proposed 
update to the hospital-specific rates which includes the proposed 
3.1 percent market basket update reduced by the proposed 0.4 
percentage point for the productivity adjustment. As a result, we 
are proposing to make a 2.7 percent update to the hospital-specific 
rates.
    Overall, hospitals would experience a 3.1 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 2.7 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. We also proposed a permanent 10-percent 
cap on the reduction in a MS-DRG's relative weight in a given year 
and an associated recalibration cap budget neutrality factor to 
account for the proposed 10-percent cap on relative weight 
reductions 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 2023 MS-DRG relative weights will be 100 percent cost-
based and 100 percent MS-DRGs. For FY 2023, we are proposing to 
calculate the MS-DRGs using the FY 2021 MedPAR data grouped to the 
proposed Version 40 (FY 2023) 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 1.000491 and the proposed 
recalibration cap budget neutrality factor of 0.999765 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, 
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 2023 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, 18-04, and 20-01. (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; 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; and to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45163) for a discussion of our adoption of the 
CBSA update in OMB Bulletin No. 20-01 for the FY 2022 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 2023 is based on data 
submitted for hospital cost reporting periods, beginning on or after 
October 1, 2018 and before October 1, 2019. The estimated impact of 
the updated wage 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 2022 wage index, the labor-related share 
of 67.6 percent, under the OMB delineations and having a 100-percent 
occupational mix adjustment applied, to a model using the proposed 
FY 2023 pre-reclassification wage index 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 40 MS-DRG GROUPER constant. The FY 2023 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 2023, 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 2023 wage budget neutrality factor is 
1.001303 and the overall proposed payment change is 0 percent.
    Column 3 shows the impacts of updating the wage data. 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 2.7 percent compared to FY 2022. Therefore, the 
only manner in which to maintain or exceed the previous year's wage 
index was to match or exceed the proposed 2.7 percent increase in 
the national average hourly wage. Of the 3,093 hospitals with wage 
data for both FYs 2022 and 2023, 1,384 or 44.7 percent would 
experience an average hourly wage increase of 2.7 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 2023 relative to FY 2022. 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) 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

[[Page 28709]]

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.
[GRAPHIC] [TIFF OMITTED] TP10MY22.259

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 2023.
    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 0.985346 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).
    Geographic reclassification generally benefits hospitals in 
rural areas. We estimate that the geographic reclassification would 
increase payments to rural hospitals by an average of 1.0 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 2023.

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 2022 IPPS/LTCH PPS final rules, and this FY 2023 
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 2023 rural floor budget neutrality factor 
to be applied to the wage index of 0.993656, 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 2023 wage 
index of providers before the rural floor adjustment and the 
proposed post-reclassification FY 2023 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 192 hospitals would receive the rural floor in 
FY 2023. All IPPS hospitals in our model would have their wage 
indexes reduced by the proposed rural floor budget neutrality 
adjustment of 0.993656. 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 3.3 
percent increase in payments primarily due to the application of the 
rural floor in Massachusetts.

f. Effects of the Application of the Proposed Imputed Floor, Proposed 
Frontier State Wage Index and Proposed Out-Migration Adjustment (Column 
6)

    This column shows the combined effects of the application of the 
following: (1) The imputed floor under section 1886(d)(3)(E)(iv)(I) 
and (II) of the Act, which 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; (2) 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 (3) 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 three wage index provisions are not budget neutral and 
would increase payments overall by 0.3 percent compared to the 
provisions not being in effect.
    Section 1886(d)(3)(E)(iv)(III) of the Act provides that the 
imputed floor wage index for all-urban States shall not be applied 
in a budget neutral manner. Therefore, the

[[Page 28710]]

imputed floor adjustment is estimated to increase IPPS operating 
payments by approximately $140 million. There are an estimated 69 
providers in Connecticut, Delaware, Washington, DC, New Jersey, and 
Rhode Island that will receive the imputed floor wage index.
    The term ``frontier States'' is defined in the statute as States 
in which at least 50 percent of counties have a population density 
less than 6 persons per square mile. Based on these criteria, 5 
States (Montana, Nevada, North Dakota, South Dakota, and Wyoming) 
are considered frontier States and an estimated 44 hospitals located 
in those States would receive a frontier wage index of 1.0000. 
Overall, this provision is not budget neutral and is estimated to 
increase IPPS operating payments by approximately $64 million.
    In addition, section 1886(d)(13) of the Act provides for an 
increase in the wage index for hospitals located in certain counties 
that have a relatively high percentage of hospital employees who 
reside in the county, but work in a different area with a higher 
wage index. Hospitals located in counties that qualify for the 
payment adjustment would receive an increase in the wage index that 
is equal to a weighted average of the difference between the wage 
index of the resident county, post-reclassification and the higher 
wage index work area(s), weighted by the overall percentage of 
workers who are employed in an area with a higher wage index. There 
are an estimated 245 providers that would receive the out-migration 
wage adjustment in FY 2023. 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 $55 
million.

g. Effects of the Expiration of MDH Special Payment Status (Column 7)

    Column 7 shows our estimate of the changes in payments due to 
the expiration of MDH status, a nonbudget neutral payment provision. 
Section 50205 of the Bipartisan Budget Act of 2018 (Pub. L. 115-123, 
enacted on February 9, 2018) extended the MDH program (which, under 
previous law, was to be in effect for discharges before October 1, 
2017 only) for discharges occurring on or after October 1, 2017, 
through FY 2022 (that is, for discharges occurring on or before 
September 30, 2022). Therefore, under current law, the MDH program 
will expire at the end of FY 2022. Hospitals that qualified to be 
MDHs receive the higher of payments made based on the Federal rate 
or the payments made based on the Federal rate amount plus 75 
percent of the difference between payments based on the Federal rate 
and payments based on the hospital-specific rate (a hospital-
specific cost-based rate). Because this provision was not budget 
neutral, the expiration of this payment provision results in a 0.2 
percent decrease in payments overall. There are currently 174 MDHs, 
of which we estimate 120 would have been paid under the blended 
payment of the Federal rate and hospital-specific rate if the MDH 
program had not expired. Because those 120 MDHs will no longer 
receive the blended payment and will be paid only under the Federal 
rate in FY 2023, it is estimated that those hospitals would 
experience an overall decrease in payments of approximately $219 
million.

h. Effects of All FY 2022 Proposed Changes (Column 8)

    Column 8 shows our estimate of the proposed changes in payments 
per discharge from FY 2022 and FY 2023, resulting from all changes 
reflected in this proposed rule for FY 2023. 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 1.4 percent for FY 2023 relative to FY 
2022 and for this row is primarily driven by the proposed changes 
reflected in Column 1. Column 8 includes the proposed annual 
hospital update of 3.2 percent to the national standardized amount. 
This proposed annual hospital update includes the proposed 3.1 
percent market basket update reduced by the proposed 0.4 percentage 
point 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 2.7 
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, combined with the other adjustments 
described previously and shown in Table I, would result in a 1.4 
percent increase in payments in FY 2023 relative to FY 2022.
    This column also reflects the estimated effect of outlier 
payments returning to their targeted levels in FY 2023 as compared 
to the estimated outlier payments for FY 2022 produced from our 
payment simulation model. As discussed in section II.A.4.j. of the 
Addendum to this proposed rule, the statute requires that 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, and also requires that the average standardized amount be 
reduced by a factor to account for the estimated proportion of total 
DRG payments made to outlier cases. We are proposing to continue to 
use a 5.1 percent target (or an outlier offset factor of 0.949) in 
calculating the outlier offset to the standardized amount, just as 
we did for FY 2022. Therefore, our estimate of payments per 
discharge for FY 2023 from our payment simulation model reflects 
this 5.1 percent outlier payment target. Our payment simulation 
model shows that estimated outlier payments for FY 2022 exceed that 
target by approximately 1.8 percent. Therefore, our estimate of the 
proposed changes in payments per discharge from FY 2022 and FY 2023 
in Column 8 reflects the estimated -1.8 percent change in outlier 
payments produced by our payment simulation model when returning to 
the 5.1 percent outlier target for FY 2023. There are also 
interactive effects among the various factors comprising the payment 
system that we are not able to isolate, which may contribute to our 
estimate of the proposed changes in payments per discharge from FY 
2022 and FY 2023 in Column 8.
    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 1.4 percent for FY 2023. Hospitals in 
urban areas would experience a 1.4 percent increase in payments per 
discharge in FY 2023 compared to FY 2022. Hospital payments per 
discharge in rural areas are estimated to increase by 1.1 percent in 
FY 2023.

3. Impact Analysis of Table II

    Table II presents the projected impact of the proposed changes 
for FY 2023 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 2022 with the estimated 
proposed average payments per discharge for FY 2023, 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 8 
of Table I.
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H. Effects of Other Proposed 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.D. 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 Policy Changes Relating to New Medical Service and 
Technology Add On Payments

a. Proposed FY 2023 Status of Technologies Approved for FY 2022 New 
Technology Add-On Payments

    In section II.F.5.a of the preamble of this proposed rule, we 
are proposing to continue to make new technology add-on payments for 
the 15 technologies listed in the table later in this section in FY 
2023 because these technologies would still be considered new for 
purposes of new technology add-on payments. 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 the applicant's 
estimate at the time they submitted their original application and 
the increase in new technology add-on payments for FY 2023 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 15 technologies for which we are proposing to 
continue to make new technology add-on payments in FY 2023:

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b. Proposed FY 2023 Applications for New Technology Add-On Payments

    In sections II.F.6. and 7. of the preamble to this proposed 
rule, we discuss 26 technologies for which we received applications 
for add-on payments for new medical services and technologies for FY 
2023. We note that of the 37 applications (19 alternative and 18 
traditional) we received, 11 applicants withdrew their application 
(6 alternative and 5 traditional) 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.7. 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 Breakthrough Device program will be considered not substantially 
similar to an existing technology for purposes of the new technology 
add-on payment under the IPPS, and will not need to demonstrate that 
the technology represents a substantial clinical improvement. These 
technologies must still be within the 2-3 year newness period, as 
discussed in II.F.1.a.(1) of this proposed rule, and must also still 
meet the cost criterion.
    As also discussed in section II.F.7. of the preamble of this 
proposed rule, we are proposing to approve 13 alternative pathway 
applications submitted for FY 2023 new technology add-on payments. 
We note that one technology is still pending Breakthrough Device 
Designation. We also note that one 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 through 47308). We are inviting public 
comment on whether the technology has any operating costs; to the 
extent we determine that there are no operating costs associated 
with the use of the technology, it would not be eligible for new 
technology add-on payment.
    Based on preliminary information from the applicants at the time 
of this proposed rule, we estimate that total payments for the 13 
technologies that applied under the alternative pathway, if 
approved, would be in excess of approximately $82 million for FY 
2023, based on the total estimated FY 2023 payments for new 
technologies that are part of the Breakthrough Device program. 
Because cost information has not yet been provided for two of the 13 
technologies under the alternative pathway, including the sole QIDP 
applicant, we have not included those technologies in the estimate. 
We did not receive any LPAD applications for add-on payments for new 
technologies for FY 2023. We note that the 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 13 technologies 
that applied under the traditional pathway discussed in section 
II.F.6. of the preamble of this proposed rule will meet the criteria 
for new technology add-on payments for FY 2023. Consequently, it is 
premature to estimate the potential payment impact of these 13 
technologies for any potential new technology add-on payments for FY 
2023. We note that, as in past years, if any of the technologies 
that applied under the traditional pathway are found to be eligible 
for new technology add-on payments for FY 2023, in the FY 2023 IPPS/
LTCH PPS final rule, we would discuss the estimated payment impact 
for FY 2023.

2. Effects of the Proposed Changes to Medicare DSH and Uncompensated 
Care Payments for FY 2022

a. Effects of the Proposed Changes to Medicare DSH To Ensure Only 
Appropriate Days Are Counted in the Numerator of the Medicaid Fraction

    As discussed in section IV.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 who receive health insurance authorized by a section 1115 
demonstration that provides essential health benefits (EHB) as set 
forth in 42 CFR part 440, subpart C, for an Alternative Benefit Plan 
(ABP). We further propose to include in the Medicaid fraction those 
days of patients who have bought health insurance that provides EHB 
using premium assistance authorized by a section 1115 demonstration 
that is equal to at least 90 percent of the cost of the health 
insurance, on that day. To the extent that this proposed policy 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 2023 and 
Proposed New Supplemental Payment for Indian Health Service Hospitals 
and Tribal Hospitals and Hospitals Located in Puerto Rico

    As discussed in section IV.D. of the preamble of this proposed 
rule, under section

[[Page 28714]]

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 2023 is $6,537,657,797.52. 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 65.71 percent. For FY 2022, the amount available to be 
distributed for uncompensated care was $7,192,008,709.70 or 75 
percent of the amount that otherwise would have been paid for 
Medicare DSH payment adjustments adjusted by a Factor 2 of 68.57 
percent. In addition, under our proposal to establish a new 
supplemental payment for Indian Health Service (IHS) and Tribal 
Hospitals and Puerto Rico Hospitals, these hospitals would receive 
approximately $91.6 million in supplemental payments, as determined 
based on the difference between each hospital's FY 2022 UCP (reduced 
by--9.1 percent, which is the projected change between the proposed 
FY 2023 total uncompensated care payment amount and the total 
uncompensated care payment amount for FY 2022) and its FY 2023 UCP 
as calculated using the proposed methodology for FY 2023. For this 
proposed rule, the total proposed uncompensated care payments and 
proposed supplemental payments equal approximately $6.629 billion. 
For FY 2023, we are proposing to use two years of data on 
uncompensated care costs from Worksheet S-10 of the FY 2018 and 2019 
cost reports to calculate Factor 3 for all DSH-eligible hospitals, 
including IHS/Tribal hospitals and Puerto Rico hospitals. For a 
complete discussion regarding the proposed methodology for 
calculating Factor 3 for FY 2023 and the proposed methodology for 
calculating the proposed new supplemental payments, we refer readers 
to sections IV.D. and IV.E. of the preamble of this proposed rule.
    To estimate the impact of the combined effect of the 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 along with our proposal to use our 
authority under section 1886(d)(5)(I) of the Act to establish a new 
supplemental payment for Puerto Rico hospitals and IHS and Tribal 
hospitals, we compared total uncompensated care payments estimated 
in the FY 2022 IPPS/LTCH PPS final rule to the combined total of 
proposed uncompensated care payments and proposed supplemental 
payments estimated in this FY 2023 IPPS/LTCH PPS proposed 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 Factor 2 of 68.57 percent and 
multiplied by a Factor 3 calculated using the methodology described 
in the FY 2022 IPPS/LTCH PPS final rule. For FY 2023, we calculated 
75 percent of the estimated amount that would be paid as Medicare 
DSH payments during FY 2023 absent section 3133 of the Affordable 
Care Act, adjusted by a proposed Factor 2 of 65.71 percent and 
multiplied by a Factor 3 calculated using the methodology described 
previously. For the proposed supplemental payments for IHS/Tribal 
hospitals and Puerto Rico hospitals, we calculated the difference 
between the hospital's adjusted base year amount (as determined 
based on the hospital's FY 2022 uncompensated care payment) and the 
hospital's FY 2023 uncompensated care payment.
    Our analysis included 2,380 hospitals that are projected to be 
eligible for DSH in FY 2023. It did not include hospitals that had 
terminated their participation in the Medicare program as of 
February 3, 2022, Maryland hospitals, new hospitals, and SCHs that 
are expected to be paid based on their hospital-specific rates. The 
26 hospitals that are anticipated to be participating in the Rural 
Community Hospital Demonstration Program were excluded from this 
analysis, as participating hospitals are not eligible to receive 
empirically justified Medicare DSH payments and uncompensated care 
payments. In addition, the data from merged or acquired hospitals 
were combined under the surviving hospital's CMS certification 
number (CCN), and the non-surviving CCN was excluded from the 
analysis. The estimated impact of the proposed changes in Factors 1, 
2, and 3 on uncompensated care payments and of the proposal to 
establish a new supplemental payment for IHS/Tribal hospitals and 
Puerto Rico hospitals across all hospitals projected to be eligible 
for DSH payments in FY 2023, by hospital characteristic, is 
presented in the following table:
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    The changes in projected FY 2023 uncompensated care payments and 
proposed supplemental payments compared to the total uncompensated 
care payments in FY 2022 are driven by a proposed decrease in Factor 
1 and a proposed decrease in Factor 2 and the proposal to establish 
a new supplemental payment for DSH-eligible IHS/Tribal hospitals and 
Puerto Rico hospitals. The proposed Factor 1 has decreased from the 
FY 2022 final rule's Factor 1 of $10.489 billion to this proposed 
rule's Factor 1 of $9.949 billion, while the proposed percent change 
in the percent of individuals who are uninsured (Factor 2) has 
decreased from 68.57 percent to 65.71 percent. In addition, we note 
that there is a slight increase in the number of projected DSHs to 
2,380 at the time of the development for this proposed rule compared 
to the projected 2,366 DSHs in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45587). Based on the proposed changes, the impact analysis 
found that, across all projected DSH eligible hospitals, proposed FY 
2023 uncompensated care payments and proposed supplemental payments 
are estimated at approximately $6.629 billion, or a proposed 
decrease of approximately 7.82 percent from FY 2022 uncompensated 
care payments (approximately $7.192 billion). While the proposed 
changes would result in a net decrease in the total amount available 
to be distributed in uncompensated care payments and proposed 
supplemental payments, the projected payment decreases vary by 
hospital type. This redistribution of payments is caused by proposed 
changes in Factor 3 and the proposal to establish a new supplemental 
payment for DSH-eligible IHS/Tribal hospitals and Puerto Rico 
hospitals. As seen in the previous table, a percent change of less 
than negative 7.82 percent indicates that hospitals within the 
specified category are projected to experience a larger decrease in 
payments, on average, compared to the universe of projected FY 2023 
DSH hospitals. Conversely, a percent change greater than negative 
7.82 percent indicates that a hospital type is projected to have a 
smaller decrease or an increase compared to the overall average. The 
variation in the distribution of overall payments by hospital 
characteristic is largely dependent on a given hospital's 
uncompensated care costs as reported on the Worksheet S-10 and used 
in the Factor 3 computation and whether the hospital is eligible to 
receive the proposed new supplemental payment.
    Rural hospitals, in general, are projected to experience larger 
decreases in uncompensated care payments and proposed supplemental 
payments than their urban counterparts. Overall, rural hospitals are

[[Page 28717]]

projected to receive an 8.45 percent decrease in payments, which is 
a greater decrease than the overall hospital average, while urban 
hospitals are projected to receive a 7.79 percent decrease in 
payments, which is slightly smaller than the overall hospital 
average.
    By bed size, larger rural hospitals are projected to receive the 
largest decreases in uncompensated care payments and proposed 
supplemental payments. Rural hospitals with 250+ beds are projected 
to receive a 9.44 percent payment decrease, and rural hospitals with 
100-249 beds are projected to receive an 8.84 percent decrease. 
Smaller rural hospitals with 0-99 beds are projected to receive an 
8.00 percent payment decrease. Among urban hospitals, the smallest 
and largest urban hospitals, those with 0-99 and 250+ beds, are 
projected to receive a decrease in payments that is greater than the 
overall hospital average, at 8.32 and 7.87 percent, respectively. In 
contrast, urban hospitals with 100-249 beds are projected to receive 
a 7.42 percent decrease in payments, which is a smaller decrease 
than the overall hospital average.
    By region, rural hospitals are generally expected to receive 
similar or larger than average decreases in uncompensated care 
payments and proposed supplemental payments in all regions, except 
for rural hospitals in the Middle Atlantic Region, which are 
projected to receive a smaller than average decrease of 7.80 
percent, rural hospitals in South Atlantic Region, which are 
projected to receive a decrease of 7.27 percent in payments, rural 
hospitals in the West South Central Region, which are projected to 
receive a smaller than average decrease of 7.55 percent, and rural 
hospitals in East North Central Region, which are projected to 
receive an increase of 11.21 percent. Rural hospitals in the Pacific 
Region are projected to receive an increase of 17.96 percent in 
payments. Regionally, urban hospitals are projected to receive a 
more varied range of payment changes. Urban hospitals in the New 
England, Middle Atlantic, and South Atlantic Regions, as well as 
hospitals in Puerto Rico, are projected to receive larger than 
average decreases in payments. Urban hospitals in the East North 
Central, East South Central, West North Central, West South Central, 
Mountain, and Pacific Regions are projected to receive smaller than 
average decreases in payments.
    By payment classification, although hospitals in urban payment 
areas overall are expected to receive a 7.24 percent decrease in 
uncompensated care payments and proposed supplemental payments, 
hospitals in large urban payment areas are expected to see a 
decrease in payments of 5.85 percent, while rural hospitals are 
expected to receive a decrease in payments of 8.81 percent. 
Hospitals in other urban payment areas are projected to receive the 
largest decrease of 9.87 percent.
    Nonteaching hospitals are projected to receive a payment 
decrease of 6.58 percent, teaching hospitals with fewer than 100 
residents are projected to receive a payment decrease of 7.54 
percent, and teaching hospitals with 100+ residents have a projected 
payment decrease of 8.99 percent. Proprietary and voluntary 
hospitals are projected to receive smaller than average decreases of 
7.58 and 6.67 percent respectively, while government hospitals are 
expected to receive a larger payment decrease of 10.19 percent. 
Hospitals with less than 25 percent Medicare utilization and 
hospitals with 25 to 50 percent Medicare utilization are projected 
to receive decreases of 8.19 and 7.78 percent, respectively, while 
hospitals with 50-65 percent are projected to receive a small 
increase of 0.12 percent and hospitals with greater than 65 percent 
Medicare utilization are projected to receive a large increase of 
8.56 percent. All hospitals with less than 50 percent Medicaid 
utilization are projected to receive smaller decreases in 
uncompensated care payments and proposed supplemental payments than 
the overall hospital average percent change, while hospitals with 
50-65 percent Medicaid utilization are projected to receive larger 
decreases of 16.55 percent. Hospitals with greater than 65 percent 
Medicaid utilization are projected to receive the smallest decrease 
of 0.79 percent.
    The above impact table reflects the modeled FY 2023 
uncompensated care payments and proposed supplemental payments for 
IHS/Tribal and Puerto Rico hospitals. In FY 2023, we note that the 
IHS/Tribal hospitals' and Puerto Rico hospitals' proposed 
uncompensated care payments are estimated to decrease by 
approximately $103 million. However, the proposed supplemental 
payments to IHS/Tribal hospitals and Puerto Rico hospitals are 
estimated to be approximately $92 million.

3. Effects of Proposed Reductions Under the Hospital Readmissions 
Reduction Program for FY 2023

    In section V.H of the preamble of this proposed rule, we discuss 
our proposed policies for the FY 2023 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 estimated FY 2023 payment adjustment factors that 
account for the suppression of the pneumonia readmission measure for 
this proposed rule, we used the data from the FY 2022 Hospital 
Readmissions Reduction Program for the five non-suppressed measures 
(acute myocardial infarction--AMI, heart failure--HF, chronic 
obstructive pulmonary disease--COPD, coronary artery bypass graft--
CABG, and total hip arthroplasty/total knee arthroplasty--THA/TKA) 
and the FY 2022 Hospital IPPS Proposed Rule Impact File to analyze 
results by hospital characteristics. Hospitals are stratified into 
quintiles based on the proportion of dual-eligible stays among 
Medicare fee-for-service (FFS) and managed care stays between July 
1, 2017, and December 1, 2019 (that is, the FY 2022 Hospital 
Readmissions Reduction Program's applicable period).\1\ 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 2023 IPPS/LTCH PPS final rule, we will provide an updated 
estimate of the financial impact using the proportion of dually-
eligible beneficiaries, ERRs, and aggregate payments for each 
condition/procedure and all discharges for applicable hospitals from 
the FY 2023 Hospital Readmissions Reduction Program applicable 
period (that is, July 1, 2018, through June 30, 2021). We note that 
for the FY 2023 applicable period, we will only be assessing data 
from July 1, 2018, through December 1, 2019, and from July 1, 2020, 
through June 30, 2021, 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.\2\
---------------------------------------------------------------------------

    \1\ Although the FY 2022 performance period is July 1, 2017, 
through June 30, 2020, we note that first and second quarter data 
from CY 2020 is excluded from program calculations 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 will be 
adjusted to July 1, 2017, through December 1, 2019.
    \2\ Although the FY 2023 performance period is July 1, 2018, 
through June 30, 2021, we note that first and second quarter data 
from CY 2020 is excluded from program calculations 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 will be 
adjusted to July 1, 2018, through December 1, 2019, and then July 1, 
2020, through June 30, 2021.
---------------------------------------------------------------------------

    The results in the table include 2,987 non-Maryland hospitals 
eligible to receive a penalty during the performance period. 
Hospitals are eligible to receive a penalty if they have 25 or more 
eligible discharges for at least one measure between July 1, 2017, 
and December 1, 2019. The second column in the table indicates the 
total number of non-Maryland hospitals with available data for each 
characteristic that have an estimated payment adjustment factor less 
than 1 (that is, penalized hospitals).
    The third column in the table indicates the percentage of 
penalized hospitals among those eligible to receive a penalty by 
hospital characteristic. For example, 77.83 percent of eligible 
hospitals characterized as non-teaching hospitals are expected to be 
penalized. Among teaching hospitals, 86.71 percent of eligible 
hospitals with fewer than 100 residents and 91.34 percent of 
eligible hospitals with 100 or more residents are expected to be 
penalized. The fourth column in the table estimates the financial 
impact on hospitals by hospital characteristic. The table shows the 
share of penalties as a percentage of all base operating DRG 
payments for hospitals with each characteristic. This is calculated 
as the sum of penalties for all hospitals with that characteristic 
over the sum of all base operating DRG payments for those hospitals 
between January 1, 2019 and December 31, 2019 (CY 2019). For 
example,

[[Page 28718]]

the penalty as a share of payments for non-teaching hospitals is 
0.60 percent. This means that total penalties for all non-teaching 
hospitals are 0.60 percent of total payments for non-teaching 
hospitals. Measuring the financial impact on hospitals as a 
percentage of total base operating DRG payments accounts for 
differences in the amount of base operating DRG payments for 
hospitals with the characteristic when comparing the financial 
impact of the program on different groups of hospitals.
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4. Effects of Changes Under the FY 2023 Hospital Value-Based Purchasing 
(VBP) Program

    In section V.I. 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 and 
five healthcare-associated infection (HAI) measures, as well as to 
change the scoring and payment methodologies for the FY 2023 program 
year, such that hospitals 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 would calculate the measure 
rates for all of the measures we have selected for the FY 2023 
program year, but 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 and Safety domains. We would also 
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 2023 
discharge and would then receive a value-based incentive payment 
percentage that would 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 2023 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 2023 program year could be more 
variable than the FY 2021 TPSs due to the impacts of the COVID-19 
PHE on FY 2023 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 2021 update to the FY 2021 
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 2023 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 in their base operating DRG payment 
amount. On average, urban hospitals in the West North Central region 
and rural hospitals in the Pacific region would have the highest 
positive percentage change in the base operating DRG payment amount. 
Urban hospitals in the South Atlantic, West South Central, Mountain 
and Pacific regions, as well as rural hospitals in the New England, 
South Atlantic, West South Central and Mountain regions would have a 
negative percentage change in the base operating DRG payment amount. 
Hospitals in all other regions (both urban and rural) would 
experience an average positive percentage change in base operating 
DRG payment amounts.
    With respect to hospitals' Medicare utilization as a percent of 
inpatient days (MCR), as the MCR percent increases, the average 
percentage change in the base operating DRG payment amounts would 
generally increase, except for hospitals with over 65 percent MCR. 
As DSH percent increases, the average percentage change in the base 
operating DRG payment amounts would generally increase. On average, 
teaching hospitals would have a higher percentage change in their 
base operating DRG payment amounts compared to non-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.
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    The actual FY 2023 program year's TPSs would not be reviewed and 
corrected by hospitals until after the FY 2023 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 2023 are not 
finalized.

5. Effects of Proposed Requirements Under the HAC Reduction Program for 
FY 2023

    We are presenting the estimated impact of the FY 2023 Hospital-
Acquired Condition (HAC) Reduction Program on hospitals by hospital 
characteristic in the following two tables. The tables in this 
section present the estimated proportion of hospitals in the worst-
performing quartile of Total HAC Scores by hospital characteristic. 
Both tables later in the section include 3,067 non-Maryland 
hospitals that participate in the HAC Reduction Program. 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 tables indicate the number 
of hospitals for each characteristic that would be in the worst-
performing quartile of Total HAC Scores. The fourth column in the 
table indicates the proportion

[[Page 28723]]

of hospitals for each characteristic that would be in the worst 
performing quartile of Total HAC Scores.
    In section V.J.2.b.(2). of the preamble of this proposed rule, 
we are proposing to suppress all six measures from the HAC Reduction 
Program, calculate only measure results for the HAI measures for the 
FY 2023 program, and not calculate measure scores or Total HAC 
Scores. Accordingly, if the proposal is finalized, then no hospitals 
will be in the worst-performing quartile and no hospitals will 
receive a payment reduction in the FY 2023 HAC Reduction Program.\3\ 
In Table 1 later in the section, we are presenting the estimated 
impact of the FY 2023 HAC Reduction Program on hospitals by hospital 
characteristic if the proposal in section V.J.2.b.(2). of the 
preamble of this proposed rule is finalized and FY 2023 HAC 
Reduction Program measure scores and Total HAC scores are not 
calculated. Therefore, Table 1 illustrates the number of hospitals 
participating in the FY 2023 HAC Reduction Program by hospital 
characteristic; however, the remaining two columns reflect values of 
zero because no hospital would be in the worst-performing quartile.
---------------------------------------------------------------------------

    \3\ If this proposal is finalized, we anticipate reduced savings 
to the Medicare trust fund that is otherwise estimated at 
approximately $350 million.
---------------------------------------------------------------------------

    In Table 2 later in the section, we are presenting the estimated 
impact of the FY 2023 HAC Reduction Program on hospitals by hospital 
characteristic if the proposal in section V.J.2.b.(2). of the 
preamble of this proposed rule is not finalized. If the proposal in 
section V.J.2.b.(2). of the preamble of this proposed rule is not 
finalized, these FY 2023 HAC Reduction Program results would be 
calculated using the previously finalized HAC Reduction Program 
scoring methodology 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.
    In Table 2 later in the section, we calculate hospitals' CMS 
Patient Safety and Adverse Events Composite (CMS PSI 90) measure 
results based on Medicare fee-for-service (FFS) discharges from July 
1, 2019, to December 31, 2019, and version 11.0 of the CMS PSI 
software. Hospitals' measure results for the Centers for Disease 
Control and Prevention (CDC) Central Line-Associated Bloodstream 
Infection (CLABSI), Catheter-Associated Urinary Tract Infection 
(CAUTI), Colon and Abdominal Hysterectomy Surgical Site Infection 
(SSI), Methicillin-resistant Staphylococcus aureus (MRSA) 
bacteremia, and Clostridium difficile Infection (CDI) measures are 
derived from standardized infection ratios (SIRs) calculated with 
hospital surveillance data reported to the National Healthcare 
Safety Network (NHSN) for infections occurring between January 1, 
2019, and December 31, 2019. To analyze the results by hospital 
characteristic, we used the FY 2022 Proposed Rule Impact File.
    The hospitals indicated in the third column of Table 2 later in 
the section, would receive a payment reduction under the FY 2023 HAC 
Reduction Program if the proposal in section V.J.2.b.(2). of the 
preamble of this proposed rule is not finalized. For example, with 
regard to teaching status, as illustrated by Table 2, if the 
proposal in section V.J.2.b.(2). of the preamble of this proposed 
rule is not finalized, 426 hospitals out of 1,929 hospitals 
characterized as non-teaching hospitals would be subject to a 
payment reduction. Among teaching hospitals, 221 out of 875 
hospitals with fewer than 100 residents and 117 out of 257 hospitals 
with 100 or more residents would be subject to a payment reduction.
    The fourth column in Table 2 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 2023 HAC Reduction Program if the proposal in 
section V.J.2.b.(2). is not finalized. For example, 22.1 percent of 
the 1,929 hospitals characterized as non-teaching hospitals, 25.3 
percent of the 875 teaching hospitals with fewer than 100 residents, 
and 45.5 percent of the 257 teaching hospitals with 100 or more 
residents would be subject to a payment reduction.
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6. Effects of the Proposed Changes to IME and Direct GME Payments

a. Change to Direct GME Calculation in Response to Decision in Milton 
S. Hershey Medical Center et al. v. Azar II

    As discussed in section V.F.2. of the preamble of this proposed 
rule, we are proposing to implement a modified direct GME payment 
policy for all teaching hospitals. Specifically, effective for cost 
reporting periods beginning on or after October 1, 2001, for cost 
reports that are reopenable or open, we are proposing that if the 
hospital's unweighted number of FTE residents exceeds the FTE cap, 
and the number of weighted FTE residents also exceeds that FTE cap, 
the respective primary care and obstetrics and gynecology weighted 
FTE counts and other weighted FTE counts are adjusted to make the 
total weighted FTE count equal the FTE cap. If the number of 
weighted FTE residents does not exceed that FTE cap, then the 
allowable weighted FTE count for direct GME payment is the actual 
weighted FTE count. We have estimated the impact of this proposed 
change for FY 2023 to be $170 million.

b. Effects of the Proposal To Allow Medicare GME Affiliation Agreements 
Within Certain Rural Track FTE Limitations

    In section V.F.4. of the preamble of this proposed rule, we are 
proposing to allow urban and rural hospitals that participate in the 
same separately accredited 1-2 family medicine rural track program 
and have rural track FTE limitations to enter into ``rural track 
Medicare GME affiliation agreements'' in order to share those cap 
slots, and facilitate the cross-training of residents. In addition, 
we propose to only allow urban and rural hospitals to participate in 
rural track Medicare GME affiliated groups if they have rural track 
FTE limitations in place prior to October 1, 2022. We propose that 
eligible urban and rural hospitals may enter into rural track 
Medicare GME affiliation agreements effective with the July 1, 2023, 
academic year. Because no newly funded cap slots will be created, 
only existing funded cap slots would be shared between the 
participating affiliated hospitals, there is no financial impact to 
this proposal.

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 
2023, 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 
previous extension period). In addition, the statute provides for 
continued participation for all hospitals participating in the 
demonstration program as of December 30, 2019.
    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 
2023 is $71,955,710, which we are proposing to include in the budget 
neutrality offset adjustment for FY 2023. 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 2016 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. At this time, for the FY 2023 
proposed rule, all of the finalized cost reports are available for 
the 17 hospitals that completed cost report periods beginning in FY 
2017 under the demonstration payment methodology; these cost reports 
show the actual costs of the demonstration for this fiscal year to 
be $35,989,928. We note that the FY 2017 IPPS final rule included no 
budget neutrality offset amount for that fiscal year. The final rule 
for FY 2017 preceded the re-authorization of the demonstration under 
the Cures Act. Anticipating that the demonstration would end in 
2016, we projected no demonstration cost estimate for the upcoming 
fiscal year, FY

[[Page 28728]]

2017, while we stated that we would continue to reconcile actual 
costs when all finalized cost reports for previous fiscal years 
under the demonstration became available (81 FR 57037). Thus, 
keeping with past practice, for this proposed rule we are including 
the actual costs of the demonstration as determined from finalized 
cost reports for FY 2017 within the budget neutrality offset amount 
for this upcoming fiscal year.
    Therefore, for this FY 2023 IPPS/LTCH PPS proposed rule, the 
proposed budget neutrality offset amount for FY 2023 is based on the 
sum of two amounts:
     The amount representing the difference applicable to FY 
2023 between the sum of the estimated reasonable cost amounts that 
would be paid under the demonstration for covered inpatient services 
to the 26 hospitals participating in the fiscal year and the sum of 
the estimated amounts that would generally be paid if the 
demonstration had not been implemented. This estimated amount is 
$71,955,710.
     The amount by which the actual costs of the 
demonstration in FY 2017 (as shown by finalized cost reports from 
that fiscal year) differ from the amount determined for FY 2017. 
Since no budget neutrality offset was conducted in FY 2017, the 
amount of this difference is the actual cost amount for FY 2017, or 
$35,989,928.
    We propose to subtract the sum of these amounts ($107,945,638) 
from the national IPPS rates for FY 2023.
    We note that the total amount of the adjustment may change if 
there are any revisions prior to the final rule to the data used to 
formulate this estimate. We will also revise the budget neutrality 
offset amount in case of any re-settlement to finalized cost reports 
or changes to statutory provisions that affect the methodology for 
determining the budget neutrality estimate for the upcoming year.

8. Effects of Continued Implementation of the Frontier Community Health 
Integration Project (FCHIP) Demonstration

    In section VIIB.2. of the preamble of this proposed rule 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. Section 123 of Public Law 110-275 initially 
required a 3-year period of performance. The FCHIP Demonstration 
began on August 1, 2016, and concluded on July 31, 2019 (referred to 
in this section as the ``initial period''). Section 129 of the 
Consolidated Appropriations Act (Pub. L. 116-159) extended the FCHIP 
Demonstration by 5 years (referred to in this section as the 
``extension period'' of the demonstration). The FCHIP Demonstration 
resumed on January 1, 2022 and CAHs participating in the 
demonstration project during the extension period shall begin such 
participation in the cost reporting year that begins on or after 
January 1. Budget neutrality estimates for the demonstration 
described in the preamble of this proposed rule are based on the 
demonstration extension period.
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45323 through 45328), CMS waived certain Medicare rules for CAHs 
participating in the demonstration initial period 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 services. 
These waivers were implemented with the goal of increasing access to 
care with no net increase in costs. As we explained in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45323 through 45328), 10 CAHs were 
selected for participation in the demonstration initial period. 
Section 129 of Public Law 116-159, stipulates that only the 10 CAHs 
that participated in the initial period of the FCHIP Demonstration 
are eligible to participate during the extension period. Among the 
eligible CAHs, six elected to participate in the extension period. 
The selected CAHs are located in two states--Montana and North 
Dakota--and are implementing the three intervention services. In the 
FY 2022 IPPS/LTCH PPS final rule, CMS concluded that the initial 
period of the FCHIP Demonstration had satisfied the budget 
neutrality requirement described in section 123(g)(1)(B) of Public 
Law 110-275. Therefore, CMS did not apply a budget neutrality 
payment offset policy for the initial period of the demonstration. 
In addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), we finalized a policy to address the budget 
neutrality requirement for the demonstration initial period. We also 
discussed this policy 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), 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).
    As explained in the FY 2022 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 finalized for the demonstration 
initial period of performance in the FY 2022 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.
    For this proposed rule, CMS is proposing to adopt the same 
budget neutrality policy contingency plan used during the 
demonstration initial period to ensure that the budget neutrality 
requirement in section 123 of Public Law 110-275 is met during the 
demonstration extension period. 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 5-year 
extension period is 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.
    Under the policy finalized in the FY 2022 IPPS/LTCH PPS final 
rule, we adopted the policy finalized in the FY 2017 IPPS/LTCH PPS 
final rule, in the event the demonstration initial period was found 
not to have been budget neutral, any excess costs would be recouped 
over a period of 3 cost reporting years. For the FY 2023 proposed 
rule, we seek public comment on this proposal, as we are revising an 
aspect of the policy finalized in the FY 2022 IPPS/LTCH PPS final 
rule. Our new proposed policy is in the event the demonstration 
extension period is found not to have been budget neutral, any 
excess costs would be recouped within one fiscal year. We believe 
our new proposed policy is a more efficient timeframe for the 
government to conclude the demonstration operational requirements 
(such as analyzing claims data, cost report data and/or other data 
sources) to adjudicate the budget neutrality payment recoupment 
process due to any excess cost that occurred as result of the 
demonstration extension period. As explained in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45323 through 45328), because of the 
small scale of the demonstration, we indicated that we did not 
believe it would be feasible to implement budget neutrality for the 
demonstration initial period by reducing payments to only the 
participating CAHs. Therefore, in the event that this demonstration 
extension period is found to result in aggregate payments in excess 
of the amount that would have been paid if this demonstration 
extension period were not implemented, CMS policy is to comply with 
the budget neutrality requirement finalized in the FY 2022 IPPS/LTCH 
PPS final rule, by reducing payments to all CAHs, not just those 
participating in the demonstration extension period. 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. As we explained in the FY 2022 IPPS/LTCH PPS 
final rule, we believe 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.
    As explained in the FY 2022 IPPS/LTCH PPS final rule, we 
finalized a policy to address the demonstration budget neutrality 
methodology and analytical approach for the

[[Page 28729]]

initial period of the demonstration. Therefore, for this proposed 
rule, we propose to adopt the same budget neutrality methodology and 
analytical approach used during the demonstration initial period to 
ensure budget neutrality for 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, 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. Therefore, we are 
not proposing to apply a budget neutrality payment offset to 
payments to CAHs in FY 2023. This policy will have no impact for any 
national payment system for FY 2023.

9. Effects of Codification of the Costs Incurred for Qualified and Non-
Qualified Deferred Compensation Plans

    In section X.A. of the preamble of the proposed rule, we set 
forth our proposals to codify the costs incurred for qualified and 
non-qualified deferred compensation plans. We do not beleive that 
there are any costs associated with proposed codification of this 
policy.

10. Effects of Condition of Participation (CoP) Requirements for 
Hospitals and CAHs To Report Data Elements To Address Any Future 
Pandemics and Epidemics as Determined by the Secretary

    Section X.B. of the preamble of this proposed rule would revise 
the hospital and CAH infection prevention and control CoP 
requirements to require hospitals and CAHs, after the conclusion of 
the current COVID-19 PHE, to continue COVID-19 and seasonal 
influenza related reporting. The proposed revisions would continue 
to apply upon conclusion of the COVID-19 Public Health Emergency 
(PHE) and would continue until April 30, 2024, unless the Secretary 
establishes an earlier ending date. For COVID-19 reporting, the 
categories of data elements that this report would, to the extent as 
determined by the Secretary, include are as follows: Suspected and 
confirmed COVID-19 infections among patients and staff; total COVID-
19 deaths among patients and staff; personal protective equipment 
and testing supplies in the facility; ventilator use, capacity and 
supplies in the facility; total hospital bed and intensive care unit 
bed census and capacity; staffing shortages; COVID-19 vaccine 
administration data of patients and staff; and relevant therapeutic 
inventories and/or usage. For seasonal influenza, the categories of 
data elements that this report would, to the extent as determined by 
the Secretary, include are as follows: Confirmed influenza 
infections among patients and staff; total influenza deaths among 
patients and staff; and confirmed co-morbid influenza and COVID-19 
infections among patients and staff. We propose to require hospitals 
and CAHs to report specific data elements to the CDC's National 
Health Safety Network (NHSN), or other CDC-supported surveillance 
systems, as determined by the Secretary. Furthermore, this proposal 
would also allow for the scope and frequency of data collection to 
be reduced and limited responsive to evolving clinical and 
epidemiological circumstances. We are also proposing to require 
that, unless the Secretary specifies an alternative format by which 
a hospital (or a CAH) must report each applicable infection 
(confirmed and suspected) and the applicable vaccination data in a 
format that provides person-level information, to include medical 
record identifier, race, ethnicity, age, sex, residential county and 
zip code, and relevant comorbidities for affected patients, unless 
the Secretary specifies an alternative format by which the hospital 
(or CAH) would be required report these data elements. We are also 
proposing in this provision to limit any person-level, directly or 
potentially individually identifiable, information for affected 
patients to items outlined in this section or otherwise specified by 
the Secretary. We note that the provided information obtained in 
this surveillance system that would permit identification of any 
individual or institution is collected with a guarantee that it will 
be held in strict confidence, will be used only for the purposes 
stated, and will not otherwise be disclosed or released without the 
consent of the individual, or the institution in accordance with 
Section 304, 306, and 308(d) of the Public Health Service Act (42 
U.S.C. 242b, 242k, and 242m(d)). Reporting frequency and 
requirements would be communicated to hospitals, stakeholders, and 
the public following a model similar to that which we used to inform 
regulated entities at the beginning of the COVID-19 PHE (see QSO-21-
03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). As discussed in section XII.B. of the preamble 
of this proposed rule, Collection of Information Requirements, we 
expect a burden increase of $38,204,400 or approximately $6,162 per 
facility annually for weekly reporting. This estimate likely 
overestimates the costs associated with reporting because it assumes 
that all hospitals and CAHs will report manually. Efforts are 
underway to automate hospital and CAH reporting that have the 
potential to significantly decrease reporting burden and improve 
reliability.
    In addition, the rule proposes to establish reporting 
requirements for future PHEs related to epidemics and pandemics by 
requiring hospitals and CAHs to electronically report information on 
Acute Respiratory Illness (including, but not limited to, Seasonal 
Influenza Virus, Influenza-like Illness, and Severe Acute 
Respiratory Infection), SARS-CoV-2/COVID-19, and other viral and 
bacterial pathogens or infectious diseases of pandemic or epidemic 
potential. This collection would only occur when the Secretary has 
declared a Public Health Emergency (PHE), as defined in Sec.  
400.200, directly related to such specific pathogens and infectious 
diseases. Specifically, when the Secretary has declared a PHE, we 
propose to require hospitals and CAHs to report specific data 
elements to the CDC's National Health Safety Network (NHSN), or 
other CDC-supported surveillance systems, as determined by the 
Secretary. The proposed requirements of this section would apply to 
local, state, and national PHEs as declared by the Secretary. 
Relevant to the declared PHE, the categories of data elements that 
this report would include are as follows: Suspected and confirmed 
infections of the relevant infectious disease pathogen among 
patients and staff; total deaths attributed to the relevant 
infectious disease pathogen among patients and staff; personal 
protective equipment and other relevant supplies in the facility; 
capacity and supplies in the facility relevant to the immediate and 
long term treatment of the relevant infectious disease pathogen, 
such as ventilator and dialysis/continuous renal replacement therapy 
capacity and supplies; total hospital bed and intensive care unit 
bed census, capacity, and capability; staffing shortages; vaccine 
administration status of patients and staff for conditions monitored 
under this section and where a specific vaccine is applicable; 
relevant therapeutic inventories and/or usage; isolation capacity, 
including airborne isolation capacity; and key co-morbidities and/or 
exposure risk factors of patients being treated for the pathogen or 
disease of interest in this section that are captured with 
interoperable data standards and elements. We are also proposing to 
require that, unless the Secretary specifies an alternative format 
by which a hospital (or a CAH) must report each applicable infection 
(confirmed and suspected) and the applicable vaccination data in a 
format that provides person-level information, to include medical 
record identifier, race, ethnicity, age, sex, residential county and 
zip code, and relevant comorbidities for affected patients, unless 
the Secretary specifies an alternative format by which the hospital 
(or CAH) would be required report these data elements. We are also 
proposing in this provision to limit any person-level, directly or 
potentially individually identifiable, information for affected 
patients to items outlined in this section or otherwise specified by 
the Secretary. We note that the provided information obtained in 
this surveillance system that would permit identification of any 
individual or institution is collected with a guarantee that it will 
be held in strict confidence, will be used only for the purposes 
stated, and will not otherwise be disclosed or released without the 
consent of the individual, or the institution in accordance with 
Section 304, 306, and 308(d) of the Public Health Service Act (42 
U.S.C. 242b, 242k, and 242m(d)). Lastly, we are proposing that a 
hospital (or a CAH) would provide the information specified on a 
daily basis, unless the Secretary specifies a lesser frequency, to 
the Centers for Disease Control and Prevention's National Healthcare 
Safety Network (NHSN) or other CDC-supported surveillance systems as 
determined by the Secretary. We expect that as a result of the need 
to comply with existing COVID-19 reporting requirements, hospitals 
have already established some infrastructure to collect, maintain, 
and report data related to infectious diseases, and we anticipate 
that providers will continue to build on and maintain these systems. 
Therefore, we believe that most hospitals would need a

[[Page 28730]]

minimal amount of time to begin reporting data in the event a new 
PHE is declared. CMS will notify regulated entities stakeholders, 
and the public of the start date of necessary reporting, reporting 
frequency and other requirements via subregulatory guidance, 
following a model similar to that which we used to inform regulated 
entities at the beginning of the COVID-19 PHE (see QSO-21-03-
Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). We would also note that extensive delays would 
prevent the proposed reporting from fully serving the intended 
purposes of quickly responding to a PHE in ways that minimize health 
and safety risks. We acknowledge that there are uncertainties in 
planning for future emergencies, and CMS understands that there are 
lots of incentives and pathways to consider with regard to 
preparedness. Therefore, we are soliciting public comment on how to 
best align and incentivize preparedness, while also reducing ongoing 
burden and costs on regulated entities, and ensuring flexibility to 
quickly respond to emergencies. We are also soliciting comment on 
the burden impacts related to reporting for a specified infectious 
disease when a future PHE is declared. We also acknowledge that 
respondents may have to track and invest in infrastructure in order 
to be prepared to timely and accurately report on the specified 
frequency. Thus, respondents may face ongoing burdens associated 
with this collection even in the case of reduced frequency of 
submissions. We solicit comment on this potentiality.

I. Effects of Proposed Changes in the Capital IPPS

1. General Considerations

    For the impact analysis presented in this section, we used data 
from the December 2021 update of the FY 2021 MedPAR file and the 
December 2021 update of the Provider-Specific File (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 December 2021 update of the most recently 
available hospital cost report data 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 
proposed 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 December 2021 update of the FY 2021 MedPAR 
file, we simulated payments under the capital IPPS for FY 2022 and 
the proposed payments for FY 2023 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 2023 is as follows:
    (Standard Federal rate) x (DRG weight) x (GAF) x (COLA for 
hospitals located in Alaska and Hawaii) x (1 + DSH adjustment factor 
+ IME adjustment factor, if applicable).
    In addition to the other adjustments, hospitals may receive 
outlier payments for those cases that qualify under the threshold 
established for each fiscal year. We modeled payments for each 
hospital by multiplying the capital Federal rate by the GAF and the 
hospital's case-mix. Then we added estimated payments for indirect 
medical education, disproportionate share, and outliers, if 
applicable. For purposes of this impact analysis, the model includes 
the following assumptions:
     The capital Federal rate was updated, beginning in FY 
1996, by an analytical framework that considers changes in the 
prices associated with capital-related costs and adjustments to 
account for forecast error, changes in the case-mix index, allowable 
changes in intensity, and other factors. As discussed in section 
III.A.1. of the Addendum to this proposed rule, the proposed update 
to the capital Federal rate is 1.70 percent for FY 2023.
     In addition to the proposed FY 2023 update factor, the 
proposed FY 2023 capital Federal rate was calculated based on a 
proposed GAF/DRG budget neutrality adjustment factor of 1.0023, a 
proposed budget neutrality factor for the lowest quartile hospital 
wage index adjustment and the proposed 5 percent cap on wage index 
decreases policy of 0.9971, and a proposed outlier adjustment factor 
of 0.9445.

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 2023 on total 
capital payments per case, using a universe of 3,141 hospitals. As 
previously described, the individual hospital payment parameters are 
taken from the best available data, including the December 2021 
update of the FY 2021 MedPAR file, the December 2021 update to the 
PSF, and the most recent available cost report data from the 
December 2021 update of HCRIS. In Table III, we present a comparison 
of estimated total payments per case for FY 2022 and estimated 
proposed total payments per case for FY 2023 based on the proposed 
FY 2023 payment policies. Column 2 shows estimates of payments per 
case under our model for FY 2022. Column 3 shows estimates of 
proposed payments per case under our model for FY 2023. Column 4 
shows the proposed total percentage change in payments from FY 2022 
to FY 2023. The change represented in Column 4 includes the proposed 
1.70 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 2023 are expected to decrease 0.4 percent compared to 
capital payments per case in FY 2022. This expected decrease is 
primarily due to the proposed 1.70 percent update to the capital 
Federal rate for FY 2023 being more than offset by an expected 
decrease in capital outlier payments. As discussed in section 
III.A.2. of the Addendum to this proposed rule, we estimate for FY 
2023 that outlier payments for capital-related PPS payments would 
equal 5.55 percent of inpatient capital-related payments. Although 
in the FY 2022 IPPS/LTCH PPS final rule we estimated for FY 2022 
that outlier payments for capital-related PPS payments would equal 
5.29 percent of inpatient capital related payments, our payment 
simulation model for this proposed rule shows that for FY 2022, 
estimated outlier payments for capital-related PPS payments are 
approximately 7.5 percent of inpatient capital-related payments. 
This difference in our estimate of FY 2022 outlier payments compared 
to our estimate of FY 2023 outlier payments is reflected in the 
average change in capital payments per case in FY 2023 as compared 
to FY 2022. In addition, an estimated decrease in capital DSH 
payments due to the estimated increase in the number of hospitals 
that reclassify from urban to rural under Sec.  412.103 contributes 
to the overall expected decrease in average capital payments per 
case in FY 2023 as compared to FY 2022. We approximate that there 
are 72 hospitals classified as urban (for payment purposes) and 
receiving capital DSH payments in FY 2022, that will be classified 
as rural (for payment purposes) and will not receive capital DSH 
payments in FY 2023. Under Sec.  412.320, 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 2023 as compared to capital payments per case in FY 
2022 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 0.4 
percent decrease in capital payments per case from FY 2022 to FY 
2023 for all hospitals (as shown in Table III).
    The geographic comparison shows that, on average, hospitals in 
both urban and rural classifications would experience a decrease in 
capital IPPS payments per case in FY 2023 as compared to FY 2022. 
Capital IPPS payments per case would decrease by an estimated 0.4 
percent for hospitals in urban areas while payments to hospitals in 
rural areas would decrease by 0.3 percent in FY 2022 to FY 2023.
    The comparisons by region show that the change in capital 
payments per case from FY 2022 to FY 2023 for urban areas range from 
a 0.7 percent decrease for the New England region to a 0.6 percent 
increase for Puerto Rico. Meanwhile, the change in capital

[[Page 28731]]

payments per case from FY 2022 to FY 2023 for rural areas range from 
a 1.6 percent decrease for the Mountain rural region to a 0.6 
percent increase 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.
    The comparison by hospital type of ownership (Voluntary, 
Proprietary, and Government) shows that proprietary hospitals are 
expected to experience an increase in capital payments per case from 
FY 2022 to FY 2023 of 0.1 percent. Meanwhile, voluntary hospitals 
and government hospitals are expected to experience a decrease in 
capital payments per case from FY 2022 to FY 2023 of 0.5 percent and 
0.1 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 
2023. 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 2023, we show the proposed 
average capital payments per case for reclassified hospitals for FY 
2023. Urban reclassified hospitals are expected to experience a 
decrease in capital payments of 0.6 percent; urban nonreclassified 
hospitals are expected to experience a decrease in capital payments 
of 0.1 percent. The higher expected decrease 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 number of hospitals that 
reclassify from urban to rural under Sec.  412.103. Rural 
reclassified hospitals are expected to experience an increase in 
capital payments of 0.1 percent; rural nonreclassified hospitals are 
expected to experience a decrease in capital payments of 0.8 
percent.
BILLING CODE 4120-01-P
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[GRAPHIC] [TIFF OMITTED] TP10MY22.274

BILLING CODE 4120-01-C

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 
2023. In the preamble of this proposed rule, we specify the 
statutory authority for the provisions that are presented, identify 
the policies for FY 2023, 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 339 LTCHs included in this impact analysis. We note 
that, although there are currently approximately 346 LTCHs, for 
purposes of this impact analysis, we

[[Page 28733]]

excluded the data of all-inclusive rate providers consistent with 
the development of the FY 2023 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, 2 
of these 339 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 
2.7 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 2023.
    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. We note that section 3711(b)(2) of the CARES Act has provided 
a waiver of the application of the site neutral payment rate for 
LTCH cases admitted during the COVID-19 PHE period. At the time of 
development of this proposed rule, the COVID-19 PHE is still in 
effect. Therefore, all LTCH PPS cases up to this point in FY 2022 
have been paid the LTCH PPS standard Federal rate regardless of 
whether the discharge met the statutory patient criteria. Since the 
expiration date of the COVID-19 PHE is not yet known, for purposes 
of this impact analysis, estimates of total LTCH PPS payments for 
site neutral payment rate cases in FYs 2022 and 2023 were calculated 
using the site neutral payment rate determined under Sec.  
412.522(c) and the provisions of the CARES Act were not considered.
    Based on the best available data for the 339 LTCHs in our 
database that were considered in the analyses used for this proposed 
rule, we estimate that overall LTCH PPS payments in FY 2023 would 
increase by approximately 0.8 percent (or approximately $25 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 2021 LTCH cases that were used for the analysis 
in this proposed rule, approximately 28 percent of those cases were 
classified as site neutral payment rate cases (that is, 28 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 2023 will not 
change significantly from the most recent historical data. We 
estimate IPPS comparable per diem amounts using the prior year's 
IPPS rates and factors, updated to reflect estimated changes to the 
IPPS rates and payments proposed for FY 2023. Taking this into 
account along with other proposed changes that would apply to the 
site neutral payment rate cases in FY 2023, we estimate that 
aggregate LTCH PPS payments for these site neutral payment rate 
cases will increase by approximately 2.3 percent (or approximately 
$8 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 and payments reflected in our estimate of 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 2023 represent approximately 11 percent of 
estimated aggregate FY 2023 LTCH PPS payments.
    Based on the FY 2021 LTCH cases that were used for the analysis 
in this proposed rule, approximately 72 percent of LTCH cases will 
meet the patient-level criteria for exclusion from the site neutral 
payment rate in FY 2023, 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 2023 will increase approximately 0.7 percent (or 
approximately $18 million). This estimated increase in LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases in FY 2023 
is primarily due to the proposed 2.7 percent annual update to the 
LTCH PPS standard Federal payment rate for FY 2023 and the projected 
1.7 percent decrease in high cost outlier payments as a percentage 
of total LTCH PPS standard Federal payment rate payments, which is 
discussed later in this section.
    Based on the 339 LTCHs that were represented in the FY 2021 LTCH 
cases that were used for the analyses in this proposed rule 
presented in this Appendix, we estimate that aggregate FY 2022 LTCH 
PPS payments will be approximately $2.993 billion, as compared to 
estimated aggregate proposed FY 2023 LTCH PPS payments of 
approximately $3.018 billion, resulting in an estimated overall 
increase in LTCH PPS payments of approximately $25 million. We note 
that the estimated $25 million increase in LTCH PPS payments in FY 
2023 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 2022 is 
$44,713.67. For FY 2023, we are proposing to establish an LTCH PPS 
standard Federal payment rate of $45,952.67 which reflects the 
proposed 2.7 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 1.000691 (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 $45,057.78. 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 2.7 percent to the LTCH PPS 
standard Federal payment rate is projected to result in an increase 
of 2.6 percent in payments per discharge for LTCH PPS standard 
Federal payment rate cases from FY 2022 to FY 2023, on average, for 
all LTCHs (Column 6). The estimated increase of 2.6 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 2.6 percent.
    For FY 2023, we are proposing to update the wage index values 
based on the most recent available data (data from cost reporting 
periods beginning during FY 2019 which is the same data used for the 
proposed FY 2023 IPPS wage index). We also are proposing a labor-
related share of 68.2 percent for FY 2023, based on the most recent 
available data (IGI's fourth quarter 2021 forecast) on the relative 
importance of the labor-related share of operating and capital costs 
of the 2017-based LTCH market basket. We also are proposing to apply 
an area wage level budget neutrality factor of 1.000691 to ensure 
that the proposed changes to the area wage level adjustment would 
not result in any change in estimated aggregate LTCH PPS payments to 
LTCH PPS standard Federal payment rate cases.
    For LTCH PPS standard Federal payment rate cases, we currently 
estimate high cost outlier payments as a percentage of total LTCH 
PPS standard Federal payment rate payments will decrease from FY 
2022 to FY 2023. Based on the FY 2021 LTCH cases that were used for 
the analyses in this proposed rule, we estimate that the FY 2022 
high cost outlier threshold of $33,015 (as established in the FY 
2022 IPPS/LTCH PPS final rule) would result in estimated high cost 
outlier payments for LTCH PPS standard Federal payment rate cases in 
FY 2022 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 9.7 percent of the estimated total LTCH PPS standard 
Federal payment

[[Page 28734]]

rate payments in FY 2022. Combined with our estimate that FY 2023 
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 2023, this will result 
in an estimated decrease in high cost outlier payments as a 
percentage of total LTCH PPS standard Federal payment rate payments 
of approximately 1.7 percent between FY 2022 and FY 2023. We note 
that, in calculating these estimated high cost outlier payments, we 
inflated charges reported on the FY 2021 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 2023 by comparing estimated FY 2022 LTCH 
PPS payments to estimated FY 2023 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 0.7 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 2021 data for the 17 
rural LTCHs (out of 337 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 2023 of approximately 
$25 million. This estimated increase in payments reflects the 
projected increase in payments to LTCH PPS standard Federal payment 
rate cases of approximately $18 million and the projected increase 
in payments to site neutral payment rate cases of approximately $8 
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 2023 LTCH PPS payments (that 
is, FY 2021 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 2023, it is 
necessary to estimate payments per discharge for FY 2022 using the 
rates, factors, and the policies established in the FY 2022 IPPS/
LTCH PPS final rule and estimate payments per discharge for FY 2023 
using the proposed rates, factors, and the policies in this FY 2023 
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:
     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 2022 and 
proposed FY 2023 payments on a case-by-case basis using historical 
LTCH claims from the FY 2021 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 2021

[[Page 28735]]

MedPAR files. For modeling FY 2022 LTCH PPS payments, we used the FY 
2022 standard Federal payment rate of $44,713.67 (or $43,836.08 for 
LTCHs that failed to submit quality data as required under the 
requirements of the LTCH QRP). Similarly, for modeling payments 
based on the proposed FY 2023 LTCH PPS standard Federal payment 
rate, we used the proposed FY 2023 standard Federal payment rate of 
$45,952.67 (or $45,057.78 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 2022 LTCH PPS payments, we used the current FY 2022 
labor-related share (67.9 percent), the wage index values 
established in the Tables 12A and 12B listed in the Addendum to the 
FY 2022 IPPS/LTCH PPS final rule (which are available via the 
internet on the CMS website), the FY 2022 HCO fixed-loss amount for 
LTCH PPS standard Federal payment rate cases of $33,015 (as 
reflected in the FY 2022 IPPS/LTCH PPS final rule), and the FY 2022 
COLA factors (shown in the table in section V.C. of the Addendum to 
that final rule) to adjust the FY 2022 nonlabor-related share (32.1 
percent) for LTCHs located in Alaska and Hawaii. Similarly, for 
modeling proposed FY 2023 LTCH PPS payments, we used the proposed FY 
2023 LTCH PPS labor-related share (68.2 percent), the proposed FY 
2023 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 2023 HCO fixed-loss 
amount for LTCH PPS standard Federal payment rate cases of $44,182 
(as discussed in section V.D.3. of the Addendum to this proposed 
rule), and the proposed FY 2023 COLA factors (shown in the table in 
section V.C. of the Addendum to this proposed rule) to adjust the 
proposed FY 2023 nonlabor-related share (31.8 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 2021 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 2022 to 
FY 2023 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 2022 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 2023 
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 2022 to FY 
2023 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 2022 to FY 2023 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 2022 (Column 4) to FY 2023 (Column 5) for 
all proposed changes.
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d. Results

    Based on the FY 2021 LTCH cases (from 337 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 standard Federal payment rate cases are 
projected to increase 0.7 percent, on average, for all LTCHs from FY 
2022 to FY 2023 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 0.7 percent increase 
in LTCH PPS payments per discharge was determined by comparing 
estimated proposed FY 2023 LTCH PPS payments (using the proposed 
payment rates and factors discussed in this proposed rule) to 
estimated FY 2022 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 2023 by 2.7 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 
1.000691 (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 2.7 percent annual update to the LTCH PPS standard 
Federal payment rate is projected to result in approximately a 2.6 
percent increase in estimated payments per discharge for LTCH PPS 
standard Federal payment rate cases for all LTCHs from FY 2022 to FY 
2023. 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 2022 to FY 2023 for all 
hospitals is 0.7 percent. The projected increase for both urban and 
rural hospitals is also 0.7.

(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 44 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 experience an increase in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 of 0.9 percent and 0.4 
percent, respectively. LTCHs that began participating in the 
Medicare program between October 1983 and September 1993 are 
projected to experience an increase in estimated payments per 
discharge for LTCH PPS standard Federal payment rate cases from FY 
2022 to FY 2023 of 1.0 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 a 
decrease in estimated payments per discharge for LTCH PPS standard 
Federal payment rate cases from FY 2022 to FY 2023 of 0.4 percent.

(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 16 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, proprietary LTCHs are expected to 
experience an increase in payments to LTCH PPS standard Federal 
payment rate cases of 0.8 percent. Voluntary LTCHs are expected to 
experience a decrease in payments to LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 of 0.1 percent. 
Meanwhile, government owned and operated LTCHs are expected to 
experience no change in payments to LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023.

(4) Census Region

    The comparisons by region show that the changes in estimated 
payments per discharge for LTCH PPS standard Federal payment rate 
cases from FY 2022 to FY 2023 are projected to range from a 1.2 
percent decrease in the West North Central region to a 1.2 percent 
increase in the West South Central and Mountain regions. These 
regional variations are primarily due to the proposed changes to the 
area wage adjustment and estimated changes in outlier payments.

(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, 0.2 percent. LTCHs with 0-24 beds are 
projected to experience the largest increase in payments of 1.4 
percent. The remaining bed size categories are projected to 
experience an increase in payments in the range of 0.5 to 1.0 
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 
2023 relative to FY 2022 of approximately $25 million (or 
approximately 0.8 percent) for the 339 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 2023 relative to FY 2022 of approximately $8 million (or 
approximately 2.3 percent) for the 339 LTCHs in our database. (As 
noted previously, we estimate payments to site neutral payment rate 
cases in FY 2023 represent approximately 11 percent of total 
estimated FY 2023 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 2023 
relative to FY 2022 of approximately 25 million (or approximately 
0.8 percent) for the 339 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 Requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program

    In section IX.E. of the preamble of this proposed rule, we 
discuss our current requirements and proposals for hospitals to 
report quality data under the Hospital IQR Program to receive the 
full annual percentage

[[Page 28739]]

increase for the FY 2023 payment determination and subsequent years.
    In this proposed rule, we are proposing to adopt the following 
measures: (1) Hospital Commitment to Health Equity, beginning with 
the CY 2023 reporting period/FY 2025 payment determination; (2) 
Screening for Social Drivers of Health beginning with voluntary 
reporting in the CY 2023 reporting period and mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (3) Screen Positive Rate for Social Drivers of Health 
beginning with voluntary reporting in the CY 2023 reporting period 
and mandatory reporting beginning with the CY 2024 reporting period/
FY 2026 payment determination; (4) Cesarean Birth electronic 
clinical quality measure (eCQM) with inclusion in the measure set 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination, and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination; (5) Severe Obstetric 
Complications eCQM with inclusion in the measure set beginning with 
the CY 2023 reporting period/FY 2025 payment determination, and 
mandatory reporting beginning with the CY 2024 reporting period/FY 
2026 payment determination; (6) Hospital-Harm--Opioid-Related 
Adverse Events eCQM beginning with the CY 2024 reporting period/FY 
2026 payment determination; (7) Global Malnutrition Composite Score 
eCQM, beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (8) Hospital-Level, Risk Standardized Patient-
Reported Outcomes Performance Measure (PRO-PM) Following Elective 
Primary Total Hip Arthroplasty (THA) and/or Total Knee Arthroplasty 
(TKA), beginning with two voluntary periods followed by mandatory 
reporting beginning with the reporting period which runs from July 
1, 2025, through June 30, 2026, impacting the FY 2028 payment 
determination; (9) Medicare Spending Per Beneficiary (MSPB) Hospital 
beginning with the FY 2024 payment determination; and (10) Hospital-
Level Risk-Standardized Complications Rate (RSCR) Following Elective 
Primary THA/TKA beginning with the FY 2024 payment determination. We 
are proposing refinements to two current measures beginning with the 
FY 2024 payment determination: (1) Hospital-Level, Risk-Standardized 
Payment Associated with an Episode of Care for Primary Elective THA/
TKA; and (2) Excess Days in Acute Care (EDAC) After Hospitalization 
for Acute Myocardial Infarction (AMI). We are also proposing to: (1) 
Establish a hospital designation related to maternal care to be 
publicly-reported on a public-facing website beginning in Fall 2023, 
and are seeking comments on other potential associated activities 
regarding this designation; (2) modify our eCQM reporting and 
submission requirements whereby we are increasing the total number 
of eCQMs to be reported from four to six eCQMs beginning with the CY 
2024 reporting period/FY 2026 payment determination; (3) modify our 
case threshold exemptions and zero denominator declaration policies 
for hybrid measures as we believe they are not applicable for those 
measure types beginning with the FY 2026 payment determination; (4) 
adopt reporting and submission requirements for PRO-PMs; and (5) 
modify our eCQM validation policy to increase the reporting of 
medical requests from 75 percent of records to 100 percent of 
records beginning with the FY 2025 payment.
    As shown in the summary table in section XII.B.4. of the 
preamble of this proposed rule, we estimate a total information 
collection burden increase for 3,150 IPPS hospitals of 746,300 hours 
at a cost of $23,437,906 annually associated for our proposed 
policies and updated burden estimates across a 4-year period from 
the CY 2023 reporting period/FY 2025 payment determination through 
the CY 2026 reporting period/FY 2028 payment determination, compared 
to our currently approved information collection burden estimates.
    In section IX.E.5.a. of the preamble of this proposed rule, we 
are proposing the Hospital Commitment to Health Equity structural 
measure. In order for hospitals to receive a point for each of the 
five domains in the measure, affirmative attestations are required 
for each of the elements within a domain. For hospitals that are 
unable to attest affirmatively for an element, there are likely to 
be additional costs associated with activities such as updating 
hospital policies, engaging senior leadership, participating in new 
quality improvement activities, performing additional data analysis, 
and training staff. The extent of these costs will vary from 
hospital to hospital depending on what activities the hospital is 
already performing, hospital size, and the individual choices each 
hospital makes in order to meet the criteria necessary to attest 
affirmatively.
    In section IX.E.5.b.(1). of the preamble of this proposed rule, 
we are proposing the Screening for Social Drivers of Health measure. 
For hospitals that are not currently administering some screening 
mechanism and elect to begin doing so as a result of this policy, 
there would be some non-recurring costs associated with changes in 
workflow and information systems to collect the data. The extent of 
these costs is difficult to quantify as different hospitals may 
utilize different modes of data collection (for example paper-based, 
electronically patient-directed, clinician-facilitated, etc.). In 
addition, depending on the method of data collection utilized, the 
time required to complete the survey may add a negligible amount of 
time to patients visits.
    In section IX.E.5.g. of the preamble of this proposed rule, we 
are proposing the THA/TKA PRO-PM. For hospitals that are not 
currently collecting this data and elect to begin doing so as a 
result of this policy, there would be some non-recurring costs 
associated with changes in workflow and information systems to 
collect the data. The extent of these costs is difficult to quantify 
as different hospitals may utilize different modes of data 
collection (for example paper-based, electronically patient-
directed, clinician-facilitated, etc.). While we assume the majority 
of hospitals will report data for this measure via the HQR System, 
we assume some hospitals may elect to submit measure data via a 
third-party CMS-approved survey vendor, for which there are 
associated costs. Under OMB control number 0938-0981 for the HCAHPS 
Survey measure (expiration date September 30, 2024), an estimate of 
approximately $4,000 per hospital is used to account for these 
costs. This estimate originates from 2012, therefore, to account for 
inflation (assuming end of CY 2012 to end of CY 2021), we adjust the 
price using the Bureau of Labor Statistics Consumer Price Index and 
estimate an updated cost of approximately $4,856 ($4,000 x 121.4 
percent).\4\
---------------------------------------------------------------------------

    \4\ U.S. Bureau of Labor Statistics. Historical CPI-U data. 
Accessed on March 10, 2022. Available at: https://www.bls.gov/cpi/tables/supplemental-files/historical-cpi-u-202112.pdf.
---------------------------------------------------------------------------

    We note that in sections IX.E.5.c., IX.E.5.d., IX.E.5.e, and 
IX.E.5.f. of the preamble of this proposed rule, we are proposing to 
adopt four new 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 finalized provisions, 
we believe that costs are multifaceted and include not only the 
burden associated with reporting, but also the costs associated with 
implementing and maintaining Hospital IQR Program measures in 
hospitals' EHR systems for all of the eCQMs available for use in the 
Hospital IQR Program (83 FR 41771). Additionally, two of the four 
eCQMs are being proposed as mandatory beginning with the CY 2024 
reporting period/FY 2026 payment determination and for subsequent 
years; we account for the burden of collection of information in 
section XII.B.4. (Collection of Information) in our proposed policy 
to increase our eCQM reporting and submission requirements from four 
eCQMs to six eCQMs. Because hospitals are already reporting eCQMs, 
we do not believe there are any additional costs associated with 
increasing the number of eCQMs hospitals must report beyond the 
burden discussed in the collection of information section and the 
costs previously discussed related to adopting new eCQMs.
    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 the Hospital IQR 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 Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program

    In section IX.F. of the preamble of this proposed rule, we 
discuss our 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.F.4. of the preamble of this proposed rule, we are 
proposing to: (1) Adopt and codify a patient safety exception for 
the

[[Page 28740]]

measure removal policy; (2) begin public display of the End-of-Life 
(EOL) measures beginning with the FY 2024 program year data; and (3) 
begin public display of the 30-Day Unplanned Readmissions for Cancer 
Patients measures beginning with the FY 2024 program year data. We 
do not believe any of these provisions will result in additional 
financial impact beyond the information collection burden of 0 hours 
discussed in section XII.B.XX of the preamble of this proposed rule.

M. Effects of Requirements for the Long-Term Care Hospital Quality 
Reporting Program (LTCH QRP)

    In section IX.G. of the preamble of this proposed rule, we are 
soliciting comment on several issues but are not proposing any 
policy changes. Given that there are no costs for this provision.

N. Effects of Requirements Regarding the Medicare Promoting 
Interoperability Program

    In section IX.H. of this proposed rule, we are proposing the 
following changes for eligible hospitals and critical access 
hospitals (CAHs) that attest to CMS under the Medicare Promoting 
Interoperability Program: (1) To require and modify the Electronic 
Prescribing Objective's Query of PDMP measure while maintaining the 
associated points at 10 points beginning with the electronic health 
record (EHR) reporting period in CY 2023; (2) to expand the Query of 
Prescription Drug Monitoring Program (PDMP) measure to include 
Schedule II, III, and IV drugs beginning with the CY 2023 EHR 
reporting period; (3) to add a new Health Information Exchange (HIE) 
Objective option, the Enabling Exchange Under Trusted Exchange 
Framework and Common Agreement (TEFCA) measure (requiring a yes/no 
response) beginning with the CY 2023 EHR reporting period; (4) to 
modify the Public Health and Clinical Data Exchange Objective by 
adding an Antibiotic Use and Resistance (AUR) measure in addition to 
the current four required measures (Syndromic Surveillance 
Reporting, Immunization Registry Reporting, Electronic Case 
Reporting, and Electronic Reportable Laboratory Result Reporting) 
beginning in the CY 2023 EHR reporting period; (5) to consolidate 
the current options from three to two levels of active engagement 
for the Public Health and Clinical Data Exchange Objective and to 
require the reporting of active engagement for the measures under 
the objective beginning with the CY 2023 EHR reporting period; (6) 
to institute public reporting of certain Medicare Promoting 
Interoperability Program data beginning with the CY 2023 EHR 
reporting period; (7) to modify the scoring methodology for the 
Promoting Interoperability Program beginning in the CY 2023 
reporting period; and (8) to remove regulation text for the 
objectives and measures in the Medicare Promoting Interoperability 
Program from paragraph (e) under 42 CFR 495.24 and add new paragraph 
(f) beginning in CY 2023. We are also proposing to adopt four eCQMs: 
(1) Severe Obstetric Complications eCQM beginning with the CY 2023 
reporting period, followed by mandatory reporting beginning with the 
CY 2024 reporting period; (2) Cesarean Birth (ePC-02) eCQM beginning 
with the CY 2023 reporting period followed by mandatory reporting 
beginning with the CY 2024 reporting period; (3) Hospital-Harm--
Opioid-Related Adverse Events eCQM beginning with the CY 2024 
reporting period; and (4) Global Malnutrition Composite Score eCQM 
beginning with the CY 2024 reporting period. Lastly, we are 
proposing a modification to our eCQM reporting and submission 
requirements whereby we are increasing the total number of eCQMs to 
be reported from four to six eCQMs beginning with the CY 2024 
reporting period.
    As shown in summary table in section XII.B.9.k. of the preamble 
of this proposed rule, we estimate a total information collection 
burden increase for 4,500 eligible hospitals and CAHs of 5,513 hours 
at a cost of $233,730 annually associated with our proposed policies 
and updated burden estimates across the CY 2023 and CY 2024 EHR 
reporting periods compared to our currently approved information 
collection burden estimates. We refer readers to section XII.B.9. 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.
    In section IX.H.4. of the preamble of this proposed rule, we are 
proposing to add the Enabling Exchange Under TEFCA measure to the 
Health Information Exchange Objective. Eligible hospitals and CAHs 
currently may choose to report the two Support Electronic Referral 
Loop measures or may choose to report the HIE Bi-Directional 
Exchange measure. With the addition of this measure, eligible 
hospitals and CAHs would be able to choose to attest to Enabling 
Exchange Under TEFCA as an alternative to reporting on other 
measures in the objective. This proposal seeks to provide an 
opportunity for eligible hospitals and CAHs that are already 
voluntarily connecting to and exchanging information with the TEFCA 
network to earn credit for the Health Information Exchange 
Objective. Because attesting to this measure is voluntary and we 
assume eligible hospitals and CAHs would already be engaging in the 
activities necessary to attest ``yes'', we assume no additional 
financial impact as a result of this policy.
    In section IX.H.5.b. of the preamble of this proposed rule, we 
are proposing to adopt a new Antimicrobial Use and Resistance (AUR) 
Surveillance measure for eligible hospitals and CAHs under the 
Promoting Interoperability Program's Public Health and Clinical Data 
Exchange Objective with associated exclusions beginning in the CY 
2023 reporting period. To attest successfully, an eligible hospital 
or CAH must be in active engagement with CDC's National Healthcare 
Safety Network (NHSN) to submit AUR data and receive a report from 
NHSN indicating their successful submission of AUR data for the EHR 
reporting period. Participation in NHSN's surveillance requires the 
purchase or building of an AUR reporting solution. While thousands 
of hospitals have voluntarily done this to date, for hospitals who 
would be required to, we estimate the cost to range between $17,000 
and $388,500 annually, with a median of $187,400.\5\ We believe 
these associated costs are outweighed by the more than $4.6 billion 
in health care costs spent annually treating antibiotic resistance 
threats.\6\
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    \5\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051263/.
    \6\ https://www.cdc.gov/drugresistance/solutions-initiative/stories/partnership-estimates-healthcare-cost.html.
---------------------------------------------------------------------------

    In section IX.H.5.c. of the preamble of this proposed rule, we 
are proposing to reduce the number of active engagement options from 
three to two and combine the ``completed registration to submit 
data'' option with the ``testing'' and validation option. Because 
these options were first available in 2016 and the vast majority of 
eligible hospitals and CAHs have completed the ``completed 
registration to submit data'' option in the years since, we believe 
any financial impact associated with this proposal to be negligible. 
Regarding the proposal to allow eligible hospitals and CAHs to spend 
only one EHR reporting period at the Pre-production and Validation 
phase, because the goal for all eligible hospitals and CAHs has 
historically been to eventually be at the Validated Data Production 
option, we do not believe there is any additional financial impact 
associated with this proposal.
    In section IX.H.10.a.(2). of the preamble of this proposed rule, 
we are proposing to adopt four new 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 
finalized provisions, we believe that costs are multifaceted and 
include not only the burden associated with reporting but also the 
costs associated with implementing and maintaining program measures 
in hospitals' EHR systems for all of the eCQMs available for use in 
the Promoting Interoperability Program (83 FR 41771). Additionally, 
for two of the four eCQMs being proposed as mandatory beginning with 
the CY 2024 reporting period and for subsequent years, we account 
for the burden of collection of information in section XII.B.9.e. 
(Collection of Information) in our proposed policy to increase our 
eCQM reporting and submission requirements from four eCQMs to six 
eCQMs.

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. Proposed Use of FY 2021 Data and Proposed Methodology Modifications 
for the FY 2023 IPPS and LTCH PPS Ratesetting

    As discussed in section I.F. of the preamble of this proposed 
rule, 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.

[[Page 28741]]

The cost report data source is the Medicare hospital cost report 
data files from the most recent quarterly Healthcare Cost Report 
Information System (HCRIS) release. Our goal is always to use the 
best available data overall for ratesetting. Ordinarily, the best 
available MedPAR data is 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. Ordinarily, 
the best available cost report data is based on the cost reports 
beginning 3 fiscal years prior to the fiscal year that is the 
subject of the rulemaking.
    We also stated that given the persistence of the effects of the 
virus that causes COVID-19 in the Medicare FY 2020 data, the 
Medicare FY 2021 data, and the CDC hospitalization data, coupled 
with the expectation for future variants, we believe that it is 
reasonable to assume that some Medicare beneficiaries will continue 
to be hospitalized with COVID-19 at IPPS hospitals and LTCHs in FY 
2023. Accordingly, we believe it is appropriate to use FY 2021 data, 
as the most recent available data during the period of the COVID-19 
PHE, for purposes of the FY 2023 IPPS and LTCH PPS ratesetting. 
However, we also believe it is reasonable to assume based on the 
information available at this time that there will be fewer COVID-19 
hospitalizations in FY 2023 than in FY 2021 given the more recent 
trends in the CDC hospitalization data since the Omicron variant 
peak in January, 2022. Accordingly, because we anticipate Medicare 
inpatient hospitalizations for COVID-19 will continue in FY 2023 but 
at a lower level, we are proposing to use FY 2021 data for purposes 
of the FY 2023 IPPS and LTCH PPS ratesetting but with the following 
modifications to our usual ratesetting methodologies to account for 
the anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals and LTCHs as compared to FY 2021.
     Calculate the relative weights for FY 2023 by first 
calculating two sets of weights, one including and one excluding 
COVID-19 claims in the FY 2021 data, and then averaging the two sets 
of relative weights to determine the proposed FY 2023 relative 
weight values.
     Modify our methodologies for determining the FY 2023 
outlier fixed-loss amount for IPPS cases and LTCH PPS standard 
Federal payment rate cases to use charge inflation factors based on 
the increase in charges that occurred from FY 2018 to FY 2019, which 
is the last 1-year period prior to the COVID-19 PHE and to use CCR 
adjustment factors based on the change in CCRs that occurred between 
the March 2019 PSF and the March 2020 PSF, which is the last 1-year 
period prior to the COVID-19 PHE.
    We refer the reader to section II.E.2.c. of the preamble and 
section II.A.4.j. of the Addendum of this proposed rule for a 
complete discussion regarding these proposed modifications to our 
usual ratesetting methodologies.
    As an alternative to our proposal, we considered not making any 
of these proposed modifications to our usual methodologies for the 
calculation of the FY 2023 MS-DRG and MS-LTC-DRG relative weights or 
the usual methodologies used to determine the FY 2023 outlier fixed-
loss amount for IPPS cases and LTCH PPS standard Federal payment 
rate cases. Specifically, under this alternative approach, we 
would--
     Calculate the relative weights using our usual 
methodology for FY 2023 by including all COVID-19 claims in the FY 
2021 data with no averaging of the relative weights as calculated 
with and without the COVID-19 cases to determine the proposed FY 
2023 relative weight values; and
     Use the same data we would ordinarily use for purposes 
of this FY 2023 rulemaking to compute the charge inflation factors 
and CCR adjustment factors in determining the FY 2023 outlier fixed-
loss amount for IPPS cases and LTCH PPS standard Federal payment 
rate cases; specifically:
    ++ Charge inflation factors based on the increase in charges 
that occurred from FY 2020 to FY 2021, which is the latest full 
fiscal year period of MedPAR data available to determine the 
increase in charges.
    ++ CCR adjustment factors based on the change in CCRs that 
occurred between the December 2020 PSF and the December 2021 PSF, 
which is the latest 1-year period of the PSF to determine the 
adjustment factors to the CCRs for this proposed rule (for the final 
rule, we typically use updated PSF data to determine the CCR 
adjustment factor which for FY 2023 would be based on the change in 
CCRs that occurred between the March 2021 PSF and the March 2022 
PSF).
    We note the FY 2023 outlier fixed-loss amount would be 
significantly higher under this alternative considered.
    We further note that this alternative approach and the related 
supplemental data files reflect the application of the proposed 
permanent 10 percent cap on the reduction in a MS-DRG's relative 
weight in a given fiscal year, beginning in FY 2023, as discussed in 
section II.E.2.d. of the preamble of this proposed rule.
    In order to facilitate comments on this alternative approach as 
well as comments on our proposed modifications to our usual 
methodologies, we are making available the following files:
     MS-DRG and MS-LTC-DRG relative weighting factors and 
length of stay information calculated using the FY 2021 data without 
the proposed averaging approach described previously.
     A file with the budget neutrality and other ratesetting 
adjustments calculated under this alternative considered.
     Other proposed rule supporting data files based on this 
alternative considered that will assist in facilitating comments, 
including: The IPPS and LTCH PPS Impact Files; the AOR/BOR File; the 
Case Mix Index File; and, the Standardizing File.
    These IPPS specific files can be found on the CMS website at 
https://www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps, along with the data files and information for our 
proposed FY 2023 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 2023 LTCH PPS 
ratesetting.

P. Overall Conclusion

1. Acute Care Hospitals

    Acute care hospitals are estimated to experience a decrease of 
approximately $0.263 billion in FY 2023, including operating, 
capital, and new technology changes, as well as increased GME 
payments under our proposed changes in response to Milton S. Hershey 
Medical Center, et al. v. Becerra and payments under the proposal to 
establish a new supplemental payment for IHS/Tribal and Puerto Rico 
hospitals. The estimated change in operating payments is 
approximately $0.6 billion (discussed in section I.G. and I.H. of 
this Appendix). The estimated change in capital payments is 
approximately -$0.028 billion (discussed in section I.I. of this 
Appendix). The estimated change in new technology add-on payments is 
approximately -$0.835 billion as discussed in section I.H. of this 
Appendix. The change in new technology add-on payments reflects the 
net impact of new applications under the alternative pathways and 
continuing new technology add-on payments. Total may differ from the 
sum of the components due to rounding.
    Table I. of section I.G. of this Appendix also demonstrates the 
estimated redistributional impacts of the IPPS budget neutrality 
requirements for the proposed MS-DRG and wage index changes, and for 
the wage index reclassifications under the MGCRB.
    We estimate that hospitals would experience a 0.4 percent 
decrease in capital payments per case, as shown in Table III. of 
section I.I. of this Appendix. We project that there would be a $28 
million decrease in capital payments in FY 2023 compared to FY 2022.
    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 2023. 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 
proposed change in payments under the LTCH PPS for FY 2023. 
Accordingly, based on the best available data for the 339 LTCHs 
included in our analysis, we estimate that overall FY 2023 LTCH PPS 
payments would increase approximately $25 million relative to FY 
2022 primarily due to the proposed annual update to the LTCH PPS 
standard Federal rate.

Q. Regulatory Review Cost Estimation

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this proposed rule, we 
should estimate the cost associated with regulatory review. Due to 
the uncertainty involved with accurately quantifying the number of 
entities that will review the rule, we assume that the total number 
of unique commenters on last year's proposed rule will

[[Page 28742]]

be the number of reviewers of this proposed rule. We acknowledge 
that this assumption may understate or overstate the costs of 
reviewing this 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 these 
reasons, we believe that the number of past commenters would be a 
fair estimate of the number of reviewers of this rule. We welcome 
any comments on the approach in estimating the number of entities 
which will review this proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of this proposed rule, 
and therefore for the purposes of our estimate we assume that each 
reviewer reads approximately 50 percent of the rule. We seek 
comments on this assumption.
    Using the wage information from the BLS for medical and health 
service managers (Code 11-9111), we estimate that the cost of 
reviewing this rule is $115.22 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 23.99 hours for the staff to review half of this 
proposed or final rule. For each entity that reviews the rule, the 
estimated cost is $2,764.23 (23.99 hours x $115.22). Therefore, we 
estimate that the total cost of reviewing this regulation is 
$77,614,146 ($2,764.23 x 28,078 reviewers).

II. Accounting Statements and Tables

A. Acute Care Hospitals

    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), 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 -$0.263 billion.
[GRAPHIC] [TIFF OMITTED] TP10MY22.277

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 2023 
relative to FY 2022 of approximately $25 million based on the data 
for 339 LTCHs in our database that are subject to payment under the 
LTCH PPS. Therefore, as required by OMB Circular A-4 (available at 
https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), 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 339 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 $25 million.
[GRAPHIC] [TIFF OMITTED] TP10MY22.278

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 would have an economically significant 
impact on small entities as explained in this Appendix. Therefore, 
the Secretary has certified that this proposed rule will have a 
significant economic impact on a substantial number of small 
entities. For example, the majority of the 3,141 IPPS hospitals 
included in the impact analysis shown in ``Table I.--Impact Analysis 
of Proposed Changes to the IPPS for Operating Costs for FY 2023,'' 
on average are expected to see increases in the range of 1.4 
percent, primarily due to the proposed hospital rate update, as 
discussed in section I.G. of this

[[Page 28743]]

Appendix. On average, the proposed rate update for these hospitals 
is estimated to be 3.1 percent.
    The majority of the 339 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 2023 
(Estimated FY 2023 Payments Compared to Estimated FY 2022 
Payments)'' on average are expected to see an increase of 
approximately 0.7 percent, primarily due to the proposed 2.7 percent 
annual update to the LTCH PPS standard Federal payment rate for FY 
2023 and the projected 1.7 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 603 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 (348 hospitals) and 50-99 beds (211 
hospitals) are expected to experience a decrease in payments from FY 
2022 to FY 2023 of 0.2 percent and 0.1 percent, respectively, 
primarily driven by the proposed hospital rate update and the 
expiration of the MDH provision, 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 (17 hospitals) shown in Table IV. in section 
I.J. of this Appendix have less than 100 beds. These hospitals are 
expected to experience an increase in payments from FY 2022 to FY 
2023 of 0.7 percent, primarily due to the proposed 2.7 percent 
annual update to the LTCH PPS standard Federal payment rate for FY 
2023 and the projected 1.7 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 2022, that threshold level is approximately $165 
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 13132

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a proposed rule (and subsequent 
final rule) that imposes substantial direct requirement costs on 
state and local governments, preempts state law, or otherwise has 
federalism implications. This proposed rule would not have a 
substantial direct effect on state or local governments, preempt 
states, or otherwise have a federalism implication.

VII. 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 prior rulemaking, we have engaged in 
consultation with Tribal officials on the methodology for 
determining uncompensated care payments to IHS and Tribal hospitals. 
As discussed in section IV.D of the preamble of this proposed rule, 
we are proposing, beginning in FY 2023, to discontinue the use of 
low-income insured days as a proxy for the uncompensated care costs 
of IHS and Tribal hospitals and to begin using data on uncompensated 
care costs from Worksheet S-10 to determine uncompensated care 
payments to IHS and Tribal hospitals. In addition, as discussed in 
section IV.E of the preamble of this proposed rule, after 
considering input received from these consultations with Tribal 
officials, we are proposing to establish a new supplemental payment 
for IHS/Tribal hospitals also beginning in FY 2023 to avoid undue 
long-term financial disruption to these hospitals as a result of our 
proposal to discontinue the use of low-income insured days as a 
proxy for uncompensated care. 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 this rulemaking.

VIII. 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 2023, 
consistent with our approach for FY 2022, 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 2023

A. Proposed FY 2023 Inpatient Hospital Update

    As discussed in section IV.A. of the preamble to this proposed 
rule, for FY 2023, consistent with section 1886(b)(3)(B) of the Act, 
as amended by sections 3401(a) and 10319(a) of the Affordable Care 
Act, we are setting the applicable percentage increase by applying 
the following adjustments in the following sequence. Specifically, 
the applicable percentage increase under the IPPS is equal to the 
rate-of-increase in the hospital market basket for IPPS hospitals in 
all areas, subject to a reduction of one-quarter of the applicable 
percentage increase (prior to the application of other statutory 
adjustments; also referred to as the market basket update or rate-
of-increase (with no adjustments)) for hospitals that fail to submit 
quality information under rules established by the Secretary in 
accordance with section 1886(b)(3)(B)(viii) of the Act and a 
reduction of three-quarters of the applicable percentage increase 
(prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals not considered to be meaningful 
electronic

[[Page 28744]]

health record (EHR) users in accordance with section 
1886(b)(3)(B)(ix) of the Act, and then subject to an adjustment 
based on changes in economy-wide productivity (the productivity 
adjustment). Section 1886(b)(3)(B)(xi) of the Act, as added by 
section 3401(a) of the Affordable Care Act, states that application 
of the productivity adjustment may result in the applicable 
percentage increase being less than zero. (We note that section 
1886(b)(3)(B)(xii) of the Act required an additional reduction each 
year only for FYs 2010 through 2019.)
    We note that, in compliance with section 404 of the MMA, in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45194 through 45204), we 
replaced the 2014-based IPPS operating and capital market baskets 
with the rebased and revised 2018-based IPPS operating and capital 
market baskets beginning in FY 2022.
    In this FY 2023 IPPS/LTCH PPS proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, we are proposing to base the 
proposed FY 2023 market basket update used to determine the 
applicable percentage increase for the IPPS on IGI's fourth quarter 
2021 forecast of the 2018-based IPPS market basket rate-of-increase 
with historical data through third quarter 2021, which is estimated 
to be 3.1 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 2023 IPPS/LTCH PPS proposed 
rule, based on IGI's fourth quarter 2021 forecast, we are proposing 
a productivity adjustment of 0.4 percentage point for FY 2023. We 
are also proposing that if more recent data subsequently become 
available, we would use such data, if appropriate, to determine the 
FY 2023 market basket update and productivity adjustment for the FY 
2023 IPPS/LTCH PPS final rule.
    Therefore, based on IGI's fourth quarter 2021 forecast of the 
2018-based IPPS market basket update and the productivity 
adjustment, depending on whether a hospital submits quality data 
under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital 
that submits quality data) and is a meaningful EHR user under 
section 1886(b)(3)(B)(ix) of the Act (hereafter referred to as a 
hospital that is a meaningful EHR user), we are proposing four 
possible applicable percentage increases that could be applied to 
the standardized amount, as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TP10MY22.279

B. Proposed Update for SCHs for FY 2023

    Section 1886(b)(3)(B)(iv) of the Act provides that the FY 2023 
applicable percentage increase in the hospital-specific rate for 
SCHs 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). Therefore, under current 
law, the MDH program will expire at the end of FY 2022. We refer 
readers to section V.D. of the preamble of this proposed rule for 
further discussion of the expiration of the MDH program.
    As previously stated, the update to the hospital specific rate 
for SCHs 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.

C. Proposed FY 2023 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 2021 forecast of the 2018-based 
IPPS market basket update with historical data through third quarter 
2021, for this FY 2023 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 3.1 percent 
and a productivity adjustment of 0.4 percentage point. Therefore, 
for FY 2023, 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 2023 for Puerto Rico 
hospitals:

[[Page 28745]]

     For a Puerto Rico hospital that is a meaningful EHR 
user, we are proposing an applicable percentage increase to the FY 
2023 operating standardized amount of 2.7 percent (that is, the FY 
2023 estimate of the proposed market basket rate-of-increase of 3.1 
percent less an adjustment of 0.4 percentage point for the proposed 
productivity 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 1.15 percent (that is, the FY 2023 
estimate of the proposed market basket rate-of-increase of 3.1 
percent, less an adjustment of 1.55 percentage point (the proposed 
market basket rate-of-increase of 3.1 percent x 0.75 x (\2/3\) for 
failure to be a meaningful EHR user), and less an adjustment of 0.4 
percentage point for the proposed productivity 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 2023 market basket update and the 
productivity adjustment for the FY 2023 IPPS/LTCH PPS final rule.

D. Proposed Update for Hospitals Excluded From the IPPS for FY 2023

    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, 
religious nonmedical health care institutions (RNHCIs) are paid 
under the provisions of Sec.  413.40, which also use section 
1886(b)(3)(B)(ii) of the Act to update the percentage increase in 
the rate-of-increase limits.
    Currently, children's hospitals, PPS-excluded cancer hospitals, 
RNHCIs, and short-term acute care hospitals located in the U.S. 
Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa are among the remaining types of hospitals still paid under 
the reasonable cost methodology, subject to the rate-of-increase 
limits. In addition, in accordance with Sec.  412.526(c)(3) of the 
regulations, extended neoplastic disease care hospitals (described 
in Sec.  412.22(i) of the regulations) also are subject to the rate-
of-increase limits. As discussed in section VI. of the preamble of 
this proposed rule, 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, 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 2023 and 
subsequent fiscal years. Accordingly, for FY 2023, 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 2023 percentage increase in the 2018-based 
IPPS operating market basket. For this proposed rule, the current 
estimate of the IPPS operating market basket percentage increase for 
FY 2023 is 3.1 percent. We are proposing that if more recent data 
subsequently become available, we would use such data, if 
appropriate, to determine the FY 2023 market basket update for the 
FY 2023 IPPS/LTCH PPS final rule.

E. Proposed Update for LTCHs for FY 2023

    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 2023 by 2.7 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 productivity 
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 1.027 in determining the LTCH PPS standard Federal rate 
for FY 2023. For LTCHs that fail to submit quality data for FY 2023, 
we are proposing to establish an annual update to the LTCH PPS 
standard Federal rate of 0.7 percent (that is, the proposed annual 
update for FY 2023 of 2.7 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 1.007 in determining the LTCH PPS standard 
Federal rate for FY 2023. (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 2.7 percent for FY 
2023 does not reflect any budget neutrality factors.)

III. Secretary's Recommendations

    MedPAC is recommending inpatient hospital rates be updated by 
the amount specified in current law. 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.
    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 3.1 percent.
    For FY 2023, 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 2.7 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 0.7 percent.

IV. MedPAC Recommendation for Assessing Payment Adequacy and Updating 
Payments in Traditional Medicare

    In its March 2022 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 the amount specified in current 
law. MedPAC stated that their payment adequacy indicators are mixed 
but generally positive, and MedPAC anticipates changes caused by the 
PHE to be temporary. MedPAC anticipates that their recommendation to 
update the IPPS payment rate by the amount specified under current 
law in 2023 will be enough to maintain beneficiaries' access to 
hospital inpatient and outpatient care and keep IPPS payment rates 
close to the cost of delivering high-quality care efficiently. We 
refer readers to the March 2022 MedPAC report, which is available 
for download at www.medpac.gov, for a complete discussion on these 
recommendations.

[[Page 28746]]

    Response: With regard to MedPAC's recommendation of an update to 
the hospital inpatient rates equal to the amount specified in 
current law, section 1886(b)(3)(B) of the Act sets the requirements 
for the FY 2023 applicable percentage increase. Therefore, 
consistent with the statute, we are proposing an applicable 
percentage increase for FY 2023 of 2.7 percent, provided the 
hospital submits quality data and is a meaningful EHR user 
consistent with these statutory requirements.
    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. 2022-08268 Filed 4-18-22; 4:15 pm]
BILLING CODE 4120-01-P