[Federal Register Volume 88, Number 68 (Monday, April 10, 2023)]
[Proposed Rules]
[Pages 21316-21422]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-07137]



[[Page 21315]]

Vol. 88

Monday,

No. 68

April 10, 2023

Part III





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Parts 411, 413, 488, et al.





Medicare Program; Prospective Payment System and Consolidated Billing 
for Skilled Nursing Facilities; Updates to the Quality Reporting 
Program and Value-Based Purchasing Program for Federal Fiscal Year 
2024; Proposed Rule

  Federal Register / Vol. 88 , No. 68 / Monday, April 10, 2023 / 
Proposed Rules  

[[Page 21316]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 411, 413, 488, and 489

[CMS-1779-P]
RIN 0938-AV02


Medicare Program; Prospective Payment System and Consolidated 
Billing for Skilled Nursing Facilities; Updates to the Quality 
Reporting Program and Value-Based Purchasing Program for Federal Fiscal 
Year 2024

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 update payment rates, including 
implementing the second phase of the Patient Driven Payment Model 
(PDPM) parity adjustment recalibration. This proposed rule also 
proposes updates to the diagnosis code mappings used under PDPM, the 
SNF Quality Reporting Program (QRP), and the SNF Value-Based Purchasing 
(VBP) Program. We are also proposing to eliminate the requirement for 
facilities to actively waive their right to a hearing in writing, 
instead treating the failure to submit a timely request for a hearing 
as a constructive waiver.

DATES: To be assured consideration, comments must be received at one of 
the addresses provided below, by June 5, 2023.

ADDRESSES: In commenting, please refer to file code CMS-1779-P.
    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 submit electronic comments on this 
regulation to http://www.regulations.gov. Follow the ``Submit a 
comment'' instructions.
    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-1779-P, P.O. Box 8016, 
Baltimore, MD 21244-8016.
    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 to 
the following address ONLY: Centers for Medicare & Medicaid Services, 
Department of Health and Human Services, Attention: CMS-1779-P, Mail 
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
    For information on viewing public comments, see the beginning of 
the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: 
    [email protected] for issues related to the SNF PPS.
    Heidi Magladry, (410) 786-6034, for information related to the 
skilled nursing facility quality reporting program.
    Alexandre Laberge, (410) 786-8625, for information related to the 
skilled nursing facility value-based purchasing program.
    Lorelei Kahn, (443) 803-8643, for information related to the Civil 
Money Penalties Waiver of Hearing.

SUPPLEMENTARY INFORMATION: Inspection of Public Comments: All comments 
received before the close of the comment period are available for 
viewing by the public, including any personally identifiable or 
confidential business information that is included in a comment. We 
post all comments received before the close of the comment period on 
the following website as soon as possible after they have been 
received: http://www.regulations.gov. Follow the search instructions on 
that website to view public comments. CMS will not post on 
Regulations.gov public comments that make threats to individuals or 
institutions or suggest that the individual will take actions to harm 
the individual. CMS continues to encourage individuals not to submit 
duplicative comments. We will post acceptable comments from multiple 
unique commenters even if the content is identical or nearly identical 
to other comments.

Availability of Certain Tables Exclusively Through the Internet on the 
CMS Website

    As discussed in the FY 2014 SNF PPS final rule (78 FR 47936), 
tables setting forth the Wage Index for Urban Areas Based on CBSA Labor 
Market Areas and the Wage Index Based on CBSA Labor Market Areas for 
Rural Areas are no longer published in the Federal Register. Instead, 
these tables are available exclusively through the internet on the CMS 
website. The wage index tables for this proposed rule can be accessed 
on the SNF PPS Wage Index home page, at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.
    Readers who experience any problems accessing any of these online 
SNF PPS wage index tables should contact Kia Burwell at (410) 786-7816.
    To assist readers in referencing sections contained in this 
document, we are providing the following Table of Contents.

Table of Contents

I. Executive Summary
    A. Purpose
    B. Summary of Major Provisions
    C. Summary of Cost and Benefits
    D. Advancing Health Information Exchange
II. Background on SNF PPS
    A. Statutory Basis and Scope
    B. Initial Transition for the SNF PPS
    C. Required Annual Rate Updates
III. Proposed SNF PPS Rate Setting Methodology and FY 2024 Update
    A. Federal Base Rates
    B. SNF Market Basket Update
    C. Case-Mix Adjustment
    D. Wage Index Adjustment
    E. SNF Value-Based Purchasing Program
    F. Adjusted Rate Computation Example
IV. Additional Aspects of the SNF PPS
    A. SNF Level of Care--Administrative Presumption
    B. Consolidated Billing
    C. Payment for SNF-Level Swing-Bed Services
    D. Revisions to the Regulation Text
V. Other SNF PPS Issues
    A. Technical Updates to PDPM ICD-10 Mappings
VI. Skilled Nursing Facility Quality Reporting Program (SNF QRP)
    A. Background and Statutory Authority
    B. General Considerations Used for the Selection of Measures for 
the SNF QRP
    C. SNF QRP Quality Measure Proposals
    D. Principles for Selecting and Prioritizing SNF QRP Quality 
Measures and Concepts Under Consideration for Future Years: Request 
for Information (RFI)
    E. Health Equity Update
    F. Form, Manner, and Timing of Data Submission Under the SNF QRP
    G. Proposed Policies Regarding Public Display of Measure Data 
for the SNF QRP
VII. Skilled Nursing Facility Value-Based Purchasing Program (SNF 
VBP)
    A. Statutory Background
    B. SNF VBP Program Measures
    C. SNF VBP Performance Period and Baseline Period Proposals
    D. SNF VBP Performance Standards
    E. Proposed Changes to the SNF VBP Performance Scoring 
Methodology
    F. Proposed Update to the Extraordinary Circumstances Exception 
Policy Regulation Text
    G. Proposal to Update the Validation Process for the SNF VBP 
Program
    H. SNF Value-Based Incentive Payments for FY 2024
    I. Public Reporting on the Provider Data Catalog Website
VIII. Civil Money Penalties: Waiver of Hearing, Automatic Reduction 
of Penalty Amount
IX. Collection of Information Requirements
X. Response to Comments
XI. Economic Analyses
    A. Regulatory Impact Analysis
    B. Regulatory Flexibility Act Analysis

[[Page 21317]]

    C. Unfunded Mandates Reform Act Analysis
    D. Federalism Analysis
    E. Regulatory Review Costs

I. Executive Summary

A. Purpose

    This proposed rule would update the SNF prospective payment rates 
for fiscal year (FY) 2024, as required under section 1888(e)(4)(E) of 
the Social Security Act (the Act). It also responds to section 
1888(e)(4)(H) of the Act, which requires the Secretary to provide for 
publication of certain specified information relating to the payment 
update (see section II.C. of this proposed rule) in the Federal 
Register before the August 1 that precedes the start of each FY. In 
addition, this proposed rule includes proposals for the Skilled Nursing 
Facility Quality Reporting Program (SNF QRP) for the FY 2025, FY 2026, 
and FY 2027 program years. This proposed rule would add three new 
measures to the SNF QRP, remove three measures from the SNF QRP, and 
modify one measure in the SNF QRP. This proposed rule would also make 
policy changes to the SNF QRP, and begin public reporting of four 
measures. In addition, this proposed rule includes an update on our 
health equity efforts and requests information on principles we would 
use to select and prioritize SNF QRP quality measures in future years. 
Finally, this proposed rule includes proposals for the Skilled Nursing 
Facility Value-Based Purchasing Program (SNF VBP), including adopting 
new quality measures for the SNF VBP Program, proposing several updates 
to the Program's scoring methodology, including a Health Equity 
Adjustment, and proposing new processes to validate SNF VBP data. We 
are proposing changes to the current long-term care (LTC) facility 
requirements that would simplify and streamline the current 
requirements and thereby increase provider flexibility and reduce 
unnecessary administrative burden, while also allowing facilities to 
focus on providing healthcare to residents to meet their needs. This 
proposal was previously proposed and published in the July 18, 2019 
Federal Register in the proposed rule entitled, ``Medicare and Medicaid 
Programs; Requirements for Long-Term Care Facilities: Regulatory 
Provisions to Promote Efficiency, and Transparency'' (84 FR 34718). We 
are re-proposing this proposed revision for a facility to waive its 
hearing rights and receive a reduction in civil money penalties in an 
effort to gather additional feedback from interested parties.

B. Summary of Major Provisions

    In accordance with sections 1888(e)(4)(E)(ii)(IV) and (e)(5) of the 
Act, the Federal rates in this proposed rule would reflect an update to 
the rates that we published in the SNF PPS final rule for FY 2023 (87 
FR 47502, August 3, 2022). In addition, this proposed rule includes a 
forecast error adjustment for FY 2024 and includes the second phase of 
the PDPM parity adjustment recalibration. This proposed rule also 
proposes updates to the diagnosis code mappings used under the PDPM.
    Beginning with the FY 2025 SNF QRP, we propose to modify the COVID-
19 Vaccination Coverage among Healthcare Personnel measure, adopt the 
Discharge Function Score measure, and remove the (1) Application of 
Percent of Long-Term Care Hospital Patients with an Admission and 
Discharge Functional Assessment and a Care Plan That Addresses Function 
measure, (2) the Application of IRF Functional Outcome Measure: Change 
in Self-Care Score for Medical Rehabilitation Patients measure, and (3) 
the Application of IRF Functional Outcome Measure: Change in Mobility 
Score for Medical Rehabilitation Patients measure. Beginning with the 
FY 2026 SNF QRP, we propose to adopt the CoreQ: Short Stay Discharge 
measure and the COVID-19 Vaccine: Percent of Patients/Residents Who Are 
Up to Date measure. We also propose changes to the SNF QRP data 
completion thresholds for the Minimum Data Set (MDS) data items 
beginning with the FY 2026 SNF QRP and to make certain revisions to 
regulation text at Sec.  413.360. This proposed rule also contains 
proposals pertaining to the public reporting of the (1) Transfer of 
Health Information to the Patient-Post-Acute Care measure, (2) the 
Transfer of Health Information to the Provider-PAC measure, (3) the 
Discharge Function Score measure, and (4) the COVID-19 Vaccine: Percent 
of Patients/Residents Who Are Up to Date measure. In addition, we are 
seeking information on principles for selecting and prioritizing SNF 
QRP quality measures and concepts and provide an update on our 
continued efforts to close the health equity gap, including under the 
SNF QRP.
    We are proposing several updates for the SNF VBP Program We are 
proposing to adopt a Health Equity Adjustment that rewards top tier 
performing SNFs that serve higher proportions of SNF residents with 
dual eligibility status, effective with the FY 2027 program year and to 
adopt a variable payback percentage to maintain an estimated payback 
percentage for all SNFs of no less than 60 percent. We are proposing to 
adopt four new quality measures to the SNF VBP Program, one taking 
effect beginning with the FY 2026 program year and three taking effect 
beginning with the FY 2027 program year. We are also proposing to 
refine the Skilled Nursing Facility 30-Day Potentially Preventable 
Readmission (SNFPPR) measure specifications and update the name to the 
Skilled Nursing Facility Within-Stay Potentially Preventable 
Readmission (SNF WS PPR) measure effective with the FY 2028 program 
year. We are proposing to adopt new processes to validate SNF VBP 
program data.
    In addition, we are proposing to eliminate the requirement for 
facilities facing a civil money penalty to actively waive their right 
to a hearing in writing in order to receive a penalty reduction. We 
would create, in its place, a constructive waiver process that would 
operate by default when CMS has not received a timely request for a 
hearing. The accompanying 35 percent penalty reduction would remain. 
This proposed revision would result in lower administrative costs for 
most LTC facilities facing civil money penalties (CMPs), and would 
streamline and reduce the administrative burden for CMS. This proposal 
was previously proposed and published in the July 18, 2019 Federal 
Register.

C. Summary of Cost and Benefits

                       Table 1--Cost and Benefits
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       Provision description                Total transfers/costs
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FY 2024 SNF PPS payment rate        The overall economic impact of this
 update.                             proposed rule is an estimated
                                     increase of $1.2 billion in
                                     aggregate payments to SNFs during
                                     FY 2024.
FY 2025 SNF QRP changes...........  The overall economic impact of this
                                     proposed rule to SNFs is an
                                     estimated benefit of $1,037,261 to
                                     SNFs during FY 2025.

[[Page 21318]]

 
FY 2026 SNF QRP changes...........  The overall economic impact of this
                                     proposed rule to SNFs who would be
                                     exempt from the proposed CoreQ:
                                     Short Stay Discharge measure
                                     reporting requirements and the
                                     increase in burden from the
                                     addition of the Patient/Resident
                                     COVID-19 Vaccine measure is an
                                     estimated increase in aggregate
                                     cost from FY 2025 of $866,772.
                                    The overall economic impact of this
                                     proposed rule to SNFs who
                                     participate in the proposed CoreQ:
                                     Short Stay Discharge measure
                                     reporting requirements and the
                                     increase in burden from the
                                     addition of the Patient/Resident
                                     COVID-19 Vaccine measure is an
                                     estimated increase in aggregate
                                     cost from FY 2025 of $61,580,090.
FY 2027 SNF QRP changes...........  The overall economic impact of this
                                     proposed rule to SNFs who would be
                                     exempt from the proposed CoreQ:
                                     Short Stay Discharge measure
                                     reporting requirements is an
                                     estimated increase in aggregate
                                     cost from FY 2026 of $88,181.
                                    The overall economic impact of this
                                     proposed rule to SNFs who
                                     participate in the proposed CoreQ:
                                     Short Stay Discharge measure
                                     reporting requirements is an
                                     estimated increase in aggregate
                                     cost from FY 2026 of $63,344,417.
FY 2024 SNF VBP changes...........  The overall economic impact of the
                                     SNF VBP Program is an estimated
                                     reduction of $184.85 million in
                                     aggregate payments to SNFs during
                                     FY 2024.
FY 2026 SNF VBP changes...........  The overall economic impact of the
                                     SNF VBP Program is an estimated
                                     reduction of $196.50 million in
                                     aggregate payments to SNFs during
                                     FY 2026.
FY 2027 SNF VBP changes...........  The overall economic impact of the
                                     SNF VBP Program is an estimated
                                     reduction of $166.86 million in
                                     aggregate payments to SNFs during
                                     FY 2027.
FY 2028 SNF VBP changes...........  The overall economic impact of the
                                     SNF VBP Program is an estimated
                                     reduction of $170.98 million in
                                     aggregate payments to SNFs during
                                     FY 2028.
FY 2024 Enforcement Provisions for  The overall impact of this
 LTC Facilities Requirements         regulatory change is an estimated
 Changes.                            administrative cost savings of
                                     $2,299,716 to LTC facilities and
                                     $772,044 to the Federal Government
                                     during FY 2024.
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D. 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 interested parties 
to develop Health Level Seven International[supreg] (HL7) Fast 
Healthcare Interoperability Resource[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 the 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 communication and hearing (SPLASCH) 
pathology.\3\ We encourage PAC provider and health IT vendor 
participation as the efforts advance.
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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/.
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    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 and in the ONC Interoperability Standards 
Advisory (ISA). The 2023 ISA is available at https://www.healthit.gov/sites/isa/files/inline-files/2023%20Reference%20Edition_ISA_508.pdf.
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    \4\ Centers for Medicare & Medicaid Services. Newsroom. Fact 
sheet: CMS Data Element Library Fact Sheet. June 21, 2018. Available 
at https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet.
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    We are also working with ONC to advance the United States Core Data 
for Interoperability (USCDI), a standardized set of health data classes 
and constituent data elements for nationwide, interoperable health 
information exchange.\5\ We are collaborating with ONC and other 
Federal agencies to define and prioritize additional data 
standardization needs and develop consensus 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 has launched the USCDI+ 
initiative to support the identification and establishment of domain 
specific datasets that build on the core USCDI foundation.\6\ The 
USCDI+ quality measurement domain currently being developed aims to 
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, including the needs of programs supporting quality 
measurement for long-term and post-acute care.
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    \5\ USCDI. Available at https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
    \6\ USCDI+. Available at https://www.healthit.gov/topic/interoperability/uscdi-plus.
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    The 21st Century Cures Act (Cures Act) (Public Law 114-255, enacted 
December 13, 2016) required HHS and ONC to take steps to promote 
adoption and use of electronic health record (EHR) technology.\7\ 
Specifically, section

[[Page 21319]]

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 full network-to 
network exchange of health information nationally. On January 18, 2022, 
ONC announced a significant milestone by releasing the Trusted Exchange 
Framework \8\ and Common Agreement Version 1.\9\ The Trusted Exchange 
Framework is 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 Qualified Health Information 
Network Technical Framework Version 1 (incorporated by reference into 
the Common Agreement) 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 technical and policy architecture of how 
exchange occurs under 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.\10\ On February 13, 2023, HHS marked a new milestone during 
an event at HHS headquarters,\11\ which recognized the first set of 
applicants accepted for onboarding to the Common Agreement as Qualified 
Health Information Networks (QHINs). QHINs will be entities that will 
connect directly to each other to serve as the core for nationwide 
interoperability.\12\ For more information, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \7\ Sections 4001 through 4008 of Public Law 114-255. Available 
at https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm.
    \8\ 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.
    \9\ 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.
    \10\ 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.
    \11\ ``Building TEFCA,'' Micky Tripathi and Mariann Yeager, 
Health IT Buzz Blog. February 13, 2023. https://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/interoperability-electronic-health-and-medical-records/building-tefca.
    \12\ 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.
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    We invite providers to learn more about these important 
developments and how they are likely to affect SNFs.

II. Background on SNF PPS

A. Statutory Basis and Scope

    As amended by section 4432 of the Balanced Budget Act of 1997 (BBA 
1997) (Pub. L. 105-33, enacted August 5, 1997), section 1888(e) of the 
Act provides for the implementation of a PPS for SNFs. This methodology 
uses prospective, case-mix adjusted per diem payment rates applicable 
to all covered SNF services defined in section 1888(e)(2)(A) of the 
Act. The SNF PPS is effective for cost reporting periods beginning on 
or after July 1, 1998, and covers all costs of furnishing covered SNF 
services (routine, ancillary, and capital-related costs) other than 
costs associated with approved educational activities and bad debts. 
Under section 1888(e)(2)(A)(i) of the Act, covered SNF services include 
post-hospital extended care services for which benefits are provided 
under Part A, as well as those items and services (other than a small 
number of excluded services, such as physicians' services) for which 
payment may otherwise be made under Part B and which are furnished to 
Medicare beneficiaries who are residents in a SNF during a covered Part 
A stay. A comprehensive discussion of these provisions appears in the 
May 12, 1998 interim final rule (63 FR 26252). In addition, a detailed 
discussion of the legislative history of the SNF PPS is available 
online at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf.
    Section 215(a) of the Protecting Access to Medicare Act of 2014 
(PAMA) (Pub. L. 113-93, enacted April 1, 2014) added section 1888(g) to 
the Act requiring the Secretary to specify an all-cause all-condition 
hospital readmission measure and an all-condition risk-adjusted 
potentially preventable hospital readmission measure for the SNF 
setting. Additionally, section 215(b) of PAMA added section 1888(h) to 
the Act requiring the Secretary to implement a VBP program for SNFs. 
Finally, section 2(c)(4) of the Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 (Pub. L. 113-185, enacted October 
6, 2014) amended section 1888(e)(6) of the Act, which requires the 
Secretary to implement a QRP for SNFs under which SNFs report data on 
measures and resident assessment data. Finally, section 111 of the 
Consolidated Appropriations Act, 2021 (CAA 2021) updated section 
1888(h) of the Act, authorizing the Secretary to apply up to nine 
additional measures to the VBP program for SNFs.

B. Initial Transition for the SNF PPS

    Under sections 1888(e)(1)(A) and (e)(11) of the Act, the SNF PPS 
included an initial, three-phase transition that blended a facility-
specific rate (reflecting the individual facility's historical cost 
experience) with the Federal case-mix adjusted rate. The transition 
extended through the facility's first 3 cost reporting periods under 
the PPS, up to and including the one that began in FY 2001. Thus, the 
SNF PPS is no longer operating under the transition, as all facilities 
have been paid at the full Federal rate effective with cost reporting 
periods beginning in FY 2002. As we now base payments for SNFs entirely 
on the adjusted Federal per diem rates, we no longer include adjustment 
factors under the transition related to facility-specific rates for the 
upcoming FY.

C. Required Annual Rate Updates

    Section 1888(e)(4)(E) of the Act requires the SNF PPS payment rates 
to be updated annually. The most recent annual update occurred in a 
final rule that set forth updates to the SNF PPS payment rates for FY 
2023 (87 FR 47502, August 3, 2022).
    Section 1888(e)(4)(H) of the Act specifies that we provide for 
publication annually in the Federal Register the following:
     The unadjusted Federal per diem rates to be applied to 
days of covered SNF services furnished during the upcoming FY.

[[Page 21320]]

     The case-mix classification system to be applied for these 
services during the upcoming FY.
     The factors to be applied in making the area wage 
adjustment for these services.
    Along with other revisions discussed later in this preamble, this 
proposal would set out the required annual updates to the per diem 
payment rates for SNFs for FY 2024.

III. Proposed SNF PPS Rate Setting Methodology and FY 2024 Update

A. Federal Base Rates

    Under section 1888(e)(4) of the Act, the SNF PPS uses per diem 
Federal payment rates based on mean SNF costs in a base year (FY 1995) 
updated for inflation to the first effective period of the PPS. We 
developed the Federal payment rates using allowable costs from 
hospital-based and freestanding SNF cost reports for reporting periods 
beginning in FY 1995. The data used in developing the Federal rates 
also incorporated a Part B add-on, which is an estimate of the amounts 
that, prior to the SNF PPS, would be payable under Part B for covered 
SNF services furnished to individuals during the course of a covered 
Part A stay in a SNF.
    In developing the rates for the initial period, we updated costs to 
the first effective year of the PPS (the 15-month period beginning July 
1, 1998) using a SNF market basket, and then standardized for 
geographic variations in wages and for the costs of facility 
differences in case-mix. In compiling the database used to compute the 
Federal payment rates, we excluded those providers that received new 
provider exemptions from the routine cost limits, as well as costs 
related to payments for exceptions to the routine cost limits. Using 
the formula that the BBA 1997 prescribed, we set the Federal rates at a 
level equal to the weighted mean of freestanding costs plus 50 percent 
of the difference between the freestanding mean and weighted mean of 
all SNF costs (hospital-based and freestanding) combined. We computed 
and applied separately the payment rates for facilities located in 
urban and rural areas and adjusted the portion of the Federal rate 
attributable to wage-related costs by a wage index to reflect 
geographic variations in wages.

B. SNF Market Basket Update

1. SNF Market Basket
    Section 1888(e)(5)(A) of the Act requires us to establish a SNF 
market basket that reflects changes over time in the prices of an 
appropriate mix of goods and services included in covered SNF services. 
Accordingly, we have developed a SNF market basket that encompasses the 
most commonly used cost categories for SNF routine services, ancillary 
services, and capital-related expenses. In the SNF PPS final rule for 
FY 2018 (82 FR 36548 through 36566), we rebased and revised the SNF 
market basket, which included updating the base year from FY 2010 to 
2014. In the SNF PPS final rule for FY 2022 (86 FR 42444 through 
42463), we rebased and revised the SNF market basket, which included 
updating the base year from 2014 to 2018.
    The SNF market basket is used to compute the market basket 
percentage increase that is used to update the SNF Federal rates on an 
annual basis, as required by section 1888(e)(4)(E)(ii)(IV) of the Act. 
This market basket percentage increase is adjusted by a forecast error 
adjustment, if applicable, and then further adjusted by the application 
of a productivity adjustment as required by section 1888(e)(5)(B)(ii) 
of the Act and described in section III.B.4. of this proposed rule.
    As outlined in this proposed rule, we propose a FY 2024 SNF market 
basket percentage increase of 2.7 percent based on IHS Global Inc.'s 
(IGI's) fourth quarter 2022 forecast of the 2018-based SNF market 
basket (before application of the forecast error adjustment and 
productivity adjustment). We also propose that if more recent data 
subsequently become available (for example, a more recent estimate of 
the market basket and/or the productivity adjustment), we would use 
such data, if appropriate, to determine the FY 2024 SNF market basket 
percentage increase, labor-related share relative importance, forecast 
error adjustment, or productivity adjustment in the SNF PPS final rule.
2. Market Basket Update Factor for FY 2024
    Section 1888(e)(5)(B) of the Act defines the SNF market basket 
percentage increase as the percentage change in the SNF market basket 
from the midpoint of the previous FY to the midpoint of the current FY. 
For the Federal rates outlined in this proposed rule, we use the 
percentage change in the SNF market basket to compute the update factor 
for FY 2024. This factor is based on the FY 2024 percentage increase in 
the 2018-based SNF market basket reflecting routine, ancillary, and 
capital-related expenses. Sections 1888(e)(4)(E)(ii)(IV) and 
(e)(5)(B)(i) of the Act require that the update factor used to 
establish the FY 2024 unadjusted Federal rates be at a level equal to 
the SNF market basket percentage increase. Accordingly, we determined 
the total growth from the average market basket level for the period of 
October 1, 2022 through September 30, 2023 to the average market basket 
level for the period of October 1, 2023 through September 30, 2024. 
This process yields a percentage increase in the 2018-based SNF market 
basket of 2.7 percent.
    As further explained in section III.B.3. of this proposed rule, as 
applicable, we adjust the percentage increase by the forecast error 
adjustment from the most recently available FY for which there is final 
data and apply this adjustment whenever the difference between the 
forecasted and actual percentage increase in the market basket exceeds 
a 0.5 percentage point threshold in absolute terms. Additionally, 
section 1888(e)(5)(B)(ii) of the Act requires us to reduce the market 
basket percentage increase by the productivity adjustment (the 10-year 
moving average of changes in annual economy-wide private nonfarm 
business total factor productivity (TFP) for the period ending 
September 30, 2024) which is estimated to be 0.2 percentage point, as 
described in section III.B.4. of this proposed rule.
    We also note that section 1888(e)(6)(A)(i) of the Act provides 
that, beginning with FY 2018, SNFs that fail to submit data, as 
applicable, in accordance with sections 1888(e)(6)(B)(i)(II) and (III) 
of the Act for a fiscal year will receive a 2.0 percentage point 
reduction to their market basket update for the fiscal year involved, 
after application of section 1888(e)(5)(B)(ii) of the Act (the 
productivity adjustment) and section 1888(e)(5)(B)(iii) of the Act (the 
market basket increase). In addition, section 1888(e)(6)(A)(ii) of the 
Act states that application of the 2.0 percentage point reduction 
(after application of section 1888(e)(5)(B)(ii) and (iii) of the Act) 
may result in the market basket percentage change being less than zero 
for a fiscal year, and may result in payment rates for a fiscal year 
being less than such payment rates for the preceding fiscal year. 
Section 1888(e)(6)(A)(iii) of the Act further specifies that the 2.0 
percentage point reduction is applied in a noncumulative manner, so 
that any reduction made under section 1888(e)(6)(A)(i) of the Act 
applies only to the fiscal year involved, and that the reduction cannot 
be taken into account in computing the payment amount for a subsequent 
fiscal year.
3. Forecast Error Adjustment
    As discussed in the June 10, 2003 supplemental proposed rule (68 FR 
34768) and finalized in the August 4,

[[Page 21321]]

2003 final rule (68 FR 46057 through 46059), Sec.  413.337(d)(2) 
provides for an adjustment to account for market basket forecast error. 
The initial adjustment for market basket forecast error applied to the 
update of the FY 2003 rate for FY 2004 and took into account the 
cumulative forecast error for the period from FY 2000 through FY 2002, 
resulting in an increase of 3.26 percent to the FY 2004 update. 
Subsequent adjustments in succeeding FYs take into account the forecast 
error from the most recently available FY for which there is final data 
and apply the difference between the forecasted and actual change in 
the market basket when the difference exceeds a specified threshold. We 
originally used a 0.25 percentage point threshold for this purpose; 
however, for the reasons specified in the FY 2008 SNF PPS final rule 
(72 FR 43425), we adopted a 0.5 percentage point threshold effective 
for FY 2008 and subsequent FYs. As we stated in the final rule for FY 
2004 that first issued the market basket forecast error adjustment (68 
FR 46058), the adjustment will reflect both upward and downward 
adjustments, as appropriate.
    For FY 2022 (the most recently available FY for which there is 
final data), the forecasted or estimated increase in the SNF market 
basket was 2.7 percent, and the actual increase for FY 2022 is 6.3 
percent, resulting in the actual increase being 3.6 percentage points 
higher than the estimated increase. Accordingly, as the difference 
between the estimated and actual amount of change in the market basket 
exceeds the 0.5 percentage point threshold, under the policy previously 
described (comparing the forecasted and actual market basket percentage 
increase), the FY 2024 market basket percentage increase of 2.7 percent 
would be adjusted upward to account for the forecast error adjustment 
of 3.6 percentage points, resulting in a SNF market basket percentage 
increase of 6.3 percent, which is then reduced by the productivity 
adjustment of 0.2 percentage point, discussed in section III.B.4. of 
this proposed rule. This results in a proposed SNF market basket update 
for FY 2024 of 6.1 percent.
    Table 2 shows the forecasted and actual market basket increases for 
FY 2022.

            Table 2--Difference Between the Actual and Forecasted Market Basket Increases for FY 2022
----------------------------------------------------------------------------------------------------------------
                                                                Forecasted FY    Actual FY 2022      FY 2022
                            Index                              2022 increase *    increase **       difference
----------------------------------------------------------------------------------------------------------------
SNF..........................................................             2.7              6.3              3.6
----------------------------------------------------------------------------------------------------------------
* Published in Federal Register; based on second quarter 2021 IGI forecast (2018-based SNF market basket).
** Based on the fourth quarter 2022 IGI forecast (2018-based SNF market basket).

4. Productivity Adjustment
    Section 1888(e)(5)(B)(ii) of the Act, as added by section 3401(b) 
of the Patient Protection and Affordable Care Act (Affordable Care Act) 
(Pub. L. 111-148, enacted March 23, 2010) requires that, in FY 2012 and 
in subsequent FYs, the market basket percentage under the SNF payment 
system (as described in section 1888(e)(5)(B)(i) of the Act) is to be 
reduced annually by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act. Section 1886(b)(3)(B)(xi)(II) of the 
Act, in turn, defines the productivity adjustment to be equal to the 
10-year moving average of changes in annual economy-wide, private 
nonfarm business multifactor productivity (MFP) (as projected by the 
Secretary for the 10-year period ending with the applicable FY, year, 
cost-reporting period, or other annual period).
    The U.S. Department of Labor's Bureau of Labor Statistics (BLS) 
publishes the official measure of productivity for the U.S. We note 
that previously the productivity measure referenced at section 
1886(b)(3)(B)(xi)(II) of the Act was published by BLS as private 
nonfarm business multifactor productivity. Beginning with the November 
18, 2021 release of productivity data, BLS replaced the term MFP with 
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) of the 
Act is now published by BLS as private nonfarm business total factor 
productivity. We refer readers to the BLS website at www.bls.gov for 
the BLS historical published TFP data. A complete description of the 
TFP projection methodology is available on our website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch. In addition, in 
the FY 2022 SNF final rule (86 FR 42429) we noted that, effective with 
FY 2022 and forward, we changed the name of this adjustment to refer to 
it as the ``productivity adjustment,'' rather than the ``MFP 
adjustment.''
    Per section 1888(e)(5)(A) of the Act, the Secretary shall establish 
a SNF market basket that reflects changes over time in the prices of an 
appropriate mix of goods and services included in covered SNF services. 
Section 1888(e)(5)(B)(ii) of the Act, added by section 3401(b) of the 
Affordable Care Act, requires that for FY 2012 and each subsequent FY, 
after determining the market basket percentage described in section 
1888(e)(5)(B)(i) of the Act, the Secretary shall reduce such percentage 
by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act. Section 1888(e)(5)(B)(ii) of the Act 
further states that the reduction of the market basket percentage by 
the productivity adjustment may result in the market basket percentage 
being less than zero for a FY and may result in payment rates under 
section 1888(e) of the Act being less than such payment rates for the 
preceding fiscal year. Thus, if the application of the productivity 
adjustment to the market basket percentage calculated under section 
1888(e)(5)(B)(i) of the Act results in a productivity-adjusted market 
basket percentage that is less than zero, then the annual update to the 
unadjusted Federal per diem rates under section 1888(e)(4)(E)(ii) of 
the Act would be negative, and such rates would decrease relative to 
the prior FY.
    Based on the data available for this FY 2024 SNF PPS proposed rule, 
the current proposed productivity adjustment (the 10-year moving 
average of changes in annual economy-wide private nonfarm business TFP 
for the period ending September 30, 2024) is projected to be 0.2 
percentage point.
    Consistent with section 1888(e)(5)(B)(i) of the Act and Sec.  
413.337(d)(2), and as discussed previously in section III.B.1. of this 
proposed rule, the proposed market basket percentage for FY 2024 for 
the SNF PPS is based on IGI's fourth quarter 2022 forecast of the SNF 
market basket percentage, which is estimated to be 2.7 percent. This 
market basket percentage

[[Page 21322]]

is then increased by 3.6 percentage points, due to application of the 
forecast error adjustment discussed earlier in section III.B.3. of this 
proposed rule. Finally, as discussed earlier in section III.B.4. of 
this proposed rule, we are applying a proposed 0.2 percentage point 
productivity adjustment to the FY 2024 SNF market basket percentage. 
Therefore, the resulting proposed productivity-adjusted FY 2024 SNF 
market basket update is equal to 6.1 percent, which reflects a market 
basket percentage increase of 2.7 percent, plus the 3.6 percentage 
points forecast error adjustment, and less the 0.2 percentage point to 
account for the productivity adjustment. Thus, we propose to apply a 
net SNF market basket update factor of 6.1 percent in our determination 
of the FY 2024 SNF PPS unadjusted Federal per diem rates.
5. Unadjusted Federal Per Diem Rates for FY 2024
    As discussed in the FY 2019 SNF PPS final rule (83 FR 39162), in FY 
2020 we implemented a new case-mix classification system to classify 
SNF patients under the SNF PPS, the PDPM. As discussed in section 
V.B.1. of that final rule (83 FR 39189), under PDPM, the unadjusted 
Federal per diem rates are divided into six components, five of which 
are case-mix adjusted components (Physical Therapy (PT), Occupational 
Therapy (OT), Speech-Language Pathology (SLP), Nursing, and Non-Therapy 
Ancillaries (NTA)), and one of which is a non-case-mix component, as 
existed under the previous RUG-IV model. We propose to use the SNF 
market basket, adjusted as described previously in sections III.B.1. 
through III.B.4. of this proposed rule, to adjust each per diem 
component of the Federal rates forward to reflect the change in the 
average prices for FY 2024 from the average prices for FY 2023. We also 
propose to further adjust the rates by a wage index budget neutrality 
factor, described later in section III.D. of this proposed rule.
    Further, in the past, we used the revised Office of Management and 
Budget (OMB) delineations adopted in the FY 2015 SNF PPS final rule (79 
FR 45632, 45634), with updates as reflected in OMB Bulletin Nos. 15-01 
and 17-01, to identify a facility's urban or rural status for the 
purpose of determining which set of rate tables would apply to the 
facility. As discussed in the FY 2021 SNF PPS proposed and final rules, 
we adopted the revised OMB delineations identified in OMB Bulletin No. 
18-04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status 
effective beginning with FY 2021.
    Tables 3 and 4 reflect the updated unadjusted Federal rates for FY 
2024, prior to adjustment for case-mix.

                                                Table 3--FY 2024 Unadjusted Federal Rate Per Diem--URBAN
--------------------------------------------------------------------------------------------------------------------------------------------------------
                  Rate component                           PT               OT              SLP            Nursing            NTA          Non-case-mix
--------------------------------------------------------------------------------------------------------------------------------------------------------
Per Diem Amount...................................          $70.08           $65.23           $26.16          $122.15           $92.16          $109.39
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                                Table 4--FY 2024 Unadjusted Federal Rate Per Diem--RURAL
--------------------------------------------------------------------------------------------------------------------------------------------------------
                  Rate component                           PT               OT              SLP            Nursing            NTA          Non-case-mix
--------------------------------------------------------------------------------------------------------------------------------------------------------
Per Diem Amount...................................          $79.88           $73.36           $32.96          $116.71           $88.05          $111.41
--------------------------------------------------------------------------------------------------------------------------------------------------------

C. Case-Mix Adjustment

    Under section 1888(e)(4)(G)(i) of the Act, the Federal rate also 
incorporates an adjustment to account for facility case-mix, using a 
classification system that accounts for the relative resource 
utilization of different patient types. The statute specifies that the 
adjustment is to reflect both a resident classification system that the 
Secretary establishes to account for the relative resource use of 
different patient types, as well as resident assessment data and other 
data that the Secretary considers appropriate. In the FY 2019 final 
rule (83 FR 39162, August 8, 2018), we finalized a new case-mix 
classification model, the PDPM, which took effect beginning October 1, 
2019. The previous RUG-IV model classified most patients into a therapy 
payment group and primarily used the volume of therapy services 
provided to the patient as the basis for payment classification, thus 
creating an incentive for SNFs to furnish therapy regardless of the 
individual patient's unique characteristics, goals, or needs. PDPM 
eliminates this incentive and improves the overall accuracy and 
appropriateness of SNF payments by classifying patients into payment 
groups based on specific, data-driven patient characteristics, while 
simultaneously reducing the administrative burden on SNFs.
    The PDPM uses clinical data from the MDS to assign case-mix 
classifiers to each patient that are then used to calculate a per diem 
payment under the SNF PPS, consistent with the provisions of section 
1888(e)(4)(G)(i) of the Act. As discussed in section IV.A. of this 
proposed rule, the clinical orientation of the case-mix classification 
system supports the SNF PPS's use of an administrative presumption that 
considers a beneficiary's initial case-mix classification to assist in 
making certain SNF level of care determinations. Further, because the 
MDS is used as a basis for payment, as well as a clinical assessment, 
we have provided extensive training on proper coding and the timeframes 
for MDS completion in our Resident Assessment Instrument (RAI) Manual. 
As we have stated in prior rules, for an MDS to be considered valid for 
use in determining payment, the MDS assessment should be completed in 
compliance with the instructions in the RAI Manual in effect at the 
time the assessment is completed. For payment and quality monitoring 
purposes, the RAI Manual consists of both the Manual instructions and 
the interpretive guidance and policy clarifications posted on the 
appropriate MDS website at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/MDS30RAIManual.html.
    Under section 1888(e)(4)(H) of the Act, each update of the payment 
rates must include the case-mix classification methodology applicable 
for the upcoming FY. The FY 2024 payment rates set forth in this 
proposed rule reflect the use of the PDPM case-mix classification 
system from October 1, 2023, through September 30, 2024. The case-mix 
adjusted PDPM payment rates for FY 2024 are listed separately for urban 
and rural SNFs, in Tables 5 and 6 with corresponding case-mix values.

[[Page 21323]]

    Given the differences between the previous RUG-IV model and PDPM in 
terms of patient classification and billing, it was important that the 
format of Tables 5 and 6 reflect these differences. More specifically, 
under both RUG-IV and PDPM, providers use a Health Insurance 
Prospective Payment System (HIPPS) code on a claim to bill for covered 
SNF services. Under RUG-IV, the HIPPS code included the three-character 
RUG-IV group into which the patient classified, as well as a two-
character assessment indicator code that represented the assessment 
used to generate this code. Under PDPM, while providers still use a 
HIPPS code, the characters in that code represent different things. For 
example, the first character represents the PT and OT group into which 
the patient classifies. If the patient is classified into the PT and OT 
group ``TA'', then the first character in the patient's HIPPS code 
would be an A. Similarly, if the patient is classified into the SLP 
group ``SB'', then the second character in the patient's HIPPS code 
would be a B. The third character represents the Nursing group into 
which the patient classifies. The fourth character represents the NTA 
group into which the patient classifies. Finally, the fifth character 
represents the assessment used to generate the HIPPS code.
    Tables 5 and 6 reflect the PDPM's structure. Accordingly, Column 1 
of Tables 5 and 6 represents the character in the HIPPS code associated 
with a given PDPM component. Columns 2 and 3 provide the case-mix index 
and associated case-mix adjusted component rate, respectively, for the 
relevant PT group. Columns 4 and 5 provide the case-mix index and 
associated case-mix adjusted component rate, respectively, for the 
relevant OT group. Columns 6 and 7 provide the case-mix index and 
associated case-mix adjusted component rate, respectively, for the 
relevant SLP group. Column 8 provides the nursing case-mix group (CMG) 
that is connected with a given PDPM HIPPS character. For example, if 
the patient qualified for the nursing group CBC1, then the third 
character in the patient's HIPPS code would be a ``P.'' Columns 9 and 
10 provide the case-mix index and associated case-mix adjusted 
component rate, respectively, for the relevant nursing group. Finally, 
columns 11 and 12 provide the case-mix index and associated case-mix 
adjusted component rate, respectively, for the relevant NTA group.
    Tables 5 and 6 do not reflect adjustments which may be made to the 
SNF PPS rates as a result of the SNF VBP Program, discussed in section 
VII. of this proposed rule, or other adjustments, such as the variable 
per diem adjustment. Further, in the past, we used the revised OMB 
delineations adopted in the FY 2015 SNF PPS final rule (79 FR 45632, 
45634), with updates as reflected in OMB Bulletin Nos, 15-01 and 17-01, 
to identify a facility's urban or rural status for the purpose of 
determining which set of rate tables would apply to the facility. As 
discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we adopted 
the revised OMB delineations identified in OMB Bulletin No. 18-04 
(available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) to identify a facility's urban or rural status 
effective beginning with FY 2021.
    In the FY 2023 SNF PPS final rule (87 FR 47502), we finalized a 
proposal to recalibrate the PDPM parity adjustment over 2 years 
starting in FY 2023, which means that, for each of the PDPM case-mix 
adjusted components, we lowered the PDPM parity adjustment factor from 
46 percent to 42 percent in FY 2023 and we would further lower the PDPM 
parity adjustment factor from 42 percent to 38 percent in FY 2024. 
Following this methodology, which is further described in the FY 2023 
SNF PPS final rule (87 FR 47525 through 47534), Tables 5 and 6 
incorporate the second phase of the PDPM parity adjustment 
recalibration.

                                                           Table 5--PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--URBAN
                                                                         [Including the parity adjustment recalibration]
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                                       Nursing    Nursing
                   PDPM group                      PT CMI    PT rate     OT CMI    OT rate    SLP CMI    SLP rate             Nursing CMG                CMI        rate     NTA CMI    NTA rate
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
A..............................................       1.45    $101.62       1.41     $91.97       0.64     $16.74  ES3..............................       3.84    $469.06       3.06    $282.01
B..............................................       1.61     112.83       1.54     100.45       1.72      45.00  ES2..............................       2.90     354.24       2.39     220.26
C..............................................       1.78     124.74       1.60     104.37       2.52      65.92  ES1..............................       2.77     338.36       1.74     160.36
D..............................................       1.81     126.84       1.45      94.58       1.38      36.10  HDE2.............................       2.27     277.28       1.26     116.12
E..............................................       1.34      93.91       1.33      86.76       2.21      57.81  HDE1.............................       1.88     229.64       0.91      83.87
F..............................................       1.52     106.52       1.51      98.50       2.82      73.77  HBC2.............................       2.12     258.96       0.68      62.67
G..............................................       1.58     110.73       1.55     101.11       1.93      50.49  HBC1.............................       1.76     214.98  .........  .........
H..............................................       1.10      77.09       1.09      71.10        2.7      70.63  LDE2.............................       1.97     240.64  .........  .........
I..............................................       1.07      74.99       1.12      73.06       3.34      87.37  LDE1.............................       1.64     200.33  .........  .........
J..............................................       1.34      93.91       1.37      89.37       2.83      74.03  LBC2.............................       1.63     199.10  .........  .........
K..............................................       1.44     100.92       1.46      95.24        3.5      91.56  LBC1.............................       1.35     164.90  .........  .........
L..............................................       1.03      72.18       1.05      68.49       3.98     104.12  CDE2.............................       1.77     216.21  .........  .........
M..............................................       1.20      84.10       1.23      80.23  .........  .........  CDE1.............................       1.53     186.89  .........  .........
N..............................................       1.40      98.11       1.42      92.63  .........  .........  CBC2.............................       1.47     179.56  .........  .........
O..............................................       1.47     103.02       1.47      95.89  .........  .........  CA2..............................       1.03     125.81  .........  .........
P..............................................       1.02      71.48       1.03      67.19  .........  .........  CBC1.............................       1.27     155.13  .........  .........
Q..............................................  .........  .........  .........  .........  .........  .........  CA1..............................       0.89     108.71  .........  .........
R..............................................  .........  .........  .........  .........  .........  .........  BAB2.............................       0.98     119.71  .........  .........
S..............................................  .........  .........  .........  .........  .........  .........  BAB1.............................       0.94     114.82  .........  .........
T..............................................  .........  .........  .........  .........  .........  .........  PDE2.............................       1.48     180.78  .........  .........
U..............................................  .........  .........  .........  .........  .........  .........  PDE1.............................       1.39     169.79  .........  .........
V..............................................  .........  .........  .........  .........  .........  .........  PBC2.............................       1.15     140.47  .........  .........
W..............................................  .........  .........  .........  .........  .........  .........  PA2..............................       0.67      81.84  .........  .........
X..............................................  .........  .........  .........  .........  .........  .........  PBC1.............................       1.07     130.70  .........  .........
Y..............................................  .........  .........  .........  .........  .........  .........  PA1..............................       0.62      75.73  .........  .........
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------


                                                           Table 6--PDPM Case-Mix Adjusted Federal Rates and Associated Indexes--RURAL
                                                                         [Including the parity adjustment recalibration]
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                                       Nursing    Nursing
                   PDPM group                      PT CMI    PT rate     OT CMI    OT rate    SLP CMI    SLP rate             Nursing CMG                CMI        rate     NTA CMI    NTA rate
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
A..............................................       1.45    $115.83       1.41    $103.44       0.64     $21.09  ES3..............................       3.84    $448.17       3.06    $269.43

[[Page 21324]]

 
B..............................................       1.61     128.61       1.54     112.97       1.72      56.69  ES2..............................       2.90     338.46       2.39     210.44
C..............................................       1.78     142.19       1.60     117.38       2.52      83.06  ES1..............................       2.77     323.29       1.74     153.21
D..............................................       1.81     144.58       1.45     106.37       1.38      45.48  HDE2.............................       2.27     264.93       1.26     110.94
E..............................................       1.34     107.04       1.33      97.57       2.21      72.84  HDE1.............................       1.88     219.41       0.91      80.13
F..............................................       1.52     121.42       1.51     110.77       2.82      92.95  HBC2.............................       2.12     247.43       0.68      59.87
G..............................................       1.58     126.21       1.55     113.71       1.93      63.61  HBC1.............................       1.76     205.41  .........  .........
H..............................................       1.10      87.87       1.09      79.96        2.7      88.99  LDE2.............................       1.97     229.92  .........  .........
I..............................................       1.07      85.47       1.12      82.16       3.34     110.09  LDE1.............................       1.64     191.40  .........  .........
J..............................................       1.34     107.04       1.37     100.50       2.83      93.28  LBC2.............................       1.63     190.24  .........  .........
K..............................................       1.44     115.03       1.46     107.11        3.5     115.36  LBC1.............................       1.35     157.56  .........  .........
L..............................................       1.03      82.28       1.05      77.03       3.98     131.18  CDE2.............................       1.77     206.58  .........  .........
M..............................................       1.20      95.86       1.23      90.23  .........  .........  CDE1.............................       1.53     178.57  .........  .........
N..............................................       1.40     111.83       1.42     104.17  .........  .........  CBC2.............................       1.47     171.56  .........  .........
O..............................................       1.47     117.42       1.47     107.84  .........  .........  CA2..............................       1.03     120.21  .........  .........
P..............................................       1.02      81.48       1.03      75.56  .........  .........  CBC1.............................       1.27     148.22  .........  .........
Q..............................................  .........  .........  .........  .........  .........  .........  CA1..............................       0.89     103.87  .........  .........
R..............................................  .........  .........  .........  .........  .........  .........  BAB2.............................       0.98     114.38  .........  .........
S..............................................  .........  .........  .........  .........  .........  .........  BAB1.............................       0.94     109.71  .........  .........
T..............................................  .........  .........  .........  .........  .........  .........  PDE2.............................       1.48     172.73  .........  .........
U..............................................  .........  .........  .........  .........  .........  .........  PDE1.............................       1.39     162.23  .........  .........
V..............................................  .........  .........  .........  .........  .........  .........  PBC2.............................       1.15     134.22  .........  .........
W..............................................  .........  .........  .........  .........  .........  .........  PA2..............................       0.67      78.20  .........  .........
X..............................................  .........  .........  .........  .........  .........  .........  PBC1.............................       1.07     124.88  .........  .........
Y..............................................  .........  .........  .........  .........  .........  .........  PA1..............................       0.62      72.36  .........  .........
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

D. Wage Index Adjustment

    Section 1888(e)(4)(G)(ii) of the Act requires that we adjust the 
Federal rates to account for differences in area wage levels, using a 
wage index that the Secretary determines appropriate. Since the 
inception of the SNF PPS, we have used hospital inpatient wage data in 
developing a wage index to be applied to SNFs. We propose to continue 
this practice for FY 2024, as we continue to believe that in the 
absence of SNF-specific wage data, using the hospital inpatient wage 
index data is appropriate and reasonable for the SNF PPS. As explained 
in the update notice for FY 2005 (69 FR 45786), the SNF PPS does not 
use the hospital area wage index's occupational mix adjustment, as this 
adjustment serves specifically to define the occupational categories 
more clearly in a hospital setting; moreover, the collection of the 
occupational wage data under the inpatient prospective payment system 
(IPPS) also excludes any wage data related to SNFs. Therefore, we 
believe that using the updated wage data exclusive of the occupational 
mix adjustment continues to be appropriate for SNF payments. As in 
previous years, we would continue to use the pre-reclassified IPPS 
hospital wage data, without applying the occupational mix, rural floor, 
or outmigration adjustment, as the basis for the SNF PPS wage index. 
For FY 2024, the updated wage data are for hospital cost reporting 
periods beginning on or after October 1, 2019 and before October 1, 
2020 (FY 2020 cost report data).
    We note that section 315 of the Medicare, Medicaid, and SCHIP 
Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-
554, enacted December 21, 2000) gave the Secretary the discretion to 
establish a geographic reclassification procedure specific to SNFs, but 
only after collecting the data necessary to establish a SNF PPS wage 
index that is based on wage data from nursing homes. To date, this has 
proven to be unfeasible due to the volatility of existing SNF wage data 
and the significant amount of resources that would be required to 
improve the quality of the data. More specifically, auditing all SNF 
cost reports, similar to the process used to audit inpatient hospital 
cost reports for purposes of the IPPS wage index, would place a burden 
on providers in terms of recordkeeping and completion of the cost 
report worksheet. Adopting such an approach would require a significant 
commitment of resources by CMS and the Medicare Administrative 
Contractors, potentially far in excess of those required under the 
IPPS, given that there are nearly five times as many SNFs as there are 
inpatient hospitals. While we continue to believe that the development 
of such an audit process could improve SNF cost reports in such a 
manner as to permit us to establish a SNF-specific wage index, we do 
not believe this undertaking is feasible at this time.
    In addition, we propose to continue to use the same methodology 
discussed in the SNF PPS final rule for FY 2008 (72 FR 43423) to 
address those geographic areas in which there are no hospitals, and 
thus, no hospital wage index data on which to base the calculation of 
the FY 2022 SNF PPS wage index. For rural geographic areas that do not 
have hospitals and, therefore, lack hospital wage data on which to base 
an area wage adjustment, we propose to continue using the average wage 
index from all contiguous Core-Based Statistical Areas (CBSAs) as a 
reasonable proxy. For FY 2024, there are no rural geographic areas that 
do not have hospitals, and thus, this methodology will not be applied. 
For rural Puerto Rico, we propose not to apply this methodology due to 
the distinct economic circumstances there; due to the close proximity 
of almost all of Puerto Rico's various urban and non-urban areas, this 
methodology would produce a wage index for rural Puerto Rico that is 
higher than that in half of its urban areas. Instead, we would continue 
using the most recent wage index previously available for that area. 
For urban areas without specific hospital wage index data, we propose 
to continue using the average wage indexes of all urban areas within 
the State to serve as a reasonable proxy for the wage index of that 
urban CBSA. For FY 2024, the only urban area without wage index data 
available is CBSA 25980, Hinesville-Fort Stewart, GA.
    In the SNF PPS final rule for FY 2006 (70 FR 45026, August 4, 
2005), we adopted the changes discussed in OMB Bulletin No. 03-04 (June 
6, 2003), which announced revised definitions for MSAs and the creation 
of micropolitan statistical areas and combined statistical areas. In 
adopting the CBSA geographic designations, we

[[Page 21325]]

provided for a 1-year transition in FY 2006 with a blended wage index 
for all providers. For FY 2006, the wage index for each provider 
consisted of a blend of 50 percent of the FY 2006 MSA-based wage index 
and 50 percent of the FY 2006 CBSA-based wage index (both using FY 2002 
hospital data). We referred to the blended wage index as the FY 2006 
SNF PPS transition wage index. As discussed in the SNF PPS final rule 
for FY 2006 (70 FR 45041), after the expiration of this 1-year 
transition on September 30, 2006, we used the full CBSA-based wage 
index values.
    In the FY 2015 SNF PPS final rule (79 FR 45644 through 45646), we 
finalized changes to the SNF PPS wage index based on the newest OMB 
delineations, as described in OMB Bulletin No. 13-01, beginning in FY 
2015, including a 1-year transition with a blended wage index for FY 
2015. 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). 
Subsequently, on July 15, 2015, OMB issued OMB Bulletin No. 15-01, 
which provided minor 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 and were 
adopted under the SNF PPS in the FY 2017 SNF PPS final rule (81 FR 
51983, August 5, 2016). In addition, on August 15, 2017, OMB issued 
Bulletin No. 17-01 which announced a new urban CBSA, Twin Falls, Idaho 
(CBSA 46300) which was adopted in the SNF PPS final rule for FY 2019 
(83 FR 39173, August 8, 2018).
    As discussed in the FY 2021 SNF PPS final rule (85 FR 47594), we 
adopted the revised OMB delineations identified in OMB Bulletin No. 18-
04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) beginning October 1, 2020, including a 1-year 
transition for FY 2021 under which we applied a 5 percent cap on any 
decrease in a hospital's wage index compared to its wage index for the 
prior fiscal year (FY 2020). The updated OMB delineations more 
accurately reflect the contemporary urban and rural nature of areas 
across the country, and the use of such delineations allows us to 
determine more accurately the appropriate wage index and rate tables to 
apply under the SNF PPS.
    In the FY 2023 SNF PPS final rule (87 FR 47521 through 47525), we 
finalized a policy to apply a permanent 5 percent cap on any decreases 
to a provider's wage index from its wage index in the prior year, 
regardless of the circumstances causing the decline. Additionally, we 
finalized a policy that a new SNF would be paid the wage index for the 
area in which it is geographically located for its first full or 
partial FY with no cap applied because a new SNF would not have a wage 
index in the prior FY. We amended the SNF PPS regulations at 42 CFR 
413.337(b)(4)(ii) to reflect this permanent cap on wage index 
decreases. A full discussion of the adoption of this policy is found in 
the FY 2023 SNF PPS final rule.
    As we previously stated in the FY 2008 SNF PPS proposed and final 
rules (72 FR 25538 through 25539, and 72 FR 43423), this and all 
subsequent SNF PPS rules and notices are considered to incorporate any 
updates and revisions set forth in the most recent OMB bulletin that 
applies to the hospital wage data used to determine the current SNF PPS 
wage index. OMB issued further revised CBSA delineations in OMB 
Bulletin No. 20-01, on March 6, 2020 (available on the web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). 
However, we determined that the changes in OMB Bulletin No. 20-01 do 
not impact the CBSA-based labor market area delineations adopted in FY 
2021. Therefore, CMS did not propose to adopt the revised OMB 
delineations identified in OMB Bulletin No. 20 01 for FY 2022 or 2023, 
and for these reasons CMS is likewise not making such a proposal for FY 
2024.The wage index applicable to FY 2024 is set forth in Tables A and 
B available on the CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html.
    Once calculated, we would apply the wage index adjustment to the 
labor-related portion of the Federal rate. Each year, we calculate a 
labor-related share, based on the relative importance of labor-related 
cost categories (that is, those cost categories that are labor-
intensive and vary with the local labor market) in the input price 
index. In the SNF PPS final rule for FY 2022 (86 FR 42437), we 
finalized a proposal to revise the labor-related share to reflect the 
relative importance of the 2018-based SNF market basket cost weights 
for the following cost categories: 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 proportion of 
Capital-Related expenses. The methodology for calculating the labor-
related portion beginning in FY 2022 is discussed in detail in the FY 
2022 SNF PPS final rule (86 FR 42461 through 42463).
    We calculate the labor-related relative importance from the SNF 
market basket, and it approximates the labor-related portion of the 
total costs after taking into account historical and projected price 
changes between the base year and FY 2024. The price proxies that move 
the different cost categories in the market basket do not necessarily 
change at the same rate, and the relative importance captures these 
changes. Accordingly, the relative importance figure more closely 
reflects the cost share weights for FY 2024 than the base year weights 
from the SNF market basket. We calculate the labor-related relative 
importance for FY 2024 in four steps. First, we compute the FY 2024 
price index level for the total market basket and each cost category of 
the market basket. Second, we calculate a ratio for each cost category 
by dividing the FY 2024 price index level for that cost category by the 
total market basket price index level. Third, we determine the FY 2024 
relative importance for each cost category by multiplying this ratio by 
the base year (2018) weight. Finally, we add the FY 2024 relative 
importance for each of the labor-related cost categories (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 Capital-Related expenses) to produce the FY 2024 
labor-related relative importance.
    Table 7 summarizes the proposed labor-related share for FY 2024, 
based on IGI's fourth quarter 2022 forecast of the 2018-based SNF 
market basket, compared to the labor-related share that was used for 
the FY 2023 SNF PPS final rule.

[[Page 21326]]



            Table 7--Labor-Related Share, FY 2023 and FY 2024
------------------------------------------------------------------------
                                                             Proposed
                                             Relative        relative
                                            importance,     importance,
                                           labor-related   labor-related
                                          share, FY 2023  share, FY 2024
                                           22:2 forecast   22:4 forecast
                                                \1\             \2\
------------------------------------------------------------------------
Wages and salaries......................            51.9            52.2
Employee benefits.......................             9.5             9.5
Professional fees: Labor-related........             3.5             3.4
Administrative & facilities support                  0.6             0.6
 services...............................
Installation, maintenance & repair                   0.4             0.4
 services...............................
All other: Labor-related services.......             2.0             2.0
Capital-related (.391)..................             2.9             2.9
                                         -------------------------------
    Total...............................            70.8            71.0
------------------------------------------------------------------------
\1\ Published in the Federal Register; Based on the second quarter 2022
  IHS Global Inc. forecast of the 2018-based SNF market basket.
\2\ Based on the fourth quarter 2022 IHS Global Inc. forecast of the
  2018-based SNF market basket.

    To calculate the labor portion of the case-mix adjusted per diem 
rate, we would multiply the total case-mix adjusted per diem rate, 
which is the sum of all five case-mix adjusted components into which a 
patient classifies, and the non-case-mix component rate, by the FY 2024 
labor-related share percentage provided in Table 7. The remaining 
portion of the rate would be the non-labor portion. Under the previous 
RUG-IV model, we included tables which provided the case-mix adjusted 
RUG-IV rates, by RUG-IV group, broken out by total rate, labor portion 
and non-labor portion, such as Table 9 of the FY 2019 SNF PPS final 
rule (83 FR 39175). However, as we discussed in the FY 2020 final rule 
(84 FR 38738), under PDPM, as the total rate is calculated as a 
combination of six different component rates, five of which are case-
mix adjusted, and given the sheer volume of possible combinations of 
these five case-mix adjusted components, it is not feasible to provide 
tables similar to those that existed in the prior rulemaking.
    Therefore, to aid interested parties in understanding the effect of 
the wage index on the calculation of the SNF per diem rate, we have 
included a hypothetical rate calculation in Table 9.
    Section 1888(e)(4)(G)(ii) of the Act also requires that we apply 
this wage index in a manner that does not result in aggregate payments 
under the SNF PPS that are greater or less than would otherwise be made 
if the wage adjustment had not been made. For FY 2024 (Federal rates 
effective October 1, 2023), we apply an adjustment to fulfill the 
budget neutrality requirement. We meet this requirement by multiplying 
each of the components of the unadjusted Federal rates by a budget 
neutrality factor, equal to the ratio of the weighted average wage 
adjustment factor for FY 2023 to the weighted average wage adjustment 
factor for FY 2024. For this calculation, we would use the same FY 2022 
claims utilization data for both the numerator and denominator of this 
ratio. We define the wage adjustment factor used in this calculation as 
the labor portion of the rate component multiplied by the wage index 
plus the non-labor portion of the rate component. The proposed budget 
neutrality factor for FY 2024 is 0.9998.
    We note that if more recent data become available (for example, 
revised wage data), we would use such data, as appropriate, to 
determine the wage index budget neutrality factor in the SNF PPS final 
rule.
    We invite public comment on the proposed SNF wage adjustment for FY 
2024.

E. SNF Value-Based Purchasing Program

    Beginning with payment for services furnished on October 1, 2018, 
section 1888(h) of the Act requires the Secretary to reduce the 
adjusted Federal per diem rate determined under section 1888(e)(4)(G) 
of the Act otherwise applicable to a SNF for services furnished during 
a fiscal year by 2 percent, and to adjust the resulting rate for a SNF 
by the value-based incentive payment amount earned by the SNF based on 
the SNF's performance score for that fiscal year under the SNF VBP 
Program. To implement these requirements, we finalized in the FY 2019 
SNF PPS final rule the addition of Sec.  413.337(f) to our regulations 
(83 FR 39178).
    Please see section VII. of this proposed rule for further 
discussion of our proposed updates to the SNF VBP Program.

F. Adjusted Rate Computation Example

    Tables 8 through 10 provide examples generally illustrating payment 
calculations during FY 2024 under PDPM for a hypothetical 30-day SNF 
stay, involving the hypothetical SNF XYZ, located in Frederick, MD 
(Urban CBSA 23224), for a hypothetical patient who is classified into 
such groups that the patient's HIPPS code is NHNC1. Table 8 shows the 
adjustments made to the Federal per diem rates (prior to application of 
any adjustments under the SNF VBP Program as discussed previously and 
taking into account the second phase of the parity adjustment 
recalibration discussed in section III.C. of this proposed rule) to 
compute the provider's case-mix adjusted per diem rate for FY 2024, 
based on the patient's PDPM classification, as well as how the variable 
per diem (VPD) adjustment factor affects calculation of the per diem 
rate for a given day of the stay. Table 9 shows the adjustments made to 
the case-mix adjusted per diem rate from Table 8 to account for the 
provider's wage index. The wage index used in this example is based on 
the FY 2024 SNF PPS wage index that appears in Table A available on the 
CMS website at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/WageIndex.html. Finally, Table 10 provides the case-mix 
and wage index adjusted per-diem rate for this patient for each day of 
the 30-day stay, as well as the total payment for this stay. Table 10 
also includes the VPD adjustment factors for each day of the patient's 
stay, to clarify why the patient's per diem rate changes for certain 
days of the stay. As illustrated in Table 10, SNF XYZ's total PPS 
payment for this particular patient's stay would equal $21,677.34.

[[Page 21327]]



                            Table 8--PDPM Case-Mix Adjusted Rate Computation Example
----------------------------------------------------------------------------------------------------------------
                                            Per diem rate calculation
-----------------------------------------------------------------------------------------------------------------
                                                                                        VPD
               Component                     Component group      Component rate    adjustment     VPD adj. rate
                                                                                      factor
----------------------------------------------------------------------------------------------------------------
PT....................................  N.......................          $98.11            1.00          $98.11
OT....................................  N.......................           92.63            1.00           92.63
SLP...................................  H.......................           70.63            1.00           70.63
Nursing...............................  N.......................          179.56            1.00          179.56
NTA...................................  C.......................          160.36            3.00          481.08
Non-Case-Mix..........................  ........................          109.39  ..............          109.39
                                                                 -----------------------------------------------
    Total PDPM Case-Mix Adj. Per Diem.  ........................  ..............  ..............        1,031.40
----------------------------------------------------------------------------------------------------------------


                                                  Table 9--Wage Index Adjusted Rate Computation Example
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                         PDPM wage index adjustment calculation
---------------------------------------------------------------------------------------------------------------------------------------------------------
                                                           PDPM case-mix                                                                  Total case mix
                       HIPPS code                          adjusted per    Labor portion    Wage index      Wage index       Non-labor    and wage index
                                                               diem                                        adjusted rate      portion        adj. rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
NHNC1...................................................       $1,031.40         $732.29          0.9648         $706.51         $299.11       $1,005.62
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                   Table 10--Adjusted Rate Computation Example
----------------------------------------------------------------------------------------------------------------
                                                                                                   Case mix and
                                                                      NTA VPD        PT/OT VPD      wage index
                           Day of stay                              adjustment      adjustment     adjusted per
                                                                      factor          factor         diem rate
----------------------------------------------------------------------------------------------------------------
1...............................................................             3.0             1.0       $1,005.62
2...............................................................             3.0             1.0        1,005.62
3...............................................................             3.0             1.0        1,005.62
4...............................................................             1.0             1.0          692.92
5...............................................................             1.0             1.0          692.92
6...............................................................             1.0             1.0          692.92
7...............................................................             1.0             1.0          692.92
8...............................................................             1.0             1.0          692.92
9...............................................................             1.0             1.0          692.92
10..............................................................             1.0             1.0          692.92
11..............................................................             1.0             1.0          692.92
12..............................................................             1.0             1.0          692.92
13..............................................................             1.0             1.0          692.92
14..............................................................             1.0             1.0          692.92
15..............................................................             1.0             1.0          692.92
16..............................................................             1.0             1.0          692.92
17..............................................................             1.0             1.0          692.92
18..............................................................             1.0             1.0          692.92
19..............................................................             1.0             1.0          692.92
20..............................................................             1.0             1.0          692.92
21..............................................................             1.0            0.98          689.20
22..............................................................             1.0            0.98          689.20
23..............................................................             1.0            0.98          689.20
24..............................................................             1.0            0.98          689.20
25..............................................................             1.0            0.98          689.20
26..............................................................             1.0            0.98          689.20
27..............................................................             1.0            0.98          689.20
28..............................................................             1.0            0.96          685.48
29..............................................................             1.0            0.96          685.48
30..............................................................             1.0            0.96          685.48
                                                                 -----------------------------------------------
    Total Payment...............................................  ..............  ..............       21,677.34
----------------------------------------------------------------------------------------------------------------

IV. Additional Aspects of the SNF PPS

A. SNF Level of Care--Administrative Presumption

    The establishment of the SNF PPS did not change Medicare's 
fundamental requirements for SNF coverage. However, because the case-
mix classification is based, in part, on the beneficiary's need for 
skilled nursing care and therapy, we have attempted, where possible, to 
coordinate claims review procedures with the existing resident 
assessment process and case-mix classification system discussed in 
section III.C. of this proposed rule. This

[[Page 21328]]

approach includes an administrative presumption that utilizes a 
beneficiary's correct assignment, at the outset of the SNF stay, of one 
of the case-mix classifiers designated for this purpose to assist in 
making certain SNF level of care determinations.
    In accordance with Sec.  413.345, we include in each update of the 
Federal payment rates in the Federal Register a discussion of the 
resident classification system that provides the basis for case-mix 
adjustment. We also designate those specific classifiers under the 
case-mix classification system that represent the required SNF level of 
care, as provided in 42 CFR 409.30. This designation reflects an 
administrative presumption that those beneficiaries who are correctly 
assigned one of the designated case-mix classifiers on the initial 
Medicare assessment are automatically classified as meeting the SNF 
level of care definition up to and including the assessment reference 
date (ARD) for that assessment.
    A beneficiary who does not qualify for the presumption is not 
automatically classified as either meeting or not meeting the level of 
care definition, but instead receives an individual determination on 
this point using the existing administrative criteria. This presumption 
recognizes the strong likelihood that those beneficiaries who are 
correctly assigned one of the designated case-mix classifiers during 
the immediate post-hospital period would require a covered level of 
care, which would be less likely for other beneficiaries.
    In the July 30, 1999 final rule (64 FR 41670), we indicated that we 
would announce any changes to the guidelines for Medicare level of care 
determinations related to modifications in the case-mix classification 
structure. The FY 2018 final rule (82 FR 36544) further specified that 
we would henceforth disseminate the standard description of the 
administrative presumption's designated groups via the SNF PPS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html (where such designations appear in the paragraph 
entitled ``Case Mix Adjustment''), and would publish such designations 
in rulemaking only to the extent that we actually intend to propose 
changes in them. Under that approach, the set of case-mix classifiers 
designated for this purpose under PDPM was finalized in the FY 2019 SNF 
PPS final rule (83 FR 39253) and is posted on the SNF PPS website 
(https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html), in the paragraph entitled ``Case Mix Adjustment.''
    However, we note that this administrative presumption policy does 
not supersede the SNF's responsibility to ensure that its decisions 
relating to level of care are appropriate and timely, including a 
review to confirm that any services prompting the assignment of one of 
the designated case-mix classifiers (which, in turn, serves to trigger 
the administrative presumption) are themselves medically necessary. As 
we explained in the FY 2000 SNF PPS final rule (64 FR 41667), the 
administrative presumption is itself rebuttable in those individual 
cases in which the services actually received by the resident do not 
meet the basic statutory criterion of being reasonable and necessary to 
diagnose or treat a beneficiary's condition (according to section 
1862(a)(1) of the Act). Accordingly, the presumption would not apply, 
for example, in those situations where the sole classifier that 
triggers the presumption is itself assigned through the receipt of 
services that are subsequently determined to be not reasonable and 
necessary. Moreover, we want to stress the importance of careful 
monitoring for changes in each patient's condition to determine the 
continuing need for Part A SNF benefits after the ARD of the initial 
Medicare assessment.

B. Consolidated Billing

    Sections 1842(b)(6)(E) and 1862(a)(18) of the Act (as added by 
section 4432(b) of the BBA 1997) require a SNF to submit consolidated 
Medicare bills to its Medicare Administrative Contractor (MAC) for 
almost all of the services that its residents receive during the course 
of a covered Part A stay. In addition, section 1862(a)(18) of the Act 
places the responsibility with the SNF for billing Medicare for 
physical therapy, occupational therapy, and speech-language pathology 
services that the resident receives during a noncovered stay. Section 
1888(e)(2)(A) of the Act excludes a small list of services from the 
consolidated billing provision (primarily those services furnished by 
physicians and certain other types of practitioners), which remain 
separately billable under Part B when furnished to a SNF's Part A 
resident. These excluded service categories are discussed in greater 
detail in section V.B.2. of the May 12, 1998 interim final rule (63 FR 
26295 through 26297).
    Effective with services furnished on or after January 1, 2024, 
section 4121(a)(4) of the Consolidated Appropriations Act, 2023 (CAA 
2023) added marriage and family therapists and mental health counselors 
to the list of practitioners at section 1888(e)(2)(A)(ii) of the Act 
whose services are excluded from the consolidated billing provision. We 
note that there are no rate adjustments required to the per diem to 
offset these exclusions, as payments for services made under section 
1888(e)(2)(A)(ii) of the Act are not specified under the requirement at 
section 1888(e)(4)(G)(iii) of the Act as services for which the 
Secretary must ``provide for an appropriate proportional reduction . . 
. equal to the aggregate increase in payments attributable to the 
exclusion''. See section IV.D. of this proposed rule for a discussion 
of the proposed regulatory updates implementing this change.
    A detailed discussion of the legislative history of the 
consolidated billing provision is available on the SNF PPS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Legislative_History_2018-10-01.pdf. In particular, section 
103 of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act 
of 1999 (BBRA 1999) (Pub. L. 106-113, enacted November 29, 1999) 
amended section 1888(e)(2)(A)(iii) of the Act by further excluding a 
number of individual high-cost, low probability services, identified by 
HCPCS codes, within several broader categories (chemotherapy items, 
chemotherapy administration services, radioisotope services, and 
customized prosthetic devices) that otherwise remained subject to the 
provision. We discuss this BBRA 1999 amendment in greater detail in the 
SNF PPS proposed and final rules for FY 2001 (65 FR 19231 through 
19232, April 10, 2000, and 65 FR 46790 through 46795, July 31, 2000), 
as well as in Program Memorandum AB-00-18 (Change Request #1070), 
issued March 2000, which is available online at www.cms.gov/transmittals/downloads/ab001860.pdf.
    As explained in the FY 2001 proposed rule (65 FR 19232), the 
amendments enacted in section 103 of the BBRA 1999 not only identified 
for exclusion from this provision a number of particular service codes 
within four specified categories (that is, chemotherapy items, 
chemotherapy administration services, radioisotope services, and 
customized prosthetic devices), but also gave the Secretary the 
authority to designate additional, individual services for exclusion 
within each of these four specified service categories. In the proposed 
rule for FY 2001, we also noted that the BBRA 1999 Conference report 
(H.R. Conf. Rep. No. 106-479 at 854 (1999)) characterizes the

[[Page 21329]]

individual services that this legislation targets for exclusion as 
high-cost, low probability events that could have devastating financial 
impacts because their costs far exceed the payment SNFs receive under 
the PPS. According to the conferees, section 103(a) of the BBRA 1999 is 
an attempt to exclude from the PPS certain services and costly items 
that are provided infrequently in SNFs. By contrast, the amendments 
enacted in section 103 of the BBRA 1999 do not designate for exclusion 
any of the remaining services within those four categories (thus, 
leaving all of those services subject to SNF consolidated billing), 
because they are relatively inexpensive and are furnished routinely in 
SNFs.
    As we further explained in the final rule for FY 2001 (65 FR 
46790), and as is consistent with our longstanding policy, any 
additional service codes that we might designate for exclusion under 
our discretionary authority must meet the same statutory criteria used 
in identifying the original codes excluded from consolidated billing 
under section 103(a) of the BBRA 1999: they must fall within one of the 
four service categories specified in the BBRA 1999; and they also must 
meet the same standards of high cost and low probability in the SNF 
setting, as discussed in the BBRA 1999 Conference report. Accordingly, 
we characterized this statutory authority to identify additional 
service codes for exclusion as essentially affording the flexibility to 
revise the list of excluded codes in response to changes of major 
significance that may occur over time (for example, the development of 
new medical technologies or other advances in the state of medical 
practice) (65 FR 46791).
    Effective with items and services furnished on or after October 1, 
2021, section 134 in Division CC of the CAA 2021 established an 
additional category of excluded codes in section 1888(e)(2)(A)(iii)(VI) 
of the Act, for certain blood clotting factors for the treatment of 
patients with hemophilia and other bleeding disorders along with items 
and services related to the furnishing of such factors under section 
1842(o)(5)(C) of the Act. Like the provisions enacted in the BBRA 1999, 
section 1888(e)(2)(A)(iii)(VI) of the Act gives the Secretary the 
authority to designate additional items and services for exclusion 
within the category of items and services related to blood clotting 
factors, as described in that section. Finally, as noted previously in 
this proposed rule, section 4121(a)(4) CAA 2023 amended section 
1888(e)(2)(A)(ii) of the Act to exclude marriage and family therapist 
services and mental health counselor services from consolidated billing 
effective January 1, 2024.
    In this proposed rule, we specifically invite public comments 
identifying HCPCS codes in any of these five service categories 
(chemotherapy items, chemotherapy administration services, radioisotope 
services, customized prosthetic devices, and blood clotting factors) 
representing recent medical advances that might meet our criteria for 
exclusion from SNF consolidated billing. We may consider excluding a 
particular service if it meets our criteria for exclusion as specified 
previously. We request that commenters identify in their comments the 
specific HCPCS code that is associated with the service in question, as 
well as their rationale for requesting that the identified HCPCS 
code(s) be excluded.
    We note that the original BBRA amendment and the CAA 2021 
identified a set of excluded items and services by means of specifying 
individual HCPCS codes within the designated categories that were in 
effect as of a particular date (in the case of the BBRA 1999, July 1, 
1999, and in the case of the CAA 2021, July 1, 2020), as subsequently 
modified by the Secretary. In addition, as noted in this section of the 
preamble, the statute (sections 1888(e)(2)(A)(iii)(II) through (VI) of 
the Act) gives the Secretary authority to identify additional items and 
services for exclusion within the five specified categories of items 
and services described in the statute, which are also designated by 
HCPCS code. Designating the excluded services in this manner makes it 
possible for us to utilize program issuances as the vehicle for 
accomplishing routine updates to the excluded codes to reflect any 
minor revisions that might subsequently occur in the coding system 
itself, such as the assignment of a different code number to a service 
already designated as excluded, or the creation of a new code for a 
type of service that falls within one of the established exclusion 
categories and meets our criteria for exclusion.
    Accordingly, in the event that we identify through the current 
rulemaking cycle any new services that would actually represent a 
substantive change in the scope of the exclusions from SNF consolidated 
billing, we would identify these additional excluded services by means 
of the HCPCS codes that are in effect as of a specific date (in this 
case, October 1, 2023). By making any new exclusions in this manner, we 
could similarly accomplish routine future updates of these additional 
codes through the issuance of program instructions. The latest list of 
excluded codes can be found on the SNF Consolidated Billing website at 
https://www.cms.gov/Medicare/Billing/SNFConsolidatedBilling.

C. Payment for SNF-Level Swing-Bed Services

    Section 1883 of the Act permits certain small, rural hospitals to 
enter into a Medicare swing-bed agreement, under which the hospital can 
use its beds to provide either acute- or SNF-level care, as needed. For 
critical access hospitals (CAHs), Part A pays on a reasonable cost 
basis for SNF-level services furnished under a swing-bed agreement. 
However, in accordance with section 1888(e)(7) of the Act, SNF-level 
services furnished by non-CAH rural hospitals are paid under the SNF 
PPS, effective with cost reporting periods beginning on or after July 
1, 2002. As explained in the FY 2002 final rule (66 FR 39562), this 
effective date is consistent with the statutory provision to integrate 
swing-bed rural hospitals into the SNF PPS by the end of the transition 
period, June 30, 2002.
    Accordingly, all non-CAH swing-bed rural hospitals have now come 
under the SNF PPS. Therefore, all rates and wage indexes outlined in 
earlier sections of this proposed rule for the SNF PPS also apply to 
all non-CAH swing-bed rural hospitals. As finalized in the FY 2010 SNF 
PPS final rule (74 FR 40356 through 40357), effective October 1, 2010, 
non-CAH swing-bed rural hospitals are required to complete an MDS 3.0 
swing-bed assessment which is limited to the required demographic, 
payment, and quality items. As discussed in the FY 2019 SNF PPS final 
rule (83 FR 39235), revisions were made to the swing bed assessment to 
support implementation of PDPM, effective October 1, 2019. A discussion 
of the assessment schedule and the MDS effective beginning FY 2020 
appears in the FY 2019 SNF PPS final rule (83 FR 39229 through 39237). 
The latest changes in the MDS for swing-bed rural hospitals appear on 
the SNF PPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/index.html.

D. Revisions to the Regulation Text

    We propose to make the following revisions in the regulation text. 
To reflect the recently-enacted exclusion of marriage and family 
therapist services and mental health counselor services from SNF 
consolidated billing at section 1888(e)(2)(A)(ii) of the Act (as 
discussed in section IV.B of this proposed rule), we propose to 
redesignate current Sec.  411.15(p)(2)(vi) through (xviii) as 
Sec. Sec.  411.15(p)(2)(viii) through (xx),

[[Page 21330]]

respectively. In addition, we propose to redesignate Sec.  489.20(s)(6) 
through (18) as Sec.  489.20(s)(8) through (20), respectively. We also 
propose to add new regulation text at Sec. Sec.  411.15(p)(2)(vi) and 
(vii) and 489.20(s)(6) and (7). Specifically, proposed new Sec. Sec.  
411.15(p)(2)(vi) and 489.20(s)(6) would reflect the exclusion of 
services performed by a marriage and family therapist, as defined in 
section 1861(lll)(2) of the Act. Proposed new Sec. Sec.  
411.15(p)(2)(vii) and 489.20(s)(7) would reflect the exclusion of 
services performed by a mental health counselor, as defined in section 
1861(lll)(4) of the Act.

V. Other SNF PPS Issues

A. Technical Updates to PDPM ICD-10 Mappings

1. Background
    In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the 
implementation of the Patient Driven Payment Model (PDPM), effective 
October 1, 2019. The PDPM utilizes the International Classification of 
Diseases, 10th Revision, Clinical Modification (ICD-10-CM, hereafter 
referred to as ICD-10) codes in several ways, including using the 
patient's primary diagnosis to assign patients to clinical categories 
under several PDPM components, specifically the PT, OT, SLP and NTA 
components. While other ICD-10 codes may be reported as secondary 
diagnoses and designated as additional comorbidities, the PDPM does not 
use secondary diagnoses to assign patients to clinical categories. The 
ICD-10 code to clinical category mapping used under PDPM (hereafter 
referred to as PDPM ICD-10 code mapping) are available on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM.
    In the FY 2020 SNF PPS final rule (84 FR 38750), we outlined the 
process by which we maintain and update the PDPM ICD-10 code mapping, 
as well as the SNF Grouper software and other such products related to 
patient classification and billing, to ensure that they reflect the 
most up to date codes. Beginning with the updates for FY 2020, we apply 
nonsubstantive changes to the PDPM ICD-10 code mapping through a 
subregulatory process consisting of posting the updated PDPM ICD-10 
code mapping on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. Such nonsubstantive 
changes are limited to those specific changes that are necessary to 
maintain consistency with the most current PDPM ICD-10 code mapping.
    On the other hand, substantive changes that go beyond the intention 
of maintaining consistency with the most current PDPM ICD-10 code 
mapping, such as changes to the assignment of a code to a clinical 
category or comorbidity list, will be proposed through notice and 
comment rulemaking because they are changes that affect policy. We note 
that, in the case of any diagnoses that are either currently mapped to 
Return to Provider or that we are proposing to classify into this 
category, this is not intended to reflect any judgment on the 
importance of recognizing and treating these conditions. Rather, we 
believe that there are more specific or appropriate diagnoses that 
would better serve as the primary diagnosis for a Part-A covered SNF 
stay.
2. Proposed Clinical Category Changes for New ICD-10 Codes for FY 2023
    Each year, we review the clinical category assigned to new ICD-10 
diagnosis codes and propose changing the assignment to another clinical 
category if warranted. This year, we are proposing changing the 
clinical category assignment for the following five new ICD-10 codes 
that were effective on October 1, 2022:
     D75.84 Other platelet-activating anti-platelet factor 4 
(PF4) disorders is mapped to the clinical category of Return to 
Provider. Patients with anti-PF4 disorders have blood clotting 
disorders. Examples of disorders to be classified with D75.84 are 
spontaneous heparin-induced thrombocytopenia (without heparin 
exposure), thrombosis with thrombocytopenia syndrome, and vaccine-
induced thrombotic thrombocytopenia. Due to the similarity of this code 
to other anti-PF4 disorders, we propose to change the assignment to 
Medical Management.
     F43.81 Prolonged grief disorder and F43.89 Other reactions 
to severe stress are mapped to the clinical category of Medical 
Management. However, while we believe that SNFs serve an important role 
in providing services to those beneficiaries suffering from mental 
illness, the SNF setting is not the setting that would be most 
beneficial to treat a patient for whom these diagnoses are coded as the 
patient's primary diagnosis. For this reason, we propose changing the 
clinical category of both codes to Return to Provider. We would 
encourage providers to continue reporting these codes as secondary 
diagnoses, to ensure that we are able to identify these patients and 
that they are receiving appropriate care.
     G90.A Postural orthostatic tachycardia syndrome (POTS) is 
mapped to the clinical category of Acute Neurologic. POTS is a type of 
orthostatic intolerance that causes the heart to beat faster than 
normal when transitioning from sitting or lying down to standing up, 
causing changes in blood pressure, increase in heart rate, and 
lightheadedness. The treatment for POTS involves hydration, physical 
therapy, and vasoconstrictor medications, which are also treatments for 
codes such as E86.0 Dehydration and E86.1 Hypovolemia that are mapped 
to the Medical Management category. Since the medical interventions are 
similar, we propose changing the assignment for POTS to Medical 
Management.
     K76.82 Hepatic encephalopathy is mapped to the clinical 
category of Return to Provider. Hepatic encephalopathy is a condition 
resulting from severe liver disease, where toxins build up in the blood 
that can affect brain function and lead to a change in medical status. 
Prior to the development of this code, multiple codes were used to 
characterize this condition such as K76.6 Portal hypertension, K76.7 
Hepatorenal syndrome, and K76.89 Other unspecified diseases of liver, 
which are mapped to the Medical Management category. Since these codes 
describe similar liver conditions, we propose to change the assignment 
to Medical Management.
    We invite comments on the proposed substantive changes to the PDPM 
ICD-10 code mapping discussed in this section, as well as comments on 
additional substantive and nonsubstantive changes that commenters 
believe are necessary.
3. Proposed Clinical Category Changes for Unspecified Substance Use 
Disorder Codes
    Effective with stays beginning on and after October 1, 2022, ICD-10 
diagnosis codes F10.90 Alcohol use, unspecified, uncomplicated, F10.91 
Alcohol use, unspecified, in remission, F11.91 Opioid use, unspecified, 
in remission, F12.91 Cannabis use, unspecified, in remission, F13.91 
Sedative, hypnotic or anxiolytic use, unspecified, in remission, and 
F14.91 Cocaine use, unspecified, in remission went into effect and were 
mapped to the clinical category of Medical Management. We reviewed 
these 6 unspecified substance use disorder (SUD) codes and propose 
changing the assignment from Medical Management to Return to Provider 
because the codes are not specific as to if they refer to abuse or 
dependence, and there are other specific codes

[[Page 21331]]

available for each of these conditions that would be more appropriate 
as a primary diagnosis for a SNF stay. For example, diagnosis code 
F10.90 Alcohol use, unspecified, uncomplicated is not specific as to 
whether the patient has alcohol abuse or alcohol dependence. There are 
more specific codes that could be used instead, such as F10.10 Alcohol 
abuse, uncomplicated or F10.20 Alcohol dependence, uncomplicated, that 
may serve as the primary diagnosis for a SNF stay and are appropriately 
mapped to the clinical category of Medical Management.
    Moreover, we believe that increased accuracy of coding primary 
diagnoses aligns with CMS' broader efforts to ensure better quality of 
care. Therefore, we reviewed all 458 ICD-10 SUD codes from code 
categories F10 to F19 and propose reassigning 162 additional 
unspecified SUD codes to Return to Provider from Medical Management 
because the codes are not specific as to if they refer to abuse or 
dependence. We would note that this policy change would not affect a 
large number of SNF stays. Our data from FY 2021 show that the 162 
unspecified SUD codes were used as primary diagnoses for only 323 SNF 
stays (0.02 percent) and as secondary diagnoses for 9,537 SNF stays 
(0.54 percent). The purpose of enacting this policy is to continue an 
ongoing effort to refine the PDPM ICD-10 code mapping each year to 
ensure more accurate coding of primary diagnoses. We would encourage 
providers to continue reporting these codes as secondary diagnoses, to 
ensure that we are able to identify these patients and that they are 
receiving appropriate care.
    Table 1, Proposed Clinical Category Changes for Unspecified 
Substance Use Disorder Codes, which lists all 168 codes included in 
this proposal, is available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. We invite 
comments on the proposed substantive changes to the PDPM ICD-10 code 
mapping discussed in this section, as well as comments on additional 
substantive and nonsubstantive changes that commenters believe are 
necessary.
3. Proposed Clinical Category Changes for Certain Subcategory Fracture 
Codes
    Each year, we invite comments on additional substantive and 
nonsubstantive changes that commenters believe are necessary to the 
PDPM ICD-10 code mapping. In the FY 2023 final rule (87 FR 47524), we 
described how one commenter recommended that CMS consider revising the 
PDPM ICD-10 code mapping to reclassify certain subcategory S42.2--
humeral fracture codes. The commenter highlighted that certain 
encounter codes for humeral fractures, such as those ending in the 7th 
character of A for an initial encounter for fracture, are permitted the 
option to be mapped to a surgical clinical category, denoted on the 
PDPM ICD-10 code mapping as May be Eligible for One of the Two 
Orthopedic Surgery Categories (that is, major joint replacement or 
spinal surgery, or orthopedic surgery) if the resident had a major 
procedure during the prior inpatient stay that impacts the SNF care 
plan. However, the commenter noted that other encounter codes within 
the same code family, such as those ending in the 7th character of D 
for subsequent encounter for fracture with routine healing, are mapped 
to the Non-Surgical Orthopedic/Musculoskeletal without the surgical 
option. The commenter requested that we review all subcategory S42.2--
fracture codes to ensure that the appropriate surgical clinical 
category could be selected for joint aftercare. Since then, the 
commenter has also contacted CMS with a similar suggestion for M84.552D 
Pathological fracture in neoplastic disease, left femur, subsequent 
encounter for fracture with routine healing.
    We have since reviewed the suggested code subcategories to 
determine the most efficient manner for addressing this discrepancy. We 
propose adding the surgical option that allows 45 subcategory S42.2--
codes for displaced fractures to be eligible for one of two orthopedic 
surgery categories. However, we note that this proposal does not extend 
to subcategory S42.2--codes for nondisplaced fractures, which typically 
do not require surgery. We also propose adding the surgical option to 
subcategory 46 M84.5--codes for pathological fractures to certain major 
weight-bearing bones to be eligible for one of two orthopedic surgery 
categories.
    Table 2, Proposed Clinical Category Changes for S42.2 and M84.5 
Fracture Codes, which lists all 91 codes included in this proposal, is 
available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. We invite comments on the proposed 
substantive changes to the PDPM ICD-10 code mapping discussed in this 
section, as well as comments on additional substantive and 
nonsubstantive changes that commenters believe are necessary.
4. Proposed Clinical Category Changes for Unacceptable Principal 
Diagnosis Codes
    In the FY 2023 final rule (87 FR 47525) we described how several 
commenters referred to instances when SNF claims were denied for 
including a primary diagnosis code that is listed on the PDPM ICD-10 
code mapping as a valid code, but that is not accepted by some Medicare 
Administrative Contractors (MACs) that use the Hospital Inpatient 
Prospective Payment System (IPPS) Medicare Code Editor (MCE) lists when 
evaluating the primary diagnosis codes listed on SNF claims. In the 
IPPS, a patient's diagnosis is entered into the Medicare claims 
processing systems and subjected to a series of automated screens 
called the MCE. The MCE lists are designed to identify cases that 
require further review before classification into an MS-DRG. We note 
that all codes on the MCE lists are able to be reported; however, a 
code edit may be triggered that the MAC may either choose to bypass or 
return to the provider to resubmit. Updates to the MCE lists are 
proposed on an annual basis and discussed through IPPS rulemaking when 
new codes or policies involving existing codes are introduced.
    Commenters recommended that CMS seek to align the PDPM ICD-10 code 
mapping with the MCE in treating diagnoses that are Return to Provider, 
specifically referring to the Unacceptable Principal Diagnosis edit 
code list in the Definition of Medicare Code Edits, which is available 
on the CMS website at https://www.cms.gov/medicare/medicare-fee-for-service-payment/acuteinpatientpps/ms-drg-classifications-and-software. 
The Unacceptable Principal Diagnosis edit code list contains selected 
codes that describe a circumstance that influences an individual's 
health status but not a current illness or injury, or codes that are 
not specific manifestations but may be due to an underlying cause, and 
which are considered unacceptable as a principal diagnosis.
    We have identified 95 codes from the MCE Unacceptable Principal 
Diagnosis edit code list that are mapped to a valid clinical category 
on the PDPM ICD-10 code mapping, and that were coded as primary 
diagnoses for 14,808 SNF stays (0.84 percent) in FY 2021. Table 3, 
Proposed Clinical Category Changes for Unacceptable Principal Diagnosis 
Codes, which lists all 95 codes included in this proposal, is available 
on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/PDPM. As stated previously in this section of 
this

[[Page 21332]]

proposed rule, we note that reporting these codes as a primary 
diagnosis for a SNF stay may trigger an edit that the MAC may either 
choose to bypass or return to the provider to resubmit, and therefore 
not all of these 14,808 stays were denied by the MACs.
    After clinical review, we concur that these 95 codes listed in 
Table 3 on the CMS website should be assigned to Return to Provider. 
For the diagnosis codes listed in Table 3 on the CMS website that are 
from the category B95 to B97 range and contain the suffix ``as the 
cause of diseases classified elsewhere'', the ICD-10 coding convention 
for such etiology and manifestation codes, where certain conditions 
have both an underlying etiology and multiple body system 
manifestations due to the underlying etiology, dictates that the 
underlying condition should be sequenced first, followed by the 
manifestation. The ICD-10 coding guidelines also state that codes from 
subcategory G92.0--Immune effector cell-associated neurotoxicity 
syndrome, subcategory R40.2--Coma scale, and subcategory S06.A--
Traumatic brain injury should only be reported as secondary diagnoses, 
as there are more specific codes that should be sequenced first. 
Additionally, the ICD-10 coding guidelines state that diagnosis codes 
in categories Z90 and Z98 are status codes, indicating that a patient 
is either a carrier of a disease or has the sequelae or residual of a 
past disease or condition, and are not reasons for a patient to be 
admitted to a SNF. Lastly, our clinicians determined that diagnosis 
code Z43.9 Encounter for attention to unspecified artificial opening 
should be assigned to the clinical category Return to Provider because 
there are more specific codes that identify the site for the artificial 
opening.
    Therefore, we propose to reassign the 95 codes listed in Table 3 on 
the CMS website from the current default clinical category on the PDPM 
ICD-10 code mapping to Return to Provider. We also propose to make 
future updates to align the PDPM ICD-10 code mapping with the MCE 
Unacceptable Principal Diagnosis edit code list on a subregulatory 
basis going forward. Moreover, we are soliciting comment on aligning 
with the MCE Manifestation codes not allowed as principal diagnosis 
edit code list, which contains diagnosis codes that are the 
manifestation of an underlying disease, not the disease itself, and 
therefore should not be used as a principal diagnosis, and the 
Questionable admission codes edit code list, which contains diagnoses 
codes that are not usually sufficient justification for admission to an 
acute care hospital. While these MCE lists were not mentioned by 
commenters, we believe that some MACs may be applying these edit lists 
to SNF claims and this could cause continued differences between the 
PDPM ICD-10 code mapping and the IPPS MCE. If finalized, we also 
propose to make future updates to align the PDPM ICD-10 code mapping 
with the MCE Manifestation codes not allowed as principal diagnosis 
edit code list and the Questionable admission codes edit code list on a 
subregulatory basis going forward.
    We invite comments on the proposed substantive changes to the PDPM 
ICD-10 code mapping discussed in this section, as well as comments on 
additional substantive and nonsubstantive changes that commenters 
believe are necessary.

VI. Skilled Nursing Facility Quality Reporting Program (SNF QRP)

A. Background and Statutory Authority

    The Skilled Nursing Facility Quality Reporting Program (SNF QRP) is 
authorized by section 1888(e)(6) of the Act, and it applies to 
freestanding SNFs, SNFs affiliated with acute care facilities, and all 
non-critical access hospital (CAH) swing-bed rural hospitals. Section 
1888(e)(6)(A)(i) of the Act requires the Secretary to reduce by 2 
percentage points the annual market basket percentage increase 
described in section 1888(e)(5)(B)(i) of the Act applicable to a SNF 
for a fiscal year (FY), after application of section 1888(e)(5)(B)(ii) 
of the Act (the productivity adjustment) and section 1888(e)(5)(B)(iii) 
of the Act, in the case of a SNF that does not submit data in 
accordance with sections 1888(e)(6)(B)(i)(II) and (III) of the Act for 
that FY. Section 1890A of the Act requires that the Secretary establish 
and follow a pre-rulemaking process, in coordination with the 
consensus-based entity (CBE) with a contract under section 1890(a) of 
the Act, to solicit input from certain groups regarding the selection 
of quality and efficiency measures for the SNF QRP. We have codified 
our program requirements in our regulations at 42 CFR part 413.
    In this proposed rule, we are proposing to adopt three new 
measures, remove three existing measures, and modify one existing 
measure. Second, we are seeking information on principles we could use 
to select and prioritize SNF QRP quality measures in future years. 
Third, we are providing an update on our health equity efforts. Fourth, 
we are proposing several administrative changes, including a change to 
the SNF QRP data completion thresholds and a data submission method for 
the proposed CoreQ: Short Stay Discharge questionnaire. Finally, we are 
proposing to begin public reporting of four measures. These proposals 
are further specified below.

B. General Considerations Used for the Selection of Measures for the 
SNF QRP

    For a detailed discussion of the considerations we use for the 
selection of SNF QRP quality, resource use, or other measures, we refer 
readers to the FY 2016 SNF (PPS) final rule (80 FR 46429 through 
46431).
1. Quality Measures Currently Adopted for the FY 2024 SNF QRP
    The SNF QRP currently has 16 measures for the FY 2024 program year, 
which are listed in Table 11. For a discussion of the factors used to 
evaluate whether a measure should be removed from the SNF QRP, we refer 
readers to Sec.  413.360(b)(2).

  Table 11--Quality Measures Currently Adopted for the FY 2024 SNF QRP
------------------------------------------------------------------------
               Short name                   Measure name & data source
------------------------------------------------------------------------
   Resident Assessment Instrument Minimum Data Set (Assessment-Based)
------------------------------------------------------------------------
Pressure Ulcer/Injury..................  Changes in Skin Integrity Post-
                                          Acute Care: Pressure Ulcer/
                                          Injury.
Application of Falls...................  Application of Percent of
                                          Residents Experiencing One or
                                          More Falls with Major Injury
                                          (Long Stay).
Application of Functional Assessment/    Application of Percent of Long-
 Care Plan.                               Term Care Hospital (LTCH)
                                          Patients with an Admission and
                                          Discharge Functional
                                          Assessment and a Care Plan
                                          That Addresses Function.
Change in Mobility Score...............  Application of IRF Functional
                                          Outcome Measure: Change in
                                          Mobility Score for Medical
                                          Rehabilitation Patients.
Discharge Mobility Score...............  Application of IRF Functional
                                          Outcome Measure: Discharge
                                          Mobility Score for Medical
                                          Rehabilitation Patients.
Change in Self-Care Score..............  Application of the IRF
                                          Functional Outcome Measure:
                                          Change in Self-Care Score for
                                          Medical Rehabilitation
                                          Patients.
Discharge Self-Care Score..............  Application of IRF Functional
                                          Outcome Measure: Discharge
                                          Self-Care Score for Medical
                                          Rehabilitation Patients.

[[Page 21333]]

 
DRR....................................  Drug Regimen Review Conducted
                                          With Follow-Up for Identified
                                          Issues-Post Acute Care (PAC)
                                          Skilled Nursing Facility (SNF)
                                          Quality Reporting Program
                                          (QRP).
TOH-Provider *.........................  Transfer of Health (TOH)
                                          Information to the Provider
                                          Post-Acute Care (PAC).
TOH-Patient *..........................  Transfer of Health (TOH)
                                          Information to the Patient
                                          Post-Acute Care (PAC).
------------------------------------------------------------------------
                              Claims-Based
------------------------------------------------------------------------
MSPB SNF...............................  Medicare Spending Per
                                          Beneficiary (MSPB)--Post Acute
                                          Care (PAC) Skilled Nursing
                                          Facility (SNF) Quality
                                          Reporting Program (QRP).
DTC....................................  Discharge to Community (DTC)--
                                          Post Acute Care (PAC) Skilled
                                          Nursing Facility (SNF) Quality
                                          Reporting Program (QRP).
PPR....................................  Potentially Preventable 30-Day
                                          Post-Discharge Readmission
                                          Measure for Skilled Nursing
                                          Facility (SNF) Quality
                                          Reporting Program (QRP).
SNF HAI................................  SNF Healthcare-Associated
                                          Infections (HAI) Requiring
                                          Hospitalization.
------------------------------------------------------------------------
                                  NHSN
------------------------------------------------------------------------
HCP COVID-19 Vaccine...................  COVID-19 Vaccination Coverage
                                          among Healthcare Personnel
                                          (HCP).
HCP Influenza Vaccine..................  Influenza Vaccination Coverage
                                          among Healthcare Personnel
                                          (HCP).
------------------------------------------------------------------------
* In response to the public health emergency (PHE) for the Coronavirus
  Disease 2019 (COVID-19), we released an Interim Final Rule (85 FR
  27595 through 27597) which delayed the compliance date for collection
  and reporting of the Transfer of Health (TOH) Information measures for
  at least 2 full fiscal years after the end of the PHE. The compliance
  date for the collection and reporting of the Transfer of Health
  Information measures was revised to October 1, 2023 in the FY 2023 SNF
  PPS final rule (87 FR 47547 through 47551).

C. SNF QRP Quality Measure Proposals

    In this proposed rule, we include SNF QRP proposals for the FY 
2025, FY 2026, and FY 2027 program years. This proposed rule would add 
new measures to the SNF QRP as well as remove measures from the SNF 
QRP. Beginning with the FY 2025 SNF QRP, we are proposing to (1) modify 
the COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) 
measure, (2) adopt the Discharge Function Score measure,\13\ which we 
are specifying under section 1888(e)(6)(B)(i) of the Act, and (3) 
remove three current measures: (i) the Application of Percent of Long-
Term Care Hospital (LTCH) Patients with an Admission and Discharge 
Functional Assessment and a Care Plan That Addresses Function measure, 
(ii) the Application of IRF Functional Outcome Measure: Change in Self-
Care Score for Medical Rehabilitation Patients measure, and (iii) the 
Application of IRF Functional Outcome Measure: Change in Mobility Score 
for Medical Rehabilitation Patients measure.
---------------------------------------------------------------------------

    \13\ This measure was submitted to the Measures Under 
Consideration (MUC) List as the Cross-Setting Discharge Function 
Score. Subsequent to the MAP Workgroup meetings, the measure 
developer modified the name. Discharge Function Score for Skilled 
Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
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    We are proposing to adopt two new measures beginning with the FY 
2026 SNF QRP: (i) the CoreQ: Short Stay Discharge measure which we are 
specifying under section 1899B(d)(1) of the Act, and (ii) the COVID-19 
Vaccine: Percent of Patients/Residents Who Are Up to Date measure, 
which we are specifying under section 1899B(d)(1) of the Act.
1. SNF QRP Quality Measure Proposals Beginning With the FY 2025 SNF QRP
a. Proposed Modification of the COVID-19 Vaccination Coverage Among 
Healthcare Personnel (HCP) Measure Beginning With the FY 2025 SNF QRP
(1) Background
    On January 31, 2020, the Secretary declared a public health 
emergency (PHE) for the United States in response to the global 
outbreak of SARS-CoV-2, a novel (new) coronavirus that causes a disease 
named ``coronavirus disease 2019'' (COVID-19).\14\ Subsequently, in the 
FY 2022 SNF PPS final rule (86 FR 42480 through 42489), we adopted the 
COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) (HCP 
COVID-19 Vaccine) measure for the SNF QRP. The HCP COVID-19 Vaccine 
measure requires each SNF to submit data on the percentage of HCP 
eligible to work in the SNF for at least one day during the reporting 
period, excluding persons with contraindications to FDA-authorized or -
approved COVID-19 Vaccines, who have received a complete vaccination 
course against SARS-CoV-2. Since that time, COVID-19 has continued to 
spread domestically and around the world with more than 102.7 million 
cases and 1.1 million deaths in the United States as of February 13, 
2023.\15\ In recognition of the ongoing significance and complexity of 
COVID-19, the Secretary has renewed the PHE on April 21, 2020, July 23, 
2020, October 2, 2020, January 7, 2021, April 15, 2021, July 19, 2021, 
October 15, 2021, January 14, 2022, April 12, 2022, July 15, 2022, 
October 13, 2022, January 11, 2023, and February 9, 2023.\16\ The 
Department of Health and Human Services (HHS) announced plans to let 
the PHE expire on May 11, 2023 and stated that the public health 
response to COVID-19 remains a public health priority with a whole of 
government approach to combating the virus, including through 
vaccination efforts.\17\
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    \14\ U.S. Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. Determination 
that a Public Health Emergency Exists. January 31, 2020. https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \15\ Centers for Disease Control and Prevention. COVID Data 
Tracker. February 13, 2023. https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
    \16\ U.S. Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. Renewal of 
Determination that a Public Health Emergency Exists. February 9, 
2023. https://aspr.hhs.gov/legal/PHE/Pages/COVID19-9Feb2023.aspx.
    \17\ U.S. Department of Health and Human Services. Fact Sheet: 
COVID-19 Public Health Emergency Transition Roadmap. February 9, 
2023. https://www.hhs.gov/about/news/2023/02/09/fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.
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    In the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) and 
in the Revised Guidance for Staff Vaccination Requirements,\18\ we 
stated that vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19. We continue to believe it 
is important to incentivize and track HCP vaccination in SNFs through 
quality measurement in order to protect HCP, residents, and caregivers, 
and to help sustain the ability of SNFs to continue serving their 
communities throughout the PHE and beyond. At the time we issued the FY 
2022 SNF PPS final rule, the Food and Drug Administration (FDA) had 
issued emergency use authorizations (EUAs) for COVID-19 vaccines 
manufactured

[[Page 21334]]

by Pfizer-BioNTech,\19\ Moderna,\20\ and Janssen.\21\ The Pfizer-
BioNTech vaccine was authorized for ages 12 and older and the Moderna 
and Janssen vaccines for ages 18 and older. Shortly following the 
publication of the final rule, on August 23, 2021, the FDA issued an 
approval for the Pfizer-BioNTech vaccine, marketed as Comirnaty.\22\ 
The FDA issued approval for the Moderna vaccine, marketed as Spikevax, 
on January 31, 2022 \23\ and an EUA for the Novavax vaccine, on July 
13, 2022.\24\ The FDA also issued EUAs for single booster doses of the 
then authorized COVID-19 vaccines. As of November 19, 2021 \25\ \26\ 
\27\ a single booster dose of each COVID-19 vaccine was authorized for 
all eligible individuals 18 years of age and older. EUAs were 
subsequently issued for a second booster dose of the Pfizer-BioNTech 
and Moderna vaccines in certain populations in March 2022.\28\ FDA 
first authorized the use of a booster dose of bivalent or ``updated'' 
COVID-19 vaccines from Pfizer-BioNTech and Moderna in August 2022.\29\
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    \18\ Centers for Medicare & Medicaid Services. Revised Guidance 
for Staff Vaccination Requirements QSO-23-02-ALL. October 26, 2022. 
https://www.cms.gov/files/document/qs0-23-02-all.pdf.
    \19\ Food and Drug Administration. FDA Takes Key Action in Fight 
Against COVID-19 By Issuing Emergency Use Authorization for First 
COVID-19 Vaccine. December 11, 2020. https://www.fda.gov/news-events/press-announcements/fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19.
    \20\ Food and Drug Administration. FDA Takes Additional Action 
in Fight Against COVID-19 By Issuing Emergency Use Authorization for 
Second COVID-19 Vaccine. December 18, 2020. https://www.fda.gov/news-events/press-announcements/fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid.
    \21\ Food and Drug Administration. FDA Issues Emergency Use 
Authorization for Third COVID-19 Vaccine. February 27, 2021. https://www.fda.gov/news-events/press-announcements/fda-issues-emergency-use-authorization-third-covid-19-vaccine.
    \22\ Food and Drug Administration. FDA Approves First COVID-19 
Vaccine. August 23, 2021. https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine.
    \23\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Takes Key Action by Approving Second COVID-19 Vaccine. 
January 31, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.
    \24\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Emergency Use of Novavax COVID-19 Vaccine, 
Adjuvanted. July 13, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-emergency-use-novavax-covid-19-vaccine-adjuvanted.
    \25\ Food and Drug Administration. FDA Authorizes Booster Dose 
of Pfizer-BioNTech COVID-19 Vaccine for Certain Populations. 
September 22, 2021. https://www.fda.gov/news-events/press-announcements/fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations.
    \26\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Takes Additional Actions on the Use of a Booster Dose 
for COVID-19 Vaccines. October 20, 2021. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-additional-actions-use-booster-dose-covid-19-vaccines.
    \27\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Expands Eligibility for COVID-19 Vaccine Boosters. 
November 19, 2021. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-expands-eligibility-covid-19-vaccine-boosters.
    \28\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Second Booster Dose of Two COVID-19 Vaccines 
for Older and Immunocompromised Individuals. March 29, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-second-booster-dose-two-covid-19-vaccines-older-and.
    \29\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID-19 
Vaccines for Use as a Booster Dose. August 31, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
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(a) Measure Importance
    While the impact of COVID-19 vaccines on asymptomatic infection and 
transmission is not yet fully known, there are now robust data 
available on COVID-19 vaccine effectiveness across multiple populations 
against severe illness, hospitalization, and death. Two-dose COVID-19 
vaccines from Pfizer-BioNTech and Moderna were found to be 88 percent 
and 93 percent effective against hospitalization for COVID-19, 
respectively, over 6 months for adults over age 18 without 
immunocompromising conditions.\30\ During a SARS-CoV-2 surge in the 
spring and summer of 2021, 92 percent of COVID-19 hospitalizations and 
91 percent of COVID-19-associated deaths were reported among persons 
not fully vaccinated.\31\ Real-world studies of population-level 
vaccine effectiveness indicated similarly high rates of efficacy in 
preventing SARS-CoV-2 infection among frontline workers in multiple 
industries, with a 90 percent effectiveness in preventing symptomatic 
and asymptomatic infection from December 2020 through August 2021.\32\ 
Vaccines have also been highly effective in real-world conditions at 
preventing COVID-19 in HCP with up to 96 percent efficacy for fully 
vaccinated HCP, including those at risk for severe infection and those 
in racial and ethnic groups disproportionately affected by COVID-
19.\33\ In the presence of high community prevalence of COVID-19, 
residents of nursing homes with low staff vaccination coverage had 
cases of COVID-19 related deaths 195 percent higher than those among 
residents of nursing homes with high staff vaccination coverage.\34\ 
Overall, data demonstrate that COVID-19 vaccines are effective and 
prevent severe disease, hospitalization, and death.
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    \30\ Centers for Disease Control and Prevention. Morbidity and 
Mortality Weekly Report (MMWR). Comparative Effectiveness of 
Moderna, Pfizer-BioNTech, and Janssen (Johnson & Johnson) Vaccines 
in Preventing COVID-19 Hospitalizations Among Adults Without 
Immunocompromising Conditions--United States, March-August 2021. 
September 24, 2021. https://cdc.gov/mmwr/volumes/70/wr/mm7038e1.htm?s_cid=mm7038e1_w.
    \31\ Centers for Disease Control and Prevention. Morbidity and 
Mortality Weekly Report (MMWR). Monitoring Incidence of COVID-19 
Cases, Hospitalizations, and Deaths, by Vaccination Status--13 U.S. 
Jurisdictions, April 4-July 17, 2021. September 10, 2021. https://cdc.gov.mmwr/volumes/70/wr/mm7037e1.htm?s_cid=mm7037e1_w.
    \32\ Centers for Disease Control and Prevention. Morbidity and 
Mortality Weekly Report (MMWR). Effectiveness of COVID-19 Vaccines 
in Preventing SARS-CoV-2 Infection Among Frontline Workers Before 
and During B.1.617.2 (Delta) Variant Predominance--Eight U.S. 
Locations, December 2020-August 2021. August 27, 2021. https://cdc.gov/mmwr/volume/70/wr/mm7034e4.htm?s_cid=mm7034e4_w.
    \33\ Pilishvili T., Gierke R., Fleming-Dutra K.E., et al. 
Effectiveness of mRNA Covid-19 Vaccine among U.S. Health Care 
Personnel. N Engl J Med. 2021 Dec 16;385(25):e90. doi: 10.1056/
NEJMoa2106599. PMID: 34551224; PMCID: PMC8482809.
    \34\ McGarry B.E., Barnett M.L., Grabowski D.C., Gandhi A.D. 
Nursing Home Staff Vaccination and Covid-19 Outcomes. N Engl J Med. 
2022 Jan 27;386(4):397-398. doi: 10.1056/NEJMc2115674. PMID: 
34879189; PMCID: PMC8693685.
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    As SARS-CoV-2 persists and evolves, our COVID-19 vaccination 
strategy must remain responsive. When we adopted the HCP COVID-19 
Vaccine measure in the FY 2022 SNF PPS final rule, we stated that the 
need for booster doses of COVID-19 vaccine had not been established and 
no additional doses had been recommended (86 FR 42484 through 42485). 
We also stated that we believed the numerator was sufficiently broad to 
include potential future boosters as part of a ``complete vaccination 
course'' and that the measure was sufficiently specified to address 
boosters (86 FR 42485). Since we adopted the HCP COVID-19 Vaccine 
measure in the FY 2022 SNF PPS final rule, new variants of SARS-CoV-2 
have emerged around the world and within the United States. 
Specifically, the Omicron variant (and its related subvariants) is 
listed as a variant of concern by the Centers for Disease Control and 
Prevention (CDC) because it spreads more easily than earlier 
variants.\35\ Vaccine manufacturers have responded to the Omicron 
variant by developing bivalent COVID-19 vaccines, which include a 
component of the original virus strain to provide broad protection 
against COVID-19 and a component of the Omicron variant to provide 
better protection against COVID-19 caused by the Omicron

[[Page 21335]]

variant.\36\ These booster doses of the bivalent COVID-19 vaccines have 
been shown to increase immune response to SARS-CoV-2 variants, 
including Omicron, particularly in individuals that are more than 6 
months removed from receipt of their primary series.\37\ The FDA issued 
EUAs for booster doses of two bivalent COVID-19 vaccines, one from 
Pfizer-BioNTech \38\ and one from Moderna,\39\ and strongly encourages 
anyone who is eligible to consider receiving a booster dose with a 
bivalent COVID-19 vaccine to provide better protection against 
currently circulating variants.\40\ COVID-19 booster doses are 
associated with a greater reduction in infections among HCP relative to 
those who only received primary series vaccination, with a rate of 
breakthrough infections among HCP who received only a two-dose regimen 
of 21.4 percent compared to a rate of 0.7 percent among boosted 
HCP.41 42
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    \35\ Centers for Disease Control and Prevention. Variants of the 
Virus. https://www.cdc.gov/coronavirus/2019-ncov/variants/index.html.
    \36\ Food and Drug Administration. COVID-19 Bivalent Vaccine 
Boosters. https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/covid-19-bivalent-vaccine-boosters.
    \37\ Chalkias S., Harper C., Vrbicky K., et al. A Bivalent 
Omicron-Containing Booster Vaccine Against COVID-19. N Engl J Med. 
2022 Oct 6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 
36112399; PMCID: PMC9511634.
    \38\ Food and Drug Administration. Pfizer-BioNTech COVID-19 
Vaccines. https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccines.
    \39\ Food and Drug Administration. Moderna COVID-19 Vaccines. 
https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccines.
    \40\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID-19 
Vaccines for Use as a Booster Dose. August 31, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
    \41\ Prasad N., Derado G., Nanduri S.A., et al. Effectiveness of 
a COVID-19 Additional Primary or Booster Vaccine Dose in Preventing 
SARS-CoV-2 Infection Among Nursing Home Residents During Widespread 
Circulation of the Omicron Variant--United States, February 14-March 
27, 2022. Morbidity and Mortality Weekly Report (MMWR). 2022 May 
6;71(18):633-637. doi: 10.15585/mmwr.mm7118a4. PMID: 35511708; 
PMCID: PMC9098239.
    \42\ Oster Y., Benenson S., Nir-Paz R., Buda I., Cohen M.J. The 
Effect of a Third BNT162b2 Vaccine on Breakthrough Infections in 
Health Care Workers: a Cohort Analysis. Clin Microbiol Infect. 2022 
May;28(5):735.e1-735.e3. doi: 10.1016/j.cmi.2022.01.019. PMID: 
35143997; PMCID: PMC8820100.
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    We believe that vaccination remains the most effective means to 
prevent the severe consequences of COVID-19, including severe illness, 
hospitalization, and death. Given the availability of vaccine efficacy 
data, EUAs issued by the FDA for bivalent boosters, the continued 
presence of SARS-CoV-2 in the United States, and variance among rates 
of booster dose vaccination, it is important to update the 
specifications of the HCP COVID-19 Vaccine measure to reflect recent 
updates that explicitly specify for HCP to receive primary series and 
booster vaccine doses in a timely manner. Given the persistent spread 
of COVID-19, we continue to believe that monitoring and surveillance is 
important and provides residents, beneficiaries, and their caregivers 
with information to support informed decision making. Beginning with 
the FY 2025 SNF QRP, we propose to modify the HCP COVID-19 Vaccine 
measure to replace the term ``complete vaccination course'' with the 
term ``up to date'' in the HCP vaccination definition. We also propose 
to update the numerator to specify the time frames within which an HCP 
is considered up to date with recommended COVID-19 vaccines, including 
booster doses, beginning with the FY 2025 SNF QRP.
(b) Measure Testing
    The CDC conducted beta testing of the modified HCP COVID-19 Vaccine 
measure by assessing if the collection of information on additional/
booster vaccine doses received by HCP was feasible, as information on 
receipt of booster vaccine doses is required for determining if HCP are 
up to date with the current COVID-19 vaccination. Feasibility was 
assessed by calculating the proportion of facilities that reported 
additional/booster doses of the COVID-19 vaccine. The assessment was 
conducted in various facility types, including SNFs, using vaccine 
coverage data for the first quarter of calendar year (CY) 2022 
(January-March), which was reported through the CDC's National 
Healthcare Safety Network (NHSN). Feasibility of reporting additional/
booster doses of vaccine is evident by the fact that 99.2 percent of 
SNFs reported vaccination additional/booster coverage data to the NHSN 
for the first quarter of 2022.\43\ Additionally, HCP COVID-19 Vaccine 
measure scores calculated using January 1-March 31, 2022 data had a 
median of 31.8 percent and an interquartile range of 18.9 to 49.7 
percent, indicating a measure performance gap as there are clinically 
significant differences in booster/additional dose vaccination coverage 
rates among SNFs.\44\
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    \43\ National Quality Forum. Measure Application Partnership 
(MAP) Post-Acute Care/Long-Term Care: 2022-2023 Measures Under 
Consideration (MUC) Cycle Measure Specifications. December 1, 2022. 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=97883.
    \44\ National Quality Forum. Measure Application Partnership 
(MAP) Post-Acute Care/Long-Term Care: 2022-2023 Measures Under 
Consideration (MUC) Cycle Measure Specifications. December 1, 2022. 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=97883.
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(2) Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that, absent an 
exception under section 1899B(e)(2)(B) of the Act, measures specified 
under section 1899B of the Act be endorsed by a consensus-based entity 
(CBE) with a contract under section 1890(a). In the case of a specified 
area or medical topic determined appropriate by the Secretary for which 
a feasible and practical measure has not been endorsed, section 
1899B(e)(2)(B) permits the Secretary to specify a measure that is not 
so endorsed, as long as due consideration is given to measures that 
have been endorsed or adopted by a consensus organization identified by 
the Secretary.
    The current version of the HCP COVID-19 Vaccine (``Quarterly 
Reporting of COVID-19 Vaccination Coverage Among Healthcare 
Personnel'') measure recently received endorsement by the CBE on July 
26, 2022.\45\ However, this measure received endorsement based on its 
specifications depicted in the FY 2022 SNF PPS final rule (86 FR 42480 
through 42489), and does not capture information about whether HCP are 
up to date with their COVID-19 vaccinations. The proposed modification 
of this measure utilizes the term up to date in the HCP vaccination 
definition and updates the numerator to specify the time frames within 
which an HCP is considered up to date with recommended COVID-19 
vaccines, including booster doses. We were unable to identify any CBE-
endorsed measures for SNFs that captured information on whether HCP are 
up to date with their COVID-19 vaccinations, and we found no other 
feasible and practical measure on this topic.
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    \45\ National Quality Forum. 3636 Quarterly Reporting of COVID-
19 Vaccination Coverage among Healthcare Personnel. Accessed 
February 6, 2023. Available at https://www.qualityforum.org/QPS/3636.
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    Therefore, after consideration of other available measures, we find 
that the exception under section 1899B(e)(2)(B) of the Act applies and 
are proposing the modified measure, HCP COVID-19 Vaccine, beginning 
with the FY 2025 SNF QRP. The CDC, the measure developer, is pursuing 
CBE endorsement for this modified version of the measure.

[[Page 21336]]

(3) Measure Applications Partnership (MAP) Review
    We refer readers to the FY 2022 SNF PPS final rule (86 FR 42482) 
for more information on the initial review of the HCP COVID-19 Vaccine 
measure by the Measure Application Partnership (MAP).
    In accordance with section 1890A of the Act, the pre-rulemaking 
process includes making publicly available a list of quality and 
efficiency measures, called the Measures Under Consideration (MUC) 
List, that the Secretary is considering adopting for use in the 
Medicare program(s), including our quality reporting programs. This 
allows interested parties to provide recommendations to the Secretary 
on the measures included on the MUC List. We submitted the updated 
version of the HCP COVID-19 Vaccine measure on the MUC List entitled 
``List of Measures under Consideration for December 1, 2022'' \46\ for 
the 2022-2023 pre-rulemaking cycle for consideration by the MAP. 
Interested parties submitted four comments to the MAP during the pre-
rulemaking process on the proposed modifications of the HCP COVID-19 
Vaccine measure. Three commenters noted that it is important that HCP 
be vaccinated against COVID-19 and supported measurement and reporting 
as an important strategy to help healthcare organizations assess their 
performance in achieving high rates of up to date vaccination of their 
HCP. One of these commenters noted that the measure would provide 
valuable information to the government as part of its ongoing response 
to the pandemic. The other two commenters do not believe it should be 
used in a pay-for-performance program, and one raised concerns of 
potential unintended consequences, such as frequency of reporting and 
the potential State regulations with which such a requirement might 
conflict. One commenter did not support the measure, raising several 
concerns with the measure, including that the data have never been 
tested for validity or reliability. Finally, three of the four 
commenters raised concern about the difficulty of defining up to date 
for purposes of the modified measure.
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    \46\ Centers for Medicare & Medicaid Services. Overview of the 
List of Measures Under Consideration for December 1, 2022. https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
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    Shortly after publication of the MUC List, several MAP workgroups 
met to provide input on the measure. First, the MAP Health Equity 
Advisory Group convened on December 6-7, 2022. The MAP Health Equity 
Advisory Group questioned whether the measure excludes residents with 
contraindications to FDA authorized or approved COVID-19 vaccines, and 
whether the measure will be stratified by demographic factors. The 
measure developer (that is the CDC) confirmed that HCP with 
contraindications to the vaccines are excluded from the measure 
denominator, but the measure will not be stratified since the data are 
submitted at an aggregate rather than an individual level.
    The MAP Rural Health Advisory Group met on December 8-9, 2022, 
during which a few members expressed concerns about data collection 
burden, given that small rural hospitals may not have employee health 
software. The measure developer acknowledged the challenge of getting 
adequate documentation and emphasized their goal is to ensure the 
measures do not present a burden on the provider. The measure developer 
also noted that the model used for the HCP COVID-19 Vaccine measure is 
based on the Influenza Vaccination Coverage among HCP measure (CBE 
#0431), and it intends to utilize a similar approach to the modified 
HCP COVID-19 Vaccine measure if vaccination strategy becomes seasonal. 
The measure developer acknowledged that if COVID-19 becomes seasonal, 
the measure model could evolve to capture seasonal vaccination.
    Next, the MAP Post-Acute Care/Long-Term Care (PAC/LTC) workgroup 
met on December 12, 2022 and provided input on the on the modification 
for the HCP COVID-19 Vaccine measure. The MAP PAC/LTC workgroup noted 
that the previous version of the measure received endorsement from the 
CBE (CBE #3636),\47\ and that the CDC intends to submit the updated 
measure for endorsement. The PAC/LTC workgroup voted to support the 
staff recommendation of conditional support for rulemaking pending 
testing indicating the measure is reliable and valid, and endorsement 
by the CBE.
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    \47\ National Quality Forum. 3636 Quarterly Reporting of COVID-
19 Vaccination Coverage among Healthcare Personnel. Accessed 
February 6, 2023. https://www.qualityforum.org/QPS/3636.
---------------------------------------------------------------------------

    Following the PAC/LTC workgroup meeting, a public comment period 
was held in which interested parties commented on the PAC/LTC 
workgroup's preliminary recommendations, and the MAP received three 
comments. Two supported the update to the measure, one of which 
strongly supported the vaccination of HCP against COVID-19. Although 
these commenters supported the measure, one commenter recommended CBE 
endorsement for the updated measure, and encouraged us to monitor any 
unintended consequences from the measure. Two commenters noted the 
challenges associated with the measure's specifications. Specifically, 
one noted the broad definition of the denominator and another 
recommended a vaccination exclusion or exception due to religious 
beliefs. Finally, one commenter raised issues related to the time lag 
between data collection and public reporting on Care Compare and 
encouraged us to provide information as to whether the measure is 
reflecting vaccination rates accurately and encouraging HCP 
vaccination.
    The MAP Coordinating Committee convened on January 24-25, 2023, 
during which the measure was placed on the consent calendar and 
received a final recommendation of conditional support for rulemaking 
pending testing indicating the measure is reliable and valid, and 
endorsement by the CBE. We refer readers to the final MAP 
recommendations, titled 2022-2023 MAP Final Recommendations.\48\
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    \48\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/sites/default/files/2022-2023-MAP-Final-Recommendations-508.xlsx.
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(4) Quality Measure Calculation
    The HCP COVID-19 Vaccine measure is a process measure developed by 
the CDC to track COVID-19 vaccination coverage among HCP in facilities 
such as SNFs. The HCP COVID-19 Vaccine measure is a process measure and 
is not risk-adjusted.
    The denominator would be the number of HCP eligible to work in the 
facility for at least one day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination that are 
described by the CDC.\49\ SNFs report the following four categories of 
HCP to NHSN, and the first three categories are included in the measure 
denominator:
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    \49\ Centers for Disease Control and Prevention. 
Contraindications and precautions. https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
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     Employees: This includes all persons who receive a direct 
paycheck from the reporting facility (that is, on the facility's 
payroll), regardless of clinical responsibility or patient contact.
     Licensed independent practitioners (LIPs): This includes 
physicians (MD, DO), advanced practice nurses, and physician assistants 
who are affiliated with the reporting facility, but are not directly 
employed by it (that is, they do not receive a paycheck from the

[[Page 21337]]

facility), regardless of clinical responsibility or patient contact. 
Post-residency fellows are also included in this category if they are 
not on the facility's payroll.
     Adult students/trainees and volunteers: This includes all 
medical, nursing, or other health professional students, interns, 
medical residents, or volunteers aged 18 or over who are affiliated 
with the healthcare facility, but are not directly employed by it (that 
is, they do not receive a direct paycheck from the facility), 
regardless of clinical responsibility or patient contact.
     Other contract personnel: Contract personnel are defined 
as persons providing care, treatment, or services at the facility 
through a contract who do not fall into any of the above-mentioned 
denominator categories. This also includes vendors providing care, 
treatment, or services at the facility who may or may not be paid 
through a contract. Facilities are required to enter data on other 
contract personnel for submission in the NHSN application, but data 
from this category are not included in the HCP COVID-19 Vaccine 
measure.\50\
---------------------------------------------------------------------------

    \50\ For more details on the reporting of other contract 
personnel, we refer readers to the NHSN COVID-19 Vaccination 
Protocol, Weekly COVID-19 Vaccination Module for Healthcare 
Personnel, https://www.cdc.gov/nhsn/pdfs/hps/covidvax/protocol-hcp-508.pdf.
---------------------------------------------------------------------------

    The denominator excludes denominator-eligible individuals with 
contraindications as defined by the CDC.\51\ We are not proposing any 
changes to the denominator exclusions.
---------------------------------------------------------------------------

    \51\ Centers for Disease Control and Prevention. 
Contraindications and precautions. Available at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
---------------------------------------------------------------------------

    The numerator would be the cumulative number of HCP in the 
denominator population who are considered up to date with CDC-
recommended COVID-19 vaccines. Providers should refer to the definition 
of up to date as of the first day of the applicable reporting quarter, 
which can be found at https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. For example, for the proposed updated 
measure, HCP would be considered up to date during the quarter four of 
the CY 2022 reporting period for the SNF QRP if they met one of the 
following criteria:
    1. Individuals who received an updated bivalent \52\ booster dose, 
or
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    \52\ The updated (bivalent) Moderna and Pfizer-BioNTech boosters 
target the most recent Omicron subvariants. The updated (bivalent) 
boosters were recommended by the CDC on September 2, 2022. As of 
this date, the original, monovalent mRNA vaccines are no longer 
authorized as a booster dose for people ages 12 years and older.
---------------------------------------------------------------------------

    2a. Individuals who received their last booster dose less than 2 
months ago, or
    2b. Individuals who completed their primary series \53\ less than 2 
months ago.
---------------------------------------------------------------------------

    \53\ Completing a primary series means receiving a two-dose 
series of a COVID-19 vaccine or a single dose of Janssen/J&J COVID-
19 vaccine.
---------------------------------------------------------------------------

    We note that for purposes of NHSN surveillance, the CDC used this 
definition of up to date during quarter 4 2022 surveillance period 
(September 26, 2022-December 25, 2022).
    We refer readers to https://www.cdc.gov/nhsn/nqf/index.html for 
more details on the measure specifications.
    While we are not proposing any changes to the data submission or 
reporting process for the HCP COVID-19 Vaccine measure, we are 
proposing that for purposes of meeting FY 2025 SNF QRP compliance, SNFs 
would report individuals who are up to date beginning in quarter four 
of CY 2023. Under the data submission and reporting process, SNFs would 
collect the numerator and denominator for the modified HCP COVID-19 
Vaccine measure for at least one self-selected week during each month 
of the reporting quarter and submit the data to the NHSN Healthcare 
Personnel Safety (HPS) Component before the quarterly deadline. If a 
SNF submits more than one week of data in a month, the most recent 
week's data would be used to calculate the measure. Each quarter, the 
CDC would calculate a single quarterly HCP COVID-19 vaccination 
coverage rate for each SNF, which would be calculated by taking the 
average of the data from the three weekly rates submitted by the SNF 
for that quarter. Beginning with the FY 2026 SNF QRP, SNFs would be 
required to submit data for the entire calendar year.
    We are also proposing that public reporting of the modified version 
of the HCP COVID-19 Vaccine measure would begin with the October 2024 
Care Compare refresh or as soon as technically feasible.
    We invite public comment on our proposal to modify the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure beginning 
with the FY 2025 SNF QRP.
b. Proposed Adoption of the Discharge Function Score Measure Beginning 
With the FY 2025 SNF QRP
(1) Background
    SNFs provide short-term skilled nursing care and rehabilitation 
services, including physical and occupational therapy and speech-
language pathology services. The most common resident conditions are 
septicemia, joint replacement, heart failure and shock, hip and femur 
procedures (not including major joint replacement), and pneumonia.\54\ 
Septicemia progressing to sepsis is often associated with long-term 
functional deficits and increased mortality in survivors.\55\ 
Rehabilitation of function, however, has been shown to be effective and 
is associated with reducing mortality and improving quality of 
life.56 57
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    \54\ Medicare Payment Advisory Commission. Report to the 
Congress: Medicare and the Health Care Delivery System. June 2021. 
https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/jun21_medpac_report_to_congress_sec.pdf.
    \55\ Winkler D., Rose N., Freytag A., Sauter W., Spoden M., 
Schettler A., Wedekind L., Storch J., Ditscheid B., Schlattmann P., 
Reinhart K., G[uuml]nster C., Hartog C.S., Fleischmann-Struzek C. 
The Effect of Post-acute Rehabilitation on Mortality, Chronic Care 
Dependency, Health Care Use and Costs in Sepsis Survivors. Ann Am 
Thorac Soc. 2022 Oct 17. doi: 10.1513/AnnalsATS.202203-195OC. Epub 
ahead of print. PMID: 36251451.
    \56\ Chao P.W., Shih C.J., Lee Y.J., Tseng C.M., Kuo S.C., Shih 
Y.N., Chou K.T., Tarng D.C., Li S.Y., Ou S.M., Chen Y.T. Association 
of Post discharge Rehabilitation with Mortality in Intensive Care 
Unit Survivors of Sepsis. Am J Respir Crit Care Med. 2014 Nov 
1;190(9):1003-11. doi: 10.1164/rccm.201406-1170OC. PMID: 25210792.
    \57\ Taito S., Taito M., Banno M., Tsujimoto H., Kataoka Y., 
Tsujimoto Y. Rehabilitation for Patients with Sepsis: A Systematic 
Review and Meta-Analysis. PLoS One. 2018 Jul 26;13(7):e0201292. doi: 
10.1371/journal.pone.0201292. Erratum in: PLoS One. 2019 Aug 
21;14(8):e0221224. PMID: 30048540; PMCID: PMC6062068.
---------------------------------------------------------------------------

    Section 1888(e)(6)(B)(i) of the Act, cross-referencing subsections 
(b), (c), and (d) of section 1899B of the Act, requires CMS to develop 
and implement standardized quality measures from five quality measure 
domains, including the domain of functional status, cognitive function, 
and changes in function and cognitive function across the post-acute 
care (PAC) settings, including SNFs. To satisfy this requirement, we 
adopted the Application of Percent of Long-Term Care Hospital Patients 
with an Admission and Discharge Functional Assessment and a Care Plan 
That Addresses Function (Application of Functional Assessment/Care 
Plan) measure, for the SNF QRP in the FY 2016 SNF PPS final rule (80 FR 
46444 through 46453). While this process measure allowed for the 
standardization of functional assessments across assessment instruments 
and facilitated cross-setting data collection, quality measurement, and 
interoperable data exchange, we believe it is now topped out and are 
proposing to remove it in section VI.C.1.c. of this proposed rule. 
While there are other outcome measures addressing functional status 
\58\ that can

[[Page 21338]]

reliably distinguish performance among providers in the SNF QRP, these 
outcome measures are not cross-setting in nature because they rely on 
functional status items not collected in all PAC settings. In contrast, 
a cross-setting functional outcome measure would align measure 
specifications across settings, including the use of a common set of 
standardized functional assessment data elements.
---------------------------------------------------------------------------

    \58\ The measures include: IRF Functional Outcome Measure: 
Change in Self-Care Score for Medical Rehabilitation Patients, IRF 
Functional Outcome Measure: Change in Mobility Score for Medical 
Rehabilitation Patients, IRF Functional Outcome Measure: Discharge 
Self-Care Score for Medical Rehabilitation Patients, IRF Functional 
Outcome Measure: Discharge Mobility Score for Medical Rehabilitation 
Patients.
---------------------------------------------------------------------------

(a) Measure Importance
    Maintenance or improvement of physical function among older adults 
is increasingly an important focus of health care. Adults age 65 years 
and older constitute the most rapidly growing population in the United 
States, and functional capacity in physical (non-psychological) domains 
has been shown to decline with age.\59\ Moreover, impaired functional 
capacity is associated with poorer quality of life and an increased 
risk of all-cause mortality, postoperative complications, and cognitive 
impairment, the latter of which can complicate the return of a resident 
to the community from post-acute care.60 61 62 Nonetheless, 
evidence suggests that physical functional abilities, including 
mobility and self-care, are modifiable predictors of resident outcomes 
across PAC settings, including functional recovery or decline after 
post-acute care,63 64 65 66 67 rehospitalization 
rates,68 69 70 discharge to community,71 72 and 
falls.\73\
---------------------------------------------------------------------------

    \59\ High K.P., Zieman S., Gurwitz J., Hill C., Lai J., Robinson 
T., Schonberg M., Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \60\ Clouston S.A., Brewster P., Kuh D., Richards M., Cooper R., 
Hardy R., Rubin M.S., Hofer S.M. The dynamic relationship between 
physical function and cognition in longitudinal aging cohorts. 
Epidemiol Rev. 2013;35(1):33-50. doi: 10.1093/epirev/mxs004. Epub 
2013 Jan 24. PMID: 23349427; PMCID: PMC3578448.
    \61\ Michael Y.L., Colditz G.A., Coakley E., Kawachi I. Health 
behaviors, social networks, and healthy aging: cross-sectional 
evidence from the Nurses' Health Study. Qual Life Res. 1999 
Dec;8(8):711-22. doi: 10.1023/a:1008949428041. PMID: 10855345.
    \62\ High K.P., Zieman S., Gurwitz J., Hill C., Lai J., Robinson 
T., Schonberg M., Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \63\ Deutsch A., Palmer L., Vaughan M., Schwartz C., McMullen T. 
Inpatient Rehabilitation Facility Patients' Functional Abilities and 
Validity Evaluation of the Standardized Self-Care and Mobility Data 
Elements. Arch Phys Med Rehabil. 2022 Feb 11:S0003-9993(22)00205-2. 
doi: 10.1016/j.apmr.2022.01.147. Epub ahead of print. PMID: 
35157893.
    \64\ Hong I., Goodwin J.S., Reistetter T.A., Kuo Y.F., Mallinson 
T., Karmarkar A., Lin Y.L., Ottenbacher K.J. Comparison of 
Functional Status Improvements Among Patients With Stroke Receiving 
Postacute Care in Inpatient Rehabilitation vs Skilled Nursing 
Facilities. JAMA Netw Open. 2019 Dec 2;2(12):e1916646. doi: 10.1001/
jamanetworkopen.2019.16646. PMID: 31800069; PMCID: PMC6902754.
    \65\ Alcusky M., Ulbricht C.M., Lapane K.L. Postacute Care 
Setting, Facility Characteristics, and Poststroke Outcomes: A 
Systematic Review. Arch Phys Med Rehabil. 2018;99(6):1124-1140.e9. 
doi:10.1016/j.apmr.2017.09.005. PMID: 28965738; PMCID: PMC5874162.
    \66\ Chu C.H., Quan A.M.L, McGilton K.S. Depression and 
Functional Mobility Decline in Long Term Care Home Residents with 
Dementia: a Prospective Cohort Study. Can Geriatr J. 2021;24(4):325-
331. doi:10.5770/cgj.24.511. PMID: 34912487; PMCID: PMC8629506.
    \67\ Lane N.E., Stukel T.A., Boyd C.M., Wodchis W.P. Long-Term 
Care Residents' Geriatric Syndromes at Admission and Disablement 
Over Time: An Observational Cohort Study. J Gerontol A Biol Sci Med 
Sci. 2019;74(6):917-923. doi:10.1093/gerona/gly151. PMID: 29955879; 
PMCID: PMC6521919.
    \68\ Li C.Y., Haas A., Pritchard K.T., Karmarkar A., Kuo Y.F., 
Hreha K., Ottenbacher K.J. Functional Status Across Post-Acute 
Settings is Associated With 30-Day and 90-Day Hospital Readmissions. 
J Am Med Dir Assoc. 2021 Dec;22(12):2447-2453.e5. doi: 10.1016/
j.jamda.2021.07.039. Epub 2021 Aug 30. PMID: 34473961; PMCID: 
PMC8627458.
    \69\ Middleton A., Graham J.E., Lin Y.L., Goodwin J.S., Bettger 
J.P., Deutsch A., Ottenbacher K.J. Motor and Cognitive Functional 
Status Are Associated with 30-day Unplanned Rehospitalization 
Following Post-Acute Care in Medicare Fee-for-Service Beneficiaries. 
J Gen Intern Med. 2016 Dec;31(12):1427-1434. doi: 10.1007/s11606-
016-3704-4. Epub 2016 Jul 20. PMID: 27439979; PMCID: PMC5130938.
    \70\ Gustavson A.M., Malone D.J., Boxer R.S., Forster J.E., 
Stevens-Lapsley J.E. Application of High-Intensity Functional 
Resistance Training in a Skilled Nursing Facility: An Implementation 
Study. Phys Ther. 2020;100(10):1746-1758. doi: 10.1093/ptj/pzaa126. 
PMID: 32750132; PMCID: PMC7530575.
    \71\ Minor M., Jaywant A., Toglia J., Campo M., O'Dell M.W. 
Discharge Rehabilitation Measures Predict Activity Limitations in 
Patients with Stroke Six Months after Inpatient Rehabilitation. Am J 
Phys Med Rehabil. 2021 Oct 20. doi: 10.1097/PHM.0000000000001908. 
Epub ahead of print. PMID: 34686630.
    \72\ Dubin R., Veith J.M., Grippi M.A., McPeake J., Harhay M.O., 
Mikkelsen M.E. Functional Outcomes, Goals, and Goal Attainment among 
Chronically Critically Ill Long-Term Acute Care Hospital Patients. 
Ann Am Thorac Soc. 2021;18(12):2041-2048. doi:10.1513/
AnnalsATS.202011-1412OC. PMID: 33984248; PMCID: PMC8641806.
    \73\ Hoffman G.J., Liu H., Alexander N.B., Tinetti M., Braun 
T.M., Min L.C. Posthospital Fall Injuries and 30-Day Readmissions in 
Adults 65 Years and Older. JAMA Netw Open. 2019 May 3;2(5):e194276. 
doi: 10.1001/jamanetworkopen.2019.4276. PMID: 31125100; PMCID: 
PMC6632136.
---------------------------------------------------------------------------

    The implementation of interventions that improve residents' 
functional outcomes and reduce the risks of associated undesirable 
outcomes as a part of a resident-centered care plan is essential to 
maximizing functional improvement. For many people, the overall goals 
of SNF care may include optimizing functional improvement, returning to 
a previous level of independence, maintaining functional abilities, or 
avoiding institutionalization. Studies have suggested that 
rehabilitation services provided in SNFs can improve residents' 
mobility and functional independence for residents with various 
diagnoses, including cardiovascular and pulmonary conditions, 
orthopedic conditions, and stroke.74 75 Moreover, studies 
found an association between the level of therapy intensity and better 
functional improvement, suggesting that assessment of functional status 
as a health outcome in SNFs can provide valuable information in 
determining treatment decisions throughout the care continuum, such as 
the need for rehabilitation services, and discharge 
planning,76 77 78 as well as provide information to 
consumers about the effectiveness of skilled nursing services and 
rehabilitation services delivered. Because evidence shows that older 
adults experience aging heterogeneously and require individualized and 
comprehensive health care, functional status can serve as a vital 
component in informing the provision of health care and thus indicate a 
SNF's quality of care.79 80
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    \74\ Jette D.U., Warren R.L., Wirtalla C. The Relation Between 
Therapy Intensity and Outcomes of Rehabilitation in Skilled Nursing 
Facilities. Archives of Physical Medicine and Rehabilitation. 
2005;86(3):373-379. doi: 10.1016/j.apmr.2004.10.018. PMID: 15759214.
    \75\ Gustavson A.M., Malone D.J., Boxer R.S., Forster J.E., 
Stevens-Lapsley J.E. Application of High-Intensity Functional 
Resistance Training in a Skilled Nursing Facility: An Implementation 
Study. Phys Ther. 2020;100(10):1746-1758. doi: 10.1093/ptj/pzaa126. 
PMID: 32750132; PMCID: PMC7530575.
    \76\ Harry M., Woehrle T., Renier C., Furcht M., Enockson M. 
Predictive Utility of the Activity Measure for Post-Acute Care `6-
Clicks' Short Forms on Discharge Disposition and Effect on 
Readmissions: A Retrospective Observational Cohort Study. BMJ Open 
2021;11:e044278. doi: 10.1136/bmjopen-2020-044278. PMID: 33478966; 
PMCID: PMC7825271.
    \77\ Warren M., Knecht J., Verheijde J., Tompkins J. Association 
of AM-PAC ``6-Clicks'' Basic Mobility and Daily Activity Scores With 
Discharge Destination. Phys Ther. 2021 Apr;101(4):pzab043. doi: 
10.1093/ptj/pzab043. PMID: 33517463.
    \78\ Covert S., Johnson J.K., Stilphen M., Passek S., Thompson 
N.R., Katzan I. Use of the Activity Measure for Post-Acute Care ``6 
Clicks'' Basic Mobility Inpatient Short Form and National Institutes 
of Health Stroke Scale to Predict Hospital Discharge Disposition 
After Stroke. Phys Ther. 2020 Aug 31;100(9):1423-1433. doi: 10.1093/
ptj/pzaa102. PMID: 32494809.
    \79\ Criss M.G., Wingood M., Staples W., Southard V., Miller K., 
Norris T.L., Avers D., Ciolek C.H., Lewis C.B., Strunk E.R. APTA 
Geriatrics' Guiding Principles for Best Practices in Geriatric 
Physical Therapy: An Executive Summary. J Geriatr Phys Ther. 2022 
April/June;45(2):70-75. doi: 10.1519/JPT.0000000000000342. PMID: 
35384940.
    \80\ Cogan A.M., Weaver J.A., McHarg M., Leland N.E., Davidson 
L., Mallinson T. Association of Length of Stay, Recovery Rate, and 
Therapy Time per Day With Functional Outcomes After Hip Fracture 
Surgery. JAMA Netw Open. 2020 Jan 3;3(1):e1919672. doi: 10.1001/
jamanetworkopen.2019.19672. PMID: 31977059; PMCID: PMC6991278.

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[[Page 21339]]

    We are proposing to adopt the Discharge Function Score (DC 
Function) measure \81\ in the SNF QRP beginning with the FY 2025 SNF 
QRP. This assessment-based outcome measure evaluates functional status 
by calculating the percentage of Medicare Part A SNF residents who meet 
or exceed an expected discharge function score. If finalized, this 
measure would replace the topped-out Application of Functional 
Assessment/Care Plan process measure. Like the cross-setting process 
measure we are proposing to remove in section VI.C.1.c. of this 
proposed rule, the proposed DC Function measure is calculated using 
standardized resident assessment data from the current SNF assessment 
tool, the Minimum Data Set (MDS).
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    \81\ This measure was submitted to the Measures Under 
Consideration (MUC) List as the Cross-Setting Discharge Function 
Score. Subsequent to the MAP workgroup meetings, CMS modified the 
name. For more information, refer to the Discharge Function Score 
for Skilled Nursing Facilities (SNFs) Technical Report. https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
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    The DC Function measure supports our current priorities. 
Specifically, the measure aligns with the Streamline Quality 
Measurement domain in CMS's Meaningful Measurement 2.0 Framework in two 
ways. First, the proposed outcome measure would further our objective 
to prioritize outcome measures by replacing the current cross-setting 
process measure (see section VI.C.1.c of this proposed rule). This 
proposed DC Function measure uses a set of cross-setting assessment 
items which would facilitate data collection, quality measurement, 
outcome comparison, and interoperable data exchange among PAC settings; 
existing functional outcome measures do not use a set of cross-setting 
assessment items. Second, this measure adds no additional provider 
burden since it would be calculated using data from the MDS that SNFs 
are already required to collect.
    The proposed DC Function measure would also follow a calculation 
approach similar to the existing functional outcome measures, which are 
CBE endorsed, with some modifications.\82\ Specifically, the proposed 
measure (1) considers two dimensions of function (self-care and 
mobility activities) and (2) accounts for missing data by using 
statistical imputation to improve the validity of measure performance. 
The statistical imputation approach recodes missing functional status 
data to the most likely value had the status been assessed, whereas the 
current imputation approach implemented in existing functional outcome 
measures recodes missing data to the lowest functional status. A 
benefit of statistical imputation is that it uses resident 
characteristics to produce an unbiased estimate of the score on each 
item with a missing value. In contrast, the current approach treats 
residents with missing values and residents who were coded to the 
lowest functional status similarly, despite evidence suggesting varying 
measure performance between the two groups, which can lead to less 
accurate measure performances.
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    \82\ The existing measures are the IRF Functional Outcome 
Measure: Discharge Self-Care Score for Medical Rehabilitation 
Patients measure (Discharge Self-Care Score), and the Inpatient 
Rehabilitation Facility (IRF) Functional Outcome Measure: Discharge 
Mobility Score for Medical Rehabilitation Patients measure 
(Discharge Mobility Score).
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(b) Measure Testing
    Our measure developer conducted testing using FY 2019 data on the 
DC Function measure to assess validity, reliability, and reportability, 
all of which informed interested parties' feedback and Technical Expert 
Panel (TEP) input (see section VI.C.1.b.(3) of this proposed rule). 
Validity was assessed for the measure performance, the risk adjustment 
model, face validity, and statistical imputation models. Validity 
testing of measure performance entailed determining Spearman's rank 
correlations between the proposed measure's performance for providers 
with 20 or more stays and the performance of other publicly reported 
SNF quality measures. Results indicated that the measure captures the 
intended outcome based on the directionalities and strengths of 
correlation coefficients and are further detailed below in Table 12.

  Table 12--Spearman's Rank Correlation Results of DC Function Measure
               With Publicly Reported SNF Quality Measures
------------------------------------------------------------------------
        Measure--long name           Measure--short name       [rho]
------------------------------------------------------------------------
Discharge to Community--PAC SNF     Discharge to                    0.16
 QRP.                                Community.
Application of IRF Functional       Change in Self-Care             0.75
 Outcome Measure: Change in Self-    Score.
 Care Score for Medical
 Rehabilitation Patients.
Application of IRF Functional       Change in Mobility              0.78
 Outcome Measure: Change in          Score.
 Mobility Score for Medical
 Rehabilitation Patients.
Application of IRF Functional       Discharge Self-Care             0.78
 Outcome Measure: Discharge Self-    Score.
 Care Score for Medical
 Rehabilitation Patients.
Application of IRF Functional       Discharge Mobility              0.80
 Outcome Measure: Discharge          Score.
 Mobility Score for Medical
 Rehabilitation Patients.
Potentially Preventable 30-Day      Potentially                    -0.10
 Post-Discharge Readmission          Preventable
 Measure--SNF QRP.                   Readmissions within
                                     30 Days Post-
                                     Discharge.
Medicare Spending Per Beneficiary-- Medicare Spending              -0.07
 PAC SNF QRP.                        Per Beneficiary.
------------------------------------------------------------------------

    Validity testing of the risk adjustment model showed good model 
discrimination as the measure model has the predictive ability to 
distinguish residents with low expected functional capabilities from 
those with high expected functional capabilities.\83\ The ratios of 
observed-to-predicted discharge function score across eligible stays, 
by deciles of expected functional capabilities, ranged from 0.99 to 
1.01. Both the Cross-Setting Discharge Function TEPs and resident-
family feedback showed strong support for the face validity and 
importance of the proposed measure as an indicator of quality of care 
(see section VI.C.1.b.(3) of this proposed rule). Lastly, validity

[[Page 21340]]

testing of the measure's statistical imputation models indicated that 
the models demonstrate good discrimination and produce more precise and 
accurate estimates of function scores for items with missing scores 
when compared to the current imputation approach implemented in SNF QRP 
functional outcome measures, specifically the Application of IRF 
Functional Outcome Measure: Change in Self-Care Score for Medical 
Rehabilitation Patients measure (Change in Self-Care Score), the 
Application of IRF Functional Outcome Measure: Change in Mobility Score 
for Medical Rehabilitation Patients measure (Change in Mobility Score), 
the Application of IRF Functional Outcome Measure: Discharge Self-Care 
Score for Medical Rehabilitation Patients measure (Discharge Self-Care 
Score), and the Application of IRF Functional Outcome Measure: 
Discharge Mobility Score for Medical Rehabilitation Patients measure 
(Discharge Mobility Score) measures.
---------------------------------------------------------------------------

    \83\ ``Expected functional capabilities'' is defined as the 
predicted discharge function score.
---------------------------------------------------------------------------

    Reliability and reportability testing also yielded results that 
support the measure's scientific acceptability. Split-half testing 
revealed the proposed measure's good reliability, indicated by an 
intraclass correlation coefficient value of 0.81. Reportability testing 
indicated high reportability (85 percent) of SNFs meeting the public 
reporting threshold of 20 eligible stays. For additional measure 
testing details, we refer readers to the document titled Discharge 
Function Score for Skilled Nursing Facilities (SNFs) Technical 
Report.\84\
---------------------------------------------------------------------------

    \84\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report. https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

(2) Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that, absent an 
exception under section 1899B(e)(2)(B) of the Act, measures specified 
under section 1899B of the Act be endorsed by the CBE with a contract 
under section 1890(a) 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, section 
1899B(e)(2)(B) of the Act permits the Secretary to 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 CBE identified by the 
Secretary.
    The proposed DC Function measure is not CBE endorsed, so we 
considered whether there are other available measures that: (1) assess 
both functional domains of self-care and mobility in SNFs and (2) 
satisfy the requirement of the Act to specify quality measures with 
respect to functional status, cognitive function, and changes in 
function and cognitive function across the PAC settings. While the 
Application of Functional Assessment/Care Plan measure assesses both 
functional domains and satisfies the Act's requirement, this cross-
setting process measure is not CBE endorsed and the measure's 
performance among SNFs is so high and unvarying across most SNFs that 
the measure no longer offers meaningful distinctions in performance. 
Additionally, after review of other CBE endorsed measures, we were 
unable to identify any CBE endorsed measures for SNFs that meet the 
aforementioned requirements. While the SNF QRP includes CBE endorsed 
outcome measures addressing functional status,\85\ they each assess a 
single domain of function, and are not cross-setting in nature because 
they rely on functional status items not collected in all PAC settings.
---------------------------------------------------------------------------

    \85\ The measures include: Change in Self-Care Score for Medical 
Rehabilitation Patients (NQF #2633), Change in Mobility for Medical 
Rehabilitation Patients (NQF #2634), Discharge Self-Care Score for 
Medical Rehabilitation Patients (NQF #2635), Discharge Mobility 
Score for Medical Rehabilitation Patients (NQF #2636).
---------------------------------------------------------------------------

    Therefore, after consideration of other available measures, we find 
that the exception under section 1899B(e)(2)(B) of the Act applies and 
are proposing to adopt the DC Function measure, beginning with the FY 
2025 SNF QRP. We intend to submit the proposed measure to the CBE for 
consideration of endorsement when feasible.
(3) Interested Parties and Technical Expert Panel (TEP) Input
    In our development and specification of this measure, we employed a 
transparent process in which we sought input from interested parties 
and national experts and engaged in a process that allowed for pre-
rulemaking input, in accordance with section 1890A of the Act. To meet 
this requirement, we provided the following opportunities for input 
from interested parties: a focus group of patient and family/caregiver 
advocates (PFAs), two TEPs, and public comments through a request for 
information (RFI).
    First, the measure development contractor convened a PFA focus 
group, during which residents and caregivers provided support for the 
proposed measure concept. Participants emphasized the importance of 
measuring functional outcomes and found self-care and mobility to be 
critical aspects of care. Additionally, they expressed an interest in 
measures assessing the number of residents discharged from particular 
facilities with improvements in self-care and mobility, and their views 
of self-care and mobility aligned with the functional domains captured 
by the proposed measure. All feedback was used to inform measure 
development efforts.
    The measure development contractor for the DC Function measure 
subsequently convened TEPs on July 14-15, 2021 and January 26-27, 2022 
to obtain expert input on the development of a cross-setting function 
measure for use in the SNF QRP. The TEPs consisted of interested 
parties with a diverse range of expertise, including SNF and PAC 
subject matter knowledge, clinical expertise, resident and family 
perspectives, and measure development experience. The TEPs supported 
the proposed measure concept and provided substantive feedback 
regarding the measure's specifications and measure testing data.
    First, the TEP was asked whether they prefer a cross-setting 
measure that is modeled after the currently adopted Discharge Mobility 
Score and Discharge Self-Care Score measures, or one that is modeled 
after the currently adopted Change in Mobility Score and Change in 
Self-Care Score measures. With the Discharge Mobility Score and Change 
in Mobility Score measures and the Discharge Self-Care Score and Change 
in Self-Care Score measures being both highly correlated and not 
appearing to measure unique concepts, the TEP favored the Discharge 
Mobility Score and Discharge Self-Care Score measures over the Change 
in Mobility Score and Change in Self-Care Score measures and 
recommended moving forward with utilizing the Discharge Mobility Score 
and Discharge Self-Care Score measures' concepts for the development of 
a cross-setting measure.
    Second, in deciding the standardized functional assessment data 
elements to include in the cross-setting measure, the TEP recommended 
removing redundant data elements. Strong correlations between scores of 
functional items within the same functional domain suggested that 
certain items may be redundant in eliciting information about resident 
function and inclusion of these items could lead to overrepresentation 
of a particular functional area. Subsequently, our measure development 
contractor focused on the Discharge Mobility Score measure as a 
starting point for cross-setting development due to the greater number 
of cross-setting standardized functional assessment data elements for 
mobility

[[Page 21341]]

while also identifying redundant functional items that could be removed 
from a cross-setting functional measure.
    Third, the TEP supported including the cross-setting self-care 
items such that the cross-setting function measure would capture both 
self-care and mobility. Panelists agreed that self-care items added 
value to the measure and are clinically important to function. Lastly, 
the TEP provided refinements to imputation strategies to more 
accurately represent functional performance across all PAC settings, 
including the support of using statistical imputation over the current 
imputation approach implemented in existing functional outcome measures 
in the PAC QRPs. We considered all recommendations from the TEPs and we 
applied their recommendations where technically feasible and 
appropriate. Summaries of the TEP proceedings titled Technical Expert 
Panel (TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures 
Summary Report (July 2021 TEP) \86\ and Technical Expert Panel (TEP) 
for Cross-Setting Function Measure Development Summary Report (January 
2022 TEP) \87\ are available on the CMS Measures Management System 
(MMS) Hub.
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    \86\ Technical Expert Panel (TEP) for the Refinement of Long-
Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), 
Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home 
Health (HH) Function Measures Summary Report (July 2021 TEP) is 
available at https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
    \87\ Technical Expert Panel (TEP) for Cross-Setting Function 
Measure Development Summary Report (January 2022 TEP) is available 
at https://mmshub.cms.gov/sites/default/files/PAC-Function-TEP-Summary-Report-Jan2022-508.pdf.
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    Finally, we solicited feedback from interested parties on the 
importance, relevance, and applicability of a cross-setting functional 
outcome measure for SNFs through an RFI in the FY 2023 SNF PPS proposed 
rule (87 FR 22754). Commenters were supportive of a cross-setting 
functional outcome measure that is inclusive of both self-care and 
mobility items, but also provided information related to potential 
risk-adjustment methodologies, as well as other measures that could be 
used to capture functional outcomes across PAC settings (87 FR 47553).
(4) Measure Applications Partnership (MAP) Review
    In accordance with section 1890A of the Act, our pre-rulemaking 
process includes making publicly available a list of quality and 
efficiency measures, called the Measures Under Consideration (MUC) 
List, that the Secretary is considering adopting for use in Medicare 
programs. This allows interested parties to provide recommendations to 
the Secretary on the measures included on the list.
    We included the DC Function measure under the SNF QRP in the 
publicly available MUC List for December 1, 2022.\88\ After the MUC 
List was published, the CBE-convened MAP received three comments from 
interested parties in the industry on the 2022 MUC List. Two commenters 
were supportive of the measure and one was not. Among the commenters in 
support of the measure, one commenter stated that function scores are 
the most meaningful outcome measure in the SNF setting, as they not 
only assess resident outcomes but also can be used for clinical 
improvement processes. Additionally, this commenter noted the measure's 
good reliability and validity and that the measure is feasible to 
implement. The second commenter noted that the DC Function measure is 
modeled on an NQF-endorsed measure and has undergone an extensive 
formal development process. In addition, the second commenter noted 
that the DC Function measure improves on the existing functional 
outcome measures, and recommended replacing the existing function 
measures with the DC Function measure.
---------------------------------------------------------------------------

    \88\ Centers for Medicare & Medicaid Services. Overview of the 
List of Measures Under Consideration for December 1, 2022. CMS.gov. 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
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    One commenter did not support the DC Function measure and raised 
the following concerns: the ``gameability'' of the expected discharge 
score, the measure's complexity, and the difficulty of implementing a 
composite functional score.
    Shortly after, several NQF-convened MAP workgroups met to provide 
input on the DC Function measure. First, the MAP Health Equity Advisory 
Group convened on December 6-7, 2022. The MAP Health Equity Advisory 
Group did not share any health equity concerns related to the 
implementation of the DC Function measure, and only requested 
clarification regarding measure specifications from the measure 
steward. The MAP Rural Health Advisory Group met on December 8-9, 2022, 
during which some of the group's members provided support for the DC 
Function measure and other group members did not express rural health 
concerns regarding the DC Function measure.
    The MAP PAC/LTC workgroup met on December 12, 2022 and provided 
input on the DC Function measure. During this meeting, we were able to 
address several concerns raised by interested parties after the 
publication of the MUC List. Specifically, we clarified that the 
expected discharge scores are not calculated using self-reported 
functional goals, and are simply calculated by risk-adjusting the 
observed discharge scores (see section VI.C.1.b.(5) of this proposed 
rule). Therefore, we believe that these scores cannot be ``gamed'' by 
reporting less-ambitious functional goals. We also pointed out that the 
measure is highly usable as it is similar in design and complexity to 
existing function measures and that the data elements used in this 
measure are already in use on the MDS submitted by SNFs. Lastly, we 
clarified that the DC Function measure is intended to supplement, 
rather than replace, existing SNF QRP measures for self-care and 
mobility and implements improvements on the existing Discharge Self-
Care Score and Discharge Mobility Score measures that make the measure 
more valid and harder to game.
    The MAP PAC/LTC workgroup went on to discuss other concerns with 
the DC Function measure, including (1) whether the measure is cross-
setting due to denominator populations that differ among settings, (2) 
whether the measure would adequately represent the full picture of 
function, especially for residents who may have a limited potential for 
functional gain, and (3) that the range of expected scores was too 
large to offer a valid facility-level score. We clarified that the 
denominator population in each measure setting represents the assessed 
population within the setting and that the measure satisfies the 
requirement of section 1888(e)(6) of the Act for a cross-setting 
measure in the functional status domain specified under section 
1899B(c)(1) of the Act. Additionally, we noted that the TEP had 
reviewed the item set and determined that all the self-care and 
mobility items were suitable for all settings. Further, we clarified 
that, because the DC Function measure would assess whether a resident 
met or exceeded their expected discharge score, it accounts for 
residents who are not expected to improve. Lastly, we noted that the DC 
Function measure has a high degree of correlation with the existing 
function measures and that the range of expected scores is consistent 
with the range of observed scores. The PAC/LTC workgroup voted to 
support the NQF staff recommendation of

[[Page 21342]]

conditional support for rulemaking, with the condition that we seek CBE 
endorsement.
    In response to the PAC/LTC workgroup's preliminary recommendation, 
the CBE received two more comments supporting the recommendation and 
one comment that did not. Among the commenters in support of the DC 
Function measure, one supported the measure under the condition that it 
be reviewed and refined such that its implementation supports resident 
autonomy and results in care that aligns with residents' personal 
functional goals. The second commenter supported the DC Function 
measure under the condition that it produces statistically meaningful 
information that can inform improvements in care processes. This 
commenter also expressed concern that the DC Function measure is not 
truly cross-setting because it utilizes different resident populations 
and risk-adjustment models with setting-specific covariates across 
settings. Additionally, this commenter noted that using a single set of 
cross-setting section GG items is not appropriate since the items in 
our standardized patient/resident assessment data instruments may not 
be relevant across varying resident-setting populations. The commenter 
who did not support the DC Function measure raised concern with the 
usability of a composite functional score for improving functional 
performance, and expressed support for using individual measures, such 
as the current Change in Mobility Score and Change in Self-Care Score 
measures, to attain this goal.
    Finally, the MAP Coordinating Committee convened on January 24-25, 
2023, during which NQF received one comment not in support of the PAC/
LTC workgroup's preliminary recommendation for conditional support of 
the DC Function measure. The commenter expressed concern that the DC 
Function measure competes with existing self-care and mobility measures 
in the SNF QRP. We noted that we monitor measures to determine if they 
meet any of the measure removal factors, set forth in Sec.  
413.360(b)(2), and when identified, we may remove such measure(s) 
through the rulemaking process. We noted again that the TEP had 
reviewed the item set and determined that all self-care and mobility 
items were suitable for all settings. The MAP Coordinating Committee 
members expressed support for reviewing existing measures for removal 
as well as support for the DC Function measure, favoring the 
implementation of a single, standardized function measure across PAC 
settings. The MAP Coordinating Committee unanimously upheld the PAC/LTC 
workgroup recommendation of conditional support for rulemaking. We 
refer readers to the final MAP recommendations, titled 2022-2023 MAP 
Final Recommendations.\89\
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    \89\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/sites/default/files/2022-2023-MAP-Final-Recommendations-508.xlsx.
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(5) Quality Measure Calculation
    The proposed DC Function measure is an outcome measure that 
estimates the percentage of Medicare Part A SNF residents who meet or 
exceed an expected discharge score during the reporting period. The 
proposed DC Function measure's numerator is the number of SNF stays 
with an observed discharge function score that is equal to or greater 
than the calculated expected discharge function score. The observed 
discharge function score is the sum of individual function items values 
at discharge. The expected discharge function score is computed by 
risk-adjusting the observed discharge function score for each SNF stay. 
Risk adjustment controls for resident characteristics such as admission 
function score, age, and clinical conditions. The denominator is the 
total number of SNF stays with an MDS record in the measure target 
period (four rolling quarters) that do not meet the measure exclusion 
criteria. For additional details regarding the numerator, denominator, 
risk adjustment, and exclusion criteria, refer to the Discharge 
Function Score for Skilled Nursing Facilities (SNFs) Technical 
Report.\90\
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    \90\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report. https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
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    The proposed measure implements a statistical imputation approach 
for handling ``missing'' standardized functional assessment data 
elements. The coding guidance for standardized functional assessment 
data elements allows for using ``Activity Not Attempted'' (ANA) codes, 
resulting in ``missing'' information about a resident's functional 
ability on at least some items, at admission and/or discharge, for a 
substantive portion of SNF residents. Currently, functional outcome 
measures in the SNF QRP use a simple imputation method whereby all ANA 
codes or otherwise missing scores, on both admission and discharge 
records, are recoded to ``1'' or ``most dependent.'' Statistical 
imputation, on the other hand, replaces these missing values with a 
variable based on the values of other, non-missing variables in the 
assessment and on the values of other assessments which are otherwise 
similar to the assessment with a missing value. Specifically, this 
proposed DC Function measure's statistical imputation allows missing 
values (for example, the ANA codes) to be replaced with any value from 
1 to 6, based on a resident's clinical characteristics and codes 
assigned on other standardized functional assessment data elements. The 
measure implements separate imputation models for each standardized 
functional assessment data element used in the construction of the 
discharge score and the admission score. Relative to the current simple 
imputation method, this statistical imputation approach increases 
precision and accuracy and reduces the bias in estimates of missing 
item values. We refer readers to the Discharge Function Score for 
Skilled Nursing Facilities (SNFs) Technical Report \91\ for measure 
specifications and additional details.
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    \91\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report. https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
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    We invite public comment on our proposal to adopt the Discharge 
Function Score measure beginning with the FY 2025 SNF QRP.
c. Proposed Removal of the Application of Percent of Long-Term Care 
Hospital Patients With an Admission and Discharge Functional Assessment 
and a Care Plan That Addresses Function Beginning With the FY 2025 SNF 
QRP
    We are proposing to remove the Application of Percent of Long-Term 
Care Hospital Patients with an Admission and Discharge Functional 
Assessment and a Care Plan That Addresses Function (Application of 
Functional Assessment/Care Plan) measure from the SNF QRP beginning 
with the FY 2025 SNF QRP. Section 413.360(b)(2) of our regulations 
describes eight factors we consider for measure removal from the SNF 
QRP, and we believe this measure should be removed because it satisfies 
two of these factors.
    First, the Application of Functional Assessment/Care Plan measure 
meets the conditions for measure removal factor one: measure 
performance among SNFs is so high and unvarying that meaningful 
distinctions in improvements in performance can no longer be made.\92\ 
Second, this measure

[[Page 21343]]

meets the conditions for measure removal factor six: there is an 
available measure that is more strongly associated with desired 
resident functional outcomes. We believe the proposed DC Function 
measure discussed in section VI.C.1.b. of this proposed rule better 
measures functional outcomes than the current Application of Functional 
Assessment/Care Plan measure. We discuss each of these reasons in more 
detail below.
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    \92\ For more information on the factors CMS uses to base 
decisions for measure removal, we refer readers to the Code of 
Federal Regulations, Sec.  413.360(b)(2). https://www.ecfr.gov/current/title-42/chapter-IV/subchapter-B/part-413/subpart-J/section-413.360.
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    In regard to removal factor one, the Application of Functional 
Assessment/Care Plan measure has become topped out,\93\ with average 
performance rates reaching nearly 100 percent over the past 3 years 
(ranging from 99.1 percent to 98.9 percent during CYs 2019-2021).\94\ 
\95\ \96\ For the 12-month period of Q3 2020 through Q2 2021 (July 1, 
2020 through June 30, 2021), SNFs had an average score for this measure 
of 98.8 percent, with nearly 70 percent of SNFs scoring 100 percent 
\97\ and for CY 2021, SNFs had an average score of 98.9 percent, with 
nearly 63 percent of SNFs scoring 100 percent.\98\ The proximity of 
these mean rates to the maximum score of 100 percent suggests a ceiling 
effect and a lack of variation that restricts distinction among SNFs.
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    \93\ Centers for Medicare & Medicaid Services. 2022 Annual Call 
for Quality Measures Fact Sheet, p. 10. https://www.cms.gov/files/document/mips-call-quality-measures-overview-fact-sheet-2022.pdf.
    \94\ Centers for Medicare & Medicaid Services. Nursing Homes 
including Rehab Services Data Archive, 2020. Annual Files National 
Data 10-20. PQDC, https://data.cms.gov/provider-data/archived-data/nursing-homes.
    \95\ Centers for Medicare & Medicaid Services. Nursing Homes 
including Rehab Services Data Archive, 2022. Annual Files National 
Data 06-22. PQDC, https://data.cms.gov/provider-data/archived-data/nursing-homes.
    \96\ Centers for Medicare & Medicaid Services. Nursing Homes 
including Rehab Services Data Archive, 2022. Annual Files National 
Data 10-22. PQDC, https://data.cms.gov/provider-data/archived-data/nursing-homes.
    \97\ Centers for Medicare & Medicaid Services. Nursing Homes 
including Rehab Services Data Archive, 2022. Annual Files Provider 
Data 05-22. PQDC, https://data.cms.gov/provider-data/archived-data/nursing-homes.
    \98\ Centers for Medicare & Medicaid Services. Nursing Homes 
including Rehab Services Data Archive, 2022. Annual Files Provider 
Data 10-22. PQDC, https://data.cms.gov/provider-data/archived-data/nursing-homes.
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    In regard to measure removal factor six, the proposed DC Function 
measure is more strongly associated with desired resident functional 
outcomes than this current process measure, the Application of 
Functional Assessment/Care Plan measure. As described in section 
VI.C.1.b.(1)(b) of this proposed rule, the DC Function measure has the 
predictive ability to distinguish residents with low expected 
functional capabilities from those with high expected functional 
capabilities.\99\ We have been collecting standardized functional 
assessment elements across PAC settings since 2016, which has allowed 
for the development of the proposed DC Function measure and meets the 
requirements of the Act to submit standardized patient assessment data 
and other necessary data with respect to the domain of functional 
status, cognitive function, and changes in function and cognitive 
function. In light of this development, this process measure, the 
Application of Functional Assessment/Care Plan measure, which measures 
only whether a functional assessment is completed and a functional goal 
is included in the care plan, is no longer necessary, and can be 
replaced with a measure that evaluates the SNF's outcome of care on a 
resident's function.
---------------------------------------------------------------------------

    \99\ ``Expected functional capabilities'' is defined as the 
predicted discharge function score.
---------------------------------------------------------------------------

    Because the Application of Functional Assessment/Care Plan measure 
meets measure removal factors one and six, we are proposing to remove 
it from the SNF QRP beginning with the FY 2025 SNF QRP. We are also 
proposing that public reporting of the Application of Functional 
Assessment/Care Plan measure would end by the October 2024 Care Compare 
refresh or as soon as technically feasible when public reporting of the 
proposed DC Function measure would begin (see section VI.G.3. of this 
proposed rule).
    Under our proposal, SNFs would no longer be required to report a 
Self-Care Discharge Goal (that is, GG0130, Column 2) or a Mobility 
Discharge Goal (that is, GG0170, Column 2) beginning with residents 
admitted on or after October 1, 2023. We would remove the items for 
Self-Care Discharge Goal (that is, GG0130, Column 2) and Mobility 
Discharge Goal (that is, GG0170, Column 2) with the next release of the 
MDS. Under our proposal, these items would not be required to meet SNF 
QRP requirements beginning with the FY 2025 SNF QRP.
    We invite public comment on our proposal to remove the Application 
of Functional Assessment/Care Plan measure from the SNF QRP beginning 
with the FY 2025 SNF QRP.
d. Proposed Removal of the Application of IRF Functional Outcome 
Measure: Change in Self-Care Score for Medical Rehabilitation Patients 
and Removal of the Application of IRF Functional Outcome Measure: 
Change in Mobility Score for Medical Rehabilitation Patients Beginning 
With the FY 2025 SNF QRP
    We are proposing to remove the Application of the IRF Functional 
Outcome Measure: Change in Self-Care Score for Medical Rehabilitation 
Patients (Change in Self-Care Score) and the Application of IRF 
Functional Outcome Measure: Change in Mobility Score for Medical 
Rehabilitation Patients (Change in Mobility Score) measures from the 
SNF QRP beginning with the FY 2025 SNF QRP. Section 413.360(b)(2) of 
our regulations describe eight factors we consider for measure removal 
from the SNF QRP, and we believe this measure should be removed because 
it satisfies measure removal factor eight: the costs associated with a 
measure outweigh the benefits of its use in the program.
    Measure costs are multifaceted and include costs associated with 
implementing and maintaining the measure. On this basis, we are 
proposing the removal of these measures for two reasons. First, the 
costs to SNFs associated with tracking similar or duplicative measures 
in the SNF QRP outweigh any benefit that might be associated with the 
measures. Second, our costs associated with program oversight of the 
measures, including measure maintenance and public display, outweigh 
the benefit of information obtained from the measures. We discuss each 
of these in more detail below.
    We adopted the Change in Self-Care Score and Change in Mobility 
Score measures in the FY 2018 SNF PPS final rule (82 FR 36578 through 
36593), under section 1888(e)(6)(B)(i)(II) of the Act because the 
measures meet the functional status, cognitive function, and changes in 
function and cognitive function domain under section 1899B(c)(1) of the 
Act. Two additional measures addressing the functional status, 
cognitive function, and changes in function and cognitive function 
domain were adopted in the same program year: the Application of IRF 
Functional Outcome Measure: Discharge Self-Care Score for Medical 
Rehabilitation Patients (Discharge Self-Care Score) and the Application 
of IRF Functional Outcome Measure: Discharge Mobility Score for Medical 
Rehabilitation Patients (Discharge Mobility Score) measures. At the 
time

[[Page 21344]]

these four outcome measures were adopted, the amount of rehabilitation 
services received among SNF residents varied. We believed that 
measuring residents' functional changes across all SNFs on an ongoing 
basis would permit identification of SNF characteristics associated 
with better or worse resident risk adjustment outcomes as well as help 
SNFs target their own quality improvement efforts.\100\
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    \100\ Federal Register. Medicare Program; Prospective Payment 
System and Consolidated Billing for Skilled Nursing Facilities for 
FY 2018. https://www.federalregister.gov/documents/2017/05/04/2017-08521/medicare-program-prospective-payment-system-and-consolidated-billing-for-skilled-nursing-facilities#p-397.
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    We are proposing to remove the Change in Self-Care Score and Change 
in Mobility Score measures because we believe the SNF costs associated 
with tracking duplicative measures outweigh any benefit that might be 
associated with the measures. Since the adoption of these measures in 
2018, we have been monitoring the data and found that the scores for 
the two self-care functional outcome measures, Change in Self-Care 
Score and Discharge Self-Care Score, are very highly correlated in SNF 
settings (0.93).\101\ Similarly, in the monitoring data, we have found 
that the scores for the two mobility score measures, Change in Mobility 
Score and Discharge Mobility Score, are very highly correlated in SNF 
settings (0.95).\102\ The high correlation between these measures 
suggests that the Change in Self-Care Score and Discharge Self-Care 
Score and the Change in Mobility Score and the Discharge Mobility Score 
measures provide almost identical information about this dimension of 
quality to SNFs and are therefore duplicative.
---------------------------------------------------------------------------

    \101\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
    \102\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
---------------------------------------------------------------------------

    Our proposal to remove the Change in Self-Care Score and the Change 
in Mobility Score measures is supported by feedback received from the 
TEP convened for the Refinement of LTCH, IRF, SNF/NF, and HH Function 
Measures. As described in section VI.C.1.b.(3) of this proposed rule, 
the TEP panelists were presented with analyses that demonstrated the 
``Change in Score'' and ``Discharge Score'' measure sets are highly 
correlated and do not appear to measure unique concepts, and they 
subsequently articulated that it would be sensible to retire either the 
``Change in Score'' or ``Discharge Score'' measure sets for both self-
care and mobility. Based on responses to the post-TEP survey, the 
majority of panelists (nine out of 12 respondents) suggested that only 
one measure set each for self-care and mobility, respectively, is 
necessary. Of those nine respondents, six preferred retaining the 
``Discharge Score'' measure set over the ``Change in Score'' measure 
set.\103\
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    \103\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
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    Additionally, we are proposing to remove the Change in Self-Care 
Score and Change in Mobility Score measures because the program 
oversight costs outweigh the benefit of information that CMS, SNFs, and 
the public obtain from the measures. We must engage in various 
activities when administering the QRPs, such as monitoring measure 
results, producing provider preview reports, and ensuring the accuracy 
of the publicly reported data. Because these measures essentially 
provide the same information to SNFs as well as to consumers as the 
Discharge Self-Care Score and Discharge Mobility Score measures, our 
costs associated with measure maintenance and public display outweigh 
the benefit of information obtained from the measures.
    Because these measures meet the criteria for measure removal factor 
eight, we are proposing to remove the Change in Self-Care Score and 
Change in Mobility Score measures from the SNF QRP beginning with the 
FY 2025 SNF QRP. We are also proposing that public reporting of the 
Change in Self-Care Score and the Change in Mobility Score measures 
would end by the October 2024 Care Compare refresh or as soon as 
technically feasible.
    We invite public comment on our proposal to remove the Change in 
Self-Care Score and the Change in Mobility Score measures from the SNF 
QRP beginning with the FY 2025 SNF QRP.
2. SNF QRP Quality Measure Proposal Beginning With the FY 2026 SNF QRP
a. Proposed Adoption of the CoreQ: Short Stay Discharge Measure (NQF 
#2614) Beginning With the FY 2026 SNF QRP
(1) Background
    We define person-centered care as integrated healthcare services 
delivered in a setting and manner that is responsive to the individual 
and their goals, values and preferences, in a system that empowers 
residents and providers to make effective care plans together.\104\ 
Person-centered care is achieved when healthcare providers work 
collaboratively with individuals to do what is best for the health and 
well-being of individuals receiving healthcare services, and allows 
individuals to make informed decisions about their treatment that align 
with their preferences and values, such as including more choice in 
medication times, dining options, and sleeping times. Self-reported 
measures, including questionnaires assessing the individual's 
experience and satisfaction in receiving healthcare services, are 
widely used across various types of providers to assess the 
effectiveness of their person-centered care practices.
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    \104\ Centers for Medicare & Medicaid Services. Innovation 
Center. Person-Centered Care. https://innovation.cms.gov/key-concepts/person-centered-care.
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    There is currently no national standardized satisfaction 
questionnaire that measures a resident's satisfaction with the quality 
of care received by SNFs. We identified resident satisfaction with the 
quality of care received by SNFs as a measurement gap in the SNF QRP 
(see section VI.D. of this proposed rule), as did the MAP in its report 
MAP 2018 Considerations for Implementing Measure in Federal Programs: 
Post-Acute Care and Long-Term Care.\105\ Currently the SNF QRP includes 
measures of processes and outcomes that illustrate whether 
interventions are working to improve delivery of healthcare services. 
However, we believe that measuring resident satisfaction would provide 
clinical teams compelling information to use when examining the results 
of their clinical care, and can help SNFs identify deficiencies that 
other quality metrics may struggle to identify, such as

[[Page 21345]]

communication between a resident and the provider.
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    \105\ National Quality Forum. MAP 2018 Considerations for 
Implementing Measures in Federal Programs--PAC-LTC. MAP 2018 
Considerations for Implementing Measures in Federal Programs: Post-
Acute Care and Long-Term Care (cms.gov).
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    Measuring individuals' satisfaction with healthcare services using 
questionnaires has been shown to be a valid indicator for measuring 
person-centered care practices. The value of measuring consumer 
satisfaction is supported in the peer-reviewed literature using 
respondents from SNFs. One study demonstrated higher (that is, better) 
resident satisfaction is associated with the SNF receiving fewer 
deficiency citations from regulatory inspections of the SNF, and is 
also associated with higher perceived service quality.\106\ Other 
studies of the relationship between resident satisfaction and clinical 
outcomes suggest that higher overall satisfaction may contribute to 
lower 30-day readmission rates 107 108 109 and better 
adherence to treatment recommendations.110 111
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    \106\ Li Y, Li Q, Tang Y. Associations between Family Ratings on 
Satisfaction with Care and Clinical Quality-of-Care Measures for 
Nursing Home Residents. Med Care Res Rev. 2016 Feb;73(1):62-84. doi: 
10.1177/1077558715596470. Epub 2015 Jul 21. PMID: 26199288; PMCID: 
PMC4712136.
    \107\ Boulding W, Glickman SW, Manary MP, Schulman KA, Staelin 
R. Relationship between Patient Satisfaction with Inpatient Care and 
Hospital Readmission within 30 days. Am J Manag Care. 2011 
Jan;17(1):41-8. PMID: 21348567.
    \108\ Carter J, Ward C, Wexler D, Donelan K. The Association 
between Patient Experience Factors and Likelihood of 30-day 
Readmission: a Prospective Cohort Study. BMJ Qual Saf. 2018;27:683-
690. doi: 10.1136/bmjqs-2017-007184. PMID: 29146680.
    \109\ Anderson PM, Krallman R, Montgomery D, Kline-Rogers E, 
Bumpus SM. The Relationship Between Patient Satisfaction With 
Hospitalization and Outcomes Up to 6 Months Post-Discharge in 
Cardiac Patients. J Patient Exp. 2020;7(6):1685-1692. doi: 
10.117712374373520948389. PMID: 33457631 PMCID: PMC7786784.
    \110\ Barbosa CD, Balp MM, Kulich K, Germain N, Rofail D. A 
Literature Review to Explore the Link Between Treatment Satisfaction 
and Adherence, Compliance, and Persistence. Patient Prefer 
Adherence. 2012;6:39-48. doi: 10.2147/PPA.S24752. Epub 2012 Jan 13. 
PMID: 22272068; PMCID: PMC3262489.
    \111\ Krot K, Rudawska I. Is Patient Satisfaction the Key to 
Promote Compliance in Health Care Sector? Econ Sociol. 
2019;12(3):291-300. doi: 10.14254/2071-789X.2019/12-3/19.
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    We currently collect patient satisfaction data in other settings, 
such as home health, hospice, and hospital, using Consumer Assessment 
of Healthcare Providers and Systems (CAHPS[supreg]) patient experience 
surveys.\112\ These CAHPS[supreg] surveys ask individuals (or in some 
cases their families) about their experiences with, and ratings of, 
their healthcare providers, and then we publicly report the results of 
some of these patient experience surveys on Care Compare.\113\ The 
CAHPS[supreg] Nursing Home survey: Discharged Resident Instrument 
(NHCAHPS-D) was developed specifically for short-stay SNF residents 
\114\ by the Agency for Healthcare Research and Quality (AHRQ) and the 
CAHPS[supreg] consortium \115\ in collaboration with CMS. However, due 
to its length and the potential burden on SNFs and residents to 
complete it, we have not adopted it for the SNF QRP.
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    \112\ Consumer Assessment of Healthcare Providers & Systems 
(CAHPS). https://cms.gov/Research-Statistics-Data-and-Systems/Research/CAHPS.com.
    \113\ Care Compare. https://www.medicare.gov/care-compare/.
    \114\ Sangl J, Bernard S, Buchanan J, Keller S, Mitchell N, 
Castle NG, Cosenza C, Brown J, Sekscenski E, Larwood D. The 
development of a CAHPS instrument for nursing home residents. J 
Aging Soc Policy. 2007;19(2):63-82. doi: 10.1300/J031v19n02_04. 
PMID: 17409047.
    \115\ The CAHPS consortium included Harvard Medical School, The 
RAND Corporation, and Research Triangle Institute International.
---------------------------------------------------------------------------

    The CoreQ is another suite of questionnaires developed by a team of 
nursing home providers and researchers \116\ to assess satisfaction 
among residents and their families. The CoreQ suite of five measures is 
used to capture resident and family data for SNFs and assisted living 
(AL) facilities. The CoreQ was developed in 2012 by SNFs and ALs that 
partnered with researchers to develop a valid resident satisfaction 
survey for SNFs and ALs since, at the time, there was no standard 
questionnaire or set of identical questions that could be used to 
compare meaningful differences in quality between SNFs. As part of the 
development of the CoreQ measures, extensive psychometric testing was 
conducted to further refine the CoreQ measures into a parsimonious set 
of questions that capture the domain of resident and family 
satisfaction. Since 2017, the CoreQ has been used in the American 
Health Care Association (AHCA) professional recognition program, and 
several states (including New Jersey, Tennessee, and Georgia) have 
incorporated the CoreQ into their Medicaid quality incentive programs. 
In addition, 42 SNF and AL customer satisfaction vendors currently 
administer the CoreQ measures' surveys or have added the CoreQ 
questions to their questionnaires.
---------------------------------------------------------------------------

    \116\ The CoreQ was developed by Nicholas Castle, Ph.D., the 
American Health Care Association/National Center for Assisted Living 
(AHCA/NCAL), and providers with input from customer satisfaction 
vendors and residents.
---------------------------------------------------------------------------

    The CoreQ measures were designed to be different from other 
resident satisfaction surveys. The primary difference between the CoreQ 
questionnaires for residents discharged from a SNF after receiving 
short-stay services and the NHCAHPS-D survey is its length: the CoreQ 
questionnaire consists of four questions while the NHCAHPS-D has 50 
questions. Another difference is that the CoreQ measures provide one 
score that reflects a resident's overall satisfaction, while other 
satisfaction surveys do not. The CoreQ questionnaires use a 5-point 
Likert scale, and the number of respondents with an average score 
greater than or equal to 3.0 across the four questions is divided by 
the total number of valid responses to yield the SNF's satisfaction 
score.\117\
---------------------------------------------------------------------------

    \117\ What is CoreQ? www.coreq.org.
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    The CoreQ measures are also instruments that are familiar to the 
SNF community, and the CoreQ: Short Stay Discharge (CoreQ: SS DC) 
survey has already been voluntarily adopted by a large number of SNFs 
with ease. The number of SNFs voluntarily using the CoreQ: SS DC survey 
increased from 372 in the first quarter of 2016 to over 1,500 in the 
third quarter of 2019.\118\ Additionally, the measure steward, AHCA, 
reported that there have been no reported difficulties with the current 
implementation of the measure, and in fact, providers, vendors, and 
residents have reported they like the fact that the questionnaire is 
short and residents report appreciation that their satisfaction (or 
lack thereof) is being measured.
---------------------------------------------------------------------------

    \118\ 
CoreQ_Short_Stay_Appendix_Final_updated_Jan2020_Corrected_April2020_F
inalforSubmission-637229961612228954.docx. Available in the 
measure's specifications from the Patient Experience and Function 
Spring Cycle 2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/36/Spring/2020/measures/2614/shared/2614.zip.
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(a) Measure Importance
    Measuring residents' satisfaction is an effective method to assess 
whether the goals of person-centered care are achieved. Measuring 
residents' satisfaction can help SNFs identify deficiencies that the 
other quality metrics adopted in the SNF QRP cannot identify, such as 
communication between a resident and the SNF's healthcare providers. We 
believe collecting and assessing satisfaction data from SNF residents 
is important for understanding residents' experiences and preferences, 
while the collection process ensures each resident can easily and 
discreetly share their information in a manner that may help other 
potential consumers choose a SNF. Collection of resident satisfaction 
data also aligns with the person-centered care domain of CMS's 
Meaningful Measures 2.0

[[Page 21346]]

Framework,\119\ and would provide SNFs with resident-reported outcome 
information to incorporate into their quality assessment and 
performance improvement (QAPI) strategies to improve their quality of 
care.
---------------------------------------------------------------------------

    \119\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    The CoreQ: SS DC measure is a resident-reported outcome measure 
using the CoreQ: SS DC measure questionnaire which calculates the 
percentage of residents discharged in a 6-month period from a SNF, 
within 100 days of admission, who are satisfied with their SNF stay. 
The CoreQ: SS DC measure received initial NQF endorsement in 2016 and 
re-endorsement in 2020, and is a widely accepted instrument for 
measuring resident satisfaction. The measure includes a parsimonious 
set of four questions, and represents an important aspect of quality 
improvement and person-centered care. We believe it could be used to 
fill the identified gap in the SNF QRP's measure set, that is, 
measuring residents' experience of care. Therefore, we are proposing to 
adopt the CoreQ: SS DC measure for the SNF QRP beginning with the FY 
2026 SNF QRP. More information about the CoreQ questionnaire is 
available at http://www.coreq.org.
(b) Measure Testing
    The measure steward, AHCA, conducted extensive testing on the 
CoreQ: SS DC measure to assess reliability and validity prior to its 
initial NQF endorsement in 2016 and conducted additional analyses for 
the CoreQ: SS DC measure's NQF re-endorsement in 2020. These analyses 
found the CoreQ: SS DC measure to be highly reliable, valid, and 
reportable.\120\ We describe the results of these analyses in this 
section.
---------------------------------------------------------------------------

    \120\ 
CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmiss
ion-637229958835088042.docx. Available in the measure's 
specifications from the Patient Experience and Function Spring Cycle 
2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/36/Spring/2020/measures/2614/shared/2614.zip.
---------------------------------------------------------------------------

    Reliability testing included administering a pilot survey to 853 
residents, re-administering the survey to 100 of these residents, and 
then examining results at the data element level, the respondent/
questionnaire level, and the measure (that is, facility) level. The 
data elements of the CoreQ: SS DC measure were found to be highly 
repeatable, with pilot and re-administered responses agreeing between 
94 percent and 97 percent of the time, depending on the question. In 
other words, the same results were produced a high proportion of the 
time when assessed in the same population in the same time period. The 
questionnaire-level scores were also highly repeatable, with pilot and 
re-administered responses agreeing 98 percent of the time. Finally, 
reliability at the measure (that is, facility) level was also strong. 
Bootstrapping analyses in which repeated draws of residents were 
randomly selected from the measure population and scores were 
recalculated showed that 17.82 percent of scores were within 1 
percentage point of the original score, 38.14 percent were within 3 
percentage points of the original score, and 61.05 percent were within 
5 percentage points of the original score. These results demonstrate 
that the CoreQ: SS DC measure scores from the same facility are very 
stable across bootstrapped samples.
    The measure steward also conducted extensive validity testing of 
the CoreQ: SS DC measure's questionnaire, which included examination of 
the items in the questionnaire, the questionnaire format, and the 
validity of the CoreQ: SS DC measure itself.\121\
---------------------------------------------------------------------------

    \121\ 
CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmiss
ion-637229958835088042.docx. Available in the measure's 
specifications from the Patient Experience and Function Spring Cycle 
2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/36/Spring/2020/measures/2614/shared/2614.zip.
---------------------------------------------------------------------------

    First, the measure steward tested the items in the CoreQ: SS DC 
questionnaire to determine if a subset of items could reliably be used 
to produce an overall indicator of customer satisfaction. The measure 
steward started with 22 pilot questions, which assessed an individual's 
satisfaction with a number of concepts, such as food, environment, 
activities, communication, and responsiveness. Through repeated 
analyses, the number of questions was narrowed down to four. The four 
questions in the CoreQ: SS DC measure's final questionnaire were found 
to have a high degree of criterion validity, supporting that the 
instrument measures a single concept of ``customer satisfaction,'' 
rather than multiple areas of satisfaction.
    Next, the validity of the four-question CoreQ: SS DC measure 
summary score was compared to the more expansive set of 22 pilot 
questions, and was found to have a correlation value of 0.94, 
indicating that the CoreQ: SS DC measure's questionnaire consisting of 
four questions adequately represents the overall satisfaction of the 
facility.
    Finally, the measure steward found moderate levels of construct 
validity and convergent validity when the CoreQ: SS DC measure's 
relationship with Certification and Survey Provider Enhanced Reports 
(CASPER) Quality Indicators, Nursing Home Compare Quality Indicators, 
Five Star Ratings and staffing levels was examined. Therefore, the 
CoreQ: SS DC measure's questionnaire format has a high degree of both 
face validity and content validity.\122\
---------------------------------------------------------------------------

    \122\ 
CoreQ_Short_Stay_Testing_Final_v7.1_Corrected_4_20_20_FinalforSubmiss
ion-637229958835088042.docx. Available in the measure's 
specifications from the Patient Experience and Function Spring Cycle 
2020 project. Available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/36/Spring/2020/measures/2614/shared/2614.zip.
---------------------------------------------------------------------------

    Since the CoreQ: SS DC measure's original NQF endorsement in 2018, 
and its subsequent use by SNFs in quality improvement (see section 
VI.C.2.a.(1)), the measure steward conducted additional testing, 
including examining the reportability of the measure. Testing found 
that when the CoreQ: SS DC measure's questionnaires were administered 
within one week of facility discharge, the response rate was 8 percent 
higher than if it was administered 2 weeks after facility discharge. 
The measure steward analyzed responses when it allowed up to 2 months 
for a resident to respond, and found the average time to respond to the 
CoreQ: SS DC questionnaire was 2 weeks, while the response rate dropped 
much lower in the second month after facility discharge.\123\ The 
measure steward also conducted additional analyses to determine if 
there was any bias introduced into the responses to the CoreQ: SS DC's 
questionnaires that were returned during the second month, and found 
that average scores for the questionnaires returned in the second month 
were almost identical to those returned in the first month. Finally, 
the measure steward examined the time period required to collect the 
CoreQ: SS DC measure's data, and found that a majority of SNFs (that 
is, 90 percent) could achieve the minimum sample size of 20 completed 
CoreQ: SS DC questionnaires necessary for the satisfaction score to be 
reported as reliable for the SNF, when given up to 6 months. 
Additionally, once 125 consecutive completed CoreQ: SS DC

[[Page 21347]]

questionnaires were received for a particular SNF, the measure steward 
found that including additional CoreQ: SS DC questionnaires had no 
additional effect on the SNF's satisfaction score. As a result of these 
additional analyses, the recommendations to allow up to 2 months for 
CoreQ: SS DC questionnaire returns, a 6-month reporting period, and a 
ceiling of 125 completed questionnaires in a 6-month period were 
incorporated into the CoreQ: SS DC measure's specification.
---------------------------------------------------------------------------

    \123\ CoreQ Measure Worksheet-2614-Spring 2020 Cycle. Patient 
Experience and Function Project. Available at https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=93879.
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(2) Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that, absent an 
exception under section 1899B(e)(2)(B) of the Act, measures specified 
under section 1899B of the Act be endorsed by a CBE with a contract 
under section 1890(a) 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, section 
1899B(e)(2)(B) of the Act permits the Secretary to 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.
    Although the CoreQ measure is NQF-endorsed for SNFs, we did 
consider whether there were other CBE-endorsed measures capturing SNF 
resident satisfaction after discharge from a SNF in less than 100 days. 
We found several CBE measures used in other programs that assess 
resident experiences for specific resident populations, such as 
residents at end of life, residents with low back pain, and residents 
receiving psychiatric care. However, we did not find other CBE-endorsed 
measures that assess satisfaction of residents discharged within 100 
days of their admission to the SNF.
(3) Interested Parties and Technical Expert Panel (TEP) Input
    We employ a transparent process to seek input from interested 
parties and national experts and engage in a process that allows for 
pre-rulemaking input on each measure, under section 1890A of the Act. 
To meet this requirement, we solicited feedback from interested parties 
through an RFI in the FY 2022 SNF PPS proposed rule (86 FR 19998) on 
the importance, relevance, and applicability of patient-reported 
outcome (PRO) measures for SNFs. In the FY 2022 SNF PPS final rule (86 
FR 42490 through 42491), we noted that several commenters supported the 
concept of PROs while others were uncertain what we intended with the 
term ``patient-reported outcomes.'' One commenter stressed the 
importance of PROs since they determine outcomes based on information 
obtained directly from residents, and therefore provide greater insight 
into residents' experience of the outcomes of care. Another commenter 
agreed and stated that residents and caregivers are the best sources of 
information reflecting the totality of the resident experience.
    We solicited public comments from interested parties specifically 
on the inclusion of the CoreQ: SS DC measure in a future SNF QRP year 
through an RFI in the FY 2023 SNF PPS proposed rule (87 FR 22761 
through 22762). In the FY 2023 SNF PPS final rule (87 FR 47555), we 
noted that support for the CoreQ: SS DC measure specifically was mixed 
among commenters. One commenter stated that since the CoreQ: SS DC 
measure has a limited number of questions, it may not fully reflect 
resident experience at a given facility. Another commenter would not 
support the CoreQ: SS DC measure since it excludes residents who leave 
a facility against medical advice and residents with guardians, and 
this commenter stated it would be important to hear from both of these 
resident populations. Two commenters cautioned us to consider the 
burden associated with contracting with third-party vendors to 
administer the CoreQ: SS DC measure.
(4) Measure Application Partnership (MAP) Review
    The CoreQ: SS DC measure was initially endorsed by the NQF in 2016. 
It was originally reviewed by the NQF's Person- and Family-Centered 
Care (PFCC) Committee on June 6, 2016. The PFCC Committee members noted 
the importance of measuring residents' experiences and their 
preferences given health care's changing landscape. Overall, the PFCC 
Committee members liked that there was a conceptual framework 
associated with the measure submission that linked the CoreQ: SS DC 
measure with other improvement programs and organizational change 
initiatives that can help SNFs improve the quality of care they 
provide. Some PFCC Committee members expressed concern around the 
consistency of implementation across SNFs and whether scores could be 
compromised by a low response rate. All PFCC Committee members agreed 
to not risk-adjust the CoreQ: SS DC measure as it would be 
inappropriate to control for differences based on sociodemographic 
factors. We refer readers to the PFCC Final Report--Phase 3.\124\
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    \124\ The Person and Family Centered Care Final Report--Phase 3. 
https://www.qualityforum.org/Publications/2017/01/Person_and_Family_Centered_Care_Final_Report_-_Phase_3.aspx.
---------------------------------------------------------------------------

    The following year, the CoreQ: SS DC measure was included on the 
publicly available ``List of Measures under Consideration for December 
1, 2017'' \125\ for the SNF QRP Program, but the MAP did not receive 
any comments from interested parties. The CBE-convened MAP PAC/LTC 
workgroup met on December 13, 2017 and provided input on the CoreQ: SS 
DC measure. The MAP PAC/LTC workgroup offered support of the CoreQ: SS 
DC measure for rulemaking, noting that it adds value by adding 
addressing a gap area for the SNF QRP. The MAP PAC/LTC workgroup 
emphasized the value of resident-reported outcomes and noted that the 
CoreQ: SS DC measure would reflect quality of care from the resident's 
perspective. However, the MAP PAC/LTC workgroup also noted the 
potential burden of collecting the data and cautioned that the 
implementation of a new data collection requirement should be done with 
the least possible burden to the SNF.\126\
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    \125\ Centers for Medicare & Medicaid Services. List of Measures 
under Consideration for December 1, 2017. https://www.cms.gov/files/document/2017amuc-listclearancerpt.pdf.
    \126\ MAP Post-Acute Care/Long-Term Care Workgroup Project. 
2017-2018 Preliminary Recommendations. Available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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(5) Quality Measure Calculation
    The proposed CoreQ: SS DC measure is a resident-reported outcome 
measure based on the CoreQ: SS DC questionnaire that calculates the 
percentage of residents discharged in a 6-month period from a SNF, 
within 100 days of admission, who are satisfied with their SNF stay. 
Unless otherwise exempt from collecting and reporting on the CoreQ: SS 
DC measure (as discussed in section VI.F.3.b. of this proposed rule), 
we are proposing that each SNF must contract with an independent CMS-
approved CoreQ survey vendor to administer the CoreQ: SS DC measure 
questionnaire, and report the results to CMS, on behalf of the SNF (as 
specified in sections VI.F.3.a. and VI.F.3.c of this proposed rule).
    The CoreQ: SS DC measure questionnaire utilizes four questions 
(hereafter referred to as the four primary questions) and uses a 5-
point Likert scale as illustrated in Table 13.

[[Page 21348]]



         Table 13--CoreQ: Short Stay Discharge Primary Questions
------------------------------------------------------------------------
  Primary questions used in the CoreQ:     Response options for the four
   short stay discharge questionnaire         CoreQ primary questions
------------------------------------------------------------------------
1. In recommending this facility to your  Poor (1); Average (2); Good
 friends and family, how would you rate    (3); Very Good (4); Excellent
 it overall?                               (5).
2. Overall, how would you rate the
 staff?
3. How would you rate the care you
 received?
4. How would you rate how well your
 discharge needs were met?
------------------------------------------------------------------------

    We are proposing to add two ``help provided'' questions to the end 
(as questions five and six) of the CoreQ: SS DC questionnaire in order 
to determine whether to count the CoreQ: SS DC questionnaire as a 
completed questionnaire for the CoreQ: SS DC measure denominator or 
whether the questionnaire should be excluded as described in the Draft 
CoreQ: SS DC Survey Protocols and Guidelines Manual \127\ available on 
the SNF QRP Measures and Technical Information web page. These two 
``help provided'' questions are:
---------------------------------------------------------------------------

    \127\ Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. 
Chapter VIII. Data Processing and Coding. Available on the SNF QRP 
Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.
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    5. Did someone help you [the resident] complete the survey?
    6. How did that person help you [the resident]?
(a) Denominator
    The denominator is the sum of all of the questionnaire-eligible 
residents, regardless of payer, who (1) are admitted to the SNF and 
discharged within 100 days, (2) receive the CoreQ: SS DC questionnaire, 
and (3) respond to the CoreQ: SS DC questionnaire within two months of 
discharge from the SNF. However, certain residents are excluded from 
the denominator and therefore are not sent a CoreQ: SS DC questionnaire 
by the CMS-approved CoreQ survey vendor or contacted by the CMS-
approved CoreQ survey vendor for a phone interview. The residents who 
are not eligible to respond to the questionnaire, and therefore are 
excluded from the denominator for the CoreQ: SS DC measure are: (1) 
residents discharged to another hospital, another SNF, a psychiatric 
facility, an IRF, or an LTCH; (2) residents who die during their SNF 
stay; (3) residents with court-appointed legal guardians with authority 
to make decisions on behalf of the resident; (4) residents discharged 
to hospice; (5) residents who have dementia impairing their ability to 
answer the questionnaire; \128\ (6) residents who left the SNF against 
medical advice; and (7) residents with a foreign address. Additionally, 
residents are excluded from the denominator if after the CoreQ: SS DC 
questionnaire is returned: (1) the CMS-approved CoreQ survey vendor 
received the CoreQ: SS DC completed questionnaire more than two months 
after the resident was discharged from the SNF or the resident did not 
respond to attempts to conduct the interview by phone within two months 
of their SNF discharge date; (2) the CoreQ: SS DC questionnaire ``help 
provided'' question six indicates the questionnaire answers were 
answered for the resident by an individual(s) other than the resident; 
or (3) the received CoreQ: SS DC questionnaire is missing more than one 
response to the four primary questions (that is, missing two or more 
responses).
---------------------------------------------------------------------------

    \128\ Patients who have dementia impairment in their ability to 
answer the questionnaire are defined as having a Brief Interview of 
Mental Status (BIMS) score on the MDS 3.0 as 7 or lower. https://cmit.cms.gov/CMIT_public/ViewMeasure?MeasureId=3436.
---------------------------------------------------------------------------

(b) Numerator
    The numerator is the sum of the resident respondents in the 
denominator that submitted an average satisfaction score of greater 
than or equal to three for the four primary questions on the CoreQ: SS 
DC questionnaire. If a CoreQ: SS DC questionnaire is received and is 
missing only one response (out of the four primary questions in the 
questionnaire), imputation is used which represents the average value 
from the other three available responses. If a CoreQ: SS DC 
questionnaire is received and is missing more than one response to the 
four primary questions (that is, missing two or more responses), the 
CoreQ: SS DC questionnaire is excluded from the analysis (that is, no 
imputation will be used for these residents). The CoreQ: SS DC measure 
is not risk-adjusted by sociodemographic status (SDS), as the measure 
steward found no statistically significant differences (at the 5 
percent level) in scores between the SDS categories.\129\ Additional 
information about how the CoreQ: SS DC measure is calculated is 
available in the Draft CoreQ: SS DC Survey Protocols and Guidelines 
Manual \130\ on the SNF QRP Measures and Technical Information web 
page.
---------------------------------------------------------------------------

    \129\ The measure developer examined the following SDS 
categories: age, race, gender, and highest level of education. 
CoreQ: Short Stay Discharge Measure.
    \130\ Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. 
Chapter VIII. Data Processing and Coding. Available on the SNF QRP 
Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.
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    We invite public comment on our proposal to adopt the CoreQ: SS DC 
Measure beginning with the FY 2026 SNF QRP.
b. Proposed Adoption of the COVID-19 Vaccine: Percent of Patients/
Residents Who Are Up to Date Measure Beginning With the FY 2026 SNF QRP
(1) Background
    COVID-19 has been and continues to be a major challenge for PAC 
facilities, including SNFs. The Secretary first declared COVID-19 a PHE 
on January 31, 2020. As of March 23, 2023, the U.S. has reported 
103,957,053 cumulative cases of COVID-19 and 1,123,613 total deaths due 
to COVID-19.\131\ Although all age groups are at risk of contracting 
COVID-19, older persons are at a significantly higher risk of mortality 
and severe disease following infection; those over age 80 dying at five 
times the average rate.\132\ Older adults, in general, are prone to 
both acute and chronic infections owing to reduced immunity, and are a 
high-risk population.\133\ Adults age 65 and older comprise over

[[Page 21349]]

75 percent of total COVID-19 deaths despite representing 13.4 percent 
of reported cases.\134\ COVID-19 has impacted older adults' access to 
care, leading to poorer clinical outcomes, as well as taking a serious 
toll on their mental health and well-being due to social 
distancing.\135\
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    \131\ Centers for Disease Control and Prevention. COVID Data 
Tracker. https://covid.cdc.gov/covid-data-tracker/#cases_totalcases.
    \132\ United Nations. Policy Brief: The Impact of COVID-19 on 
Older Persons. May 2020. https://unsdg.un.org/sites/default/files/2020-05/Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.
    \133\ Lekamwasam R, Lekamwasam S. Effects of COVID-19 Pandemic 
on Health and Wellbeing of Older People: a Comprehensive Review. Ann 
Geriatr Med Res. 2020;24(3):166-172. doi: 10.4235/agmr.20.0027. 
PMID: 32752587; PMCID: PMC7533189.
    \134\ Centers for Disease Control and Prevention. Demographic 
Trends of COVID-19 Cases and Deaths in the US Reported to CDC. COVID 
Data Tracker. https://covid.cdc.gov/covid-data-tracker/#demographics.
    \135\ United Nations. Policy Brief: The Impact of COVID-19 on 
Older Persons. May 2020. https://unsdg.un.org/sites/default/files/2020-05/Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.
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    Since the development of the vaccines to combat COVID-19, studies 
have shown they continue to provide strong protection against severe 
disease, hospitalization, and death in adults, including during the 
predominance of Omicron BA.4 and BA.5 variants.\136\ Initial studies 
showed the efficacy of FDA-approved or authorized COVID-19 vaccines in 
preventing COVID-19. Prior to the emergence of the Delta variant of the 
virus, vaccine effectiveness against COVID-19-associated 
hospitalizations among adults age 65 and older was 91 percent for those 
who were fully vaccinated with a full mRNA vaccination (Pfizer-BioNTech 
or Moderna), and 84 percent for those receiving a viral vector vaccine 
(Janssen). Adults age 65 and older who were fully vaccinated with an 
mRNA COVID-19 vaccine had a 94 percent reduction in risk of COVID-19 
hospitalizations, while those who were partially vaccinated had a 64 
percent reduction in risk.\137\ Further, after the emergence of the 
Delta variant, vaccine effectiveness against COVID-19-associated 
hospitalizations for adults who were fully vaccinated was 76 percent 
among adults age 75 and older.\138\
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    \136\ Chalkias S, Harper C, Vrbicky K, et al. A Bivalent 
Omicron-Containing Booster Vaccine Against COVID-19. N Engl J Med. 
2022 Oct 6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 
36112399; PMCID: PMC9511634.
    \137\ Centers for Disease Control and Prevention. Fully 
Vaccinated Adults 65 and Older Are 94% Less Likely to Be 
Hospitalized with COVID-19. April 28, 2021. https://www.cdc.gov/media/releases/2021/p0428-vaccinated-adults-less-hospitalized.html.
    \138\ Interim Estimates of COVID-19 Vaccine Effectiveness 
Against COVID-19-Associated Emergency Department or Urgent Care 
Clinic Encounters and Hospitalizations Among Adults During SARS-CoV-
2 B.1.617.2 (Delta) Variant Predominance--Nine States, June-August 
2021. (Grannis SJ, et al. MMWR Morb Mortal Wkly Rep. 
2021;70(37):1291-1293. doi: 10.15585/mmwr.mm7037e2). https://www.cdc.gov/mmwr/volumes/70/wr/mm7037e2.htm.
---------------------------------------------------------------------------

    More recently, since the emergence of the Omicron variants and the 
availability of booster doses, multiple studies have shown that while 
vaccine effectiveness has waned, protection is higher among those 
receiving booster doses than among those receiving only the primary 
series.\139\ \140\ \141\ CDC data show that, among people age 50 and 
older, those who have received both a primary vaccination series and 
booster doses have a lower risk of hospitalization and dying from 
COVID-19 than their non-vaccinated counterparts.\142\ Additionally, a 
second vaccine booster dose has been shown to reduce risk of severe 
outcomes related to COVID-19, such as hospitalization or death, among 
nursing home residents. Nursing home residents who received their 
second booster dose were more likely to have additional protection 
against severe illness compared to those who received only one booster 
dose after their initial COVID-19 vaccination.\143\ Early evidence also 
demonstrates that the bivalent boosters, specifically aimed to provide 
better protection against disease caused by Omicron subvariants, have 
been quite effective, and underscores the role of up-to-date 
vaccination protocols in effectively countering the spread of COVID-
19.\144\ \145\
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    \139\ Surie D, Bonnell L, Adams K, et al. Effectiveness of 
monovalent mRNA vaccines against COVID-19-associated hospitalization 
among immunocompetent adults during BA.1/BA.2 and BA.4/BA.5 
predominant periods of SARS-CoV-2 Omicron variant in the United 
States--IVY Network, 18 States, December 26, 2021-August 31, 2022. 
MMWR Morb Mortal Wkly Rep. 2022;71(42):1327-1334. doi: 10.15585/
mmwr.mm7142a3.
    \140\ Andrews N, Stowe J, Kirsebom F, et al. Covid-19 Vaccine 
Effectiveness against the Omicron (B.1.1.529) Variant. N Engl J Med. 
2022;386(16):1532-1546. doi: 10.1056/NEJMoa2119451. PMID: 35249272; 
PMCID: PMC8908811.
    \141\ Buchan SA, Chung H, Brown KA, et al. Estimated 
Effectiveness of COVID-19 Vaccines Against Omicron or Delta 
Symptomatic Infection and Severe Outcomes. JAMA Netw Open. 
2022;5(9):e2232760. doi:10.1001/jamanetworkopen.2022.32760. PMID: 
36136332; PMCID: PMC9500552.
    \142\ Centers for Disease Control and Prevention. Rates of 
laboratory-confirmed COVID-19 hospitalizations by vaccination 
status. COVID Data Tracker. 2023, February 9. Last accessed March 
22, 2023. https://covid.cdc.gov/covid-data-tracker/#covidnet-hospitalizations-vaccination.
    \143\ Centers for Disease Control and Prevention. COVID-19 
Vaccine Effectiveness Monthly Update. COVID Data Tracker. November 
10, 2022. https://covid.cdc.gov/covid-data-tracker/#vaccine-effectiveness.
    \144\ Chalkias S, Harper C, Vrbicky K, et al. A Bivalent 
Omicron-Containing Booster Vaccine Against COVID-19. N Engl J Med. 
2022 Oct 6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 
36112399; PMCID: PMC9511634.
    \145\ Tan, S.T., Kwan, A.T., Rodr[iacute]guez-Barraquer, I. et 
al. Infectiousness of SARS-CoV-2 breakthrough infections and 
reinfections during the Omicron wave. Nat Med 29, 358-365 (2023). 
https://doi.org/10.1038/s41591-022-02138-x.
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(a) Measure Importance
    Despite the availability and demonstrated effectiveness of COVID-19 
vaccinations, significant gaps continue to exist in vaccination 
rates.\146\ As of March 22, 2023, vaccination rates among people age 65 
and older are generally high for the primary vaccination series (94.3 
percent) but lower for the first booster (73.6 percent among those who 
received a primary series) and even lower for the second booster (59.9 
percent among those who received a first booster).\147\ Additionally, 
though the uptake in boosters among people age 65 and older has been 
much higher than among people of other ages, booster uptake still 
remains relatively low compared to primary vaccination among older 
adults.\148\ Variations are also present when examining vaccination 
rates by race, gender, and geographic location.\149\ For example, 66.2 
percent of the Asian, non-Hispanic population have completed the 
primary series and 21.2 percent have received a bivalent booster dose, 
whereas 44.9 percent of the Black, non-Hispanic population have 
completed the primary series and only 8.9 percent have received the 
bivalent booster dose. Among Hispanic populations, 57.1 percent of the 
population have completed the primary series and 8.5 percent have 
received the bivalent booster dose, while in White, non-Hispanic 
populations, 51.9 percent have completed the primary series and 16.2 
percent have received a bivalent booster dose.\150\ Disparities have 
been

[[Page 21350]]

found in vaccination rates between rural and urban areas, with lower 
vaccination rates found in rural areas.\151\ \152\ Data show that 55.2 
percent of the eligible population in rural areas have completed the 
primary vaccination series, as compared to 66.5 percent of the eligible 
population in urban areas.\153\ Receipt of bivalent booster doses among 
those eligible has been lower: 18 percent of the urban population have 
received a booster dose, and 11.5 percent of the rural population have 
received a booster dose.\154\
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    \146\ Centers for Disease Control and Prevention. COVID-19 
Vaccinations in the United States. COVID Data Tracker. https://covid.cdc.gov/covid-data-tracker/#vaccinations_vacc-people-booster-percent-pop5.
    \147\ Centers for Disease Control and Prevention. COVID-19 
Vaccination Age and Sex Trends in the United States, National and 
Jurisdictional. https://data.cdc.gov/Vaccinations/COVID-19-Vaccination-Age-and-Sex-Trends-in-the-Uni/5i5k-6cmh.
    \148\ Freed M, Neuman T, Kates J, Cubanski J. Deaths Among Older 
Adults Due to COVID-19 Jumped During the Summer of 2022 Before 
Falling Somewhat in September. Kaiser Family Foundation. October 6, 
2022. https://www.kff.org/coronavirus-covid-19/issue-brief/deaths-among-older-adults-due-to-covid-19-jumped-during-the-summer-of-2022-before-falling-somewhat-in-september/.
    \149\ Saelee R, Zell E, Murthy BP, et al. Disparities in COVID-
19 Vaccination Coverage Between Urban and Rural Counties--United 
States, December 14, 2020-January 31, 2022. MMWR Morb Mortal Wkly 
Rep. 2022;71:335-340. doi: 10.15585/mmwr.mm7109a2.
    \150\ Centers for Disease Control and Prevention. Trends in 
Demographic Characteristics of People Receiving COVID-19 
Vaccinations in the United States. COVID Data Tracker. 2023, January 
20. Last accessed January 17, 2023. https://covid.cdc.gov/covid-data-tracker/#vaccination-demographics-trends.
    \151\ Saelee R, Zell E, Murthy BP, et al. Disparities in COVID-
19 Vaccination Coverage Between Urban and Rural Counties--United 
States, December 14, 2020-January 31, 2022. MMWR Morb Mortal Wkly 
Rep. 2022;71:335-340. doi: 10.15585/mmwr.mm7109a2.
    \152\ Sun Y, Monnat SM. Rural-Urban and Within-Rural Differences 
in COVID-19 Vaccination Rates. J Rural Health. 2022;38(4):916-922. 
doi: 10.1111/jrh.12625. PMID: 34555222; PMCID: PMC8661570.
    \153\ Centers for Disease Control and Prevention. Vaccination 
Equity. COVID Data Tracker; 2023, January 20. Last accessed January 
17, 2023. https://covid.cdc.gov/covid-data-tracker/#vaccination-equity.
    \154\ Centers for Disease Control and Prevention. Vaccination 
Equity. COVID Data Tracker; 2023, January 20. Last accessed January 
17, 2023. https://covid.cdc.gov/covid-data-tracker/#vaccination-equity.
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    We are proposing to adopt the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date (Patient/Resident COVID-19 
Vaccine) measure for the SNF QRP beginning with the FY 2026 SNF QRP. 
This proposed measure has the potential to increase COVID-19 
vaccination coverage of residents in SNFs, as well as prevent the 
spread of COVID-19 within the SNF resident population. This measure 
would also support the goal of the CMS Meaningful Measure Initiative 
2.0 to ``Empower consumers to make good health care choices through 
patient-directed quality measures and public transparency objectives.'' 
The proposed Patient/Resident COVID-19 Vaccine measure would be 
reported on Care Compare and would provide residents and caregivers, 
including those who are at high risk for developing serious 
complications from COVID-19, with valuable information they can 
consider when choosing a SNF. The proposed Patient/Resident COVID-19 
Vaccine measure would also facilitate resident care and care 
coordination during the hospital discharge planning process. A 
discharging hospital, in collaboration with the resident and family, 
could use this proposed measure's information on Care Compare to 
coordinate care and ensure resident preferences are considered in the 
discharge plan. Additionally, the proposed Patient/Resident COVID-19 
Vaccine measure would be an indirect measure of SNF action. Since the 
resident's COVID-19 vaccination status would be reported at discharge 
from the SNF, if a resident is not up to date with their COVID-19 
vaccine per applicable CDC guidance at the time they are admitted, the 
SNF has the opportunity to educate the resident and provide information 
on why they should become up to date with their COVID-19 vaccine. SNFs 
may also choose to administer the vaccine to the resident prior to 
their discharge from the SNF or coordinate a follow-up visit for the 
resident to obtain the vaccine at their physician's office or local 
pharmacy.
(b) Item Testing
    Our measure development contractor conducted testing of the 
proposed standardized patient/resident COVID-19 vaccination coverage 
assessment item for the Patient/Resident COVID-19 Vaccine measure using 
resident scenarios, draft guidance manual coding instructions, and 
cognitive interviews to assess SNFs' comprehension of the item and the 
associated guidance. A team of clinical experts assembled by our 
measure development contractor developed these resident scenarios to 
represent the most common scenarios that SNFs would encounter. The 
results of the item testing demonstrated that SNFs that used the draft 
guidance manual coding instructions had strong agreement (that is, 84 
percent) with the correct responses, supporting its reliability. The 
testing also provided information to improve both the item itself and 
the accompanying guidance.
(2) Competing and Related Measures
    Section 1899B(e)(2)(A) of the Act requires that, absent an 
exception under section 1899B(e)(2)(B) of the Act, each measure 
specified under section 1899B of the Act be endorsed by a CBE with a 
contract under section 1890(a) 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, section 
1899B(e)(2)(B) of the Act permits the Secretary to specify a measure 
that is not so endorsed, as long as due consideration is given to the 
measures that have been endorsed or adopted by a CBE identified by the 
Secretary. The proposed Patient/Resident COVID-19 Vaccine measure is 
not CBE endorsed and, after review of other CBE-endorsed measures, we 
were unable to identify any CBE endorsed measures for SNFs focused on 
capturing COVID-19 vaccination coverage of SNF residents. We found only 
one related measure addressing COVID-19 vaccination, the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure, adopted 
for the FY 2023 SNF QRP (86 FR 42480 through 42489), which captures the 
percentage of HCP who receive a complete COVID-19 primary vaccination 
series, but not booster doses.
    Although SNFs' COVID-19 vaccination rates are posted on Care 
Compare, these data are aggregated at the facility level, and SNFs are 
not required to report beneficiary-level data to the CDC's NHSN. The 
COVID-19 vaccination rates currently posted on Care Compare are 
obtained from CDC's NHSN, and reflect ``residents who completed primary 
vaccination series'' and ``residents who are up-to-date on their 
vaccines'' across the entire nursing home (NH) resident population. 
Residents receiving SNF care under the Medicare fee-for-service program 
differ from residents receiving long-term care in nursing homes in 
several ways. SNF residents typically enter the facility after an 
inpatient hospital stay for temporary specialized post-acute care, 
while NH residents typically have chronic or progressive medical 
conditions, requiring maintenance and supportive levels of care, and 
may reside in the NH for years. Additionally, the SNF QRP includes data 
submitted by non-CAH swing bed units whose data are only represented 
through the SNF QRP, and are not included in the COVID-19 vaccination 
data reported to the NHSN by nursing homes. The proposed Patient/
Resident COVID-19 Vaccine measure would be calculated using data 
collected on the MDS (as described in section VI.F.4. of this proposed 
rule) at the beneficiary level, which would enhance SNFs' ability to 
monitor their own infection prevention efforts with information on 
which they can act.
    Additionally, the COVID-19 reporting requirements set forth in 42 
CFR 483.80(g), finalized in the interim final rule with comment period 
(IFC) published on May 13, 2021 entitled ``Medicare and Medicaid 
Programs; COVID-19 Vaccine Requirements for Long-Term Care (LTC) 
Facilities and Intermediate Care Facilities for Individuals with 
Intellectual Disabilities (ICFs-IID) Residents, Clients, and Staff'' 
(86 FR 26315-26316) (hereafter referred to as the May 2021 IFC) are 
directed at the LTC facilities' requirements, and are separate from the 
SNF QRP. The purpose of the May 2021 IFC was to collect information 
which would allow the CDC to identify and alert us to facilities that 
may need additional

[[Page 21351]]

support in regard to vaccine administration and education.
    Instead, the purpose of the proposed Patient/Resident COVID-19 
Vaccine measure is to allow for the collection of these data under the 
SNF QRP and subsequent public reporting of SNFs' facility-level 
resident vaccination rates on Care Compare so that Medicare 
beneficiaries who require short stays can make side-by-side SNF 
comparisons. Adoption of this proposed measure would also promote 
measure harmonization across quality reporting programs and provide 
Medicare beneficiaries the information to make side-by-side comparisons 
across other facility types to facilitate informed decision making in 
an accessible and user-friendly manner. Finally, the proposed Patient/
Resident COVID-19 Vaccine measure would generate actionable data on 
vaccination rates that can be used to target quality improvement among 
SNFs.
    Therefore, after consideration of other available measures that 
assess COVID-19 vaccination rates among SNF residents, we believe the 
exception under section 1899B(e)(2)(B) of the Act applies. We intend to 
submit the proposed measure for to the CBE for consideration of 
endorsement when feasible.
(3) Interested Parties and Technical Expert Panel (TEP) Input
    First, the measure development contractor convened a focus group of 
patient and family/caregiver advocates (PFAs) to solicit input. The 
PFAs believed a measure capturing raw vaccination rate, irrespective of 
SNF action, would be most helpful in resident and caregiver decision-
making. Next, TEP meetings were held on November 19, 2021, and December 
15, 2021 to solicit feedback on the development of patient/resident 
COVID-19 vaccination measures and assessment items for the PAC 
settings. The TEP panelists voiced their support for PAC patient/
resident COVID-19 vaccination measures and agreed that developing a 
measure to report the rate of vaccination in a SNF/NH setting without 
denominator exclusions was an important goal. We considered the TEP's 
recommendations, and we applied the recommendations, where technically 
feasible and appropriate. A summary of the TEP proceedings titled 
Technical Expert Panel (TEP) for the Development of Long-Term Care 
Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled 
Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) 
COVID-19 Vaccination-Related Items and Measures Summary Report \155\ is 
available on the CMS MMS Hub.
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    \155\ Technical Expert Panel (TEP) for the Development of Long-
Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), 
Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home 
Health (HH) COVID-19 Vaccination-Related Items and Measures Summary 
Report is available on the CMS MMS Hub at https://mmshub.cms.gov/sites/default/files/COVID19-Patient-Level-Vaccination-TEP-Summary-Report-NovDec2021.pdf.
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    To seek input on the importance, relevance, and applicability of a 
patient/resident COVID-19 vaccination coverage measure, we solicited 
public comments in an RFI for publication in the FY 2023 SNF PPS 
proposed rule (87 FR 42424). Commenters were mixed on whether they 
supported the concept of a measure addressing COVID-19 vaccination 
coverage among SNF residents. Two commenters noted the measure should 
account for other variables, such as whether the vaccine was offered, 
as well as excluding residents with medical contraindications to the 
vaccine (87 FR 47553).
(4) Measure Applications Partnership (MAP) Review
    In accordance with section 1890A of the Act, the pre-rulemaking 
process includes making publicly available a list of quality and 
efficiency measures, called the Measures Under Consideration (MUC) 
List, that the Secretary is considering adopting for use in Medicare 
programs. This allows interested parties to provide recommendations to 
the Secretary on the measures included on the list. The Patient/
Resident COVID-19 Vaccine measure was included on the publicly 
available 2022 MUC List for the SNF QRP.\156\
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    \156\ Centers for Medicare & Medicaid Services. (2022). Overview 
of the List of Measures Under Consideration for December 1, 2022. 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
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    After the MUC List was published, MAP received seven comments by 
interested parties during the measure's MAP pre-rulemaking process. 
Commenters were mostly supportive of the measure and recognized the 
importance of resident COVID-19 vaccination, and that measurement and 
reporting is one important method to help healthcare organizations 
assess their performance in achieving high rates of up-to-date 
vaccination. One commenter also noted that resident engagement is 
critical at this stage of the pandemic because best available 
information indicates COVID-19 variants will continue to require 
additional boosters to avert case surges. Another commenter noted the 
benefit of less-specific criteria for inclusion in the numerator and 
denominator of the proposed Patient/Resident COVID-19 Vaccine measure, 
which would provide flexibility for the measure to remain relevant to 
current circumstances. Several commenters noted their conditional 
support, however, and raised several issues about the measure. 
Specifically, one questioned whether our intent was to replace the 
required NHSN reporting if this measure were finalized and noted it did 
not collect data on Medicare Advantage residents. Another commenter 
suggested that nursing homes might refuse to admit unvaccinated 
residents, and was concerned about the costs SNFs would incur 
purchasing the vaccines. Another commenter raised concerns about the 
measure since it did not directly measure provider actions to increase 
vaccine uptake in the numerator and that it would only collect 
vaccination information on Medicare fee-for-service residents, rather 
than all residents, regardless of payer. Finally, one commenter was 
concerned because there were no exclusions for residents who refused to 
become up to date with their COVID-19 vaccination.
    Subsequently, several MAP workgroups met to provide input on the 
measure. First, the MAP Health Equity Advisory Group convened on 
December 6, 2022. One MAP Health Equity Advisory Group member noted 
that the percentage of true contraindications for the COVID-19 vaccine 
is low, and the lack of exclusions on the measure is reasonable in 
order to minimize variation in what constitutes a 
contraindication.\157\ The MAP Rural Health Advisory Group met on 
December 8, 2022, and requested clarification of the term ``up to 
date'' and noted concerns with the perceived level of burden for 
collection of data.\158\
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    \157\ CMS Measures Management System (MMS). Measure 
Implementation: Pre-rulemaking MUC Lists and MAP reports. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \158\ CMS Measures Management System (MMS). Measure 
Implementation: Pre-rulemaking MUC Lists and MAP reports. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    Next, the MAP PAC/LTC workgroup met on December 12, 2022. The 
voting workgroup members noted the importance of reporting residents' 
vaccination status, but discussed their concerns about: (1) the 
duplication of data collection with the NHSN if an assessment-based 
measure were adopted into the SNF QRP; (2) how publicly reported rates 
would differ from the rates reported by the NHSN; (3) that the

[[Page 21352]]

Patient/Resident COVID-19 Vaccine measure does not account for resident 
refusals or those who are unable to respond; and (4) the difficulty of 
implementing the definition of ``up to date.'' We clarified during the 
PAC/LTC workgroup meeting that this measure was intended to only 
include Medicare Part A-covered SNF stays. We further noted that the 
proposed Patient/Resident COVID-19 Vaccine measure does not have 
exclusions for resident refusals because the proposed measure was 
intended to report raw rates of vaccination. We explained that raw 
rates of vaccination collected by the proposed Patient/Resident COVID-
19 Vaccine measure are important for consumer choice and PAC providers, 
including SNFs, are in a unique position to leverage their care 
processes to increase vaccination coverage in their settings to protect 
residents and prevent negative outcomes. We also clarified that the 
measure defines ``up to date'' in a manner that provides flexibility to 
reflect future changes in the CDC's guidance with respect to COVID-19 
vaccination. Finally, we clarified that, like the existing HCP COVID-19 
Vaccine measure, this measure would continue to be reported quarterly 
because the CDC has not yet determined whether COVID-19 is seasonal. 
Ultimately, the PAC/LTC workgroup did not achieve a 60 percent 
consensus vote to accept the NQF's preliminary analysis assessment of 
conditional support for the Patient/Resident COVID-19 Vaccine measure 
for SNF QRP rulemaking pending testing demonstrating the measure is 
reliable and valid, and CBE endorsement.\159\ Since the PAC/LTC 
workgroup did not reach consensus to accept, or subsequently to 
overturn the NQF staff's preliminary analysis assessment, the 
preliminary analysis assessment became the final recommendation of the 
PAC/LTC workgroup.
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    \159\ National Quality Forum MAP Post-Acute Care/Long Term Care 
Workgroup Materials. Meeting Summary--MUC Review Meeting. Accessed 
January 20, 2023. https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=97960.
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    NQF received 10 comments by interested parties in response to the 
PAC/LTC workgroup recommendations. Interested parties generally 
understood the importance of COVID-19 vaccinations' role in preventing 
the spread of COVID-19 infections, although a majority of commenters 
did not recommend the inclusion of the proposed Patient/Resident COVID-
19 Vaccine measure in the SNF QRP and raised several concerns. 
Specifically, several commenters were concerned about vaccine 
hesitancy, SNFs' inability to influence measure results based on 
factors outside of their control, duplication with NHSN reporting 
requirements, data lag in public reporting of QRP data relative to 
NHSN's current reporting of the measure, and that the proposed Patient/
Resident COVID-19 Vaccine measure is not representative of the full SNF 
population, noting that the proposed Patient/Resident COVID-19 Vaccine 
measure has not been fully tested, and encouraged us to monitor the 
measure for unintended consequences and ensure that the measure has 
meaningful results. One commenter was in support of the proposed 
Patient/Resident COVID-19 Vaccine measure and provided recommendations 
for us to consider, including an exclusion for medical 
contraindications and submitting the measure for CBE endorsement. 
Another commenter questioned why the PAC/LTC workgroup recommendation 
for SNF was not consistent with their recommendation for the proposed 
Patient/Resident COVID-19 Vaccine measure in other PAC QRPs.
    Finally, the MAP Coordinating Committee convened on January 24, 
2023, and noted concerns which were previously discussed in the PAC/LTC 
workgroup, such as the duplication of NHSN reporting requirements and 
potential for selection bias based on the resident's vaccination 
status. We were able to clarify that this measure was intended to 
include only Medicare Part A-covered SNF stays for facilities required 
to report to the SNF QRP, since the Medicare Advantage resident 
population is not part of the SNF QRP reporting requirements. We also 
noted that this measure does not have exclusions for resident refusals 
since this is a process measure intended to report raw rates of 
vaccination, and is not intended to be a measure of SNFs' actions. We 
acknowledged that a measure accounting for variables, such as SNFs' 
actions to vaccinate residents, could be important, but noted that we 
are focused on a measure which would provide and publicly report 
vaccination rates for consumers given the importance of this 
information to residents and their caregivers.
    The MAP Coordinating Committee recommended three mitigation 
strategies for the Patient/Resident COVID-19 Vaccine measure: (1) 
reconsider exclusions for medical contraindications, (ii) complete 
reliability and validity measure testing, and (iii) seek CBE 
endorsement. The Coordinating Committee ultimately reached 90 percent 
consensus on its recommendation of ``Do not Support with potential for 
mitigation.'' \160\ Despite the MAP Coordinating Committee's vote, we 
believe it is still important to propose the Patient/Resident COVID-19 
Vaccine measure for the SNF QRP. As we stated in section VI.C.2.b.(3) 
of this proposed rule, we did not include exclusions for medical 
contraindications because the PFAs we met with told us that a measure 
capturing raw vaccination rate, irrespective of any medical 
contraindications, would be most helpful in patient and family/
caregiver decision-making. We do plan to conduct reliability and 
validity measure testing once we have collected enough data, and we 
intend to submit the proposed measure to the CBE for consideration of 
endorsement when feasible. We refer readers to the final MAP 
recommendations, titled 2022-2023 MAP Final Recommendations.\161\
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    \160\ National Quality Forum Measure Applications Partnership. 
2022-2023 MAP Final Recommendations. https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=98102.
    \161\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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(5) Quality Measure Calculation
    The proposed Patient/Resident COVID-19 Vaccine measure is a process 
measure that reports the percent of stays in which residents in a SNF 
are up to date on their COVID-19 vaccinations per the CDC's latest 
guidance.\162\ This measure has no exclusions, and is not risk 
adjusted.
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    \162\ The definition of ``up to date'' may change based on CDC's 
latest guidelines and can be found on the CDC web page, ``Stay Up to 
Date with COVID-19 Vaccines Including Boosters,'' at https://www.cdc.gov/coronavirus/2019-ncov/vaccines/stay-up-to-date.html 
(updated January 9, 2023).
---------------------------------------------------------------------------

    The numerator for this measure would be the total number of 
Medicare Part A-covered SNF stays in which residents are up to date 
with their COVID-19 vaccine per CDC's latest guidance during the 
reporting year. The denominator for this measure would be the total 
number of Medicare Part A-covered SNF stays discharged during the 
reporting period. For the SNF QRP, this would apply to all freestanding 
SNFs, SNFs affiliated with acute care facilities, and all non-CAH 
swing-bed rural hospitals.
    The data source for the proposed Patient/Resident COVID-19 Vaccine 
measure is the MDS assessment instrument for SNF residents. For more 
information about the proposed data submission requirements for this 
proposed measure, we refer readers to

[[Page 21353]]

section VI.F.4. of this proposed rule. For additional technical 
information about this proposed measure, we refer readers to the draft 
measure specifications document titled Patient -Resident-COVID-Vaccine-
Draft-Specs.pdf \163\ available on the SNF QRP Measures and Technical 
Information web page.
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    \163\ Patient-Resident-COVID-Vaccine-Draft-Specs.pdf. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.
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    We invite public comments on our proposal to adopt the Patient/
Resident: COVID-19 Vaccine measure beginning with the FY 2026 SNF QRP.

D. Principles for Selecting and Prioritizing SNF QRP Quality Measures 
and Concepts Under Consideration for Future Years--Request for 
Information (RFI)

1. Background
    We have established a National Quality Strategy (NQS) \164\ for 
quality programs which supports a resilient, high-value healthcare 
system promoting quality outcomes, safety, equity, and accessibility 
for all individuals. The CMS NQS is foundational for contributing to 
improvements in health care, enhancing patient outcomes, and informing 
consumer choice. To advance these goals, leaders from across CMS have 
come together to move toward a building-block approach to streamline 
quality measures across our quality programs for the adult and 
pediatric populations. This ``Universal Foundation'' \165\ of quality 
measures will focus provider attention and reduce provider burden, as 
well as identify disparities in care, prioritize development of 
interoperable, digital quality measures, allow for cross-comparisons 
across programs, and help identify measurement gaps. The development 
and implementation of the Preliminary Adult and Pediatric Universal 
Foundation Measures will promote the best, safest, and most equitable 
care for individuals as we all come together on these critical quality 
areas.
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    \164\ Schreiber M, Richards AC, Moody-Williams J, Fleisher LA. 
The CMS National Quality Strategy: A Person-centered Approach to 
Improving Quality. Centers for Medicare & Medicaid ServicesBblog. 
June 6, 2022. https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality.
    \165\ 1 Jacobs DB, Schreiber M, Seshamani M, Tsai D, Fowler E, 
Fleisher LA. Aligning Quality Measures across CMS--The Universal 
Foundation. N Engl J Med. 2023 Mar 2; 338:776-779. doi: 10.1056/
NEJMp2215539. PMID: 36724323.
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    In alignment with the CMS NQS, the SNF QRP endeavors to move toward 
a more parsimonious set of measures while continually improving the 
quality of health care for beneficiaries. The purpose of this RFI is to 
gather input on existing gaps in SNF QRP measures and to solicit public 
comment on fully developed SNF measures that are not part of the SNF 
QRP, fully developed quality measures in other programs that may be 
appropriate for the SNF QRP, and measurement concepts that could be 
developed into SNF QRP measures, to fill these measurement gaps in the 
SNF QRP. While we will not be responding to specific comments submitted 
in response to this RFI in the FY 2024 SNF PPS final rule, we intend to 
use this input to inform future policies.
    This RFI consists of three sections. The first section discusses a 
general framework or set of principles that we could use to identify 
future SNF QRP measures. The second section draws from an environmental 
scan conducted to identify measurement gaps in the current SNF QRP, and 
measures or measure concepts that could be used to fill these gaps. The 
final section solicits public comment on: (1) the set of principles for 
selecting measures for the SNF QRP, (2) identified measurement gaps, 
and (3) measures that are available for immediate use, or that may be 
adapted or developed for use in the SNF QRP.
2. Guiding Principles for Selecting and Prioritizing Measures
    We have identified a set of principles to guide future SNF QRP 
measure set development and maintenance. These principles are intended 
to ensure that measures resonate with beneficiaries and caregivers, do 
not impose undue burden on providers, align with our PAC program goals, 
and can be readily operationalized. Specifically, measures incorporated 
into the SNF QRP should meet the following four objectives:
    1. Actionability: Optimally, SNF QRP measures should focus on 
structural elements, healthcare processes, and outcomes of care that 
have been demonstrated through clinical evidence or other best 
practices to be amenable to improvement and feasible for SNFs to 
implement.
    2. Comprehensiveness and Conciseness: SNF QRP measures should 
assess performance of all SNF core services using the smallest number 
of measures that comprehensively assess the value of care provided in 
SNF settings. Parsimony in the QRP measure set minimizes SNFs' burden 
resulting from data collection and submission.
    3. Focus on Provider Responses to Payment: The SNF PPS shapes 
incentives for care delivery. SNF performance measures should neither 
exacerbate nor induce unwanted responses to the payment systems. As 
feasible, measures should mitigate adverse incentives of the payment 
system.
    4. Compliance with CMS Statutory Requirements and Key Program 
Goals: Measures must comply with the governing statutory authorities 
and our policy to align measures with our policy initiatives, such as 
the Meaningful Measures Framework.
3. Gaps in SNF QRP Measure Set and Potential New Measures
    We conducted an environmental scan that utilized the previously 
listed principles and identified measurement gaps in the domains of 
cognitive function, behavioral and mental health, resident experience 
and resident satisfaction, and chronic conditions and pain management. 
We discuss each of these in more detail below.
a. Cognitive Function
    Illnesses associated with limitations in cognitive function, which 
may include stroke, dementia, and Alzheimer's disease, affect an 
individual's ability to think, reason, remember, problem-solve, and 
make decisions. Section 1888(e)(6)(B)(i) of the Act requires SNFs to 
submit data on quality measures under section 1899B(c)(1) of the Act, 
and cognitive function and changes in cognitive function are key 
dimensions of clinical care that are not currently represented in the 
SNF QRP.
    Two sources of information on cognitive function currently 
collected in SNFs include the Brief Interview for Mental Status (BIMS) 
and Confusion Assessment Method (CAM(copyright)).\166\ Both 
the BIMS and CAM(copyright) have been incorporated into the 
MDS as standardized patient assessment data elements. Scored by SNFs 
via direct observation, the BIMS is used to determine orientation and 
the ability to register and recall new information. The 
CAM(copyright) assesses the presence of delirium and 
inattention, and level of consciousness. While data from the BIMS and 
CAM(copyright) are collected and reported via the MDS, these 
items have not been developed into specific quality measures for the 
SNF QRP.
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    \166\ Centers for Medicare & Medicaid Services. Minimum Data Set 
(MDS) 3.0 Technical Information. Effective October 1, 2020. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqimds30technicalinformation.
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    Alternative sources of information on cognitive function include 
the Patient-Reported Outcomes Measurement

[[Page 21354]]

Information Set (PROMIS) Cognitive Function forms and the PROMIS Neuro-
Quality of Life (Neuro-QoL) measures.167 168 Developed and 
tested with a broad range of resident populations, PROMIS Cognitive 
Function assesses cognitive functioning using items related to resident 
perceptions regarding performance of cognitive tasks, such as memory 
and concentration, and perceptions of changes in these activities. The 
Neuro-QoL, which was specifically designed for use in residents with 
neurological conditions, assesses resident perceptions regarding oral 
expression, memory, attention, decision-making, planning, and 
organization.
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    \167\ HealthMeasures. List of Adult Measures: Available Neuro-
QoLTM Measures for Adult Self-Report. https://www.healthmeasures.net/explore-measurement-systems/neuro-qol/intro-to-neuro-qol/list-of-adult-measures.
    \168\ HealthMeasures. List of Adult Measures: Available 
PROMIS[supreg] Measures for Adults. https://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/list-of-adult-measures.
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    The BIMS, CAM(copyright), PROMIS Cognitive Function 
short forms, and PROMIS Neuro-QoL include items representing different 
aspects of cognitive function, from which quality measures may be 
constructed. Although these instruments have been subjected to 
feasibility, reliability, and validity testing, additional development 
and testing would be required prior to transforming the concepts 
reflected in the BIMS and CAM(copyright) (for example, 
temporal orientation, recall) into fully specified measures for 
implementation in the SNF QRP.
    Through this RFI, we are requesting comment on the availability of 
cognitive functioning measures outside of the SNF QRP that may be 
available for immediate use in the SNF QRP, or that may be adapted or 
developed for use in the SNF QRP, using the BIMS, 
CAM(copyright), PROMIS Cognitive Function short forms, and 
PROMIS Neuro-QoL, or other instruments. In addition to comment on 
specific measures and instruments, we seek input on the feasibility of 
measuring improvement in cognitive functioning during a SNF stay, which 
averages approximately 30 days; the cognitive skills (for example, 
executive functions) that are more likely to improve during a SNF stay; 
conditions for which measures of maintenance--rather than improvement 
in cognitive functioning--are more practical; and the types of 
intervention that have been demonstrated to assist in improving or 
maintaining cognitive functioning.
b. Behavioral and Mental Health
    Estimates suggest that one in five Medicare beneficiaries has a 
``common mental health disorder'' and nearly 8 percent have a serious 
mental illness.\169\ Substance use disorders (SUDs) are also common. 
Research estimates that approximately 1.7 million Medicare 
beneficiaries (8 percent) reported a SUD in the past year, with 77 
percent attributed to alcohol use and 16 percent to prescription drug 
use.\170\ In some instances, such as following a knee replacement or 
stroke, residents may develop depression, anxiety, and/or SUDs. In 
other instances, residents may have been dealing with mental or 
behavioral health issues or SUDs long before their post-acute 
admission. Left unmanaged, however, these conditions could make it 
difficult for affected residents to actively participate in medical 
rehabilitation or to adhere to the prescribed treatment regimen, 
thereby contributing to poor health outcomes.
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    \169\ Figueroa JF, Phelan J, Orav EJ, Patel V, Jha AK. 
Association of Mental Health Disorders with Health Care Spending in 
the Medicare Population. JAMA Netw Open. 2020;3(3):e201210. doi: 
10.1001/jamanetworkopen.2020.1210. PMID: 32191329; PMCID: 
PMC7082719.
    \170\ Parish WJ, Mark TL, Weber EM, Steinberg DG. Substance Use 
Disorders Among Medicare Beneficiaries: Prevalence, Mental and 
Physical Comorbidities, and Treatment Barriers. Am J Prev Med. 2022 
Aug;63(2):225-232. doi: 10.1016/j.amepre.2022.01.021. PMID: 
35331570.
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    Information on the availability and appropriateness of behavioral 
health measures in post-acute settings is limited, and the 2021 
National Impact Assessment of the CMS Quality Measures Report \171\ 
identified PAC program measurement gaps in the areas of behavioral and 
mental health. Among the mental health quality measures in current use, 
the Home Health QRP assesses the extent to which residents have been 
screened for depression and a follow-up plan is documented.\172\ 
Although it may be possible to adapt this measure for use in other PAC 
settings, this process measure does not directly assess performance in 
the management of depression and related mental health concerns.
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    \171\ Centers for Medicare & Medicaid Services. 2021 National 
Impact Assessment of the Centers for Medicare & Medicaid Services 
(CMS) Quality Measures Report. June 2021. https://www.cms.gov/files/document/2021-national-impact-assessment-report.pdf.
    \172\ Depression Screening Conducted and Follow-Up Plan 
Documented. https://cmit.cms.gov/cmit/#/MeasureView?variantId=3102&sectionNumber=1.
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    Other instruments that may be adapted to assess management of 
mental health, behavioral health, or SUDs in PAC settings include the 
CAHPS Experience of Care and Health Outcomes Survey (ECHO), which 
consists of a series of questions that may be used to understand 
residents' perspectives concerning mental health services received; 
\173\ the PROMIS \174\ suite of instruments that may be used to monitor 
and evaluate mental health and quality of life; and the National 
Institutes of Health (NIH) Toolbox for the Assessment of Neurological 
and Behavioral Health Function,\175\ which was commissioned by the NIH 
Blueprint for Neuroscience Research and includes both stand-alone 
measures and batteries of measures to assess emotional function and 
psychological well-being.
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    \173\ Agency for Healthcare Research and Quality. CAHPS Mental 
Health Care Surveys. May 2022. https://www.ahrq.gov/cahps/surveys-guidance/echo/index.html.
    \174\ HealthMeasures. Intro to PROMIS[supreg]. January 10, 2023. 
https://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis.
    \175\ HealthMeasures. NIH Toolbox. February 9, 2023. https://www.healthmeasures.net/explore-measurement-systems/nih-toolbox.
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    Like mental health issues, SUDs have been under-studied in the SNF 
and other PAC settings, even though they are among the fastest-growing 
disorders in the community-dwelling older adult 
population.176 177 Left untreated, SUDs can lead to overdose 
deaths, emergency department visits, and hospitalizations. The 
Substance Abuse and Mental Health Services Administration (SAMHSA) was 
established by Congress in 1992 to make substance use and mental 
disorder information, services, and research more accessible. As part 
of its work, SAMHSA developed the Screening, Brief Intervention, and 
Referral to Treatment (SBIRT) approach to support providers in using 
early intervention with at-risk substance users before more severe 
consequences occur, and has a number of resources available.\178\
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    \176\ Desai A, Grossberg G. Substance Use Disorders in Postacute 
and Long-Term Care Settings. Psychiatr Clin North Am. 2022 
Sep;45(3):467-482. doi: 10.1016/j.psc.2022.05.005. PMID: 36055733.
    \177\ Sorrell JM. Substance Use Disorders in Long-Term Care 
Settings: A Crisis of Care for Older Adults. J Psychosoc Nurs Ment 
Health Serv. 2017 Jan 1;55(1):24-27. doi: 10.3928/02793695-20170119-
08. PMID: 28135388.
    \178\ Substance Abuse and Mental Health Services Administration. 
Resources for Screening, Brief Intervention, and Referral to 
Treatment (SBIRT). Available at https://www.samhsa.gov/sbirt/resources.
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    We seek feedback on these and other measures or instruments that 
may be directly applied, adapted, or developed for use in the SNF QRP. 
Further, we seek comments on the degree to which measures have been or 
will require validation and testing prior to application in the SNF 
QRP. We seek input on the availability of data, the manner in which 
data could be

[[Page 21355]]

collected and reported to us, and the burden imposed on SNFs.
c. Resident Experience and Resident Satisfaction
    Resident experience measures focus on how residents experienced or 
perceived selected aspects of their care, whereas resident satisfaction 
measures focus on whether a resident's expectations were met. 
Information on resident experience of care is typically collected via a 
number of instruments that rely on resident self-reported data. The 
most prominent among these is the CAHPS suite of surveys. The Nursing 
Home Discharged Resident CAHPS,179 180 which is intended for 
use with residents who had a length of stay less than 100 days, 
measures resident experience in terms of the care environment, 
communication with staff, respect received, quality of care, autonomy, 
and activities. The CoreQ questionnaires are another set of resident 
satisfaction tools. The CoreQ is a suite of five measures used to 
capture resident and family data for SNFs and assisted living (AL) 
facilities. The CoreQ: SS DC measure assesses the level of satisfaction 
among SNF short-stay (less than 100 days) residents, and we are 
proposing to adopt it for the SNF QRP beginning with the FY 2026 SNF 
QRP (see section VI.C.2.a. of this proposed rule).
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    \179\ Agency for Healthcare Research and Quality. CAHPS Nursing 
Home Surveys. Content last reviewed April 2020. https://www.ahrq.gov/cahps/surveys-guidance/nh/index.html.
    \180\ In addition to the Discharged Resident Survey, Nursing 
Home CAHPS includes two other instruments, a Long-Stay Survey for 
Residents with a length of stay of 100 days or more, and a Family 
Member survey.
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    We seek comment on the feasibility and challenges of adapting 
existing resident experience measures for use in the SNF QRP, as well 
as on the value of adapting and/or developing other resident experience 
and satisfaction measures beyond the CoreQ: SS DC measure proposed for 
the SNF QRP in this proposed rule. We also seek input on the challenges 
of adapting existing resident experience measures and instruments, the 
challenges of collecting and reporting resident experience and resident 
satisfaction data, and the extent to which resident experience measures 
offer SNFs sufficient information to assist in quality improvement.
d. Chronic Conditions and Pain Management
    Despite the availability of measures focused on SNF clinical care 
services, existing SNF QRP measures do not directly address aspects of 
care rendered to populations with chronic conditions or SNFs' 
management of residents' pain. For example, the measures that address 
respiratory care relate to staff influenza and COVID-19 vaccination 
status. Although these measures target provider performance in 
preventing a respiratory illness with a potentially severe impact on 
morbidity and mortality, current measures fail to capture SNF 
performance in treatment or management of residents' chronic 
respiratory conditions, such as chronic obstructive pulmonary disease 
(COPD) or asthma.
    Existing measures also fail to capture SNF actions concisely for 
pain management even though pain has been demonstrated to contribute to 
falls with major injury and restrictions in mobility and daily 
activity. However, a host of other factors also contribute to these 
measure domains, making it difficult to directly link provider actions 
to performance. Instead, a measure of SNFs' actions in reducing pain 
interference in daily activities, including the ability to sleep, would 
be a more concise measure of pain management. Beginning October 1, 
2023, SNFs will begin collecting new standardized resident assessment 
data elements, including items that assess pain interference with (1) 
daily activities, (2) sleep, and (3) participation in therapy, 
providing an opportunity to develop more-concise measures of provider 
performance (84 FR 38798 through 38801).
    Through this RFI, we are seeking input on measures of chronic 
condition and pain management that may be used to assess SNF 
performance. Additionally, we seek general comment on the feasibility 
and challenges of measuring and reporting SNF performance on existing 
QRP measures, such as the Discharge Self-Care Score for Medical 
Rehabilitation Patients and Discharge Mobility Score for Medical 
Rehabilitation Patients measures, for subgroups of residents defined by 
type of chronic condition. As examples, measures could assess discharge 
outcomes for SNF residents with a hip fracture diagnosis or for 
residents admitted with a diagnosis of congestive heart failure.
4. Solicitation of Comments
    We invite general comments on the principles for identifying SNF 
QRP measures, as well as additional thoughts about measurement gaps, 
and suitable measures for filling these gaps. Specifically, we solicit 
comment on the following questions:
     Principles for Selecting and Prioritizing QRP Measures.
    ++ To what extent do you agree with the principles for selecting 
and prioritizing measures?
    ++ Are there principles that you believe CMS should eliminate from 
the measure selection criteria?
    ++ Are there principles that you believe CMS should add to the 
measure selection criteria?
     SNF QRP Measurement Gaps.
    ++ We request input on the identified measurement gaps, including 
in the areas of cognitive function, behavioral and mental health, 
resident experience and resident satisfaction, chronic conditions and 
pain management.
    ++ Are there gaps in the SNF QRP measures that have not been 
identified in this RFI?
     Measures and Measure Concepts Recommended for Use in the 
SNF QRP.
    ++ Are there measures that you believe are either currently 
available for use, or that could be adapted or developed for use in the 
SNF QRP program to assess performance in the areas of (1) cognitive 
functioning, (2) behavioral and mental health, (3) resident experience 
and resident satisfaction, (4) chronic conditions, (5) pain management, 
or (6) other areas not mentioned in this RFI?
    We also seek input on data available to develop measures, 
approaches for data collection, perceived challenges or barriers, and 
approaches for addressing challenges.

E. Health Equity Update

1. Background
    In the FY 2023 SNF PPS proposed rule (87 FR 22754 through 22760), 
we included an RFI entitled ``Overarching Principles for Measuring 
Equity and Healthcare Quality Disparities Across CMS Quality 
Programs.'' 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, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes.'' \181\ 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 and models, eliminating avoidable 
differences in health outcomes experienced by people who are 
disadvantaged or underserved, and providing the care and support that 
our

[[Page 21356]]

beneficiaries need to thrive. Our goals outlined in the CMS Framework 
for Health Equity 2022-2023 \182\ are in line with Executive Order 
13985, ``Advancing Racial Equity and Support for Underserved 
Communities Through the Federal Government.'' \183\ The goals included 
in the CMS Framework for Health Equity serve to further advance health 
equity, expand coverage, and improve health outcomes for the more than 
170 million individuals supported by our programs, and set a foundation 
and priorities for our work, including: strengthening our 
infrastructure for assessment; creating synergies across the healthcare 
system to drive structural change; and identifying and working to 
eliminate barriers to CMS-supported benefits, services, and coverage.
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    \181\ Centers for Medicare & Medicaid Services. Health Equity. 
https://www.cms.gov/pillar/health-equity. Accessed February 1, 2023.
    \182\ Centers for Medicare & Medicaid Services. CMS Framework 
for Health Equity 2022-2032. https://www.cms.gov/files/document/cms-framework-health-equity-2022.pdf.
    \183\ Executive Order 13985, ``Advancing Racial Equity and 
Support for Underserved Communities Through the Federal 
Government,'' can be found at https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/.
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    In addition to the CMS Framework for Health Equity, we seek to 
advance health equity and whole-person care as one of eight goals 
comprising the CMS National Quality Strategy (NQS).\184\ The NQS 
identifies a wide range of potential quality levers that can support 
our advancement of equity, including: (1) establishing a standardized 
approach for resident-reported data and stratification; (2) employing 
quality and value-based programs to address closing equity gaps; and 
(3) developing equity-focused data collections, analysis, regulations, 
oversight strategies, and quality improvement initiatives.
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    \184\ Centers for Medicare & Medicaid Services. What Is the CMS 
Quality Strategy? https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/CMS-Quality-Strategy.
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    A goal of this NQS is to address persistent disparities that 
underlie our healthcare system. Racial disparities in health, in 
particular, are estimated to cost the U.S. $93 billion in excess 
medical costs and $42 billion in lost productivity per year, in 
addition to economic losses due to premature deaths.\185\ At the same 
time, racial and ethnic diversity has increased in recent years with an 
increase in the percentage of people who identify as two or more races 
accounting for most of the change, rising from 2.9 percent to 10.2 
percent between 2010 and 2020.\186\ Therefore, we need to consider ways 
to reduce disparities, achieve equity, and support our diverse 
beneficiary population through the way we measure quality and display 
the data.
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    \185\ Turner A. The Business Case for Racial Equity: A Strategy 
for Growth. April 24, 2018. W.K. Kellogg Foundation and Altarum. 
https://altarum.org/RacialEquity2018.
    \186\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. Content last reviewed 
November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
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    We solicited public comments via the aforementioned RFI on changes 
that we should consider in order to advance health equity. We refer 
readers to the FY 2023 SNF PPS final rule (87 FR 47553 through 47555) 
for a summary of the public comments and suggestions we received in 
response to the health equity RFI. We will take these comments into 
account as we continue to work to develop policies, quality measures, 
and measurement strategies on this important topic.
2. Anticipated Future State
    We are committed to developing approaches to meaningfully 
incorporate the advancement of health equity into the SNF QRP. One 
option we are considering is including social determinants of health 
(SDOH) as part of new quality measures.
    Social determinants of health 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. They may have a stronger influence on the 
population's health and well-being than services delivered by 
practitioners and healthcare delivery organizations.\187\ Measure 
stratification is important for understanding differences in outcomes 
across different groups. For example, when ``pediatric measures over 
the past two decades are stratified by race, ethnicity, and income, 
they show that outcomes for children in the lowest income households 
and for Black and Hispanic children have improved faster than outcomes 
for children in the highest income households or for White children, 
thus narrowing an important health disparity.\188\ This analysis and 
comparison of the SDOH items in the assessment instruments support our 
desire to understand the benefits of measure stratification. Hospital 
providers receive such information in their confidential feedback 
reports and we think this learning opportunity would benefit post-acute 
care providers. The goals of the confidential reporting are to provide 
SNFs with their results; educate SNFs and offer the opportunity to ask 
questions; and solicit feedback from SNFs for future enhancements to 
the methods.
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    \187\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
    \188\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. Content last reviewed 
November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
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    We are considering whether health equity measures we have adopted 
for other settings, such as hospitals, could be adopted in post-acute 
care settings. We are exploring ways to incorporate SDOH elements into 
the measure specifications. For example, we could consider a future 
health equity measure like screening for social needs and 
interventions. With 30 percent to 55 percent of health outcomes 
attributed to SDOH,\189\ a measure capturing and addressing SDOH could 
encourage SNFs to identify residents' specific needs and connect them 
with the community resources necessary to overcome social barriers to 
their wellness. We could specify a health equity measure using the same 
SDOH data items that we currently collect as standardized patient 
assessment data elements under the SNF. These SDOH data items assess 
health literacy, social isolation, transportation problems, and 
preferred language (including need or want of an interpreter). We also 
see value in aligning SDOH data items across all care settings as we 
develop future health equity quality measures under our SNF QRP 
statutory authority. This would further the NQS to align quality 
measures across our programs as part of the Universal Foundation.\190\
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    \189\ World Health Organization. Social Determinants of Health. 
https://www.who.int/westernpacific/healthtopics/social-determinants-of-health.
    \190\ Jacobs DB, Schreiber M, Seshamani M, Tsai D, Fowler E, 
Fleisher LA. Aligning Quality Measures across CMS--The Universal 
Foundation. N Engl J Med. 2023 Mar 2;338:776-779. doi: 10.1056/
NEJMp2215539. PMID: 36724323.
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    As we move this important work forward, we will continue to take 
input from interested parties.

F. Form, Manner, and Timing of Data Submission Under the SNF QRP

1. Background
    We refer readers to the current regulatory text at Sec.  413.360(b) 
for information regarding the policies for reporting SNF QRP data.

[[Page 21357]]

2. Proposed Reporting Schedule for the Minimum Data Set (MDS) 
Assessment Data for the Discharge Function Score Measure Beginning With 
the FY 2025 SNF QRP
    As discussed in section VI.C.1.b. of this proposed rule, we are 
proposing to adopt the DC Function measure beginning with the FY 2025 
SNF QRP. We are proposing that SNFs would be required to report these 
MDS assessment data beginning with residents admitted and discharged on 
October 1, 2023 for purposes of the FY 2025 SNF QRP. Starting in CY 
2024, SNFs would be required to submit data for the entire calendar 
year beginning with the FY 2026 SNF QRP. Because the DC Function 
measure is calculated based on data that are currently submitted to the 
Medicare program, there would be no new burden associated with data 
collection for this measure.
    We invite public comment on this proposal.
3. Proposed Method of Data Submission and Reporting Schedule for the 
CoreQ: Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP
a. Proposed Method of Data Submission To Meet SNF QRP Requirements 
Beginning With the FY 2026 Program Year
    As discussed in section VI.C.2.a. of this proposed rule, we are 
proposing to adopt the CoreQ: SS DC measure beginning with the FY 2026 
SNF QRP. We propose that Medicare-certified SNFs and all non-CAH swing 
bed rural hospitals would be required to contract with a third-party 
vendor that is CMS-trained and approved to administer the CoreQ: SS DC 
survey on their behalf (referred to as a ``CMS-approved CoreQ survey 
vendor''). SNFs would be required to contract with a CMS-approved CoreQ 
survey vendor to ensure that the data are collected by an independent 
organization that is trained to collect this type of data, and given 
the independence of the CMS-approved CoreQ survey vendor from the SNF, 
ensure that the data collected are unbiased. The CMS-approved CoreQ 
survey vendor would be the business associate of the SNF and follow the 
minimum business requirements described in the Draft CoreQ: SS DC 
Survey Protocols and Guidelines Manual.\191\ It is important that 
respondents to the CoreQ: SS DC measure questionnaire are comfortable 
sharing their experiences with persons not directly involved in 
providing the care. This method of data collection has been used 
successfully in other settings, including for Medicare-certified home 
health agencies and hospices. The goal is to ensure that we have 
comparable data across all SNFs.
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    \191\ Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. 
Chapter III. CoreQ Survey Participation Requirements. Available on 
the SNF QRP Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.
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    CMS-approved CoreQ survey vendors administering the CoreQ: SS DC 
survey would be required to offer a toll-free assistance line and an 
electronic mail address which respondents could use to seek help. The 
toll-free telephone line must have staff that can respond to questions 
in any language in which the CMS-approved CoreQ survey vendor is 
offering the CoreQ: SS DC survey. CMS-approved CoreQ survey vendors 
must accommodate alternate telephone communications, including a 
teletypewriter (TTY). Interested vendors may apply to become a CMS-
approved CoreQ survey vendor beginning in Fall 2023. There will be a 
web page devoted specifically to the SNF CoreQ: SS DC survey and it 
will include information including the application process. SNFs 
interested in viewing similar model web pages are encouraged to visit 
the Hospital CAHPS website at https://hcahpsonline.org or the Home 
Health CAHPS website at https://homehealthcahps.org.
    We propose to require SNFs to use the protocols and guidelines for 
the proposed CoreQ: SS DC measure as defined by the Draft CoreQ: SS 
Survey Protocols and Guidelines Manual in effect at the time the 
questionnaires are sent to eligible residents. The Draft CoreQ: SS DC 
Survey Protocols and Guidelines Manual is available on the SNF QRP 
Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information. We propose that CMS-approved CoreQ survey vendors and SNFs 
be required to participate in CoreQ: SS DC measure oversight activities 
to ensure compliance with the protocols, guidelines, and questionnaire 
requirements. The purpose of the oversight activities is to ensure that 
SNFs and CMS-approved CoreQ survey vendors follow the procedures in the 
Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.
    We also propose that all CMS-approved CoreQ survey vendors develop 
a Quality Assurance Plan (QAP) for CoreQ: SS DC survey administration 
in accordance with the Draft CoreQ: SS DC Survey Protocols and 
Guidelines Manual.
    A list of CMS-approved CoreQ survey vendors would be provided on 
the website devoted specifically to the SNF CoreQ: SS DC Survey as soon 
as technically feasible.
    At Sec.  413.360, we also propose to redesignate paragraph (b)(2) 
as paragraph (b)(3) and add new paragraph (b)(2) for the CoreQ: SS DC 
measure's data submission requirements. Finally, we propose to codify 
the requirements for being a CMS-approved CoreQ: SS DC survey vendor at 
paragraphs (b)(2)(ii) through (b)(2)(iii) in regulation. The proposed 
revisions are outlined in paragraph (b)(2) in the regulation text of 
this proposed rule.
    We invite public comment on this proposal to require Medicare-
certified SNFs to contract with a third-party vendor to administer the 
CoreQ: SS DC measure questionnaire on their behalf beginning with the 
FY 2026 SNF QRP.
b. Proposed Exemptions for the CoreQ: SS DC Measure Reporting 
Requirements Beginning With the FY 2026 Program Year
(1) Low Volume Exemptions
    We are aware that there is a wide variation in the size of 
Medicare-certified SNFs. Therefore, we propose that SNFs with less than 
60 residents, regardless of payer, discharged within 100 days of SNF 
admission in the prior calendar year would be exempt from the CoreQ: SS 
DC measure data collection and reporting requirements. A SNF's total 
number of short-stay discharged residents for the period of January 1 
through December 31 for a given year would be used to determine if the 
SNF would have to participate in the CoreQ: SS DC measure in the next 
calendar year. To qualify for the exemptions, SNFs would be required to 
submit their request using the Participation Exemption Request form no 
later than December 31 of the CY prior to the reporting CY. These forms 
would be made available on a web page devoted to the SNF CoreQ: SS DC 
Survey.
(2) New Provider Exemptions
    We also propose that newly Medicare-certified SNFs (that is, those 
certified on or after January 1, 2024) be excluded from the CoreQ: SS 
DC measure reporting requirement for CY 2024, because there would be no 
information from the previous CY to determine

[[Page 21358]]

whether the SNF would be required to report or exempt from reporting 
the CoreQ: SS DC measure.
    In future years, we are proposing that SNFs certified for Medicare 
participation on or after January 1 of the reporting year would be 
excluded from reporting on the CoreQ: SS DC measure for the applicable 
SNF QRP program year. For example, if a SNF is certified for Medicare 
participation on November 1, 2024, it would be excluded from the CY 
2024 CoreQ: SS DC measure reporting requirement, and therefore, would 
not be subject to any payment penalty related to the SNF not reporting 
on the CoreQ: SS DC measure in CY 2024 for the FY 2026 SNF QRP. 
However, if a SNF is certified for Medicare participation on November 
1, 2024, it would be required to meet the CoreQ: SS DC measure 
reporting requirements in CY 2025 for the FY 2027 SNF QRP unless it 
expects to meet the low volume exemption as described in section 
VI.F.3.b.(2) of this proposed rule.
    We invite public comment on this proposal to exempt SNFs with less 
than 60 residents, regardless of payer, discharged within 100 days of 
SNF admission in the prior calendar year, and to exempt newly Medicare-
certified SNFs in their first-year certification, from the CoreQ SS DC 
measure reporting requirements for the applicable SNF QRP program year.
c. Proposed Reporting Schedule for the Data Submission of the CoreQ: 
Short Stay Discharge Measure Beginning With the FY 2026 SNF QRP
    We propose that the CoreQ: SS DC measure questionnaire be a 
component of the SNF QRP for the FY 2026 SNF QRP and subsequent years. 
To comply with the SNF QRP reporting requirements for the FY 2026 SNF 
QRP, we propose that SNFs would be required to collect data for the 
CoreQ: SS DC measure by utilizing CMS-approved CoreQ survey vendors in 
compliance with the proposed provisions at Sec.  413.360(b)(2)(i) 
through (b)(2)(iii).
    For the CoreQ: SS DC measure, we propose that SNFs would send a 
resident information file to the CMS-approved CoreQ survey vendor on a 
weekly basis so the CMS-approved CoreQ survey vendor can start 
administering the CoreQ: SS DC questionnaire within seven days after 
the reporting week closes. The resident information file, whose data is 
listed in Table 14, represents the minimum required information the 
CMS-approved CoreQ survey vendor would need to determine the residents' 
eligibility for the CoreQ: SS DC measure's questionnaire to administer 
the survey to eligible residents.

Table 14--Data Elements in the CoreQ: SS DC Measure Resident Information
                                  File
------------------------------------------------------------------------
 
-------------------------------------------------------------------------
SNF name
SNF CMS Certification Number (CCN)
National Provider Identifier (NPI)
Reporting week
Reporting year
Number of eligible residents
Resident First Name
Resident Middle Initial
Resident Last Name
Resident Date of Birth
Resident Mailing Address 1
Resident Mailing Address 2
Resident address, City
Resident address, State
Resident address, Zip Code
Telephone number, including area code
Resident email address
Gender
Payer
HMO indicator
Dual eligibility indicator
End stage renal disease
Resident date of admission
Resident date of discharge
Brief Interview of Mental Status (BIMS) score
Discharge status
Left against medical advice
Court appointed guardian
Are you of Hispanic, Latino/a, or Spanish origin?
What is your race?
What is your preferred language?
------------------------------------------------------------------------
For additional information about the data elements that would be
  included in the resident information file, see the Draft CoreQ
  Protocols and Guidelines Manual located at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information information.

    For the CoreQ: SS DC measure, we propose that SNFs would be 
required to meet or exceed two separate data completeness thresholds: 
(1) one threshold, set at 75 percent, for submission of weekly resident 
information files to the CMS-approved CoreQ survey vendor for the full 
reporting year; and (2) a second threshold, set at 90 percent, for 
completeness of the resident information files. In other words, SNFs 
would need to submit resident information files on a weekly basis that 
include at least 90 percent of the required data fields to their CMS-
approved CoreQ survey vendors for at least 75 percent of the weeks in a 
reporting year. SNFs may choose to submit resident information files 
more frequently, but must meet the minimum threshold to avoid receiving 
a 2-percentage-point reduction to their Annual Payment Update (APU). 
Although we are proposing to adopt a 75 percent data submission and 90 
percent data completeness threshold for the resident information files 
initially, we intend to propose to raise the threshold levels for 
subsequent program years through future rulemaking. We are proposing to 
codify this data completeness threshold requirement at our regulation 
at Sec.  413.360(f)(1)(iv).
    We propose an initial data submission period from January 1, 2024, 
through June 30, 2024. As described in Table 15 in this section of this 
proposed rule, in order to meet the pay-for-reporting requirement of 
the SNF QRP for the first half of the FY 2026 program year, SNFs would 
only be required to contract with a CMS-approved CoreQ survey vendor 
and submit one resident information file to their CMS-approved CoreQ 
survey vendor for at least one week during January 1, 2024 through June 
30, 2024. During this period, the CMS-approved CoreQ survey vendor 
would follow the procedures as described in the Draft CoreQ: SS DC 
Survey Protocols and Guidelines Manual.\192\ Beginning July 1, 2024, 
SNFs would be required to submit weekly resident information files for 
at least 75 percent of the weeks remaining in CY 2024.
---------------------------------------------------------------------------

    \192\ Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. 
Available on the SNF QRP Measures and Technical Information web page 
at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.

[[Page 21359]]



 Table 15--Proposed Participation Requirements for the CoreQ: Short Stay Discharge Measure Beginning With the FY
                                                  2026 SNF QRP
----------------------------------------------------------------------------------------------------------------
                                          Proposed data          Quarterly data       FY 2026 SNF APU compliance
      Data submission quarters        submission frequency    submission deadlines            thresholds
----------------------------------------------------------------------------------------------------------------
Q1 2024: January 1, 2024 through     At least one week       August 15, 2024.......  At least one weekly
 March 31, 2024.                      during either data     ......................   resident information file
Q2 2024: April 1, 2024 through June   submission quarter.    November 15, 2024.....   containing at least 90% of
 30, 2024.                                                                            the required resident
                                                                                      information for one
                                                                                      resident discharged within
                                                                                      100 days of admission.
Q3 2024: July 1, 2024 through        No less than weekly...  February 18, 2025.....  A minimum of 18 weekly
 September 30, 2024.                                                                  resident information files
                                                                                      that contain at least 90%
                                                                                      of required resident
                                                                                      information.\193\
Q4 2024: October 1, 2024 through     No less than weekly...  May 15, 2025..........
 December 31, 2024.
----------------------------------------------------------------------------------------------------------------

    Starting in CY 2025, SNFs would be required to submit resident 
information files no less than weekly for the entire calendar year 
beginning with the FY 2027 SNF QRP, as described in Table 16 in this 
section of this proposed rule.
---------------------------------------------------------------------------

    \193\ There are 26 weeks in the period July 1, 2024 and December 
31, 2024. The threshold of a minimum of 75 percent of weekly 
resident information files is applied first, meaning that a SNF must 
submit a minimum of 20 resident information files (26 x 0.75 = 19.5, 
rounded up to 20). The threshold of 90 percent for complete and 
accurate resident information files is applied second, meaning that 
a minimum of 18 submitted weekly resident information files must be 
complete and accurate (20 x 0.9 = 18).

 Table 16--Proposed Participation Requirements for the CoreQ: Short Stay Discharge Measure Beginning With the FY
                                                  2027 SNF QRP
----------------------------------------------------------------------------------------------------------------
                                          Proposed data          Quarterly data       FY 2027 SNF APU compliance
      Data submission quarters        submission frequency    submission deadlines            thresholds
----------------------------------------------------------------------------------------------------------------
Q1 2025: January 1, 2025 through     No less than weekly...  August 15, 2025.......  A minimum of 35 weekly
 March 31, 2025.                                                                      resident information files
                                                                                      that contain at least 90%
                                                                                      of required resident
                                                                                      information.\194\
Q2 2025: April 1, 2025 through June  No less than weekly...  November 17, 2025.....
 30, 2025.
Q3 2025: July 1, 2025 through        No less than weekly...  February 16, 2026.....
 September 30, 2025.
Q4 2025: October 1, 2025 through     No less than weekly...  May 15, 2026..........
 December 31, 2025.
----------------------------------------------------------------------------------------------------------------

    We are proposing that the CMS-approved CoreQ survey vendor 
administer the CoreQ: SS DC measure's questionnaire to discharged 
residents within 2 weeks of their discharge date through the U.S. 
Postal Service or by telephone. If administered by mail, the 
questionnaires must be returned to the CMS-approved CoreQ survey vendor 
within 2 months of the resident's discharge date from the SNF.
---------------------------------------------------------------------------

    \194\ There are 52 weeks in the period January 1, 2025 to 
December 31, 2025. The threshold of a minimum of 75 percent of 
weekly resident information files is applied first, meaning that a 
SNF must submit a minimum of 39 resident information files (52 x 
0.75 = 39). The threshold of 90 percent for complete and accurate 
resident information files is applied second, meaning that a minimum 
of 35 submitted weekly resident information files must be complete 
and accurate (39 x 0.9 = 35.1, rounded down).
---------------------------------------------------------------------------

    Although the CMS-approved CoreQ survey vendor would administer the 
CoreQ: SS DC measure's survey on a SNF's behalf, each SNF would be 
responsible for ensuring required data is collected and submitted to 
CMS in accordance with the SNF QRP's requirements. We strongly suggest 
that SNFs that submit their CoreQ: SS DC measure resident information 
files to their CMS-approved CoreQ survey vendor follow up with their 
CMS-approved CoreQ survey vendor to make sure the CMS-approved CoreQ 
survey vendor submits its CoreQ: SS DC survey information files to the 
CoreQ Survey Data Center well in advance of each quarterly data 
submission deadline. Each submitted CoreQ: SS DC survey information 
file would undergo validation checks before it is accepted, and if it 
does not pass, the CoreQ: SS DC survey information file would be 
rejected. Submission of CoreQ: SS DC survey information files early in 
the data submission period would allow the CMS-approved CoreQ survey 
vendor to correct any problems detected and resubmit the CoreQ: SS DC 
survey information file(s) to the CoreQ Survey Data Center before the 
deadline. We would not allow any CoreQ: SS DC survey information files 
to be submitted to the CoreQ Survey Data Center after the SNF QRP data 
submission deadline ends. However, in the event of extraordinary 
circumstances beyond the control of the provider, the SNF would be able 
to request an exemption set forth in Sec.  413.360(c). More information 
on how to request an exemption can be found on the SNF QRP 
Reconsideration and Exception & Extension web page.\195\
---------------------------------------------------------------------------

    \195\ The SNF QRP Reconsideration and Exception & Extension web 
page is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-Nursing-Facility-Quality-Reporting-Program/SNF-QR-Reconsideration-and-Exception-and-Extension.
---------------------------------------------------------------------------

    We also recommend that SNFs submitting CoreQ: SS DC resident 
information files to their CMS-approved CoreQ survey vendor promptly 
review the Data Submission Summary Reports that are described in the 
Draft CoreQ: SS DC Survey Protocols and Guidelines Manual.\196\ These 
reports will enable the

[[Page 21360]]

SNF to ensure that its CMS-approved CoreQ survey vendor has submitted 
its data on time, and that the data have been accepted by the CoreQ 
Data Center. For more information about the SNF QRP data submission 
deadlines for each CY quarter, we refer readers to the FY 2016 SNF PPS 
final rule (80 FR 46427 through 46429).
---------------------------------------------------------------------------

    \196\ Draft CoreQ: SS DC Survey Protocols and Guidelines Manual. 
Chapter X. SNF CoreQ Survey Website Reports. Available on the SNF 
QRP Measures and Technical Information web page at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/skilled-nursing-facility-quality-reporting-program/snf-quality-reporting-program-measures-and-technical-information.
---------------------------------------------------------------------------

    We invite public comment on the proposed schedule for data 
submission and the participation requirements for the CoreQ: Short Stay 
Discharge Measure beginning with the FY 2026 SNF QRP.
4. Proposed Reporting Schedule for the Data Submission of Minimum Data 
Set (MDS) Assessment Data for the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date Measure Beginning With the FY 
2026 SNF QRP
    As discussed in section VI.C.2.b. of this proposed rule, we are 
proposing to adopt the Patient/Resident COVID-19 Vaccine measure 
beginning with the FY 2026 SNF QRP. We are proposing that SNFs would be 
required to report this new MDS assessment data item beginning with 
Medicare Part A residents discharged on October 1, 2024 for purposes of 
the FY 2026 SNF QRP. Starting in CY 2025, SNFs would be required to 
submit data for the entire calendar year beginning with the FY 2027 SNF 
QRP.
    We are also proposing to add a new item to the MDS in order for 
SNFs to report the proposed Patient/Resident COVID-19 Vaccine measure. 
Specifically, a new item would be added to the MDS discharge item sets 
to collect information on whether a resident is up to date with their 
COVID-19 vaccine at the time of discharge from the SNF. A draft of the 
new item is available in the COVID-19 Vaccine: Percent of Patients/
Residents Who Are Up to Date Draft Measure Specifications.\197\
---------------------------------------------------------------------------

    \197\ COVID-19 Vaccine: Percent of Patients/Residents Who Are Up 
to Date Draft Measure Specifications is available at https://www.cms.gov/files/document/patient-resident-covid-vaccine-draft-specs.pdf.
---------------------------------------------------------------------------

    We invite public comment on this proposal.
5. Proposal To Increase the SNF QRP Data Completion Thresholds for MDS 
Data Items Beginning With the FY 2026 SNF QRP
    In the FY 2016 SNF PPS final rule (80 FR 46458), we finalized that 
SNFs would need to complete 100 percent of the data on 80 percent of 
MDSs submitted in order to be in compliance with the SNF QRP reporting 
requirements for the applicable program year, as codified in regulation 
at Sec.  413.360(f). We established this data completion threshold 
because SNFs were accustomed to submitting MDS assessments for other 
purposes and they should easily be able to meet this requirement for 
the SNF QRP. We also noted at that time our intent to raise the 
proposed 80 percent threshold in subsequent program years.\198\
---------------------------------------------------------------------------

    \198\ 80 FR 22077; 80 FR 46458.
---------------------------------------------------------------------------

    We are now proposing that, beginning with the FY 2026 SNF QRP, SNFs 
would be required to report 100 percent of the required quality measure 
data and standardized patient assessment data collected using the MDS 
on at least 90 percent of the assessments they submit through the CMS-
designated submission system.
    Complete data are needed to help ensure the validity and 
reliability of SNF QRP data items, including risk-adjustment models. 
The proposed threshold of 90 percent is based on the need for 
substantially complete records, which allows appropriate analysis of 
SNF QRP measure data for the purposes of updating quality measure 
specifications as they undergo yearly and triennial measure maintenance 
reviews with the CBE. Additionally, we want to ensure complete SNF QRP 
measure data from SNFs, which will ultimately be reported to the 
public, allowing our beneficiaries to gain a more complete 
understanding of SNF performance related to these metrics, helping them 
to make informed healthcare choices. Finally, this proposal would 
contribute to further alignment of data completion thresholds across 
the PAC settings.
    We believe SNFs should be able to meet this proposed requirement 
for the SNF QRP. Our data suggest that the majority of SNFs are already 
in compliance with, or exceeding, this proposed threshold. The complete 
list of items required under the SNF QRP is updated annually and posted 
on the SNF QRP Measures and Technical Information page.\199\
---------------------------------------------------------------------------

    \199\ The SNF QRP Measures and Technical Information page is 
available at https://www.cms.gov/Medicare/Quality-Initiatives-
Patient-Assessment-Instruments/NursingHomeQualityInits/Skilled-
Nursing-Facility-Quality-Reporting-Program/SNF-Quality-Reporting-
Program-Measures-and-Technical-Information.
---------------------------------------------------------------------------

    We are proposing that SNFs would be required to comply with the 
proposed new data completion threshold beginning with the FY 2026 SNF 
QRP. Starting in CY 2024, SNFs would be required to report 100 percent 
of the required quality measures data and standardized patient 
assessment data collected using the MDS on at least 90 percent of all 
assessments submitted January 1 through December 31 for that calendar 
year's payment determination. Any SNF that does not meet the proposed 
requirement will be subject to a reduction of 2 percentage points to 
the applicable FY APU beginning with the FY 2026 SNF QRP. We are 
proposing to update Sec.  413.360(f) of our regulations to reflect this 
new policy, as well as to clarify and make non-substantive edits to 
improve clarity of the regulation.
    We invite public comment on the proposed schedule for the increase 
of SNF QRP data completion thresholds for the MDS data items beginning 
with the FY 2026 program year.

G. Proposed Policies Regarding Public Display of Measure Data for the 
SNF QRP

1. Background
    Section 1899B(g) of the Act requires the Secretary to establish 
procedures for making the SNF QRP data available to the public, 
including the performance of individual SNFs, after ensuring that SNFs 
have the opportunity to review their data prior to public display. For 
a more detailed discussion about our policies regarding public display 
of SNF QRP measure data and procedures for the SNF's opportunity to 
review and correct data and information, we refer readers to the FY 
2017 SNF PPS final rule (81 FR 52045 through 52048).
2. Proposed Public Reporting of the Transfer of Health Information to 
the Provider--Post-Acute Care Measure and Transfer of Health 
Information to the Patient--Post-Acute Care Measure Beginning With the 
FY 2025 SNF QRP
    We are proposing to begin publicly displaying data for the 
measures: (1) Transfer of Health (TOH) Information to the Provider--
Post-Acute Care (PAC) Measure (TOH-Provider); and (2) TOH Information 
to the Patient--PAC Measure (TOH-Patient) beginning with the October 
2025 Care Compare refresh or as soon as technically feasible.
    We adopted these measures in the FY 2020 SNF PPS final rule (84 FR 
38761 through 38764). In response to the COVID-19 PHE, we released an 
Interim

[[Page 21361]]

Final Rule (85 FR 27595 through 27597) which delayed the compliance 
date for collection and reporting of the TOH-Provider and TOH-Patient 
measures to October 1 of the year that is at least two full fiscal 
years after the end of the COVID-19 PHE. Subsequently, in the FY 2023 
SNF PPS final rule (87 FR 47502), the compliance date for the 
collection and reporting of the TOH-Provider and TOH-Patient measures 
was revised to October 1, 2023. Data collection for these two 
assessment-based measures will begin with residents discharged on or 
after October 1, 2023.
    We are proposing to publicly display data for these two assessment-
based measures based on four rolling quarters of data, initially using 
discharges from January 1, 2024, through December 31, 2024 (Quarter 1 
2024 through Quarter 4 2024), and to begin publicly reporting these 
measures with the October 2025 refresh of Care Compare, or as soon as 
technically feasible. To ensure the statistical reliability of the 
data, we are proposing that we would not publicly report a SNF's 
performance on a measure if the SNF had fewer than 20 eligible cases in 
any four consecutive rolling quarters for that measure. SNFs that have 
fewer than 20 eligible cases would be distinguished with a footnote 
that states: ``The number of cases/resident stays is too small to 
report.''
    We invite public comment on our proposal for the public display of 
the (1) Transfer of Health (TOH) Information to the Provider--Post-
Acute Care (PAC) Measure (TOH-Provider), and (2) Transfer of Health 
(TOH) Information to the Patient--Post-Acute Care (PAC) Measure (TOH-
Patient) assessment-based measures.
3. Proposed Public Reporting of the Discharge Function Score Measure 
Beginning With the FY 2025 SNF QRP
    We are proposing to begin publicly displaying data for the DC 
Function measure beginning with the October 2024 refresh of Care 
Compare, or as soon as technically feasible, using data collected from 
January 1, 2023 through December 31, 2023 (Quarter 1 2023 through 
Quarter 4 2023). If finalized as proposed, a SNF's DC Function score 
would be displayed based on four quarters of data. Provider preview 
reports would be distributed in July 2024, or as soon as technically 
feasible. Thereafter, a SNF's DC Function score would be publicly 
displayed based on four quarters of data and updated quarterly. To 
ensure the statistical reliability of the data, we are proposing that 
we would not publicly report a SNF's performance on the measure if the 
SNF had fewer than 20 eligible cases in any quarter. SNFs that have 
fewer than 20 eligible cases would be distinguished with a footnote 
that states: ``The number of cases/resident stays is too small to 
report.''
    We invite public comment on the proposal for the public display of 
the Discharge Function Score assessment-based measure beginning with 
the October 2024 refresh of Care Compare, or as soon as technically 
feasible.
4. Proposed Public Reporting of the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date Measure Beginning With the FY 
2026 SNF QRP
    We are proposing to begin publicly displaying data for the COVID-19 
Vaccine: Percent of Patients/Residents Who Are Up to Date measure 
beginning with the October 2025 refresh of Care Compare or as soon as 
technically feasible using data collected for Q4 2024 (October 1, 2024 
through December 31, 2024). A SNF's Patient/Resident COVID-19 Vaccine 
percent of residents who are up to date would be displayed based on one 
quarter of data. Provider preview reports would be distributed in July 
2025 for data collected in Q4 2024, or as soon as technically feasible. 
Thereafter, the percent of SNF residents who are up to date with their 
COVID-19 vaccinations would be publicly displayed based on one quarter 
of data updated quarterly. To ensure the statistical reliability of the 
data, we are proposing that we would not publicly report a SNF's 
performance on the measure if the SNF had fewer than 20 eligible cases 
in any quarter. SNFs that have fewer than 20 eligible cases would be 
distinguished with a footnote that states: ``The number of cases/
resident stays is too small to report.''
    We invite public comment on the proposal for the public display of 
the COVID-19 Vaccine: Percent of Patients/Residents Who Are Up to Date 
measure beginning with the October 2025 refresh of Care Compare, or as 
soon as technically feasible.

VII. Skilled Nursing Facility Value-Based Purchasing (SNF VBP) Program: 
Proposed Policy Changes

A. Statutory Background

    Through the Skilled Nursing Facility Value-Based Purchasing (SNF 
VBP) Program, we award incentive payments to SNFs to encourage 
improvements in the quality of care provided to Medicare beneficiaries. 
The SNF VBP Program is authorized by section 1888(h) to the Act, and it 
applies to freestanding SNFs, SNFs affiliated with acute care 
facilities, and all non-CAH swing bed rural hospitals. We believe the 
SNF VBP Program has helped to transform how Medicare payment is made 
for SNF care, moving increasingly towards rewarding better value and 
outcomes instead of merely rewarding volume. Our codified policies for 
the SNF VBP Program can be found in our regulations at 42 CFR 
413.337(f) and 413.338.

B. SNF VBP Program Measures

1. Background
    For background on the measures we have adopted for the SNF VBP 
Program, we refer readers to the following prior final rules:
     In the FY 2016 SNF PPS final rule (80 FR 46411 through 
46419), we finalized the Skilled Nursing Facility 30-Day All-Cause 
Readmission Measure (SNFRM) as required under section 1888(g)(1) of the 
Act.
     In the FY 2017 SNF PPS final rule (81 FR 51987 through 
51995), we finalized the Skilled Nursing Facility 30-Day Potentially 
Preventable Readmission (SNFPPR) Measure as required under section 
1888(g)(2) of the Act.
     In the FY 2020 SNF PPS final rule (84 FR 38821 through 
38822), we updated the name of the SNFPPR measure to the ``Skilled 
Nursing Facility Potentially Preventable Readmissions after Hospital 
Discharge measure'' (Sec.  413.338(a)(14)).
     In the FY 2021 SNF PPS final rule (85 FR 47624), we 
amended the definition of ``SNF Readmission Measure'' in our 
regulations to reflect the updated name for the SNFPPR measure.
     In the FY 2022 SNF PPS final rule (86 FR 42503 through 
42507), we finalized a measure suppression policy for the duration of 
the PHE for COVID-19, and finalized suppression of the SNFRM for 
scoring and payment purposes for the FY 2022 SNF VBP Program. We also 
updated the lookback period for risk-adjustment in the FY 2023 
performance period (FY 2021).
     In the FY 2023 SNF PPS final rule (87 FR 47559 through 
47580), we finalized suppression of the SNFRM for scoring and payment 
purposes for the FY 2023 SNF VBP Program. We also modified the SNFRM 
beginning with the FY 2023 program year by adding a risk-adjustment 
variable for both patients with COVID-19 during the prior proximal 
hospitalization (PPH) and patients with a history of COVID-19. We also 
finalized three new quality measures for the SNF VBP Program as 
permitted under section 1888(h)(2)(A)(ii) of the Act. We finalized two 
new measures beginning with the

[[Page 21362]]

FY 2026 program year: (1) Skilled Nursing Facility Healthcare 
Associated Infections Requiring Hospitalization (SNF HAI) measure; and 
(2) Total Nursing Hours per Resident Day Staffing (Total Nurse 
Staffing) measure. We finalized an additional measure beginning with 
the FY 2027 program year: Discharge to Community--Post-Acute Care 
Measure for Skilled Nursing Facilities (DTC PAC SNF) measure.
2. Proposal To Refine the SNFPPR Measure Specifications and Update the 
Measure Name
a. Background
    Section 1888(g)(2) of the Act requires the Secretary to specify a 
resource use measure that reflects an all-condition, risk-adjusted 
potentially preventable hospital readmission rate for skilled nursing 
facilities. To meet this statutory requirement, we finalized the 
Skilled Nursing Facility Potentially Preventable Readmission (SNFPPR) 
measure in the FY 2017 SNF PPS final rule (81 FR 51987 through 51995). 
In the FY 2020 SNF PPS final rule (84 FR 38821 through 38822), we 
updated the SNFPPR measure name to the Skilled Nursing Facility 
Potentially Preventable Readmissions after Hospital Discharge measure, 
while maintaining SNFPPR as the measure short name.
    Although our testing results indicated that the SNFPPR measure was 
sufficiently developed, valid, and reliable for use in the SNF VBP at 
the time we adopted it, we have since engaged in additional measure 
development work to further align the measure's specifications with the 
specifications of other potentially preventable readmission (PPR) 
measures, including the SNF PPR post-discharge (PD) measure specified 
for the SNF QRP, and the within-stay PPR measure used in the IRF QRP. 
Based on those efforts, we are now proposing to refine the SNFPPR 
measure specifications as follows: (1) we are proposing to change the 
outcome observation window from a fixed 30-day window following acute 
care hospital discharge to within the SNF stay; and (2) we are 
proposing to change the length of time allowed between a qualifying 
prior proximal inpatient discharge (that is, the inpatient discharge 
that occurs prior to admission to the index SNF stay) and SNF admission 
from one day to 30 days. To align with those measure refinements, we 
are also proposing to update the measure name to the ``Skilled Nursing 
Facility Within-Stay Potentially Preventable Readmission (SNF WS PPR) 
Measure.''
b. Overview of the Proposed Updated Measure
    The SNF WS PPR measure estimates the risk-standardized rate of 
unplanned, potentially preventable readmissions (PPR) that occur during 
SNF stays among Medicare FFS beneficiaries. Specifically, this outcome 
measure reflects readmission rates for residents who are readmitted to 
a short-stay acute-care hospital or long-term care hospital (LTCH) with 
a principal diagnosis considered to be unplanned and potentially 
preventable while within SNF care. The measure is risk-adjusted and 
calculated using 2 consecutive years of Medicare FFS claims data.
    We have tested the proposed updated SNF WS PPR measure for 
reliability and validity. The random split-half correlation tests 
indicated good reliability with the intraclass correlation coefficient 
being notably better than that of the SNFRM. In addition, we tested the 
validity of the SNF WS PPR measure by comparing SNF WS PPR measure 
scores with those of nine other measures. The testing results indicated 
that the SNF WS PPR measure is not duplicative of those nine measures 
and provides unique information about quality of care not captured by 
the other nine measures. Validity tests also showed that the measure 
can accurately predict PPRs while controlling for differences in 
resident case-mix. We refer readers to the SNF WS PPR measure technical 
specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-technical-measure-specification.pdf.
(1) Measure Applications Partnership (MAP) Review
    We included the SNF WS PPR measure as a SNF VBP measure under 
consideration in the publicly available ``2022 Measures Under 
Consideration List.'' \200\ The MAP offered conditional support of the 
SNF WS PPR measure for rulemaking, contingent upon endorsement by the 
consensus-based entity, noting that the measure would add value to the 
Program because PPRs are disruptive and burdensome to patients. We 
refer readers to the final 2022-2023 MAP recommendations for further 
details available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    \200\ 2022 Measures Under Consideration Spreadsheet available at 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
---------------------------------------------------------------------------

c. Data Sources
    The SNF WS PPR measure is calculated using 2 consecutive years of 
Medicare FFS claims data to estimate the risk-standardized rate of 
unplanned PPRs that occur during SNF stays. Specifically, the stay 
construction, exclusions, and risk-adjustment model utilize data from 
the Medicare eligibility files and inpatient hospital claims. 
Calculating the SNF WS PPR measure using 2 years of data improved the 
measure's statistical reliability relative to 1 year of data, which is 
used in the current version of the SNFPPR measure. Because the SNF WS 
PPR measure is calculated entirely using administrative data, our 
proposed adoption of the measure would not impose any additional data 
collection or submission burden for SNFs.
d. Measure Specifications
(1) Denominator
    The population included in the measure denominator is Medicare FFS 
beneficiaries who are admitted to a SNF during a 2-year measurement 
period who are not then excluded based on the measure exclusion 
criteria, which we describe in the next section. For SNF residents with 
multiple SNF stays during the 2-year readmission window, each of those 
SNF stays is eligible for inclusion in the measure. In addition, the 
index SNF admission must have occurred within 30 days of discharge from 
a prior proximal hospital (PPH) stay, which is defined in the measure 
specifications as an inpatient stay in an IPPS hospital, a CAH, or an 
inpatient psychiatric facility. Residents who expire during the 
readmission window are included in the measure.
    The measure denominator is the risk-adjusted ``expected'' number of 
residents with a PPR that occurred during the SNF stay. This estimate 
includes risk adjustment for certain resident characteristics without 
the facility effect, which we further discuss in section VII.B.2.e. of 
this proposed rule. The ``expected'' number of residents with a PPR is 
derived from the predicted number of residents with a PPR if the same 
residents were treated at the average SNF, which is defined for 
purposes of this measure as a SNF whose facility effect is zero.
(2) Denominator Exclusions
    A SNF stay is excluded from the measure denominator if it meets at 
least one of the following conditions:
     The SNF resident is less than 18 years old.
     The SNF resident did not have at least 12 months of 
continuous FFS

[[Page 21363]]

Medicare enrollment prior to SNF admission, which is defined as the 
month of SNF admission and the 11 months prior to that admission.
     The SNF resident did not have continuous FFS Medicare 
enrollment for the entire risk period (defined as enrollment during the 
month of SNF admission through the month of SNF discharge).
     SNF stays where there was a gap of greater than 30 days 
between discharge from the PPH and the SNF admission.
     The SNF resident was discharged from the SNF against 
medical advice.
     SNF stays in which the principal diagnosis for the PPH was 
for the medical treatment of cancer. Residents with cancer whose 
principal diagnosis from the PPH was for other medical diagnoses or for 
surgical treatment of their cancer remain included in the measure).
     SNF stays in which the principle diagnosis for the PPH was 
for pregnancy (this is an atypical reason for resident to be admitted 
to SNFs).
     The SNF resident who the SNF subsequently transfers to a 
Federal hospital. A transfer to a Federal hospital is identified when 
discharge code 43 is entered for the patient discharge status field on 
the Medicare claim.
     The SNF resident received care from a provider outside of 
the United States, Puerto Rico, or a U.S. territory, as identified by 
the provider's CCN on the Medicare claim.
     SNF stays with data that are problematic (for example, 
anomalous records for hospital stays that overlap wholly or in part or 
are otherwise erroneous or contradictory).
     SNF stays that occurred in a CAH swing bed.
    For additional details on the denominator exclusions, we refer 
readers to the SNF WS PPR measure technical specifications available at 
https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-techical-specification.pdf.
(3) Numerator
    The numerator is defined as the number of SNF residents included in 
the measure denominator who also have an unplanned PPR during an index 
SNF stay. For the purposes of this measure, an unplanned PPR is defined 
as a readmission from a SNF to an acute care hospital or a long-term 
care hospital, with a diagnosis considered to be unplanned and 
potentially preventable. The numerator only includes unplanned PPRs 
that occur during the within-SNF stay period (that is, from the date of 
the SNF admission through and including the date of discharge), which 
can be a hospital readmission that occurs within the SNF stay or a 
direct transfer to a hospital on the date of the SNF discharge. Because 
this measure focuses on potentially preventable and unplanned 
readmissions, we do not count planned readmissions in the numerator. 
Further, because we consider readmissions to inpatient psychiatric 
facilities to be planned, they are also not counted in the numerator.
    The measure numerator is the risk-adjusted ``predicted'' estimate 
of the number of residents with an unplanned PPR that occurred during a 
SNF stay. This estimate starts with the unadjusted, observed count of 
the measure outcome (the number of residents with an unplanned PPR 
during a SNF stay), which is then risk-adjusted for resident 
characteristics and a statistical estimate of the SNF's facility 
effect, to become the risk-adjusted numerator.
e. Risk Adjustment
    The SNF WS PPR measure is risk-adjusted to control for risk factor 
differences across SNF residents and SNF facilities. Specifically, the 
statistical model utilizes a hierarchical logistic regression to 
estimate the effect of resident characteristics on the probability of 
readmission across all SNFs and the effect of each SNF on readmissions 
that differs from that of the average SNF (``facility effect''). The 
denominator is risk-adjusted for resident characteristics only, while 
the numerator is risk-adjusted for both resident characteristics and 
the facility effect. The specific risk adjustment variables included in 
the statistical model for this measure are the following:
     Age and sex category.
     Original reason for Medicare entitlement (disability or 
other).
     Indicator of End-Stage Renal Disease (ESRD).
     Surgery category if present (for example, cardiothoracic, 
orthopedic), as defined in the Hospital Wide Readmission (HWR) measure 
model software. The surgical procedures are grouped using the Clinical 
Classification Software (CCS) classes for ICD-10 procedures developed 
by the Agency for Healthcare Research and Quality (AHRQ).
     Principal diagnosis on PPH inpatient claim. The ICD-10 
codes are grouped clinically using the CCS mappings developed by AHRQ.
     Comorbidities from secondary diagnoses on the PPH 
inpatient claim and diagnoses from earlier hospital inpatient claims up 
to 1 year before the date of the index SNF admission (these are 
clustered using the Hierarchical Condition Categories (HCC) groups used 
by CMS).
     Length of stay in the PPH stay (categorical to account for 
nonlinearity).
     Prior acute intensive care unit (ICU) or critical care 
unit (CCU) utilization.
     Number of prior acute care hospital discharges in the 
prior year.
    For additional details on the risk adjustment model, we refer 
readers to the SNF WS PPR measure technical specifications available at 
https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-techical-specification.pdf.
f. Measure Calculation
    The SNF WS PPR measure estimates the risk-standardized rate of 
unplanned PPRs that occur during SNF stays among Medicare FFS 
beneficiaries. A lower score on this measure indicates better 
performance. The provider-level risk-standardized readmission rate 
(RSRR) of unplanned PPRs is calculated by multiplying the standardized 
risk ratio (SRR) by the mean readmission rate in the population (that 
is, all Medicare FFS residents included in the measure). The SRR is 
calculated as the predicted number of readmissions at the SNF divided 
by the expected number of readmissions for the same residents if 
treated at the average SNF. For additional details on the calculation 
method, we refer readers to the SNF WS PPR measure technical 
specifications available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-techical-specification.pdf.
g. Proposed Scoring of SNF Performance on the SNF WS PPR Measure
(1) Background
    In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we 
finalized a policy to invert SNFRM measure rates such that a higher 
measure rate reflects better performance on the SNFRM. In that final 
rule, we also stated our belief that this inversion is important for 
incentivizing improvement in a clear and understandable manner, and 
because a ``lower is better'' rate could cause confusion among SNFs and 
the public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied 
this policy to the SNF HAI measure such that a higher measure rate 
reflects better performance on the SNF HAI measure. We also stated our 
intent to apply this inversion scoring policy to all measures in the 
Program for which the calculation produces a ``lower is better'' 
measure rate. We continue to believe that inverting measure rates such 
that a higher measure rate reflects better performance on a measure is 
important

[[Page 21364]]

for incentivizing improvement in a clear and understandable manner.
    The measure rate inversion scoring policy does not change the 
measure specifications or the calculation method. We use this measure 
rate inversion only as part of the scoring methodology under the SNF 
VBP Program. The measure rate inversion is part of the methodology we 
use to generate measure scores, and resulting SNF Performance Scores, 
that are clear and understandable for SNFs and the public.
(2) Proposal To Invert the SNF WS PPR Measure Rate for SNF VBP Scoring 
Purposes
    In the previous section, we stated that a lower risk-standardized 
rate for the SNF WS PPR measure indicates better performance. 
Therefore, we are proposing to apply our measure rate inversion scoring 
policy to the SNF WS PPR measure because a ``lower is better'' rate 
could cause confusion among SNFs and the public. Specifically, we are 
proposing to calculate the scores for this measure for the SNF VBP 
Program by inverting the SNF WS PPR measure rates using the following 
calculation:

SNF WS PPR Inverted Rate = 1-Facility's SNF WS PPR Risk Standardized 
Rate

    This calculation would invert SNF WS PPR measure rates such that a 
higher measure rate would reflect better performance.
h. Confidential Feedback Reports and Public Reporting for the Proposed 
SNF WS PPR Measure
    Our confidential feedback reports and public reporting policies are 
codified at Sec.  413.338(f) of our regulation. In the FY 2023 SNF PPS 
final rule (87 FR 47591 through 47592), we revised our regulations such 
that the confidential feedback reports and public reporting policies 
apply to each measure specified for a fiscal year, which includes the 
proposed SNF WS PPR measure beginning with the FY 2028 program year.
    We invite public comment on our proposal to refine the measure 
specifications for the SNFPPR measure, and our proposal to update the 
measure's name to the ``Skilled Nursing Facility Within-Stay 
Potentially Preventable Readmissions (SNF WS PPR) measure.'' We also 
invite public comment on our proposal to invert the SNF WS PPR measure 
rate for SNF VBP Program scoring purposes.
3. Proposal To Replace the SNFRM With the SNF WS PPR Measure Beginning 
With the FY 2028 SNF VBP Program Year
    Section 1888(h)(2)(B) of the Act requires the Secretary to apply 
the measure specified under section 1888(g)(2) of the Act, instead of 
the measure specified under section 1888(g)(1) of the Act as soon as 
practicable. To meet that statutory requirement, we are proposing to 
replace the SNFRM with the proposed SNF WS PPR measure beginning with 
the FY 2028 program year. This is the first program year that we can 
feasibly implement the SNF WS PPR measure after taking into 
consideration its proposed performance period and a number of other 
statutory requirements.
    We are proposing a 2-year performance period for the proposed SNF 
WS PPR, and we believe the earliest the first performance period can 
occur is FY 2025 and FY 2026 (October 1, 2024 through September 30, 
2026). This would provide us with sufficient time to calculate and 
announce the performance standards for the proposed SNF WS PPR measure 
at least 60 days before the beginning of that performance period, as 
required under section 1888(h)(3)(C) of the Act. Additionally, we are 
required under section 1888(h)(7) of the Act to announce the net 
payment adjustments for SNFs no later than 60 days prior to the start 
of the applicable fiscal year. We calculate these payment adjustments 
using performance period data. To provide us with sufficient time to 
calculate and announce the net payment adjustments after the end of the 
proposed performance period (FY 2025 and FY 2026), we believe the 
earliest program year in which we can feasibly adopt the proposed SNF 
WS PPR measure is FY 2028.
    We invite public comment on our proposal to replace the SNFRM with 
the SNF WS PPR measure beginning with the FY 2028 SNF VBP program year.
4. Quality Measure Proposals for the SNF VBP Expansion Beginning With 
the FY 2026 Program Year
a. Background
    Section 1888(h)(2)(A)(ii) of the Act (as amended by section 
111(a)(2)(C) of the CAA 2021) allows the Secretary to expand the SNF 
VBP Program to include up to 10 quality measures with respect to 
payments for services furnished on or after October 1, 2023. These 
measures may include measures of functional status, patient safety, 
care coordination, or patient experience. Section 1888(h)(2)(A)(ii) of 
the Act also requires that the Secretary consider and apply, as 
appropriate, quality measures specified under section 1899B(c)(1) of 
the Act.
    In the FY 2023 SNF PPS final rule (87 FR 47564 through 47580), we 
adopted the first three measures for the Program expansion: (1) SNF HAI 
measure; (2) Total Nurse Staffing measure; and (3) DTC PAC SNF measure. 
We adopted the SNF HAI and Total Nurse Staffing measures beginning with 
the FY 2026 program year (FY 2024 is the first performance period). We 
also adopted the DTC PAC SNF measure beginning with the FY 2027 program 
year (FY 2024 and FY 2025 is the first performance period).
    In this proposed rule, we are proposing to adopt four additional 
measures for the Program. We are proposing to adopt one new measure 
beginning with the FY 2026 program year (FY 2024 would be the first 
performance period): Total Nursing Staff Turnover (``Nursing Staff 
Turnover'') measure. We are also proposing to adopt three new measures 
beginning with the FY 2027 program year (FY 2025 would be the first 
performance period): (1) Percent of Residents Experiencing One or More 
Falls with Major Injury (Long-Stay) (``Falls with Major Injury (Long-
Stay)'') measure; (2) Discharge Function Score for SNFs (``DC Function 
measure''); and (3) Number of Hospitalizations per 1,000 Long Stay 
Resident Days (``Long Stay Hospitalization'') measure.
    Therefore, for the FY 2024 performance period, SNF data would be 
collected for five measures: SNFRM, SNF HAI, Total Nurse Staffing, 
Nursing Staff Turnover, and DTC PAC SNF measures. Performance on the 
first four measures would affect SNF payment in the FY 2026 program 
year. Since the DTC PAC SNF measure is a 2-year measure, performance on 
that measure would affect SNF payment in the FY 2027 program year.
    Beginning with the FY 2025 performance period, SNF data would be 
collected for nine measures: SNFRM, SNF HAI, Total Nurse Staffing, 
Nursing Staff Turnover, DC Function, Falls with Major Injury (Long-
Stay), Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR measures. 
Performance on the first seven measures would affect SNF payment in the 
FY 2027 program year. Since the DTC PAC SNF and SNF WS PPR measures are 
2-year measures, performance on those measures would affect SNF payment 
in the FY 2028 program year. Further, we refer readers to section 
VII.B.3. of this proposed rule for additional details on our proposal 
to replace the SNFRM with the SNF WS

[[Page 21365]]

PPR measure beginning with the FY 2028 program year, as required by 
statute, which would mean that the FY 2027 and FY 2028 program years 
would each only have eight measures that would affect SNF payment for 
those program years. Finally, there is no additional burden on SNFs to 
submit data on these previously adopted and proposed measures for the 
SNF VBP Program.
    Table 17 provides the list of the currently adopted and newly 
proposed measures for the SNF VBP Program.

                          Table 17--Currently Adopted and Proposed New SNF VBP Measures
----------------------------------------------------------------------------------------------------------------
                                                                             First  program    First performance
          Measure name             Measure short name     Measure status          year             period *
----------------------------------------------------------------------------------------------------------------
SNF 30-Day All-Cause Readmission  SNFRM..............  Adopted,             FY 2017 **......  FY 2015.
 Measure.                                               implemented.
SNF Healthcare-Associated         SNF HAI Measure....  Adopted, not         FY 2026.........  FY 2024.
 Infections Requiring                                   implemented.
 Hospitalization Measure.
Total Nurse Staffing Hours per    Total Nurse          Adopted, not         FY 2026.........  FY 2024.
 Resident Day Measure.             Staffing Measure.    implemented.
Total Nursing Staff Turnover      Nursing Staff        Proposed...........  FY 2026 \+\.....  FY 2024.
 Measure.                          Turnover Measure.
Discharge to Community--Post-     DTC PAC SNF Measure  Adopted, not         FY 2027.........  FY 2024 and FY
 Acute Care Measure for SNFs.                           implemented.                           2025.
Percent of Residents              Falls with Major     Proposed...........  FY 2027 \+\.....  FY 2025.
 Experiencing One or More Falls    Injury (Long-Stay)
 with Major Injury (Long-Stay)     Measure.
 Measure.
Discharge Function Score for      DC Function Measure  Proposed...........  FY 2027 \+\.....  FY 2025.
 SNFs Measure.
Number of Hospitalizations per    Long Stay            Proposed...........  FY 2027 \+\.....  FY 2025.
 1,000 Long Stay Resident Days     Hospitalization
 Measure.                          Measure.
SNF Within-Stay Potentially       SNF WS PPR Measure.  Proposed...........  FY 2028 \+\.....  FY 2025 and FY
 Preventable Readmissions                                                                      2026.
 Measure.
----------------------------------------------------------------------------------------------------------------
* For each measure, we have adopted or are proposing to adopt a policy to automatically advance the beginning of
  the performance period by 1-year from the previous program year. We refer readers to section VII.C.3 of this
  proposed rule for additional information.
** Proposed to be replaced with the SNF WS PPR measure beginning with the FY 2028 program year.
\+\ Proposed first program year in which the measure would be included in the Program.


[[Page 21366]]

b. Proposal To Adopt the Total Nursing Staff Turnover Measure Beginning 
With the FY 2026 SNF VBP Program Year
    We are proposing to adopt the Total Nursing Staff Turnover Measure 
(``Nursing Staff Turnover measure'') beginning with the FY 2026 SNF VBP 
program year.
(1) Background
    Nursing home staffing, including nursing staff turnover, has long 
been considered an important indicator of nursing home 
quality.201 202 203 Longer-tenured nursing staff are more 
familiar with the residents and are better able to detect changes in a 
resident's condition. They are also more acclimated to their facility's 
procedures and thus, operate more efficiently. In contrast, higher 
nursing staff turnover can mean that nursing staff are less familiar 
with resident needs and facility procedures, which can contribute to 
lower quality of care.
---------------------------------------------------------------------------

    \201\ Centers for Medicare and Medicaid Services. 2001 Report to 
Congress: Appropriateness of Minimum Nurse Staffing Ratios in 
Nursing Homes, Phase II. Baltimore, MD: Centers for Medicare and 
Medicaid Services. http://phinational.org/wp-content/uploads/legacy/clearinghouse/PhaseIIVolumeIofIII.pdf.
    \202\ Institute of Medicine. Nursing Staff in Hospitals and 
Nursing Homes: Is It Adequate? Washington, DC: National Academy 
Press; 1996.
    \203\ ``To Advance Information on Quality of Care, CMS Makes 
Nursing Home Staffing Data Available [verbar] CMS.'' Accessed 
December 22, 2022. https://www.cms.gov/newsroom/press-releases/advance-information-quality-care-cms-makes-nursing-home-staffing-data-available.
---------------------------------------------------------------------------

    There is considerable evidence demonstrating the impact of nursing 
staff turnover on resident outcomes, with higher turnover associated 
with poorer quality of care.204 205 206 207 208 209 210 A 
recent 2019 study comparing nursing home's annualized turnover rates 
with the overall five-star ratings for the facilities found that the 
average total nursing staff annual turnover rates were 53.4 percent 
among one-star nursing homes and 40.7 percent for five-star 
facilities.\211\ The same study found a statistically significant 
relationship between higher turnover rates and lower performance on 
clinical quality measures, including hospitalization rates, readmission 
rates, and emergency department visits. \212\ Studies have also shown 
that nursing staff turnover is a meaningful factor in nursing home 
quality of care and that staff turnover influences quality 
outcomes.213 214 For example, higher staff turnover is 
associated with an increased likelihood of receiving an infection 
control citation.\215\
---------------------------------------------------------------------------

    \204\ Zheng Q, Williams CS, Shulman ET, White AJ Association 
between staff turnover and nursing home quality--evidence from 
payroll-based journal data. Journal of the American Geriatrics 
Society. May 2022. doi:10.1111/jgs.17843.
    \205\ Bostick JE, Rantz MJ, Flesner MK, Riggs CJ Systematic 
review of studies of staffing and quality in nursing homes. J Am Med 
Dir Assoc. 2006;7:366-376. https://pubmed.ncbi.nlm.nih.gov/16843237/.
    \206\ Backhaus R, Verbeek H, van Rossum E, Capezuti E, Hamer JPH 
Nursing staffing impact on quality of care in nursing homes: a 
systemic review of longitudinal studies. J Am Med Dir Assoc. 
2014;15(6):383-393. https://pubmed.ncbi.nlm.nih.gov/24529872/.
    \207\ Spilsbury K., Hewitt C., Stirk L., Bowman C. The 
relationship between nurse staffing and quality of care in nursing 
homes: a systematic review. Int J Nurs Stud. 2011; 48(6):732-750. 
https://pubmed.ncbi.nlm.nih.gov/21397229/.
    \208\ Castle N. Nursing home caregiver staffing levels and 
quality of care: a literature review. J Appl Gerontol. 2008;27:375-
405. https://doi.org/10.1177%2F0733464808321596.
    \209\ Spilsbury et al.
    \210\ Castle NG, Engberg J. Staff turnover and quality of care 
in nursing homes. Med Care. 2005 Jun;43(6):616-26. doi: 10.1097/
01.mlr.0000163661.67170.b9. PMID: 15908857.
    \211\ Zheng, Q, Williams, CS, Shulman, ET, White, AJ Association 
between staff turnover and nursing home quality--evidence from 
payroll-based journal data. J Am Geriatr Soc. 2022; 70(9): 2508-
2516. doi:10.1111/jgs.17843.
    \212\ Ibid.
    \213\ Centers for Medicare and Medicaid Services. 2001 Report to 
Congress: Appropriateness of Minimum Nurse Staffing Ratios in 
Nursing Homes, Phase II. Baltimore, MD: Centers for Medicare and 
Medicaid Services. http://phinational.org/wp-content/uploads/legacy/clearinghouse/PhaseIIVolumeIofIII.pdf.
    \214\ Loomer, L, Grabowski, DC, Yu, H, & Gandhi, A. (2021). 
Association between nursing home staff turnover and infection 
control citations. Health Services Research. https://doi.org/10.1111/1475-6773.13877.
    \215\ Loomer, L., Grabowski, D.C., Yu, H., & Gandhi, A. (2021). 
Association between nursing home staff turnover and infection 
control citations. Health Services Research. https://doi.org/10.1111/1475-6773.13877.
---------------------------------------------------------------------------

    Recently, the National Academies of Sciences, Engineering, and 
Medicine formed the Committee on the Quality of Care in Nursing homes 
to examine the delivery of care and the complex array of factors that 
influence the quality of care in nursing homes. The committee published 
a report in 2022 titled ``The National Imperative to Improve Nursing 
Home Quality.'' The report details the complex array of factors that 
influence care quality in nursing homes, including staffing variables 
such as staffing levels and turnover, and identifies several broad 
goals and recommendations to improve the quality of care in nursing 
homes.\216\ In the 2022 report, the National Academies of Sciences, 
Engineering, and Medicine highlighted the association between the high 
turnover of many nursing home staff, including RNs, and lower quality 
of care delivery in nursing homes.\217\ The report also recognized the 
need for quality measures that report on turnover rates, citing that 
increased transparency will improve patient care. Because of its 
central role in the quality of care of Medicare beneficiaries, HHS and 
the Biden-Harris Administration are also committed to improving the 
quality of care in nursing homes with respect to staffing, as stated in 
the fact sheets entitled ``Protecting Seniors by Improving Safety and 
Quality of Care in the Nation's Nursing Homes'' and ``Biden-Harris 
Administration Announces New Steps to Improve Quality of Nursing 
Homes.'' 218 219 While much of this research has been 
conducted in long-term care facilities or nursing homes, we believe 
this research is relevant to the SNF setting, because approximately 94 
percent of long-term care facilities are dually certified as both SNFs 
and nursing facilities (86 FR 42508).
---------------------------------------------------------------------------

    \216\ National Academies of Sciences, Engineering, and Medicine. 
2022. The National Imperative to Improve Nursing Home Quality: 
Honoring Our Commitment to Residents, Families, and Staff. 
Washington, DC: The National Academies Press. https://doi.org/10.17226/26526.
    \217\ National Academies of Sciences, Engineering, and Medicine, 
2022.
    \218\ The White House. (2022, February 28). FACT SHEET: 
Protecting Seniors by Improving Safety and Quality of Care in the 
Nation's Nursing Homes. https://www.whitehouse.gov/briefing-room/statements-releases/2022/02/28/fact-sheet-protecting-seniors-and-people-with-disabilities-by-improving-safety-and-quality-of-care-in-the-nations-nursing-homes/.
    \219\ The White House. (2021, October 21). FACT SHEET: Biden-
Harris Administration Announces New Steps to Improve Quality of 
Nursing Homes. https://www.whitehouse.gov/briefing-room/statements-releases/2022/10/21/fact-sheet-biden-harris-administration-announces-new-steps-to-improve-quality-of-nursing-homes/.
---------------------------------------------------------------------------

    In light of the strong association between high nursing staff 
turnover rates and negative resident outcomes, including the nursing 
staff turnover measure in the SNF VBP Program would provide a 
comprehensive assessment of the quality of care provided to residents. 
This measure would also drive improvements in nursing staff turnover 
that are likely to translate into positive resident outcomes.
    Although the proposed Nursing Staff Turnover measure is not 
specified under section 1899B(c)(1) of the Act, we believe this measure 
supports the Program's goals to improve the quality of care provided to 
Medicare beneficiaries throughout their entire SNF stay. We have long 
identified staffing as one of the vital components of a SNF's ability 
to provide quality care and use staffing data to gauge a facility's 
impact on quality of care in SNFs with more accuracy and efficacy. The 
proposed measure aligns with the topics listed under section 
1888(h)(2)(A)(ii) of the Act and with HHS and Biden-Harris 
Administration priorities. We also believe that the Nursing Staff 
Turnover

[[Page 21367]]

measure would complement the Total Nursing Hours per Resident Day 
(Total Nurse Staffing) measure, adopted in the FY 2023 SNF PPS final 
rule (87 FR 47570 through 47576). Together, these measures emphasize 
and align with our current priorities and focus areas for the Program.
(2) Overview of Measure
    The Nursing Staff Turnover measure is a structural measure that 
uses auditable electronic data reported to CMS' PBJ system to calculate 
annual turnover rates for nursing staff, including registered nurses 
(RNs), licensed practical nurses (LPNs), and nurse aides. Given the 
well-documented impact of nurse staffing on patient outcomes and 
quality of care, this proposed measure would align the Program with the 
Care Coordination domain of CMS' Meaningful Measures 2.0 Framework. The 
Nursing Staff Turnover measure is currently being measured and publicly 
reported for nursing facilities on the Care Compare website (https://www.medicare.gov/care-compare/) and is used in the Five-Star Quality 
Rating System. For more information on measure specifications and how 
this measure is used in the Five -Star Quality Rating System, we refer 
readers to the January 2023 Technical Users' Guide available at https://www.cms.gov/medicare/provider-enrollment-and-certification/certificationandcomplianc/downloads/usersguide.pdf.
    This proposed measure is constructed using daily staffing 
information submitted through the PBJ system by nursing facilities. 
Specifically, turnover is identified based on gaps in days worked, 
which helps ensure that Nursing Staff Turnover is defined the same way 
across all nursing facilities with SNF beds and that it does not depend 
on termination dates that may be reported inconsistently by these 
facilities. Individuals are identified based on the employee system ID 
and SNF identifiers in the PBJ data. We refer readers to the Nursing 
Staff Turnover measure specifications available at https://www.cms.gov/medicare/provider-enrollment-and-certification/certificationandcomplianc/downloads/usersguide.pdf.
    Payroll data are considered the gold standard for nurse staffing 
measures and are a significant improvement over the manual data 
previously used, wherein staffing information was calculated based on a 
form (CMS-671) filled out manually by the facility.\220\ The PBJ 
staffing data are electronically submitted and auditable back to 
payroll and other verifiable sources. Analyses of PBJ-based staffing 
measures show a relationship between higher nurse staffing levels and 
higher ratings for other dimensions of quality such as health 
inspection survey results and quality measures.\221\
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    \220\ https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/QSO18-17-NH.pdf.
    \221\ Zheng, Q, Williams, CS, Shulman, ET, White, AJ Association 
between staff turnover and nursing home quality--evidence from 
payroll-based journal data. J Am Geriatr Soc. 2022; 70(9): 2508-
2516.
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(a) Interested Parties and TEP Input
    In 2019 through 2022, CMS tested this measure based on input from 
the CMS Five-Star Quality Rating Systems' TEP, as well as input from 
interested parties. We began publicly reporting this measure on the 
Care Compare website via the Nursing Home Five-Star Rating System in 
January 2022.
    We solicited public feedback on this measure in a ``Request for 
Comment on Additional SNF VBP Program Measure Considerations for Future 
Years'' in the FY 2023 SNF PPS proposed rule (87 FR 22786 through 
22787). We considered the input we received as we developed our 
proposal for this measure. We refer readers to the FY 2023 SNF PPS 
final rule (87 FR 47592 through 475963) for a detailed summary of the 
feedback we received on this measure.
(b) Measure Applications Partnership (MAP) Review
    We included the Nursing Staff Turnover measure as a SNF VBP measure 
under consideration in the publicly available ``2022 Measures Under 
Consideration List.'' \222\ The MAP offered conditional support of the 
Nursing Staff Turnover measure for rulemaking, contingent upon 
endorsement by the consensus-based entity, noting that the measure 
would add value to the Program because staffing turnover is a 
longstanding indicator of nursing home quality, and it addresses the 
Care Coordination domain of the Meaningful Measures 2.0 Framework. We 
refer readers to the final 2022-2023 MAP recommendations available at 
https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    \222\ 2022 Measures Under Consideration Spreadsheet available at 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
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(3) Data Sources
    The proposed Nursing Staff Turnover measure is calculated using 
auditable, electronic staffing data submitted by each SNF for each 
quarter through the PBJ system. Specifically, this measure utilizes 
five data elements from the PBJ data, including employee ID, facility 
ID, hours worked, work date, and job title code.
(4) Inclusion and Exclusion Criteria
    We are proposing that SNFs would be excluded from the measure under 
the following conditions:
     Any SNF with 100 percent total nursing staff turnover for 
any day in the six-quarter period during which there were at least five 
eligible nurse staff. A 100 percent daily turnover is typically the 
result of changes in the employee IDs used by SNFs and does not reflect 
actual staff turnover.
     SNFs that do not submit staffing data or submitted data 
that are considered invalid (using the current exclusion rules for the 
staffing domain) for one or more of the quarters used to calculate the 
Nursing Staff turnover measure.
     SNFs that do not have resident census information (derived 
from MDS assessments).
     SNFs with fewer than five eligible nurses (RNs, LPNs and 
nurse aides) in the denominator.
(a) Denominator
    The denominator for the proposed Nursing Staff Turnover measure 
includes all eligible employees, defined as RNs, LPNs, and nurse aides, 
who are regular employees and agency staff who work at a Medicare 
certified SNF and use the same job category codes as other nurse 
staffing measures that are reported on the Care Compare website. For 
the purposes of this measure, the RN category is defined as RNs (job 
code 7), RN director of nursing (job code 5), and RNs with 
administrative duties (job code 6). The LPN category is defined as LPNs 
(job code 9) and LPNs with administrative duties (job code 8). The 
nurse aide category is defined as certified nurse aides (job code 10), 
aides in training (job code 11), and medication aides/technicians (job 
code 12). This measure only includes eligible employees who work at 
least 120 hours in a 90-day period. The timeframe for the 90-day period 
begins on the first workday observed during the quarter prior to the 
start of the performance period (termed the baseline quarter) and ends 
on the last workday, of the last month, of the second quarter of the 
performance period. Eligible employees who work infrequently (that is, 
those who work fewer than 120 hours during a 90-day period, including 
those who only occasionally cover shifts at a

[[Page 21368]]

nursing home) would be excluded from the denominator calculation.
(b) Numerator
    The numerator includes eligible employees who were included in the 
denominator and who are not identified in the PBJ data as having worked 
at the SNF for at least 60 consecutive days during the performance 
period. The 60-day gap must start during the period covered by the 
turnover measure. The turnover date is defined as the last workday 
prior to the start of the 60-day gap.
(5) Measure Calculation
    The proposed Nursing Staff Turnover measure is calculated using six 
consecutive quarters of PBJ data. Data from a baseline quarter,\223\ 
Q0, along with the first two quarters of the performance period, are 
used for identifying employees who are eligible to be included in the 
measure (denominator). The four quarters of data (Q1 through Q4) of the 
performance period are used for identifying the number of employment 
spells, defined as a continuous period of work, that ended in turnover 
(numerator). Data from the sixth quarter (Q5), which occurs after the 
four-quarter numerator (performance) period, are used to identify gaps 
in days worked that started in the last 60 days of the fifth quarter 
(Q4) used for the measure. To calculate the measure score, we first 
determine the measure denominator by identifying the total number of 
employment spells, defined as a continuous period of work. For example, 
for the FY 2026 program year, the denominator would be calculated as 
the number of eligible employees who worked 120 or more hours in a 90-
day period with the first workday of the 90-day period occurring in FY 
2023 Q4, the quarter prior to the start of the performance period (Q0), 
through FY 2024 Q2, the first 2 quarters of the performance period 
(July 1, 2023 through March 31, 2024). The numerator is calculated as 
the total number of eligible employees who had a 60-day gap from 
October 1, 2023 through September 30, 2024 during which they did not 
work. Data from FY 2025 Q1, defined as Q5 above, is also used to 
identify gaps that start within 60 days of the end of the performance 
period (August 2, 2024 through September 30, 2024).
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    \223\ The baseline quarter is specific to this measure 
calculation and not related to the SNF VBP Program's measure 
baseline period, which is part of the performance standards used to 
score the measure. The baseline quarter is the quarter prior to the 
first quarter of either the baseline period or the performance 
period for a program year.
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    We are proposing to calculate the Nursing Staff Turnover measure 
rate for the SNF VBP Program using the following formula:
[GRAPHIC] [TIFF OMITTED] TP10AP23.000

    We also note that based on analysis and previous research on 
turnover measures, and a review by a technical expert panel, the 
Nursing Staff Turnover measure is not risk-adjusted.
    We invite public comment on our proposal to adopt the Total Nursing 
Staff Turnover measure beginning with the FY 2026 SNF VBP program year.
c. Proposal To Adopt the Percent of Residents Experiencing One or More 
Falls With Major Injury (Long-Stay) Measure Beginning With the FY 2027 
SNF VBP Program Year
    We are proposing to adopt the Percent of Residents Experiencing One 
or More Falls with Major Injury (Long-Stay) Measure (``Falls with Major 
Injury (Long-Stay) measure'') beginning with the FY 2027 SNF VBP 
program year. The Falls with Major Injury (Long-Stay) measure is an 
outcome measure that estimates the percentage of long-stay residents 
who have experienced one or more falls with major injury. We refer 
readers to the specifications for this proposed measure, which are 
located in the Minimum Data Set (MDS) 3.0 Quality Measures User's 
Manual Version 15 available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures. The Falls with Major Injury (Long-Stay) measure 
was endorsed by the CBE in 2011. The measure is currently reported by 
nursing facilities under the CMS Nursing Home Quality Initiative (NHQI) 
and the Five-Star Quality Rating System and those results are publicly 
reported on the Care Compare website, available at https://www.medicare.gov/care-compare/.
(1) Background
    Falls are the leading cause of injury-related death among persons 
aged 65 years and older. According to the Centers for Disease Control 
and Prevention (CDC), approximately one in four adults aged 65 years 
and older fall each year, and fall-related emergency department visits 
are estimated at approximately 3 million per year.\224\ In 2016, nearly 
30,000 U.S. residents aged 65 years and older died as the result of a 
fall, resulting in an age-adjusted mortality rate of 61.6 deaths per 
100,000 people. This represents a greater than 30 percent increase in 
fall-related deaths from 2007, where the age-adjusted mortality rate 
was 47.0 deaths per 100,000 people.\225\ Additionally, the death rate 
from falls was higher among adults aged 85 years and older as indicated 
by a mortality rate of 257.9 deaths per 100,000 people.\226\
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    \224\ Burns E, Kakara R. Deaths from Falls Among Persons Aged 
>=65 Years--United States, 2007-2016. MMWR Morb Mortal Wkly Rep 
2018;67:509-514. DOI: http://dx.doi.org/10.15585/mmwr.mm6718a1externalicon.
    \225\ Ibid.
    \226\ Ibid.
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    Of the 1.6 million residents in U.S. nursing facilities, 
approximately half fall annually, with one in three having two or more 
falls in a year. One in every ten residents who falls has a serious 
related injury, and about 65,000 residents suffer a hip fracture each 
year.\227\ An analysis of MDS data from FY 2019 Q2 found that, among 
the 14,586 nursing facilities included in the sample, the percent of 
long-stay residents who experienced one or more falls with major injury 
ranged from zero percent to nearly 21 percent. This wide variation in 
facility -level fall rates indicates a performance gap and suggests 
that there are opportunities to improve performance on this measure.
---------------------------------------------------------------------------

    \227\ The Falls Management Program: A Quality Improvement 
Initiative for Nursing Facilities: Chapter 1. introduction and 
program overview. Agency for Healthcare Research and Quality. 
https://www.ahrq.gov/patient-safety/settings/long-term-care/resource/injuries/fallspx/man1.html. Published December 2017. 
Accessed December 13, 2022.
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    It is important to monitor injurious falls among the long-stay 
population because of the potentially negative impacts on resident 
health outcomes and quality of life. Research has found that injurious 
falls are one of the leading causes of disability and death for all 
nursing home residents. Specifically, falls have serious health 
consequences, such as reduced quality of life,

[[Page 21369]]

decreased functional abilities, anxiety and depression, serious 
injuries, and increased risk of morbidity and 
mortality.228 229
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    \228\ The Falls Management Program: A Quality Improvement 
Initiative for Nursing Facilities: Chapter 1. Introduction and 
Program Overview. Agency for Healthcare Research and Quality. 
https://www.ahrq.gov/patient-safety/settings/long-term-care/resource/injuries/fallspx/man1.html. Published December 2017. 
Accessed December 13, 2022.
    \229\ Bastami M, Azadi A. Effects of a Multicomponent Program on 
Fall Incidence, Fear of Falling, and Quality of Life among Older 
Adult Nursing Home Residents. Ann Geriatr Med Res. 2020;24(4):252-
258. doi:10.4235/agmr.20.0044.
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    Injurious falls are also a significant cost burden to the entire 
healthcare system. The U.S. spends approximately $50 billion on medical 
costs related to non-fatal fall-related injuries and $754 million on 
medical costs related to fatal falls annually.\230\ Of the amount paid 
on non-fatal fall injuries, Medicare pays approximately $29 billion, 
while private or out-of-pocket payers pay $12 billion. Research 
suggests that acute care costs incurred for falls among nursing home 
residents range from $979 for a typical case with a simple fracture to 
$14,716 for a typical case with multiple injuries.\231\ Other research 
examining hospitalizations of nursing home residents with serious fall-
related injuries (intracranial bleed, hip fracture, or other fracture) 
found an average cost of $23,723.\232\
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    \230\ Cost of older adult falls. Centers for Disease Control and 
Prevention. https://www.cdc.gov/falls/data/fall-cost.html. Published 
July 9, 2020. Accessed December 13, 2022.
    \231\ Sorensen SV, de Lissovoy G, Kunaprayoon D, Resnick B, 
Rupnow MF, Studenski S. A taxonomy and economic consequence of 
nursing home falls. Drugs Aging. 2006;23(3):251-62.
    \232\ Quigley PA, Campbell RR, Bulat T, Olney RL, Buerhaus P, 
Needleman J. Incidence and cost of serious fall-related injuries in 
nursing homes. Clin Nurs Res. Feb 2012;21(1):10-23.
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    Research has found that 78 percent of falls are anticipated 
physiologic falls, which are defined as falls among individuals who 
scored high on a risk assessment scale, meaning their risk could have 
been identified in advance of the fall.\233\ To date, studies have 
identified a number of risk factors for falls within the long-stay 
population, including impaired cognitive function, history of falls, 
difficulties with walking and balancing, vitamin D deficiency, and use 
of psychotropic medications.234 235 236 In addition, 
residents who experience dementia or depression, are underweight, or 
are over the age of 85 are at a higher risk of 
falling.237 238 239 While much of this research has been 
conducted in long-term care facilities or nursing homes, we believe 
this research is relevant to the SNF setting, because approximately 94 
percent of long-term care facilities are dually certified as both SNFs 
or nursing facilities (86 FR 42508). Therefore, these risk factors 
described above suggest that SNFs may be able to identify, reduce, and 
prevent the incidence of falls among their 
residents.240 241 242 243
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    \233\ Morse, JM. Enhancing the safety of hospitalization by 
reducing patient falls. Am J Infect Control 2002; 30(6): 376-80.
    \234\ Cost of older adult falls. Centers for Disease Control and 
Prevention. https://www.cdc.gov/falls/data/fall-cost.html. Published 
July 9, 2020. Accessed December 13, 2022.
    \235\ Galik, E, Resnick, B, Hammersla, M, & Brightwater, J 
(2014). Optimizing function and physical activity among nursing home 
residents with dementia: testing the impact of function-focused 
care. Gerontologist 54(6), 930-943. https://doi.org/10.1093/geront/gnt108.
    \236\ Broe KE, Chen TC, Weinberg J, Bischoff-Ferrari HA, Holick 
MF, Kiel DP. A higher dose of vitamin d reduces the risk of falls in 
nursing home residents: a randomized, multiple-dose study. J Am 
Geriatr Soc. 2007;55(2):234-239. doi:10.1111/j.1532-
5415.2007.01048.x.
    \237\ Zhang N, Lu SF, Zhou Y, Zhang B, Copeland L, Gurwitz JH. 
Body Mass Index, Falls, and Hip Fractures Among Nursing Home 
Residents. J Gerontol A Biol Sci Med Sci. 2018;73(10):1403-1409. 
doi:10.1093/gerona/gly039.
    \238\ Fernando E, Fraser M, Hendriksen J, Kim CH, Muir-Hunter 
SW. Risk Factors Associated with Falls in Older Adults with 
Dementia: A Systematic Review. Physiother Can. 2017;69(2):161-170. 
doi:10.3138/ptc.2016-14.
    \239\ Grundstrom AC, Guse CE, Layde PM. Risk factors for falls 
and fall-related injuries in adults 85 years of age and older. Arch 
Gerontol Geriatr. 2012;54(3):421-428. doi:10.1016/
j.archger.2011.06.008.
    \240\ Morris JN, Moore T, Jones R, et al. Validation of long-
term and post-acute care quality indicators. CMS Contract No: 500-
95-0062.
    \241\ Chen XL, Liu YH, Chan DK, Shen Q, Van Nguyen H. Chin Med J 
(Engl). Characteristics associated with falls among the elderly 
within aged care wards in a tertiary hospital: A Retrospective. 2010 
Jul; 123(13):1668-72.
    \242\ Fonad E, Wahlin TB, Winblad B, Emami A, Sandmark H. Falls 
and fall risk among nursing home residents. J Clin Nurs. 2008 Jan; 
17(1):126-34.
    \243\ Lee JE, Stokic DS. Risk factors for falls during inpatient 
rehabilitation. Am J Phys Med Rehabil. 2008 May; 87(5):341-50; quiz 
351, 422.
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    Given the effects of falls with major injury, preventing and 
reducing their occurrence in SNFs is critical to delivering safe and 
high-quality care. We believe the proposed Falls with Major Injury 
(Long-Stay) measure aligns with this goal by monitoring the occurrence 
of falls with major injury and assessing SNFs on their performance on 
fall prevention efforts. In doing so, we believe the proposed measure 
would promote patient safety and increase the transparency of care 
quality in the SNF setting, and it would address the Patient Safety 
domain of CMS' Meaningful Measures 2.0 Framework.\244\
---------------------------------------------------------------------------

    \244\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
---------------------------------------------------------------------------

    We believe there are effective interventions that SNFs can 
implement to reduce and prevent falls, including those that cause major 
injury. Specifically, several studies observed that multifactorial 
interventions such as exercise, medication review, risk assessment, 
vision assessment, and environmental assessment significantly reduce 
fall rates.245 246 247 Another study found that a single 
intervention of exercise reduced the number of resident falls in the 
nursing home setting by 36 percent and the number of recurrent fallers 
by 41 percent.\248\ Additionally, various systematic reviews link 
facility structural characteristics to falls with major injury. For 
example, the incorporation of adequate equipment throughout the 
facility, such as hip protectors or equipment used for staff education 
tasks, may reduce fall rates or fall-related 
injuries.249 250 In addition, poor communication between 
staff, inadequate staffing levels, and limited facility equipment have 
been identified as barriers to implementing fall prevention programs in 
facilities.\251\

[[Page 21370]]

Other studies have shown that proper staff education can significantly 
reduce fall rates.252 253 The effectiveness of these 
interventions suggest improvement of fall rates among SNF residents is 
possible through modification of provider-led processes and 
interventions, which supports the overall goal of the SNF VBP Program.
---------------------------------------------------------------------------

    \245\ Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A 
(2020). Efficacy and generalizability of falls prevention 
interventions in nursing homes: A systematic review and meta-
analysis. Journal of the American Medical Directors Association, 
21(8), P1024-1035.E4. https://doi.org/10.1016/j.jamda.2019.11.012.
    \246\ Tricco, AC, Thomas, SM, Veroniki, AA, Hamid, JS, Cogo, E, 
Strifler, L, Khan, PA, Robson, R, Sibley, KM, MacDonald, H, Riva, 
JJ, Thavorn, K, Wilson, C, Holroyd-Leduc, J, Kerr, GD, Feldman, F, 
Majumdar, SR, Jaglal, SB, Hui, W, & Straus, SE (2017). Comparisons 
of interventions for preventing falls in older adults: A systematic 
review and meta-analysis. Journal of the American Medical 
Association, 318(17), 1687-1699. https://doi.org/10.1001/jama.2017.15006.
    \247\ Vlaeyen, E, Coussement, J, Leysens, G, Van der Elst, E, 
Delbaere, K, Cambier, D, Denhaerynck, K, Goemaere, S, Wertelaers, A, 
Dobbels, F, Dejaeger, E, & Milisen, K (2015). Characteristics and 
effectiveness of fall prevention programs in nursing homes: A 
systematic review and meta-analysis of randomized control trials. 
Journal of the American Geriatrics Society, 6(3), 211-21. https://doi.org/10.1111/jgs.13254.
    \248\ Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A 
(2020). Efficacy and generalizability of falls prevention 
interventions in nursing homes: A systematic review and meta-
analysis. Journal of the American Medical Directors Association, 
21(8), P1024-1035.E4. https://doi.org/10.1016/j.jamda.2019.11.012.
    \249\ Crandall, M, Duncan, T, Mallat, A, Greene, W, Violano, P, 
& Christmas, B (2016). Prevention of fall-related injuries in the 
elderly: An eastern association for the surgery of trauma practice 
management guideline. Journal of Trauma and Acute Care Surgery, 
81(1), 196-206. https://doi.org/10.1097/TA.0000000000001025.
    \250\ Vlaeyen, E, Stas, J, Leysens, G, Van der Elst, E, 
Janssens, E, Dejaeger, E, Dobbels, F, & Milisen, K (2017). 
Implementation of fall prevention in residential care facilities: A 
systematic review of barriers and facilitators. International 
Journal of Nursing Studies, 70, 110-121. https://doi.org/10.1016/j.ijnurstu.2017.02.002.
    \251\ Ibid.
    \252\ Gulka, HJ, Patel, V, Arora, T, McArthur, C, & Iaboni, A 
(2020). Efficacy and generalizability of falls prevention 
interventions in nursing homes: A systematic review and meta-
analysis. Journal of the American Medical Directors Association, 
21(8), P1024-1035.E4. https://doi.org/10.1016/j.jamda.2019.11.012.
    \253\ Tricco, AC, Thomas, SM, Veroniki, AA, Hamid, JS, Cogo, E, 
Strifler, L, Khan, PA, Robson, R, Sibley, KM, MacDonald, H, Riva, 
JJ, Thavorn, K, Wilson, C, Holroyd-Leduc, J, Kerr, GD, Feldman, F, 
Majumdar, SR, Jaglal, SB, Hui, W, & Straus, SE (2017). Comparisons 
of interventions for preventing falls in older adults: A systematic 
review and meta-analysis. Journal of the American Medical 
Association, 318(17), 1687-1699. https://doi.org/10.1001/jama.2017.15006.
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(2) Overview of Measure
    The proposed Falls with Major Injury (Long-Stay) measure is an 
outcome measure that reports the percentage of long-stay residents in a 
nursing home who have experienced one or more falls with major injury 
using 1 year of data from the Minimum Data Set (MDS) 3.0. This measure 
defines major injuries as bone fractures, joint dislocations, closed 
head injuries with altered consciousness, or subdural hematomas. Long-
stay residents are defined as residents who have received 101 or more 
cumulative days of nursing home care by the end of the measure 
reporting period (performance period). This proposed measure is a 
patient safety measure reported at the facility-level.
    Although the Falls with Major Injury (Long-Stay) measure is a long-
stay measure, we believe that including a long-stay measure in the SNF 
VBP Program is appropriate because it would better capture the quality 
of care provided to the entirety of the population that resides in 
facilities that are dually certified as SNFs and nursing facilities, 
including long-stay residents who continue to receive Medicare coverage 
for certain services provided by nursing facilities. We discussed the 
potential to include long stay measures in the SNF VBP Program in the 
FY 2022 SNF PPS final rule Summary of Comments Received on Potential 
Future Measures for the SNF VBP Program (86 FR 42507 through 42510). 
Specifically, we stated that the majority of long-stay residents are 
Medicare beneficiaries, regardless of whether they are in a Medicare 
Part A SNF stay, because they are enrolled in Medicare Part B and 
receive Medicare coverage of certain services provided by long-term 
care facilities even if they are a long-stay resident. We did not 
receive any negative comments on inclusion of this specific Falls with 
Major Injury (Long-Stay) measure or long-stay measures generally in the 
Program in response to this request for comment.
    We have adopted a similar measure for the SNF QRP, titled 
Application of Percent of Residents Experiencing One or More Falls with 
Major Injury (Long Stay) (80 FR 46440 through 46444), but that measure 
excludes long-stay residents. We believe it is important to hold SNFs 
accountable for the quality of care provided to long-stay residents 
given that the majority of long-term care facilities are dually 
certified as SNFs and nursing facilities. Additionally, we believe the 
proposed Falls with Major Injury (Long-Stay) measure satisfies the 
requirement to consider and apply, as appropriate, quality measures 
specified under section 1899B(c)(1) of the Act, in which this measure 
aligns with the domain, incidence of major falls, described at section 
1899B(c)(1)(D) of the Act. Therefore, we believe it is appropriate for 
the SNF VBP program to include a falls with major injury for long-stay 
resident measure.
    Testing for this measure has demonstrated that the Falls with Major 
Injury (Long-Stay) measure has sufficient reliability and validity. For 
example, signal-to-noise and split-half reliability analyses found that 
the measure exhibited moderate reliability. Validity testing showed 
that there are meaningful differences in nursing facility-level scores 
for this measure, indicating good validity. For additional details on 
measure testing, we refer readers to the MAP PAC/LTC: 2022-2023 MUC 
Cycle Measure Specifications Manual available at https://mmshub.cms.gov/sites/default/files/map-pac-muc-measure-specifications-2022-2023.pdf.
(a) Interested Parties and TEP Input
    In considering the selection of this measure for the SNF VBP 
Program, CMS convened a TEP in March 2022 which focused on the 
identification of measurement gaps and measure development priorities 
for the Program. Panelists were largely supportive of including a falls 
with major injury measure compared to a general falls measure or a 
falls with injury measure for several reasons including: (1) the broad 
definition of falls; and (2) the consensus-based entity endorsement of 
the Falls with Major Injury (Long-Stay) measure in the Nursing Home 
Quality Initiative Program. A summary of the TEP meeting is available 
at https://mmshub.cms.gov/sites/default/files/SNF-VBP-TEP-Summary-Report-Mar2022.pdf.
(b) Measure Applications Partnership (MAP) Review
    We included the Falls with Major Injury (Long-Stay) measure for the 
SNF VBP in the publicly available ``2022 Measures Under Consideration 
List''.\254\ The MAP supported the Falls with Major Injury (Long-Stay) 
measure for rulemaking, noting that the measure would add value to the 
Program because of the lack of an existing falls measure and that it 
would help improve patient safety. We refer readers to the final 2022-
2023 MAP recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    \254\ 2022 Measures Under Consideration Spreadsheet available at 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
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(3) Data Sources
    The proposed Falls with Major Injury (Long-Stay) measure is 
calculated using 1 year of patient data collected through the MDS. The 
collection instrument is the Resident Assessment Instrument (RAI), 
which contains the MDS 3.0. The RAI is a tool used by nursing home 
staff to collect information on residents' strengths and needs. We 
describe the measure specifications in more detail below and also refer 
readers to the MDS 3.0 Quality Measures User's Manual Version 15.0 for 
further details on how these data components are utilized in 
calculating the Falls with Major Injury (Long-Stay) measure available 
at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures. Technical 
information for the MDS 3.0 is also available at https://www.cms.gov/
Medicare/Quality-Initiatives-Patient-Assessment-Instruments/
NursingHomeQualityInits/NHQIMDS30TechnicalInformation. The proposed 
Falls with Major Injury (Long-Stay) measure is calculated using data 
from the MDS, which all Medicare-certified SNFs and Medicaid-certified 
nursing facilities are currently required to report. Therefore, this 
measure would not impose any additional data collection or submission 
burden for SNFs.
(4) Measure Specifications
(a) Denominator
    All long-stay residents with one or more look-back scan assessments 
no more than 275 days prior to the target assessment, except those that 
meet the

[[Page 21371]]

exclusion criteria, are included in the measure denominator. Long-stay 
residents are defined as those who have 101 or more cumulative days of 
nursing home care by the end of the measure reporting period 
(performance period). Residents who return to the nursing home 
following a hospital discharge would not have their cumulative days in 
the facility reset to zero, meaning that days of care from a previous 
admission would be added to any subsequent admissions.
    The MDS includes a series of assessments and tracking documents, 
such as Omnibus Budget Reconciliation Act (OBRA) Comprehensive 
Assessments, OBRA Quarterly Assessments, OBRA Discharge Assessments or 
PPS assessments. For the purposes of this measure, a target assessment, 
which presents the resident's status at the end of the episode of care 
or their latest status if their episode of care is ongoing, is selected 
for each long-stay resident. Target assessments may be an Omnibus 
Budget Reconciliation Act (OBRA) admission, quarterly, annual, or 
significant change/correction assessment; or PPS 5-day assessments; or 
discharge assessment with or without anticipated return. For more 
information on how we define target assessments, we refer readers to 
the MDS 3.0 Quality Measures User's Manual Version 15.0 available at 
https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.
(b) Denominator Exclusions
    Residents are excluded from the denominator if the number of falls 
with major injury was not coded for all of the look-back scan 
assessments. A SNF would not be scored on this measure if it does not 
have long-stay residents, or residents with 101 or more cumulative days 
of care. The measure also excludes all SNF swing beds because they are 
not used for long-stay residents.
(c) Numerator
    The measure numerator includes long-stay residents with one or more 
look-back scan assessments that indicate one or more falls that 
resulted in major injury. Major injuries include bone fractures, joint 
dislocations, closed-head injuries with altered consciousness, or 
subdural hematomas. The selection period for the look-back scan 
consists of the target assessment and all qualifying earlier 
assessments in the scan.
    An assessment should be included in the scan if it meets all of the 
following conditions: (1) it is contained within the resident's 
episode, (2) it has a qualifying Reason for Assessment (RFA), (3) its 
target date is on or before the target date for the target assessment, 
and (4) its target date is no more than 275 days prior to the target 
date of the target assessment. For the purposes of this measure, we 
define the target date as the event date of an MDS record (that is, 
entry date for an entry record or discharge date for a discharge record 
or death-in-facility record) or the assessment reference date (for all 
records that are not entry, discharge, or death-in-facility). For 
additional target date details, we refer readers to Chapter 1 of the 
MDS 3.0 Quality Measures User's Manual Version 15.0 available at 
https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.
    A 275-day time period is used to include up to three quarterly OBRA 
assessments. The earliest of these assessments would have a look-back 
period of up to 93 days, which would cover a total of about 1 year. To 
calculate the measure, we scan these target assessments and any 
qualifying earlier assessments described in the previous paragraph for 
indicators of falls with major injury.
(5) Risk Adjustment
    The Falls with Major Injury (Long-Stay) measure is not risk-
adjusted. We considered risk adjustment during measure development, and 
we tested various risk-adjustment models, but none had sufficient 
predictive ability.
(6) Measure Calculation
    The Falls with Major Injury (Long-Stay) measure is calculated and 
reported at the facility level. Specifically, to calculate the measure 
score, we are proposing to first determine the measure denominator by 
identifying the total number of long-stay residents with a qualifying 
target assessment (OBRA, PPS, or discharge), one or more look-back scan 
assessments, and who do not meet the exclusion criteria. Using that set 
of residents, we calculate the numerator by identifying the total 
number of those residents with one or more look-back scan assessments 
that indicate one or more falls that resulted in major injury. We then 
divide the numerator by the denominator and multiply the resulting 
ratio by 100 to obtain the percentage of long-stay residents who 
experience one or more falls with major injury. A lower measure rate 
indicates better performance on the measure. For additional details on 
the calculation method, we refer readers to the specifications for the 
Falls with Major Injury (Long-Stay) measure included in the MDS 3.0 
Quality Measures User's Manual available at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqiqualitymeasures.
    We invite public comment on our proposal to adopt the Percent of 
Residents Experiencing One or More Falls with Major Injury (Long-Stay) 
measure beginning with the FY 2027 SNF VBP program year.
d. Proposal To Adopt the Discharge Function Score Measure Beginning 
With the FY 2027 SNF VBP Program Year
    We are proposing to adopt the Discharge Function Score (``DC 
Function'') measure beginning with the FY 2027 SNF VBP Program.\255\ We 
are also proposing to adopt this measure in the SNF QRP (see section 
VI. of this proposed rule).
---------------------------------------------------------------------------

    \255\ This measure was submitted to the Measure Under 
Consideration (MUC) List as the Cross-Setting Discharge Function 
Score. Subsequent to the MAP workgroup meetings, the measure 
developer modified the name.
---------------------------------------------------------------------------

(1) Background
    Maintenance or improvement of physical function among older adults 
is increasingly an important focus of healthcare. Adults aged 65 years 
and older constitute the most rapidly growing population in the United 
States, and functional capacity in physical (non-psychological) domains 
has been shown to decline with age.\256\ Moreover, impaired functional 
capacity is associated with poorer quality of life and an increased 
risk of all-cause mortality, postoperative complications, and cognitive 
impairment, the latter of which can complicate the return of a resident 
to the community from post-acute care.257 258 259 
Nonetheless,

[[Page 21372]]

evidence suggests that physical functional abilities, including 
mobility and self-care, are modifiable predictors of resident outcomes 
across PAC settings, including functional recovery or decline after 
post-acute care,260 261 262 263 264 rehospitalization 
rates,265 266 267 discharge to community,268 269 
and falls.\270\ Because evidence shows that older adults experience 
aging heterogeneously and require individualized and comprehensive 
healthcare, functional status can serve as a vital component in 
informing the provision of healthcare and thus indicate a SNF's quality 
of care.271 272
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    \256\ High KP, Zieman S, Gurwitz J, Hill C, Lai J, Robinson T, 
Schonberg M, Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \257\ Clouston SA, Brewster P, Kuh D, Richards M, Cooper R, 
Hardy R, Rubin MS, Hofer SM The dynamic relationship between 
physical function and cognition in longitudinal aging cohorts. 
Epidemiol Rev. 2013;35(1):33-50. doi: 10.1093/epirev/mxs004. Epub 
2013 Jan 24. PMID: 23349427; PMCID: PMC3578448.
    \258\ Michael YL, Colditz GA, Coakley E, Kawachi I. Health 
behaviors, social networks, and healthy aging: cross-sectional 
evidence from the Nurses' Health Study. Qual Life Res. 1999 
Dec;8(8):711-22. doi: 10.1023/a:1008949428041. PMID: 10855345.
    \259\ High KP, Zieman S, Gurwitz J, Hill C, Lai J, Robinson T, 
Schonberg M, Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \260\ Deutsch A, Palmer L, Vaughan M, Schwartz C, McMullen T. 
Inpatient Rehabilitation Facility Patients' Functional Abilities and 
Validity Evaluation of the Standardized Self-Care and Mobility Data 
Elements. Arch Phys Med Rehabil. 2022 Feb 11:S0003-9993(22)00205-2. 
doi: 10.1016/j.apmr.2022.01.147. Epub ahead of print. PMID: 
35157893.
    \261\ Hong I, Goodwin JS, Reistetter TA, Kuo YF, Mallinson T, 
Karmarkar A, Lin YL, Ottenbacher KJ. Comparison of Functional Status 
Improvements Among Patients With Stroke Receiving Postacute Care in 
Inpatient Rehabilitation vs Skilled Nursing Facilities. JAMA Netw 
Open. 2019 Dec 2;2(12):e1916646. doi: 10.1001/
jamanetworkopen.2019.16646. PMID: 31800069; PMCID: PMC6902754.
    \262\ Alcusky M, Ulbricht CM, Lapane KL. Postacute Care Setting, 
Facility Characteristics, and Poststroke Outcomes: A Systematic 
Review. Arch Phys Med Rehabil. 2018;99(6):1124-1140.e9. doi:10.1016/
j.apmr.2017.09.005. PMID: 28965738; PMCID: PMC5874162.
    \263\ Chu CH, Quan AML, McGilton KS. Depression and Functional 
Mobility Decline in Long Term Care Home Residents with Dementia: a 
Prospective Cohort Study. Can Geriatr J. 2021;24(4):325-331. 
doi:10.5770/cgj.24.511. PMID: 34912487; PMCID: PMC8629506.
    \264\ Lane NE, Stukel TA, Boyd CM, Wodchis WP. Long-Term Care 
Residents' Geriatric Syndromes at Admission and Disablement Over 
Time: An Observational Cohort Study. J Gerontol A Biol Sci Med Sci. 
2019;74(6):917-923. doi:10.1093/gerona/gly151. PMID: 29955879; 
PMCID: PMC6521919.
    \265\ Li CY, Haas A, Pritchard KT, Karmarkar A, Kuo YF, Hreha K, 
Ottenbacher KJ. Functional Status Across Post-Acute Settings is 
Associated With 30-Day and 90-Day Hospital Readmissions. J Am Med 
Dir Assoc. 2021 Dec;22(12):2447-2453.e5. doi: 10.1016/
j.jamda.2021.07.039. Epub 2021 Aug 30. PMID: 34473961; PMCID: 
PMC8627458.
    \266\ Middleton A, Graham JE, Lin YL, Goodwin JS, Bettger JP, 
Deutsch A, Ottenbacher KJ. Motor and Cognitive Functional Status Are 
Associated with 30-day Unplanned Rehospitalization Following Post-
Acute Care in Medicare Fee-for-Service Beneficiaries. J Gen Intern 
Med. 2016 Dec;31(12):1427-1434. doi: 10.1007/s11606-016-3704-4. Epub 
2016 Jul 20. PMID: 27439979; PMCID: PMC5130938.
    \267\ Gustavson AM, Malone DJ, Boxer RS, Forster JE, Stevens-
Lapsley JE. Application of High-Intensity Functional Resistance 
Training in a Skilled Nursing Facility: An Implementation Study. 
Phys Ther. 2020;100(10):1746-1758. doi: 10.1093/ptj/pzaa126. PMID: 
32750132; PMCID: PMC7530575.
    \268\ Minor M, Jaywant A, Toglia J, Campo M, O'Dell MW. 
Discharge Rehabilitation Measures Predict Activity Limitations in 
Patients with Stroke Six Months after Inpatient Rehabilitation. Am J 
Phys Med Rehabil. 2021 Oct 20. doi: 10.1097/PHM.0000000000001908. 
Epub ahead of print. PMID: 34686630.
    \269\ Dubin R, Veith JM, Grippi MA, McPeake J, Harhay MO, 
Mikkelsen ME. Functional Outcomes, Goals, and Goal Attainment among 
Chronically Critically Ill Long-Term Acute Care Hospital Patients. 
Ann Am Thorac Soc. 2021;18(12):2041-2048. doi:10.1513/
AnnalsATS.202011-1412OC. PMID: 33984248; PMCID: PMC8641806.
    \270\ Hoffman GJ, Liu H, Alexander NB, Tinetti M, Braun TM, Min 
LC Posthospital Fall Injuries and 30-Day Readmissions in Adults 65 
Years and Older. JAMA Netw Open. 2019 May 3;2(5):e194276. doi: 
10.1001/jamanetworkopen.2019.4276. PMID: 31125100; PMCID: 
PMC6632136.
    \271\ Criss MG, Wingood M, Staples W, Southard V, Miller K, 
Norris TL, Avers D, Ciolek CH, Lewis CB, Strunk ER. APTA Geriatrics' 
Guiding Principles for Best Practices in Geriatric Physical Therapy: 
An Executive Summary. J Geriatr Phys Ther. 2022 April/June;45(2):70-
75. doi: 10.1519/JPT.0000000000000342. PMID: 35384940.
    \272\ Cogan AM, Weaver JA, McHarg M, Leland NE, Davidson L, 
Mallinson T. Association of Length of Stay, Recovery Rate, and 
Therapy Time per Day With Functional Outcomes After Hip Fracture 
Surgery. JAMA Netw Open. 2020 Jan 3;3(1):e1919672. doi: 10.1001/
jamanetworkopen.2019.19672. PMID: 31977059; PMCID: PMC6991278.
---------------------------------------------------------------------------

    As stated in section VI. of this proposed rule, we are proposing 
this measure for the SNF QRP, and we are also proposing it for adoption 
in the SNF VBP Program under section 1888(h)(2)(A)(ii) of the Act. We 
believe it is important to measure quality across the full range of 
outcomes for Medicare beneficiaries during a SNF stay. Further, 
adoption of this measure would ensure that the SNF VBP Program's 
measure set aligns with the Person-Centered Care domain of CMS' 
Meaningful Measures 2.0 Framework.
    We included the proposed DC Function measure on the 2022-2023 MUC 
list for the Inpatient Rehabilitation Facility QRP, Home Health QRP, 
Long Term Care Hospital QRP, SNF QRP, and SNF VBP. While the DC 
Function measure is not yet implemented in the SNF QRP or other PAC 
programs, SNFs already report many of the elements that would be used 
to calculate this measure.\273\ As such, we believe SNFs have had 
sufficient time to ensure successful reporting of the data elements 
needed for this measure.
---------------------------------------------------------------------------

    \273\ National Quality Forum. (2022, December 29). MAP PAC/LTC 
Workgroup: 2022-2023 Measures Under Consideration (MUC) Review 
Meeting. Retrieved from https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier= id&ItemID=97960.

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

(2) Overview of Measure
    The proposed DC Function measure is an outcome measure that 
estimates the percentage of SNF residents who meet or exceed an 
expected discharge score during the reporting period. The proposed DC 
Function measure's numerator is the number of SNF stays with an 
observed discharge function score that is equal to or higher than the 
calculated expected discharge function score. The observed discharge 
function score is the sum of individual function items at discharge. 
The expected discharge function score is computed by risk adjusting the 
observed discharge function score for each SNF stay. Risk adjustment 
controls for resident characteristics, such as admission function 
score, age, and clinical conditions. The denominator is the total 
number of SNF stays with a MDS record in the measure target period 
(four rolling quarters) which do not meet the measure exclusion 
criteria. For additional details regarding the numerator, denominator, 
risk adjustment, and exclusion criteria, refer to the Discharge 
Function Score for Skilled Nursing Facilities (SNFs) Technical 
Report.\274\
---------------------------------------------------------------------------

    \274\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report, which is available on the SNF Quality 
Reporting Program Measures and Technical Information web page at 
https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

    The proposed DC Function measure implements a statistical 
imputation approach for handling ``missing'' standardized functional 
assessment data elements. The coding guidance for standardized 
functional assessment data elements allows for using ``Activity Not 
Attempted'' (ANA) codes, resulting in ``missing'' information about a 
patient's functional ability on at least some items, at admission and/
or discharge, for a substantive portion of SNF patients. Currently, 
functional outcome measures in the SNF QRP use a simple imputation 
method whereby all ANA codes or otherwise missing scores, on both 
admission and discharge records, are recoded to ``1'' or ``most 
dependent.'' Statistical imputation, on the other hand, replaces these 
missing values for a variable based on the values of other, non-missing 
variables in the data and which are otherwise similar to the assessment 
with a missing value. Specifically, this proposed DC Function measure's 
statistical, statistical imputation allows missing values (for

[[Page 21373]]

example, the ANA codes) to be replaced with any value from 1 to 6, 
based on a patient's clinical characteristics and codes assigned on 
other standardized functional assessment data elements. The measure 
implements separate imputation models for each standardized functional 
assessment data elements used in measure construction at admission and 
discharge. Relative to the current simple imputation method, this 
statistical imputation approach increases the precision and accuracy 
and reduces the bias in estimates for missing item scores. We refer 
readers to Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report \275\ for measure specifications and additional 
details. We also refer readers to the SNF QRP section VI.C.1.b.(1) of 
this proposed rule for additional information on Measure Importance and 
Measure Testing.
---------------------------------------------------------------------------

    \275\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report, which is available on the SNF Quality 
Reporting Program Measures and Technical Information web page at 
https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

(a) Interested Parties and TEP Input
    We convened two TEP meetings (July 2021 and January 2022), as well 
as a Patient and Family Engagement Listening Session, to collect 
feedback from interested parties on the measure's potential use in 
quality programs in the future. The TEP members expressed support for 
the measure's validity and agreed with the conceptual and operational 
definition of the measure.
    The feedback we received during the Patient and Family Engagement 
Listening Session demonstrated that this measure resonates with 
patients and caregivers. For example, participants' views of self-care 
and mobility were aligned with the functional domains captured by the 
measure, and participants found that those domains included critical 
aspects of care in post-acute care settings. Participants also 
emphasized the importance of measuring functional outcomes when 
assessing quality for SNF residents. We refer readers to the SNF QRP 
section VI.C.1.b.(3) of this proposed rule for additional discussion on 
the TEP.
(b) MAP Review
    The Discharge Function measure was included as a SNF VBP measure 
under consideration in the publicly available ``2022 Measures Under 
Consideration List.'' \276\ The MAP offered conditional support of the 
DC Function measure for rulemaking, contingent upon endorsement by the 
consensus-based entity, noting that the measure would add value to the 
Program because there are currently no measures related to functional 
status in the Program, and this measure serves as an indicator for 
whether the care provided is effective and high quality. We refer 
readers to section VI.C.1.b.(4) of this proposed rule for further 
details on the MAP's recommendations and the final 2022-2023 MAP 
recommendations available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    \276\ 2022 Measures Under Consideration Spreadsheet available at 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
---------------------------------------------------------------------------

    We invite public comment on our proposal to adopt the Discharge 
Function Score measure beginning with the FY 2027 SNF VBP program year.
e. Proposal To Adopt the Number of Hospitalizations per 1,000 Long-Stay 
Resident Days Measure Beginning With the FY 2027 SNF VBP Program Year
    We are proposing to adopt the Number of Hospitalization per 1,000 
Long Stay Resident Days Measure (``Long Stay Hospitalization measure'') 
beginning with the FY 2027 SNF VBP Program.
(1) Background
    Unplanned hospitalizations of long -stay residents can be 
disruptive and burdensome to residents. ``They can cause discomfort for 
residents, anxiety for loved ones, morbidity due to iatrogenic events, 
and excess healthcare costs.'' \277\ Studies have found that many 
unplanned hospitalizations could have been safely avoided by early 
intervention by the facility. For example, one structured review by 
expert clinicians of hospitalizations of skilled nursing facility 
residents found that two -thirds were potentially avoidable, citing a 
lack of primary care clinicians on-site and delays in assessments and 
lab orders as primary reasons behind unplanned hospitalizations.\278\ 
Another study found that standardizing advanced care planning and 
physician availability has a considerable impact on reducing 
hospitalizations.\279\ The Missouri Quality Initiative reduced 
hospitalizations by 30 percent by having a clinical resource embedded 
to influence resident care outcomes. Another study found that reducing 
hospitalizations did not increase the mortality risk for long -stay 
nursing home residents.\280\
---------------------------------------------------------------------------

    \277\ Ouslander, JG, Lamb, G, Perloe, M, Givens, JH, Kluge, L, 
Rutland, T, Atherly, A, & Saliba, D (2010). Potentially avoidable 
hospitalizations of nursing home residents: frequency, causes, and 
costs. Journal of the American Geriatrics Society, 58(4), 627-635. 
https://doi.org/10.1111/j.1532-5415.2010.02768.x.
    \278\ Ouslander, JG, Lamb, G, Perloe, M, Givens, JH, Kluge, L, 
Rutland, T, Atherly, A, & Saliba, D (2010). Potentially avoidable 
hospitalizations of nursing home residents: frequency, causes, and 
costs. Journal of the American Geriatrics Society, 58(4), 627-635. 
https://doi.org/10.1111/j.1532-5415.2010.02768.x.
    \279\ Giger, M, Voneschen, N, Brunkert, T, & Z[uacute]niga, F 
(2020). Care workers' view on factors leading to unplanned 
hospitalizations of nursing home residents: a cross-sectional 
multicenter study. Geriatric Nursing, 41(2), 110-117.
    \280\ Feng, Z, Ingber, MJ, Segelman, M, Zheng, NT, Wang, JM, 
Vadnais, A, . . . & Khatutsky, G (2018). Nursing facilities can 
reduce avoidable hospitalizations without increasing mortality risk 
for residents. Health Affairs, 37(10), 1640-1646.
---------------------------------------------------------------------------

    A review of data that were publicly reported on Care Compare shows 
that there is considerable variation in performance across nursing 
homes when it comes to unplanned hospitalizations, suggesting that 
improvement is possible through modification of facility-led processes 
and interventions. Specifically, performance on this measure ranges 
from 0.841 hospital admissions per 1,000 long stay resident days at the 
10th percentile to 2.656 hospital admissions per 1,000 long-stay 
resident days at the 90th percentile.\281\ In other words, the top 
decile of performers (10th percentile) has half the number of 
hospitalizations of the bottom decile (90th percentile). We also 
reported in 2020 that the rate of unplanned hospitalizations was 1.4 
per 1,000 nursing home resident days, suggesting these disruptive 
events are fairly common.\282\ Adopting this measure would align 
measures between Care Compare and the SNF VBP program without 
increasing the reporting burden.
---------------------------------------------------------------------------

    \281\ Data is pulled from the public facing scorecard in 2020, 
available at https://www.medicaid.gov/state-overviews/scorecard/hospitalizations-per-1000-long-stay-nursing-home-days/index.html.
    \282\ Data is pulled from the public facing scorecard in 2020, 
available at https://www.medicaid.gov/state-overviews/scorecard/hospitalizations-per-1000-long-stay-nursing-home-days/index.html.
---------------------------------------------------------------------------

    Although the proposed Long Stay Hospitalization measure is not 
specified under section 1899B(c)(1) of the Act, it aligns with the 
topics listed under section 1888(h)(2)(A)(ii) of the Act. We believe 
this outcome measure supports the Program's goals to improve the 
quality of care provided to Medicare beneficiaries throughout their 
entire SNF stay. Furthermore, the measure would align with the Care 
Coordination domain of the Meaningful Measures 2.0 Framework.
    We examined the relationship between long-stay hospitalization 
rates and other measures of quality from CMS' Five-Star Quality Rating 
System

[[Page 21374]]

using data from the December 2019 Nursing Home Compare update. Analyses 
showed that facilities with lower hospitalization rates tend to perform 
better on other dimensions of quality such as health inspection survey 
results, staffing level, other quality measures, and overall ratings.
    Although the Long Stay Hospitalization measure is a long-stay 
measure, we believe that including a long-stay measure in the SNF VBP 
Program is appropriate because it would better capture the quality of 
care provided to the entirety of the population that resides in 
facilities that are dually certified as SNFs and nursing facilities, 
including long-stay residents who continue to receive Medicare coverage 
for certain services provided by nursing facilities. We discussed the 
potential to include long stay measures in the SNF VBP Program in the 
FY 2022 SNF PPS final rule Summary of Comments Received on Potential 
Future Measures for the SNF VBP Program (86 FR 42507 through 42510). 
Specifically, we stated that the majority of long-stay residents are 
Medicare beneficiaries, regardless of whether they are in a Medicare 
Part A SNF stay, because they are enrolled in Medicare Part B and 
receive Medicare coverage of certain services provided by long-term 
care facilities even if they are a long-stay resident. We did not 
receive any negative comments on inclusion of this specific Long Stay 
Hospitalization measure or long-stay measures generally in the Program 
in response to the request for comment.
(2) Overview of Measure
    The Long Stay Hospitalization measure calculates the number of 
unplanned inpatient admissions to an acute care hospital or critical 
access hospital or outpatient observation stays that occurred among 
long-stay residents per 1,000 long stay resident days using 1 year of 
Medicare fee-for-service (FFS) claims data. A long-stay day is defined 
as any day after a resident's one-hundredth cumulative day in the 
nursing home or the beginning of the 12-month target period (whichever 
is later) and until the day of discharge, the day of death, or the end 
of the 12-month target period (whichever is earlier). We are proposing 
to risk adjust this measure, as we explain in more detail below.
(a) Measure Applications Partnership (MAP) Review
    We included the Long Stay Hospitalization measure in the publicly 
available ``2022 Measures Under Consideration List.'' \283\ The MAP 
offered conditional support of the Long Stay Hospitalization measure 
for rulemaking, contingent upon endorsement by the consensus-based 
entity, noting that the measure would add value to the Program because 
unplanned hospitalizations are disruptive and burdensome to long-stay 
residents. We refer readers to the final 2022-2023 MAP recommendations 
available at https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    \283\ 2022 Measures Under Consideration Spreadsheet available at 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
---------------------------------------------------------------------------

(3) Data Sources
    The Long Stay Hospitalization measure is calculated using Medicare 
fee-for-service (FFS) claims data. We use the inpatient hospital claims 
data to determine the hospital admission, outpatient hospital claims 
data to determine the outpatient observation stay, and items from the 
Minimum Data Set for building resident stays and for risk-adjustment.
(4) Inclusion and Exclusion Criteria
    All Medicare beneficiaries enrolled in both Part A and Part B are 
included. The measure excludes any resident enrolled in Medicare 
managed care during any portion of the resident's stay. The measure 
also excludes all days and any hospital admissions during which the 
resident was enrolled in hospice.
    The measure does not count days prior to a resident's 101st 
cumulative day, which is when the resident meets long-stay criteria. 
Furthermore, we do not include any long-stay days prior to the 
beginning of the applicable performance period. For example, if a 
resident becomes a long-stay resident on September 25, 2024, and is 
discharged on October 5, 2024, we would only count 5 days in the 
denominator during the performance period for the FY 2027 program year.
    Any days a resident was not in the facility for any reason would 
not be counted in the denominator, defined as the total observed number 
of long stay days at the facility. This means we do not count in the 
denominator any days the resident is admitted to another type of 
inpatient facility, or days temporarily residing in the community, so 
long as the NF with beds that are also certified as SNF beds submits an 
MDS discharge assessment for the temporary discharge. For example, if a 
patient became long-stay resident on December 20, but stayed with 
family on December 24 and December 25 but returned to the facility on 
December 26, we would not count those two days (24 and 25) in the 
denominator because the NF with beds that are also certified as SNF 
beds completed an MDS discharge assessment. We would also not count the 
days when a resident was admitted to a hospital, and therefore, is not 
residing at the facility in the denominator.
    We would not count an observed hospitalization of a resident, the 
numerator count, if the hospitalization occurred while the resident was 
not in the facility and had a completed MDS discharge assessment for 
the temporary discharge. In the example in the prior paragraph, if the 
resident was admitted to the hospital on December 25, during which they 
were residing with family with a completed MDS temporary discharge 
assessment, the admission would not be counted as a hospitalization for 
the NF with beds that are also certified as SNF beds (in the 
numerator). If, however, the resident returned to the NF with beds that 
are also certified as SNF beds on December 26 and was admitted to the 
hospital on December 27, then it would count as a hospitalization (in 
the numerator).
    If a resident spends 31 or more days in a row residing outside the 
NF with beds that are also certified as SNF beds, which could be in 
another facility or in the community, we would consider the resident 
discharged and they would no longer meet long-stay status. If a 
resident is discharged and then admitted to the same facility within 30 
days, we would consider the resident still in a long-stay status, and 
we would count the days in this admission in the measure denominator.
    The measure numerator includes all admissions to an acute care 
hospital or critical access hospital, for an inpatient or outpatient 
observation stay, that occur while the resident meets the long-stay 
status criteria. Observation stays are included in the numerator 
regardless of diagnosis. Planned inpatient admissions are not counted 
in the numerator since they are unrelated to the quality of care at the 
facility. Hospitalizations are classified as planned or unplanned using 
the same version of CMS' Planned Readmissions Algorithm that is used to 
calculate the percentage of short-stay residents who were re-
hospitalized after a nursing home admission in the Nursing Home Compare 
Five-Star Rating system. The algorithm identifies planned admission 
using the principal discharge diagnosis category and all procedure 
codes listed on inpatient claims, coded using the AHRQ Clinical 
Classification System (CCS) software.

[[Page 21375]]

(5) Risk Adjustment
    The risk adjustment model used for this measure is a negative 
binomial regression. Specifically, we are proposing to risk adjust the 
observed number of hospitalizations after the resident met the long-
stay status to determine the expected number of hospitalizations for 
each long-stay resident given the resident's clinical and demographic 
profile. The goal of risk adjustment is to account for differences 
across facilities in medical acuity, functional impairment, and frailty 
of the long-stay residents but not factors related to the quality of 
care provided by the facility. The data for the risk adjustment model 
are derived from Medicare inpatient claims data prior to the day the 
resident became a long-stay resident and from the most recent quarterly 
or comprehensive MDS assessment within 120 days prior to the day the 
resident became a long-stay resident.
    The risk adjustment variables derived from the claims-based data 
include age, sex, number of hospitalizations in the 365 days before the 
day the resident became a long-stay resident or beginning of the 1-year 
measurement period (whichever is later), and an outcome-specific 
comorbidity index. The MDS-based covariates span multiple domains 
including functional status, clinical conditions, clinical treatments, 
and clinical diagnoses.
    We refer readers to the measure specifications for additional 
details on the risk-adjustment model for this measure available at 
https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/CertificationandComplianc/Downloads/Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.
(6) Measure Calculation
    To get the risk adjusted rate (risk standardized rate), we take the 
observed Long Stay Hospitalization rate divided by the expected Long 
Stay Hospitalization rate, multiplied by the national Long Stay 
Hospitalization rate, as shown by the following formula:
[GRAPHIC] [TIFF OMITTED] TP10AP23.001

    The observed Long Stay Hospitalization rate is the actual number of 
hospital admissions or observation stays that met the inclusion 
criteria discussed in section VII.B.4.e.(4) of this proposed rule 
divided by the actual total number of long-stay days that met the 
inclusion criteria discussed in section VII.B.4.e.(4) of this proposed 
rule divided by 1,000 days. The observed rate is shown by the following 
formula:
[GRAPHIC] [TIFF OMITTED] TP10AP23.002

    The expected Long Stay Hospitalization rate is the expected number 
of hospital admission or observation stays that were calculated using 
the risk adjustment methodology discussed in section VII.B.4.e.(5) of 
this proposed rule, divided by the actual total number of long-stay 
days that met the inclusion criteria discussed in section VII.B.4.e.(4) 
of this proposed rule divided by 1,000 days. The expected Long Stay 
Hospitalization rate is shown by the following formula:
[GRAPHIC] [TIFF OMITTED] TP10AP23.003

    The national Long Stay Hospitalization rate is the total number of 
inpatient hospital admission or observation stays meeting the numerator 
criteria, divided by the total number of all long stay days that met 
the denominator criteria divided by 1,000. The national Long Stay 
Hospitalization rate is shown by the following formula:
[GRAPHIC] [TIFF OMITTED] TP10AP23.004

    We refer readers to the measure specification for additional 
details for this measure calculation available at https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/CertificationandComplianc/Downloads/Nursing-Home-Compare-Claims-based-Measures-Technical-Specifications-April-2019.pdf.
    We invite public comment on our proposal to adopt the Number of 
Hospitalizations per 1,000 Long-Stay Resident Days measure beginning 
with the FY 2027 SNF VBP program year.
f. Proposed Scoring of SNF Performance on the Nursing Staff Turnover, 
Falls With Major Injury (Long-Stay), and Long Stay Hospitalization 
Measures
(1) Background
    In the FY 2017 SNF PPS final rule (81 FR 52000 through 52001), we 
finalized a policy to invert SNFRM measure rates such that a higher 
measure rate reflects better performance on the SNFRM. In that final 
rule, we also stated our belief that this inversion is important for 
incentivizing improvement in a clear and understandable manner because 
a ``lower is better'' rate could cause confusion among SNFs and the 
public. In the FY 2023 SNF PPS final rule (87 FR 47568), we applied 
this policy to the

[[Page 21376]]

SNF HAI measure such that a higher measure rate reflects better 
performance on the SNF HAI measure. We also stated our intent to apply 
this inversion scoring policy to all measures in the Program for which 
the calculation produces a ``lower is better'' measure rate. We 
continue to believe that inverting measure rates such that a higher 
measure rate reflects better performance on a measure is important for 
incentivizing improvement in a clear and understandable manner.
    This measure rate inversion scoring policy does not change the 
measure specifications or the calculation method. We use this measure 
rate inversion as part of the scoring methodology under the SNF VBP 
Program. The measure rate inversion is part of the methodology we use 
to generate measure scores, and resulting SNF Performance Scores, that 
are clear and understandable for SNFs and the public.
(2) Proposal To Invert the Nursing Staff Turnover, Falls With Major 
Injury (Long-Stay), and Long Stay Hospitalization Measures Rates for 
SNF VBP Program Scoring Purposes
    In sections VII.B.4.b., VII.B.4.c., and VII.B.4.e. of this proposed 
rule, we stated that a lower measure rate for the Nursing Staff 
Turnover, Falls with Major Injury (Long-Stay), and Long Stay 
Hospitalization measures indicate better performance on those measures. 
Therefore, we are proposing to apply our measure rate inversion scoring 
policy to these measures. We are proposing to calculate the score for 
these measures for the SNF VBP Program by inverting the measure rates 
using the calculations shown in Table 18. We are not proposing to apply 
this policy to the DC Function measure because that measure, as 
currently specified and calculated, produces a ``higher is better'' 
measure rate.
[GRAPHIC] [TIFF OMITTED] TP10AP23.005

    We believe that inverting the measure rates for the Nursing Staff 
Turnover, Falls with Major Injury (Long-Stay), and Long Stay 
Hospitalization measure is important for incentivizing improvement in a 
clear and understandable manner, and for ensuring a consistent message 
that a higher measure rate reflects better performance on the measures.
    We invite public comment on our proposal to invert the measure 
rates for the Nursing Staff Turnover, Falls with Major Injury (Long-
Stay), and Long Stay Hospitalization measures for the purposes of 
scoring under the SNF VBP Program.
g. Confidential Feedback Reports and Public Reporting for Proposed 
Quality Measures
    Our confidential feedback reports and public reporting policies are 
codified at Sec.  413.338(f) of our regulations. In the FY 2023 SNF PPS 
final rule (87 FR 47591 through 47592), we revised our regulations such 
that the confidential feedback reports and public reporting policies 
apply to each measure specified for a fiscal year, which includes the 
proposed Nursing Staff Turnover measure beginning with the FY 2026 
program year, and the proposed Falls with Major Injury (Long-Stay), DC 
Function, and Long Stay Hospitalization measures beginning with the FY 
2027 program year.

C. SNF VBP Performance Periods and Baseline Proposals

1. Background
    We refer readers to the FY 2016 SNF PPS final rule (80 FR 46422) 
for a discussion of our considerations for determining performance 
periods and baseline periods under the SNF VBP Program. In the FY 2019 
SNF PPS final rule (83 FR 39277 through 39278), we adopted a policy 
whereby we will automatically adopt the performance period and baseline 
period for a SNF VBP program year by advancing the performance period 
and baseline period by 1 year from the previous program year. In the FY 
2023 SNF PPS final rule (87 FR 47580 through 47583), we adopted 
performance periods and baseline periods for three new quality measures 
beginning with the FY 2026 program year: (1) SNF HAI measure, (2) Total 
Nurse Staffing measure, and (3) DTC PAC SNF measure, and finalized the 
application of our policy to automatically adopt performance periods 
and baseline periods for subsequent program years to those new 
measures.
2. SNFRM Performance and Baseline Periods for the FY 2024 SNF VBP 
Program Year
    Under the policy finalized in the FY 2019 SNF PPS final rule (83 FR 
39277 through 39278), the baseline period for the SNFRM for the FY 2024 
program year would be FY 2020 and the performance period for the SNFRM 
for the FY 2024 program year would be FY 2022. However, in the FY 2022 
SNF PPS final rule (85 FR 42512 through 42513), we updated the FY 2024 
baseline period for the SNFRM to FY 2019 since the ECE we granted on 
March 22, 2020, due to the PHE for COVID-19, excepted qualifying claims 
for a 6-month period in FY 2020 (January 1, 2020 through June 30, 2020) 
from the calculation of the SNFRM.\284\ \285\ We refer readers to that 
final rule for additional discussion of our considerations for updating 
the FY 2024 baseline period for the SNFRM. Therefore, for the FY 2024 
program

[[Page 21377]]

year, the baseline period for the SNFRM is FY 2019 and the performance 
period for the SNFRM is FY 2022.
---------------------------------------------------------------------------

    \284\ CMS. (2020). Press Release: CMS Announces Relief for 
Clinicians, Providers, Hospitals, and Facilities Participating in 
Quality Reporting Programs in Response to COVID-19. https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
    \285\ CMS memorandum (2020) available at https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------

3. Proposed Performance Periods and Baseline Periods for the Nursing 
Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, and 
Long Stay Hospitalization Measures
a. Proposed Performance Periods for the Nursing Staff Turnover, Falls 
With Major Injury (Long-Stay), DC Function, and Long Stay 
Hospitalization Measures
    In considering the appropriate performance periods for the Nursing 
Staff Turnover, Falls with Major Injury (Long-Stay), DC Function, and 
Long Stay Hospitalization measures, we recognize that we must balance 
the length of the performance periods with our need to calculate valid 
and reliable performance scores and announce the resulting payment 
adjustments no later than 60 days prior to the program year involved, 
in accordance with section 1888(h)(7) of the Act. In addition, we refer 
readers to the FY 2017 SNF PPS final rule (81 FR 51998 through 51999) 
for a discussion of the factors we should consider when specifying 
performance periods for the SNF VBP Program, as well as our stated 
preference for 1-year performance periods. Based on these 
considerations, we believe that 1-year performance periods for these 
measures would be operationally feasible for the SNF VBP Program and 
would provide sufficiently accurate and reliable measure rates and 
resulting performance scores for the measures.
    We also recognize that we must balance our desire to specify 
performance periods for a fiscal year as close to the fiscal year's 
start date as possible to ensure clear connections between quality 
measurement and value-based payment with our need to announce the net 
results of the Program's adjustments to Medicare payments not later 
than 60 days prior to the fiscal year involved, in accordance with 
section 1888(h)(7) of the Act. In considering these constraints, and in 
alignment with other SNF VBP measures, we believe that performance 
periods that occur 2 fiscal years prior to the applicable fiscal 
program year is most appropriate for these measures.
    For these reasons, we are proposing to adopt the following 
performance periods:
     FY 2024 (October 1, 2023 through September 30, 2024) as 
the performance period for the Nursing Staff Turnover measure for the 
FY 2026 SNF VBP program year.
     FY 2025 (October 1, 2024, through September 30, 2025) as 
the performance period for the Falls with Major Injury (Long-Stay) 
measure for the FY 2027 SNF VBP program year.
     FY 2025 (October 1, 2024 through September 30, 2025) as 
the performance period for the DC Function measure for the FY 2027 SNF 
VBP program year.
     FY 2025 (October 1, 2024 through September 30, 2025) as 
the performance period for the Long Stay Hospitalization measure for 
the FY 2027 SNF VBP program year.
    In alignment with the previously adopted SNF VBP measures, we are 
also proposing that, for these measures, we would automatically adopt 
the performance period for a SNF VBP program year by advancing the 
beginning of the performance period by 1 year from the previous program 
year.
    We invite public comment on our proposals to adopt performance 
periods for the Nursing Staff Turnover, Falls with Major Injury (Long-
Stay), DC Function, and Long Stay Hospitalization measures.
b. Proposed Baseline Periods for the Nursing Staff Turnover, Falls With 
Major Injury (Long-Stay), DC Function, and Long Stay Hospitalization 
Measures
    In the FY 2016 SNF PPS final rule (80 FR 46422) we discussed that, 
as with other Medicare quality programs, we generally adopt baseline 
periods for a fiscal year that occurs prior to the performance periods 
for that fiscal year to establish measure performance standards. We 
also discussed our intent to adopt baseline periods that are as close 
as possible in duration as performance periods for a fiscal year, as 
well as our intent to seasonally align baseline periods with 
performance periods to avoid any effects on quality measurement that 
may result from tracking SNF performance during different times in a 
year. Therefore, to align with the proposed performance period length 
for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC 
Function, and Long Stay Hospitalization measures, we are proposing to 
adopt 1-year baseline periods for those measures.
    We also recognize that we are required, under section 1888(h)(3)(C) 
of the Act, to calculate and announce performance standards no later 
than 60 days prior to the start of performance periods. Therefore, we 
believe that baseline periods that occur 4 fiscal years prior to the 
applicable fiscal program year, and 2 fiscal years prior to the 
performance periods, is most appropriate for these measures and would 
provide sufficient time to calculate and announce performance standards 
prior to the start of the performance periods.
    For these reasons, we are proposing to adopt the following baseline 
periods:
     FY 2022 (October 1, 2021 through September 30, 2022) as 
the baseline period for the Nursing Staff Turnover measure for the FY 
2026 SNF VBP program year.
     FY 2023 (October 1, 2022 through September 30, 2023) as 
the baseline period for the Falls with Major Injury (Long-Stay) measure 
for the FY 2027 SNF VBP program year.
     FY 2023 (October 1, 2022 through September 30, 2023) as 
the baseline period for the Discharge Function measure for the FY 2027 
SNF VBP program year.
     FY 2023 (October 1, 2022 through September 30, 2023) as 
the baseline period for the Long Stay Hospitalization measure for the 
FY 2027 SNF VBP program year.
    In alignment with the previously adopted SNF VBP measures, we are 
also proposing that, for these measures, we would automatically adopt 
the baseline period for a SNF VBP program year by advancing the 
beginning of the baseline period by 1 year from the previous program 
year.
    We invite public comment on our proposals to adopt baseline periods 
for the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), DC 
Function, and Long Stay Hospitalization measures.
4. Proposed Performance Periods and Baseline Periods for the SNF WS PPR 
Measure Beginning With the FY 2028 SNF VBP Program Year
a. Proposed Performance Period for the SNF WS PPR Measure Beginning 
With the FY 2028 SNF VBP Program Year
    The proposed SNF WS PPR measure is calculated using 2 consecutive 
years of Medicare FFS claims data, and therefore, we are proposing to 
adopt a 2-year performance period for this measure. During the re-
specification process for the SNF WS PPR measure, we determined that 
using 2 years of data improved the measure reliability. Specifically, 
the intraclass correlation coefficient (with the Spearman-Brown 
correction applied) for the SNF WS PPR measure was 0.71 compared to 
0.56 for the SNFRM. We refer readers to section VII.B.2. of this 
proposed rule and the SNF WS PPR measure technical specifications, 
available at https://www.cms.gov/files/document/snfvbp-snfwsppr-draft-techical-specification.pdf, for additional details.
    Accordingly, we are proposing to adopt October 1, 2024 through

[[Page 21378]]

September 30, 2026 (FY 2025 and FY 2026) as the performance period for 
the SNF WS PPR measure for the FY 2028 SNF VBP program year. We believe 
that using October 1, 2024 through September 30, 2026 (FY 2025 and FY 
2026) as the performance period for the FY 2028 program year best 
balances our need for sufficient data to calculate valid and reliable 
performance scores with our requirement under section 1888(h)(7) of the 
Act to announce the resulting payment adjustments no later than 60 days 
prior to the program year involved.
    In alignment with the previously adopted SNF VBP measures, we are 
also proposing that for the SNF WS PPR measure, we would automatically 
adopt the performance period for a SNF VBP program year by advancing 
the beginning of the performance period by 1 year from the previous 
program year.
    We invite public comment on our proposals related to the 
performance periods for the SNF WS PPR measure beginning with the FY 
2028 program year.
b. Proposed Baseline Period for the SNF WS PPR Measure Beginning With 
the FY 2028 SNF VBP Program Year
    Our policy is to generally adopt a baseline period for a fiscal 
year that occurs prior to the performance period for that fiscal year 
in order to establish a measure's performance standards. We also 
generally adopt baseline periods that are as close as possible in 
duration as the performance period for a fiscal year, as well as 
seasonally aligning the baseline periods with performance periods to 
avoid any effects on quality measurement that may result from tracking 
SNF performance during different times in a year. Therefore, to align 
with the proposed performance period length for the SNF WS PPR measure, 
we are proposing a 2-year baseline period for this measure.
    We also recognize that we are required, under section 1888(h)(3)(C) 
of the Act, to calculate and announce performance standards no later 
than 60 days prior to the start of the performance period. Therefore, 
we believe that a baseline period that begins 6 fiscal years prior to 
the applicable fiscal program year, and 3 fiscal years prior to the 
applicable performance period, is most appropriate for the SNF WS PPR 
measure and would provide sufficient time to calculate and announce 
performance standards prior to the start of the performance period. For 
these reasons, we are proposing to adopt October 1, 2021 through 
September 30, 2023 (FY 2022 and FY 2023) as the baseline period for the 
SNF WS PPR measure for the FY 2028 SNF VBP program year.
    In alignment with the previously adopted SNF VBP measures, we are 
also proposing that for the SNF WS PPR measure, we would automatically 
adopt the baseline period for a SNF VBP program year by advancing the 
beginning of the baseline period by 1 year from the previous program 
year.
    We invite public comment on our proposals related to the baseline 
period for the SNF WS PPR measure beginning with FY 2028 SNF VBP 
program year.
c. SNFRM and SNF WS PPR Performance Period and Baseline Period 
Considerations
    As discussed in the previous section, we are proposing that the 
first performance period for the SNF WS PPR measure would be October 1, 
2024 through September 30, 2026 (FY 2025 and FY 2026), and the first 
baseline period would be October 1, 2021 through September 30, 2023 (FY 
2022 and FY 2023). In section VII.B.3. of this proposed rule, we are 
proposing to replace the SNFRM with the SNF WS PPR beginning with the 
FY 2028 program year. Therefore, the last program year that would 
include the SNFRM would be FY 2027. The last performance period for the 
SNFRM would be FY 2025 and the last baseline period would be FY 2023. 
We note that because the SNF WS PPR measure is a 2-year measure and the 
SNFRM is a 1-year measure, the data used to calculate the baseline and 
performance period for the SNF WS PPR measure for the FY 2028 program 
year would include data that is also used to calculate the baseline and 
performance period for the SNFRM for the FY 2027 program year. We 
believe the overlap is necessary to ensure that we can transition from 
the SNFRM to the SNF WS PPR seamlessly, without any gaps in the use of 
either measure.

D. SNF VBP Performance Standards

1. Background
    We refer readers to the FY 2017 SNF PPS final rule (81 FR 51995 
through 51998) for a summary of the statutory provisions governing 
performance standards under the SNF VBP Program and our finalized 
performance standards policy. In the FY 2019 SNF PPS final rule (83 FR 
39276 through 39277), we also adopted a policy allowing us to correct 
the numerical values of the performance standards. Further, in the FY 
2023 SNF PPS final rule (87 FR 47583 through 47584), we amended the 
definition of ``Performance Standards,'' redesignated that definition 
as Sec.  413.338(a)(12), and added additional detail for our 
performance standards correction policy at Sec.  413.338(d)(6).
    We adopted the final numerical values for the FY 2024 performance 
standards in the FY 2022 SNF PPS final rule (86 FR 42513) and adopted 
the final numerical values for the FY 2025 performance standards in the 
FY 2023 SNF PPS final rule (87 FR 47584).
    We are not proposing any changes to these performance standards 
policies in this proposed rule.
2. Estimated Performance Standards for the FY 2026 Program Year
    In the FY 2023 SNF PPS final rule (87 FR 47564 through 47576), we 
adopted two new quality measures for the FY 2026 program year: SNF HAI 
and Total Nurse Staffing measures. In section VII.B.4.b. of this 
proposed rule, we are proposing to adopt the Nursing Staff Turnover 
measure beginning with the FY 2026 program year. We are also proposing 
that the performance period for the Nursing Staff Turnover measure for 
the FY 2026 program year would be FY 2024 (October 1, 2023 through 
September 30, 2024). Therefore, the FY 2026 program year would consist 
of four measures (SNFRM, SNF HAI, Total Nurse Staffing, and Nursing 
Staff Turnover measures).
    To meet the requirements at section 1888(h)(3)(C) of the Act, we 
are providing estimated numerical performance standards for the FY 2026 
program year for the three previously adopted measures (SNFRM, SNF HAI, 
and Total Nurse Staffing measures), as well as the proposed Nursing 
Staff Turnover measure. In accordance with our previously finalized 
methodology for calculating performance standards (81 FR 51996 through 
51998), the estimated numerical values for the FY 2026 program year 
performance standards are shown in Table 19.

[[Page 21379]]



    Table 19--Estimated FY 2026 SNF VBP Program Performance Standards
------------------------------------------------------------------------
                                            Achievement
           Measure short name                threshold       Benchmark
------------------------------------------------------------------------
SNFRM...................................         0.78526         0.82818
SNF HAI Measure.........................         0.91468         0.94766
Total Nurse Staffing Measure............         3.33289         5.98339
Nursing Staff Turnover Measure..........         0.37500         0.72925
------------------------------------------------------------------------

3. Estimated Performance Standards for the DTC PAC SNF Measure for the 
FY 2027 Program Year
    In the FY 2023 SNF PPS final rule (87 FR 47576 through 47580), we 
adopted the DTC PAC SNF measure beginning with the FY 2027 program 
year. In that final rule (87 FR 47582 through 47583), we also finalized 
that the baseline and performance periods for the DTC PAC SNF measures 
would be 2 consecutive years, and that FY 2024 and FY 2025 would be the 
performance period for the DTC PAC SNF measure for the FY 2027 program 
year.
    To meet the requirements at section 1888(h)(3)(C) of Act, we are 
providing estimated numerical performance standards for the DTC PAC SNF 
measure for the FY 2027 program year. In accordance with our previously 
finalized methodology for calculating performance standards (81 FR 
51996 through 51998), the estimated numerical values for the DTC PAC 
SNF measure for the FY 2027 program year performance standards are 
shown in Table 20.
    We note that we will provide the estimated numerical performance 
standard values for the remaining measures applicable in the FY 2027 
program year in the FY 2025 SNF PPS proposed rule.

  Table 20--Estimated FY 2027 SNF VBP Program Performance Standards for
                         the DTC PAC SNF Measure
------------------------------------------------------------------------
                                            Achievement
           Measure short name                threshold       Benchmark
------------------------------------------------------------------------
DTC PAC SNF Measure.....................         0.44087         0.68956
------------------------------------------------------------------------

E. SNF VBP Performance Scoring Methodology

1. Background
    Our performance scoring policies are codified at Sec.  413.338(d) 
and (e) of our regulations. We also refer readers to the following 
prior final rules for detailed background on the scoring methodology 
for the SNF VBP Program:
     In the FY 2017 SNF PPS final rule (81 FR 52000 through 
52005), we finalized several scoring methodology policies, including a 
policy to use the higher of a SNF's achievement and improvement scores 
as that SNF's performance score for a given program year.
     In the FY 2018 SNF PPS final rule (82 FR 36614 through 
36616), we finalized: (1) a rounding policy, (2) a logistic exchange 
function, (3) a 60 percent payback percentage, and (4) a SNF 
performance ranking policy.
     In the FY 2019 SNF PPS final rule (83 FR 39278 through 
39281), we finalized several scoring methodology policies, including a 
scoring policy for SNFs without sufficient baseline period data and an 
extraordinary circumstances exception policy.
     In the FY 2022 SNF PPS final rule (86 FR 42513 through 
42515), we finalized a special scoring and payment policy for the FY 
2022 SNF VBP Program due to the impact of the PHE for COVID-19.
     In the FY 2023 SNF PPS final rule (87 FR 47584 through 
47590), we finalized a special scoring and payment policy for the FY 
2023 SNF VBP Program due to the continued impact of the PHE for COVID-
19. In that final rule, we also finalized several scoring methodology 
policies to accommodate the addition of new measures to the Program, 
including: (1) case minimum and measure minimum policies, including 
case minimums for the SNFRM, SNF HAI, Total Nurse Staffing, and DTC PAC 
SNF measures, (2) updates to the scoring policy for SNFs without 
sufficient baseline period data, (3) removal of the low-volume 
adjustment policy, and (4) a measure-level and normalization scoring 
policy to replace the previously adopted scoring methodology policies 
beginning with the FY 2026 program year.
2. Proposed Case Minimum and Measure Minimum Policies
a. Background
    We refer readers to the FY 2023 SNF PPS final rule (87 FR 47585 
through 47587) for a detailed description of our considerations for 
adopting case minimums and measure minimums. Our case minimum and 
measure minimum policies are also codified at Sec.  413.338(b) of our 
regulations.
    As discussed in section VII.B.4. of this proposed rule, we are 
proposing to adopt the Nursing Staff Turnover measure beginning with 
the FY 2026 program year; the Falls with Major Injury (Long-Stay), DC 
Function, and Long Stay Hospitalization measures beginning with the FY 
2027 program year; and the SNF WS PPR measure beginning with the FY 
2028 program year. Therefore, we are also proposing to adopt case 
minimums for the new measures and proposing to update the previously 
finalized measure minimum for the FY 2027 program year. Although the 
addition of the Nursing Staff Turnover measure beginning with FY 2026 
would increase the total number of measures for that program year, we 
believe that the previously finalized measure minimum of two measures 
remains sufficient for that program year.
b. Proposed Case Minimums During a Performance Period for the Nursing 
Staff Turnover, Falls With Major Injury (Long-Stay), DC Function, Long 
Stay Hospitalization, and SNF WS PPR Measures
    In this proposed rule, we are proposing to adopt the Nursing Staff 
Turnover measure beginning with the FY 2026 program year; the Falls 
with Major Injury (Long-Stay), Long Stay Hospitalization, and DC 
Function measures beginning with the FY 2027 program year; and the SNF 
WS PPR measure beginning with the FY 2028 program year. Therefore, to 
meet the requirements at section 1888(h)(1)(C)(i)

[[Page 21380]]

of the Act, we are concurrently proposing to adopt case minimums for 
those proposed measures.
    For the Nursing Staff Turnover measure, we are proposing that SNFs 
must have a minimum of 1 eligible stay during the 1-year performance 
period and at least 5 eligible nursing staff (RNs, LPNs, and nurse 
aides) during the 3 quarters of PBJ data included in the measure 
denominator. SNFs must meet both of these requirements in order to be 
eligible to receive a score on the measure for the applicable program 
year. We believe this case minimum requirement is appropriate and 
consistent with the findings of measure testing analyses and the 
measure specifications. For example, using FY 2021 data, we estimated 
that 80 percent of SNFs met the 5-eligible nursing staff minimum. In 
addition, we note that the 1-eligible stay and 5-eligible nursing staff 
minimums were determined to be appropriate for publicly reporting this 
measure on the Care Compare website. We believe these case minimum 
standards for public reporting purposes are also appropriate standards 
for establishing a case minimum for this measure under the SNF VBP 
Program. We also believe this case minimum requirement supports our 
objective, which is to establish case minimums that appropriately 
balance quality measure reliability with our continuing desire to score 
as many SNFs as possible on this measure.
    For the Falls with Major Injury (Long-Stay) measure, we are 
proposing that SNFs must have a minimum of 20 residents in the measure 
denominator during the 1-year performance period to be eligible to 
receive a score on the measure for the applicable fiscal program year. 
We believe this case minimum requirement is appropriate and consistent 
with the findings of measure testing analyses. For example, using FY 
2021 data, we estimated that nearly 96 percent of SNFs met the 20-
resident minimum. In addition, testing results indicated that a 20-
resident minimum produced moderately reliable measure rates for the 
purposes of public reporting.\286\ We believe these case minimum 
standards for public reporting purposes are also appropriate standards 
for establishing a case minimum for this measure under the SNF VBP 
Program. We also believe this case minimum requirement supports our 
objective, which is to establish case minimums that appropriately 
balance quality measure reliability with our continuing desire to score 
as many SNFs as possible on this measure.
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    \286\ https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    For the Long Stay Hospitalization measure, we are proposing that 
SNFs must have a minimum of 20 eligible stays during the 1-year 
performance period to be eligible to receive a score on the measures 
for the applicable fiscal program year. We believe this case minimum 
requirement is appropriate and consistent with the findings of measure 
testing analyses. For example, using CY 2021 data, we estimated that 
approximately 80 percent of SNFs met the 20-eligible stay minimum. In 
addition, we note that the 20-eligible stay minimum was determined to 
be appropriate for publicly reporting this measure under the Five-Star 
Quality Rating System. We believe these case minimum standards for 
public reporting purposes are also appropriate standards for 
establishing a case minimum for this measure under the SNF VBP Program. 
We also believe this case minimum requirement supports our objective, 
which is to establish case minimums that appropriately balance quality 
measure reliability with our continuing desire to score as many SNFs as 
possible on this measure.
    For the DC Function measure, we are proposing that SNFs must have a 
minimum of 20 eligible stays during the 1-year performance period in 
order to be eligible to receive a score on the measure for the 
applicable fiscal program year. We believe this case minimum 
requirement is appropriate and consistent with the findings of measure 
testing analyses. For example, testing results, which used FY 2019 
data, found that nearly 84 percent of SNFs met the 20-eligible stay 
minimum.\287\ In addition, those testing results indicated that a 20-
eligible stay minimum produced sufficiently reliable measure rates. We 
believe this case minimum requirement supports our objective, which is 
to establish case minimums that appropriately balance quality measure 
reliability with our continuing desire to score as many SNFs as 
possible on this measure.
---------------------------------------------------------------------------

    \287\ Discharge Function Score for Skilled Nursing Facilities 
(SNFs) Technical Report, which is available on the SNF Quality 
Reporting Program Measures and Technical Information web page at 
https://www.cms.gov/files/document/snf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

    For the SNF WS PPR measure, we are proposing that SNFs must have a 
minimum of 25 eligible stays during the 2-year performance period in 
order to be eligible to receive a score on the measure for the 
applicable fiscal program year. We believe this case minimum 
requirement is appropriate and consistent with the findings of measure 
testing analyses. For example, using FY 2020 through FY 2021 data, we 
estimated that nearly 91 percent of non-swing bed SNFs met the 25-
eligible stay minimum. In addition, testing results indicated that a 
25-eligible stay minimum produced sufficiently reliable measure 
rates.\288\ We believe this case minimum requirement supports our 
objective, which is to establish case minimums that appropriately 
balance quality measure reliability with our continuing desire to score 
as many SNFs as possible on this measure.
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    \288\ https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    We invite public comment on our proposal to adopt case minimums for 
the Nursing Staff Turnover, Falls with Major Injury (Long-Stay), Long 
Stay Hospitalization, DC Function, and SNF WS PPR measures.
c. FY 2026 Measure Minimum
    In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the 
measure minimum for the FY 2026 program year. Specifically, we 
finalized that for the FY 2026 program year, SNFs must report the 
minimum number of cases for two of the three measures during the 
applicable performance period to receive a SNF Performance Score and 
value-based incentive payment.
    In this proposed rule, we are proposing to adopt an additional 
measure for the FY 2026 program year: Nursing Staff Turnover measure, 
which means the FY 2026 SNF VBP measure set would consist of a total of 
four measures. Although we are proposing the Nursing Staff Turnover 
measure beginning with the FY 2026 program year, which would increase 
the total number of measures applicable in FY 2026, we believe that our 
previously finalized minimum of two measures for FY 2026 remains 
sufficient because if we required a minimum of three or four measures, 
all swing-bed facilities would be excluded from the Program. Two of the 
four measures that would be included in the FY 2026 program year are 
PBJ-based measures. Since swing-bed facilities do not submit PBJ data, 
those facilities would not meet the measure minimum of reporting three 
or four measures to the Program. Therefore, to ensure swing-bed 
facilities continue to have the opportunity to be included in the 
Program, we are not proposing to update the measure minimum for the FY 
2026 program year. SNFs must report the minimum number of cases for two 
of the four measures during the performance period to be included in 
the FY 2026 program year.

[[Page 21381]]

d. Proposal To Update the FY 2027 Measure Minimum
    In the FY 2023 SNF PPS final rule (87 FR 47587), we finalized the 
measure minimum for the FY 2027 program year. Specifically, we 
finalized that for the FY 2027 program year, SNFs must report the 
minimum number of cases for three of the four measures during the 
performance period to receive a SNF Performance Score and value-based 
incentive payment.
    In addition to our proposal to adopt the Nursing Staff Turnover 
measure beginning with the FY 2026 program year, we are proposing to 
adopt three additional measures beginning with the FY 2027 program 
year: Falls with Major Injury (Long-Stay), DC Function, and Long Stay 
Hospitalization measures. Therefore, the FY 2027 SNF VBP measure set 
would consist of a total of eight measures. Given the proposed changes 
to the number of measures applicable in FY 2027, we are also proposing 
to update the measure minimum for the FY 2027 program year.
    Specifically, we are proposing that for the FY 2027 program year, 
SNFs must report the minimum number of cases for four of the eight 
measures during the performance period to receive a SNF Performance 
Score and value-based incentive payment. SNFs that do not meet these 
minimum requirements would be excluded from the FY 2027 program and 
would receive their full Federal per diem rate for that fiscal year. 
Under these proposed minimum requirements, we estimate that 
approximately 8 percent of SNFs would be excluded from the FY 2027 
Program. We found that increasing the measure minimum requirement from 
three to four measures out of a total of eight measures would cause the 
number of SNFs excluded from the Program to increase from approximately 
3 percent to 8 percent of SNFs for FY 2027. However, the measure 
minimum requirement that we finalized for FY 2027 in the FY 2023 SNF 
PPS final rule (87 FR 47587), which was based on a measure set of four 
measures, excluded approximately 16 percent of SNFs. We also found that 
increasing the measure minimum requirement would have little effect on 
the percentage of SNFs that would receive a net-positive incentive 
payment multiplier (IPM) of the overall distribution of IPMs. Based on 
these testing results, we believe the proposed update to the measure 
minimum for FY 2027 aligns with our desire to ensure that as many SNFs 
as possible can receive a reliable SNF Performance Score and value-
based incentive payment.
    We invite public comment on our proposal to update the measure 
minimum for the FY 2027 SNF VBP program year.
3. Proposed Application of the SNF VBP Scoring Methodology to Proposed 
Measures
a. Background
    In the FY 2023 SNF PPS final rule (87 FR 47588 through 47590), we 
finalized several updates to the scoring methodology for the SNF VBP 
Program beginning with the FY 2026 program year. We finalized a 
measure-level scoring policy such that SNFs have the opportunity to 
earn a maximum of 10 points on each measure for achievement, and a 
maximum of nine points on each measure for improvement. The higher of 
these two scores will then be the SNF's score for each measure and used 
to calculate the SNF Performance Score, except if the SNF does not meet 
the case minimum for a given measure during the applicable baseline 
period, in which case that SNF will only be scored on achievement for 
that measure. We also finalized a normalization policy such that we 
will calculate a raw point total for each SNF by adding up that SNF's 
score on each of the measures applicable for the given program year. We 
will then normalize the raw point totals such that the SNF Performance 
Score is reflected on a 100-point scale.
    In this proposed rule, we are proposing to adopt the Nursing Staff 
Turnover measure beginning with the FY 2026 program year; and the Falls 
with Major Injury (Long-Stay), Long Stay Hospitalization, and DC 
Function measures beginning with the FY 2027 program year. To 
accommodate those proposed measures in our scoring methodology, we are 
also proposing to adjust our scoring methodology for the FY 2026 and FY 
2027 program years, which we discuss in the next section.
    We also note that we are proposing to replace the SNFRM with the 
SNF WS PPR measure beginning with the FY 2028 program year, which would 
not affect the total number of measures applicable in the Program for 
FY 2028. We intend to address the FY 2028 performance scoring 
methodology in future rulemaking.
b. Proposed FY 2026 Performance Scoring
    We are proposing to adopt the Nursing Staff Turnover measure 
beginning with the FY 2026 program year, and therefore, the FY 2026 
program year measure set would include four measures (SNFRM, SNF HAI, 
Total Nurse Staffing, and Nursing Staff Turnover measures).
    We are proposing to apply our previously finalized scoring 
methodology, which is codified at Sec.  413.338(e) of our regulations, 
to the proposed Nursing Staff Turnover measure. Specifically, we would 
award up to 10 points based on achievement, and up to nine points based 
on improvement, so long as the SNF meets the case minimum for the 
measure. The higher of these two scores would be the SNF's score for 
the measure for FY 2026, except in the instance that the SNF does not 
meet the case minimum for the measure during the applicable baseline 
period, in which case that SNF would only be scored on achievement for 
the measure.
    As previously finalized, we would then add the score for each of 
the four measures for which the SNF met the case minimum to get the raw 
point total. The maximum raw point total for the FY 2026 program year 
would be 40 points. We would then normalize each SNF's raw point total, 
based on the number of measures for which that SNF met the case 
minimum, to get a SNF Performance Score that is on a 100-point scale 
using our previously finalized normalization policy. We would only 
award a SNF Performance Score to SNFs that meet the measure minimum for 
FY 2026.
    We invite public comment on our proposal to apply our previously 
finalized scoring methodology to the proposed Nursing Staff Turnover 
measure beginning with the FY 2026 SNF VBP program year.
c. Proposed FY 2027 Performance Scoring
    We are proposing to adopt the Falls with Major Injury (Long-Stay), 
DC Function, and Long Stay Hospitalization measures beginning with the 
FY 2027 program year, and therefore, the FY 2027 program year measure 
set would include eight measures.
    Our current scoring methodology is codified at Sec.  413.338(e) of 
our regulations. Under that scoring methodology, we award up to 10 
points for each measure based on achievement, and up to nine points for 
each measure based on improvement, so long as the SNF meets the case 
minimum for a given measure. The higher of these two scores would be 
the SNF's score on that measure for FY 2027, except in the instance 
that the SNF does not meet the case minimum for a given measure during 
the applicable baseline period, in which case that SNF would only be 
scored on achievement for that measure. As previously finalized, we 
would then

[[Page 21382]]

sum the scores for each of the eight measures for which the SNF met the 
case minimum to get the raw measure point total. The maximum raw 
measure point total for the FY 2027 program year would be 80 points.
    We are proposing to apply these elements of the scoring methodology 
to the proposed Falls with Major Injury (Long-Stay), DC Function, and 
Long Stay Hospitalization measures. In addition, and as discussed 
further in section VII.E.4. of this proposed rule, we are proposing to 
adopt a Health Equity Adjustment in which eligible SNFs could earn a 
maximum of two points for each measure (including all previously 
finalized and newly proposed measures) if they are a top tier 
performing SNF, which we are proposing to define as a SNF whose score 
on the measure for the program year falls in the top third of 
performance (greater than or equal to the 66.67th percentile) on a 
given measure, and the SNF's resident population during the performance 
period that applies to the program year includes at least 20 percent of 
residents with dual eligibility status (DES). This combination of a 
SNF's performance and proportion of residents with DES would be used to 
determine a SNF's Health Equity Adjustment (HEA) bonus points. We would 
then add the total number of HEA bonus points to the normalized measure 
point total on a scale from 0 to 100, and that total would be the SNF 
Performance Score earned by the SNF for the program year. We would only 
award a SNF Performance Score to SNFs that meet the proposed measure 
minimum for FY 2027.
4. Proposal To Incorporate Health Equity Into the SNF VBP Program 
Scoring Methodology Beginning With the FY 2027 Program Year
a. Background
    Significant and persistent inequities in health outcomes exist in 
the U.S. Belonging to a racial or ethnic minority group; living with a 
disability; being a member of the lesbian, gay, bisexual, transgender, 
queer, and intersex (LGBTQI+) communities; living in a rural area; 
being a member of a religious minority; being near or below the poverty 
level; or being dually enrolled in Medicare and Medicaid, is often 
associated with worse health outcomes.\289\ \290\ \291\ \292\ \293\ 
\294\ \295\ \296\ \297\ Executive Order 13985 on Advancing Racial 
Equity and Support for Underserved Communities Through the Federal 
Government, (January 20, 2021) defines ``equity'' as ``the consistent 
and systematic fair, just, and impartial treatment of all individuals, 
including individuals who belong to underserved communities that have 
been denied such treatment, such as Black, Latino, and Indigenous and 
Native American persons, Asian Americans and Pacific Islanders and 
other persons of color; members of religious minorities; lesbian, gay, 
bisexual, transgender, queer, [and intersex] (LGBTQ[I] +); \298\ 
persons with disabilities; persons who live in rural areas; and persons 
otherwise adversely affected by persistent poverty or inequality'' (86 
FR 7009). CMS defines ``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, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes.'' \299\
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    \289\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and 30 day outcomes after acute myocardial infarction, 
heart failure, and pneumonia: Retrospective cohort study. British 
Medical Journal, 346.
    \290\ 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.
    \291\ 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.
    \292\ Rural Health Research Gateway. (2018). Rural communities: 
age, income, and health status. Rural Health Research Recap. https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \293\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \294\ Vu, M. et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; S.B.
    \295\ Nadimpalli, et al., The Association between Discrimination 
and the Health of Sikh Asian Indians Health Psychol. 2016 Apr; 
35(4): 351-355.
    \296\ 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.
    \297\ Sorbero, ME, AM Kranz, KE Bouskill, R Ross, AI Palimaru, 
and A Meyer. 2018. Addressing social determinants of health needs of 
dually enrolled beneficiaries in Medicare Advantage plans: Findings 
from interviews and case studies. RAND Corporation. Available at 
https://www.rand.org/pubs/research_reports/RR2634.html (accessed 
December 8, 2022).
    \298\ We note that the original, cited definition only 
stipulates, ``LGBTQ+'', however, HHS and the White House now 
recognize individuals who are intersex/have intersex traits. 
Therefore, we have updated the term to reflect these changes.
    \299\ CMS Strategic Plan Pillar: Health Equity. (2022). https://www.cms.gov/files/document/health-equity-fact-sheet.pdf.
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    Advancing health equity is a key pillar of CMS' strategic 
vision,\300\ and we are working to advance health equity by designing, 
implementing, and operationalizing policies and programs aimed at 
identifying and reducing health disparities. This includes the CMS 
Mapping Medicare Disparities Tool,\301\ the CMS Innovation Center's 
Accountable Health Communities Model,\302\ the CMS Disparity Methods 
stratified reporting program,\303\ the collection of standardized 
patient assessment data elements in the post-acute care setting,\304\ 
and health equity program adjustments like the Medicare Shared Savings 
Program's recently adopted health equity adjustment for Accountable 
Care Organizations that report all-payer eCQMs/MIPS CQMs (87 FR 69838 
through 69857). Further, the 2022-2032 CMS Framework for Health Equity 
outlines CMS' priorities to advance health equity, expand coverage, and 
improve health outcomes for the more than 170 million individuals 
supported by CMS programs.\305\ We also recently updated the CMS 
National Quality Strategy (NQS), which includes advancing health equity 
as one of eight strategic goals.\306\ As we continue to leverage our 
programs to improve quality of care, we note it is important to 
implement strategies that ``create aligned incentives that drive 
providers to improve health outcomes for all beneficiaries.'' \307\
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    \300\ CMS Strategic Vision. (2022). https://www.cms.gov/cms-strategic-plan.
    \301\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
    \302\ https://innovation.cms.gov/innovation-models/ahcm.
    \303\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \304\ 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.
    \305\ CMS Framework for Health Equity (2022). https://www.cms.gov/about-cms/agency-information/omh/health-equity-programs/cms-framework-for-health-equity.
    \306\ CMS National Quality Strategy (2022). Centers for Medicare 
and Medicaid Services. https://www.cms.gov/files/document/cms-national-quality-strategy-fact-sheet.pdf.
    \307\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. Second 
Report to Congress on Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program. 2020. https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
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    Prioritizing the achievement of health equity is essential in the 
SNF VBP Program because disparities in SNFs appear to be widespread, 
from admissions to quality of care to nurse staffing and turnover.\308\ 
\309\ In the 2016

[[Page 21383]]

Report to Congress, the Office of the Assistant Secretary for Planning 
and Evaluation (ASPE) reported that individuals with social risk 
factors, such as dual eligibility status, had worse outcomes and were 
more likely to be cared for by lower-quality SNFs.\310\ Individuals 
with dual eligibility status (DES) are those who are eligible for both 
Medicare and Medicaid coverage. Individuals with DES are more likely to 
have disabilities or functional impairments, more likely to be 
medically complex, more likely to have greater social needs, and have a 
greater risk of negative health outcomes compared to individuals 
without DES.\311\ They are also more likely to be admitted to SNFs that 
have lower staffing levels, have a higher share of residents who are 
enrolled in Medicaid in their total resident population, and experience 
resource constraints.\312\ In addition, studies have found that DES is 
an important predictor of admission to a low-quality SNF.\313\ All of 
these factors indicate that individuals with DES represent an 
underserved population that is more clinically complex, has greater 
social needs and is more often admitted to lower-resourced SNFs than 
those without DES. This presents significant challenges to provide 
quality care to patients with greater resource-intensive needs by 
providers that may have fewer resources, as effectively implementing 
quality improvement initiatives requires time, money, staff, and 
technology.\314\ \315\ \316\ \317\ As a result, competitive programs, 
like the current SNF VBP Program, may place some SNFs that serve this 
underserved population at a disadvantage.
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    \308\ Rivera-Hernandez, M, Rahman, M, Mor, V, & Trivedi, AN 
(2019). Racial Disparities in Readmission Rates among Patients 
Discharged to Skilled Nursing Facilities. Journal of the American 
Geriatrics Society, 67(8), 1672-1679. https://doi.org/10.1111/jgs.15960.
    \309\ Konetzka, R, Yan, K, & Werner, RM (2021). Two Decades of 
Nursing Home Compare: What Have We Learned? Medical Care Research 
and Review, 78(4), 295-310. https://doi.org/10.1177/1077558720931652.
    \310\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. First Report 
to Congress on Social Risk Factors and Performance in Medicare's 
Value-Based Purchasing Program. 2016. https://aspe.hhs.gov/sites/default/files/migrated_legacy_files/171041/ASPESESRTCfull.pdf.
    \311\ Johnston, KJ, & Joynt Maddox, KE (2019). The Role of 
Social, Cognitive, And Functional Risk Factors In Medicare Spending 
For Dual And Nondual Enrollees. Health Affairs (Project Hope), 
38(4), 569-576. https://doi.org/10.1377/hlthaff.2018.05032.
    \312\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \313\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
    \314\ Reidt, SL, Holtan, HS, Larson, TA, Thompson, B, Kerzner, 
LJ, Salvatore, TM, & Adam, TJ (2016). Interprofessional 
Collaboration to Improve Discharge from Skilled Nursing Facility to 
Home: Preliminary Data on Postdischarge Hospitalizations and 
Emergency Department Visits. Journal of the American Geriatrics 
Society, 64(9), 1895-1899. https://doi.org/10.1111/jgs.14258.
    \315\ Au, Y, Holbrook, M, Skeens, A, Painter, J, McBurney, J, 
Cassata, A, & Wang, SC (2019). Improving the quality of pressure 
ulcer management in a skilled nursing facility. International Wound 
Journal, 16(2), 550-555. https://doi.org/10.1111/iwj.13112.
    \316\ Berkowitz, RE, Fang, Z, Helfand, BKI, Jones, RN, 
Schreiber, R, & Paasche-Orlow, MK (2013). Project ReEngineered 
Discharge (RED) Lowers Hospital Readmissions of Patients Discharged 
From a Skilled Nursing Facility. Journal of the American Medical 
Directors Association, 14(10), 736-740. https://doi.org/10.1016/j.jamda.2013.03.004.
    \317\ Chisholm, L, Zhang, NJ, Hyer, K, Pradhan, R, Unruh, L, & 
Lin, F-C (2018). Culture Change in Nursing Homes: What Is the Role 
of Nursing Home Resources? INQUIRY: The Journal of Health Care 
Organization, Provision, and Financing, 55, 0046958018787043. 
https://doi.org/10.1177/0046958018787043.
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    In the FY 2023 SNF PPS proposed rule (87 FR 22789), we requested 
public comments on policy changes that we should consider on the topic 
of health equity. In the FY 2023 SNF PPS final rule (87 FR 47596 
through 47597), we provided a detailed summary of the feedback we 
received on this topic. Commenters overwhelmingly supported our 
commitment to advancing health equity for SNF residents, with some 
suggesting that we examine factors that may lead to care inequities. 
One commenter suggested we adopt risk adjustment or incentive payments 
for SNFs that admit individuals that other SNFs will not admit. Another 
commenter recommended pairing clinical data measures with social risk 
metrics to help providers deliver more comprehensive care. Overall, 
commenters were interested in understanding where disparities may exist 
and wanted us to work with SNFs and other interested parties to 
understand the greatest needs in achieving health equity to ensure any 
revisions to the Program could be implemented with minimal data burden. 
We considered all the comments we received as we developed our Health 
Equity Adjustment proposal described below.
    We believe that SNFs and providers across all settings can 
consistently perform well even when caring for a high proportion of 
individuals who are underserved,\318\ and, with the right program 
components,VBP programs can create meaningful incentives for SNFs that 
serve a high proportion of individuals who are underserved to deliver 
high quality care.\319\ \320\ \321\ \322\ \323\ \324\ We believe 
updating the scoring methodology, as detailed in the following 
sections, would appropriately measure performance and create these 
meaningful incentives for those who care for a high proportions of 
residents with DES.
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    \318\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. First Report 
to Congress on Social Risk Factors and Performance in Medicare's 
Value-Based Purchasing Program. 2016. https://aspe.hhs.gov/sites/default/files/migrated_legacy_files/171041/ASPESESRTCfull.pdf.
    \319\ Crook, HL, Zheng, J, Bleser, WK, Whitaker, RG, Masand, J, 
& Saunders, RS (2021). How Are Payment Reforms Addressing Social 
Determinants of Health? Policy Implications and Next Steps. Milbank 
Memorial Fund, Duke Margolis Center for Health Policy. https://www.milbank.org/wp-content/uploads/2021/02/Duke-SDOH-and-VBP-Issue-Brief_v3.pdf.
    \320\ Johnston, KJ, & Joynt Maddox, KE (2019). The Role of 
Social, Cognitive, And Functional Risk Factors In Medicare Spending 
For Dual And Nondual Enrollees. Health Affairs (Project Hope), 
38(4), 569-576. https://doi.org/10.1377/hlthaff.2018.05032.
    \321\ Konetzka, R, Yan, K, & Werner, RM (2021). Two Decades of 
Nursing Home Compare: What Have We Learned? Medical Care Research 
and Review, 78(4), 295-310. https://doi.org/10.1177/1077558720931652.
    \322\ Weech-Maldonado, R, Pradhan, R, Dayama, N, Lord, J, & 
Gupta, S (2019). Nursing Home Quality and Financial Performance: Is 
There a Business Case for Quality? Inquiry: A Journal of Medical 
Care Organization, Provision and Financing, 56, 46958018825191. 
https://doi.org/10.1177/0046958018825191.
    \323\ Rivera-Hernandez, M, Rahman, M, Mukamel, D, Mor, V, & 
Trivedi, A (2019). Quality of Post-Acute Care in Skilled Nursing 
Facilities That Disproportionately Serve Black and Hispanic 
Patients. The Journals of Gerontology. Series A, Biological Sciences 
and Medical Sciences, 74(5). https://doi.org/10.1093/gerona/gly089.
    \324\ Burke, RE, Xu, Y, & Rose, L (2022). Skilled Nursing 
Facility Performance and Readmission Rates Under Value-Based 
Purchasing. JAMA Network Open, 5(2), e220721. https://doi.org/10.1001/jamanetworkopen.2022.0721.
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b. Health Equity Adjustment Proposal Summary
    Section 1888(h)(4)(A) of the Act requires the Secretary to develop 
a methodology for assessing the total performance of each SNF based on 
performance standards established under section 1888(h)(3) of the Act 
with respect to the measures applied under section 1888(h)(2) of the 
Act. To further align with our goals to achieve health equity, address 
health disparities, and assess SNF performance more accurately and 
completely under the SNF VBP Program, we are proposing to apply an 
adjustment that would be added to the normalized sum of a SNF's measure 
points on SNF VBP Program measures. As described previously, residents 
with DES are an underserved population that is clinically complex, has 
significant social needs and is more frequently admitted to SNFs that 
have larger populations of Medicaid residents

[[Page 21384]]

and fewer resources than SNFs that do not care for individuals with 
DES.\325\ \326\ \327\ These lower-resourced SNFs are less likely to 
receive positive payment adjustments, which is a considerable 
limitation of the current SNF VBP program's ability to incentivize 
equitable care.\328\ Careful consideration must be taken to modify the 
Program in a way that addresses this issue and ensures that we provide 
appropriate rewards and incentives to all SNFs, including those that 
serve residents with DES. The goal of this Health Equity Adjustment is 
to not only appropriately measure performance by rewarding SNFs that 
overcome the challenges of caring for higher proportions of SNF 
residents with DES but also to incentivize those who have not achieved 
such high-quality care to work towards improvement. We believe this 
Health Equity Adjustment incentivizes high-quality care across all 
SNFs. We also believe this scoring change, through the creation of an 
adjustment designed to award points based on the quality of care 
provided and the proportion of residents with DES, is consistent with 
our strategy to advance health equity.\329\
---------------------------------------------------------------------------

    \325\ Johnston, KJ, & Joynt Maddox, KE (2019). The Role of 
Social, Cognitive, And Functional Risk Factors In Medicare Spending 
For Dual And Nondual Enrollees. Health Affairs (Project Hope), 
38(4), 569-576. https://doi.org/10.1377/hlthaff.2018.05032.
    \326\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \327\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
    \328\ Hefele JG, Wang XJ, Lim E. Fewer Bonuses, More Penalties 
at Skilled Nursing Facilities Serving Vulnerable Populations. Health 
Aff (Millwood). 2019;38(7):1127-1131. doi:10.1377/
hlthaff.2018.05393.
    \329\ Centers for Medicare & Medicaid Services. (2022) CMS 
Outlines Strategy to Advance Health Equity, Challenges Industry 
Leaders to Address Systemic Inequities. Available at https://
www.cms.gov/newsroom/press-releases/cms-outlines-strategy-advance-
health-equity-challenges-industry-leaders-address-systemic-
inequities#:~:text=In%20effort%20to%20address%20systemic%20inequities
%20across%20the,Medicare%2C%20Medicaid%20or%20Marketplace%20coverage%
2C%20need%20to%20thrive.
---------------------------------------------------------------------------

    The Health Equity Adjustment (HEA) would be calculated using a 
methodology that considers both the SNF's performance on the SNF VBP 
Program measures, and the proportion of residents with DES out of the 
total resident population in a given program year at each SNF. To be 
eligible to receive HEA bonus points, a SNF's performance would need to 
meet or exceed a certain threshold and its resident population during 
the applicable performance period for the program year would have to 
include at least 20 percent of residents with DES. Thus, SNFs that 
perform well on quality measures and serve a higher proportion of SNF 
residents with DES would receive a larger adjustment. The specific 
methodology for the proposed calculation of the HEA is described in 
section VII.E.4.d. of this proposed rule. By providing this HEA to SNFs 
that serve higher proportions of SNF residents with DES and that 
perform well on quality measures, we believe we can appropriately 
recognize the resource intensity expended to achieve high performance 
on quality measures by SNFs that serve a high proportion of SNF 
residents with DES, while also mitigating the worse health outcomes 
experienced by underserved populations through incentivizing better 
care across all SNFs.
    An analysis of payment from October 2018 for the SNF VBP Program 
found that SNFs that served higher proportions of Medicaid residents 
were less likely to receive positive payment adjustments. As noted 
previously, residents with DES are more likely to be admitted to SNFs 
with higher proportions of Medicaid residents \330\ suggesting that 
SNFs serving higher proportions of SNF residents with DES face 
challenges in utilizing their limited resources to improve the quality 
of care for their complex residents.\331\ Thus, we aimed to adjust the 
current program scoring methodology to ensure that all SNF residents, 
including those with DES, receive high-quality care. We conducted an 
analysis utilizing FY 2018-2021 measure data for our finalized and 
proposed measures, including a simulation of performance from all 8 
finalized and proposed measures for the FY 2027 Program and found that 
the HEA significantly increased the proportion of SNFs with high 
proportions of SNF residents with DES that received a positive value-
based incentive payment adjustment indicating that this approach would 
modify the SNF VBP program in the way it is intended.
---------------------------------------------------------------------------

    \330\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \331\ Hefele JG, Wang XJ, Lim E. Fewer Bonuses, More Penalties 
at Skilled Nursing Facilities Serving Vulnerable Populations. Health 
Aff (Millwood). 2019;38(7):1127-1131. doi:10.1377/
hlthaff.2018.05393.
---------------------------------------------------------------------------

    We are proposing to call this proposed adjustment the Health Equity 
Adjustment (HEA) and to adopt it beginning with the FY 2027 program 
year.
c. Proposed Health Equity Adjustment Beginning With the FY 2027 SNF VBP 
Program Year
    We propose to define the term ``underserved population'' as 
residents with DES for purposes of this HEA. DES has been established 
in the literature, including research specifically looking at 
SNFs,\332\ \333\ and has been found to be an important factor that 
impacts pay for performance and other quality programs.\334\ \335\ In 
addition, DES is currently utilized in the Hospital Readmissions 
Reduction Program.
---------------------------------------------------------------------------

    \332\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \333\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
    \334\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. First Report 
to Congress on Social Risk Factors and Performance in Medicare's 
Value-Based Purchasing Program. 2016. https://aspe.hhs.gov/sites/default/files/migrated_legacy_files/171041/ASPESESRTCfull.pdf.
    \335\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
---------------------------------------------------------------------------

    The Medicare Shared Savings Program recently adopted a health 
equity adjustment for Accountable Care Organizations that report all-
payer eCQMs/MIPS CQMs, are high-performing on quality, and serve a 
large proportion of underserved beneficiaries, as defined by dual-
eligibility/enrollment in the Medicare Part D low income subsidy (LIS) 
(meaning the individual is enrolled in a Part D plan and receives LIS) 
and an Area Deprivation Index (ADI) score of 85 or above, as detailed 
in the CY 2023 PFS final rule (87 FR 69838 through 69857). At this 
time, for the SNF VBP Program's proposed HEA, we believe that it is 
preferable to use DES to identify SNF residents who are underserved. We 
also explored alternative indicators to identify populations that are 
underserved for purposes of this proposal, such as a resident's 
eligibility for the Medicare Part D Low-Income Subsidy (LIS) program or 
whether the resident lives in an area with high deprivation, as 
measured by the Area Deprivation Index (ADI), however, we determined 
that for the current proposal, utilizing residents with DES to identify 
underserved

[[Page 21385]]

populations would best serve the goals of the adjustment. Individuals 
who are eligible for the LIS program have incomes up to 150 percent of 
the Federal poverty level.\336\ Utilizing residents who are eligible 
for the LIS program would include most residents with DES, as well as 
additional residents who may be underserved; however, the data on the 
LIS program are only available for those enrolled in Medicare Part D, 
which may limit its effectiveness, and it is not uniform across both 
States and territories. Further, those eligible for the LIS program 
have not been studied extensively in the SNF setting and the effect of 
using those eligible for the LIS program to determine a SNF's 
underserved population has also not been studied extensively. 
Geographic-based or neighborhood-level economic indices, such as the 
ADI, have been utilized to look at characteristics of healthcare 
facilities in low-resourced areas and could be used as a proxy for 
negative health outcomes due to medical and social risk factors.\337\ 
\338\ ADI appears to be an important predictor of poor health outcomes, 
even when adjusting for individual characteristics, suggesting 
neighborhood or geography may play an even more important role in 
health than individual characteristics.\339\ \340\ However, there is 
not much literature or analysis that has been conducted linking these 
indices to negative health outcomes specifically in the SNF setting. 
Therefore, we propose to only use DES data at this time to identify SNF 
residents who are underserved for this HEA proposal, given that the DES 
data are readily available, are evidenced based in the SNF setting, and 
are already used in the Hospital Readmissions Reduction Program. We 
intend to consider how to best incorporate the LIS, ADI, and other 
indicators to identify those who are underserved in future health 
equity adjustment proposals for the SNF VBP Program as more research is 
made available. We are seeking comment on the potential future use of 
these additional indicators in the RFI in section VII.E.5 of this 
proposed rule. We provide additional detail on how we would calculate 
SNF residents with DES for the purpose of this adjustment later in this 
section of this proposal.
---------------------------------------------------------------------------

    \336\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. First Report 
to Congress on Social Risk Factors and Performance in Medicare's 
Value-Based Purchasing Program. 2016. https://aspe.hhs.gov/sites/default/files/migrated_legacy_files/171041/ASPESESRTCfull.pdf.
    \337\ The University of Wisconsin Neighborhood Atlas website 
(https://www.neighborhoodatlas.medicine.wisc.edu/).
    \338\ Falvey, JR, Hade, EM, Friedman, S, Deng, R, Jabbour, J, 
Stone, RI, & Travers, JL (2022). Severe neighborhood deprivation and 
nursing home staffing in the United States. Journal of the American 
Geriatrics Society. https://doi.org/10.1111/jgs.17990.
    \339\ Chamberlain, AM, Finney Rutten, LJ, Wilson, PM, Fan, C, 
Boyd, CM, Jacobson, DJ, Rocca, WA, & St. Sauver, JL (2020). 
Neighborhood socioeconomic disadvantage is associated with 
multimorbidity in a geographically-defined community. BMC Public 
Health, 20(1), 13. https://doi.org/10.1186/s12889-019-8123-0.
    \340\ Hu, J, Kind, AJH, & Nerenz, D (2018). Area Deprivation 
Index (ADI) Predicts Readmission Risk at an Urban Teaching Hospital. 
American Journal of Medical Quality: The Official Journal of the 
American College of Medical Quality, 33(5), 493-501. https://doi.org/10.1177/1062860617753063.
---------------------------------------------------------------------------

    In order to calculate the HEA, we first propose to assign to each 
SNF 2 points for each measure for which it is a top tier performing 
SNF. We propose to define a top tier performing SNF as a SNF whose 
performance during the program year is in the top third (greater than 
or equal to the 66.67th percentile) of the performance of all SNFs on 
the measure during the same program year. Each measure would be 
assessed independently such that a SNF that is a top tier performing 
SNF for one measure would be assigned 2 points for that measure even if 
they are not a top tier performing SNF for any other measure. 
Similarly, if a SNF is a top tier performing SNF for all measures, they 
would be assigned 2 points for all measures.
    We also propose to assign a measure performance scaler for each SNF 
that would be equal to the total number of assigned points that the SNF 
earns on all measures as a result of its performance. Under this 
approach, for the FY 2027 Program Year, a SNF would receive a maximum 
measure performance scaler of 16 if the SNF is a top tier performing 
SNF on all 8 measures (both proposed and already finalized) for that 
program year. As described in more detail in the following paragraph 
and in section VII.E.4.e of this proposed rule, we decided on assigning 
a maximum point value of 2 for each measure because we believe that it 
provides an appropriate incentive to top tier performing SNFs that 
serve a high proportion of SNF residents with DES to continue their 
quality efforts, as well as an incentive for all SNFs that serve SNF 
residents with DES to improve their quality.
    Based on our calculation of measure data from FY 2018-2021 the 
average SNF Performance Score for SNFs in the top third of performance 
that care for high proportions of residents with DES (SNFs with 
proportions of residents with DES in the top third) is 8.4 points lower 
than the SNF Performance Score for SNFs in the top third of performance 
that do not care for high proportions of residents with DES (40.8 for 
high performing SNFs with high proportions of residents with DES and 
49.2 for all other high performing SNFs). Allowing for a maximum 
measure performance scaler of 16 for the FY 2027 program year would 
provide an opportunity for top tier performing SNFs that treat a high 
proportion of SNF residents with DES to close this gap. We also 
considered assigning 3 points for each measure to calculate the measure 
performance scaler. However, we determined that the maximum measure 
performance scaler a SNF could earn based on the assignment of 3 points 
per measure, 24 points, would exceed the number of points that many 
SNFs receive for their SNF Performance Score based on all Program 
measures, which diminishes the intent of the HEA as a bonus. We further 
discuss this option in section VII.E.4.e of this proposed rule. We also 
considered assigning a point value of 2 to SNFs in the middle third of 
performance (SNFs whose performance falls between the 33.33rd 
percentile and 66.67th percentile in performance) and assigning a point 
value of 4 to top tier performing SNFs for each measure to align with 
the Medicare Shared Savings Program's health equity adjustment (87 FR 
69843 through 69845). This approach would provide a greater number of 
SNFs with the opportunity to benefit from the adjustment. However, in 
the SNF VBP, this approach could reduce the size of the payment 
adjustment available to SNFs whose performance is in the top tier, 
reducing the incentives to improve and deviating considerably from the 
primary goal of the program to appropriately assess performance and 
reward high quality performance among SNFs that care for high 
proportions of residents with DES.
    We propose to define the term ``underserved multiplier'' for a SNF 
as the number representing the SNF's proportion of residents with DES 
out of its total resident population in the applicable program year, 
translated using a logistic exchange function. Due to the structure of 
the logistic exchange function, those SNFs with lower proportions of 
residents with DES have smaller underserved multipliers than their 
actual proportion of residents with DES and those SNFs with higher 
proportions of SNF residents with DES have underserved multipliers 
higher than their proportion of SNF residents with DES. The specific 
logistic function used to translate the SNF's proportion of residents 
with DES is described in section VII.E.4.d. of this proposed rule.

[[Page 21386]]

We propose to define the total resident population at each SNF as 
Medicare beneficiaries identified from the SNF's Part A claims during 
the performance period of the 1-year measures. We propose to define 
residents with DES, for purposes of this proposal, as the percentage of 
Medicare SNF residents who are also eligible for Medicaid. We propose 
to assign DES for any Medicare beneficiary who was deemed by Medicaid 
agencies to be eligible to receive Medicaid benefits for any month 
during the performance period of the 1-year measures. For example, 
during the FY 2027 program year, we would calculate the proportion of 
residents with DES during any month of FY 2025 (October 1, 2024--
September 30, 2025), which is the performance period of the FY 2027 
Program year's 1-year measures. Similarly, a SNF's total resident 
population of Medicare beneficiaries identified from the SNF's Part A 
claims would be calculated from the SNF's Part A claims during FY 2025. 
Data on DES is sourced from the State Medicare Modernization Act (MMA) 
file of dual eligible beneficiaries, which each of the 50 States and 
the District of Columbia submit to CMS at least monthly. This file is 
utilized to deem individuals with DES automatically eligible for the 
Medicare Part D Low Income Subsidy, as well as other CMS program needs 
and thus can be considered the gold standard for determining DES. We 
note that this is the same file used for determining DES in the 
Hospital Readmissions Reduction Program. More detail on this file can 
be found on the CMS website at https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/StateMMAFile and at the 
Research Data Assistance Center website at https://resdac.org/cms-data/variables/monthly-medicare-medicaid-dual-eligibility-code-january.
    We are proposing to calculate an underserved multiplier for a SNF 
if that SNF's proportion of residents with DES out of its total 
resident population during the applicable performance period of the 1-
year measures is at least 20 percent. Imposing a floor of 20 percent 
for the underserved multiplier for a SNF to be eligible to receive HEA 
bonus points, reinforces that the adjustment is intended to 
appropriately measure performance by rewarding SNFs that are serving 
higher proportions of SNF residents with DES while also achieving high 
levels of quality performance. We describe this 20 percent floor in 
further detail in section VII.E.4.d. of this proposed rule. Lastly, we 
propose to define HEA bonus points for a SNF as the product of the 
SNF's measure performance scaler and the SNF's underserved multiplier. 
The HEA bonus points would then be added to the normalized sum of all 
points a SNF is awarded for each measure.
    Through the proposed HEA bonus points, we seek to improve outcomes 
by providing incentives to SNFs to strive for high performance across 
measures, as well as to care for high proportions of residents with 
DES. The HEA bonus points calculation is purposefully designed to not 
reward poor quality. Instead, the HEA incentivizes SNFs that care for 
higher proportions of SNF residents with DES to improve their overall 
quality of care across the entire SNF population. As described more 
fully in section VII.E.4.d. of this proposed rule, the combination of 
the measure performance scaler and the underserved multiplier would 
result in a range of possible HEA bonus points that is designed to give 
the highest rewards to SNFs caring for a larger proportion of SNF 
residents with DES and delivering high quality care.
    We welcome comments on this proposal. We are proposing to amend our 
regulations at Sec.  413.338(a) to define these new scoring methodology 
terms, including underserved population, the measure performance 
scaler, top tier performing SNF, the underserved multiplier, and the 
HEA bonus points. We are also proposing to amend our regulations by 
adding a new paragraph (k) in Sec.  413.338 that implements the Health 
Equity Adjustment beginning with the FY 2027 program year.
d. Proposed Calculation Steps and Examples
    In this section, we outline the calculation steps and provide 
examples of the determination of HEA bonus points and the application 
of these HEA bonus points to the normalized sum of a SNF's measure 
points. These example calculations illustrate possible HEA bonus points 
resulting from the proposed approach, which accounts for both a SNF's 
quality performance and its proportion of residents with DES. For each 
SNF, the HEA bonus points would be calculated according to the 
following formula:

HEA bonus points = measure performance scaler x underserved multiplier

    The proposed calculation of the HEA bonus points would be as 
follows:
Step One--Calculate the Number of Measure Performance Scaler Points for 
Each SNF
    We propose to first calculate a measure performance scaler based on 
a SNF's score on each of the SNF VBP program measures. We would assign 
a point value of 2 for each measure where a SNF is a top tier 
performing SNF on that measure, such that for the FY 2027 program year, 
a SNF could receive a maximum 16 point measure performance scaler for 
being a top tier performing SNF for each of the 8 finalized and 
proposed measures. Top tier performance on each measure is calculated 
by determining the percentile that the SNF falls in based on their 
score on the measure as compared to the score earned by other SNFs who 
are eligible to receive a score on the measure. A SNF whose score is 
greater than or equal to the 66.67th (two-thirds) percentile on a given 
measure compared to all other SNFs would be considered a top tier 
performing SNF and would be assigned a point value of 2 for that 
measure. This is depicted in Table 21 for the FY 2027 program year. We 
note that if a SNF performs in the bottom two-thirds (less than 66.67th 
percentile) of performance on all measures, that SNF would be assigned 
a point value of 0 for each measure, resulting in a measure performance 
scaler of 0.
    As described previously, we are proposing to assign to each SNF a 
point value of 2 for each measure for which it is a top tier performing 
SNF, and we are proposing that the measure performance scaler would be 
the sum of the point values assigned to each measure in the SNF VBP 
Program. We modeled this proposed measure performance scaler after the 
performance scaler finalized in the Medicare Shared Savings Program's 
health equity adjustment (87 FR 69843 through 69845) for consistency 
across CMS programs, although that adjustment allows for a middle 
performance group as well. However, as described previously, because we 
aim to specifically target the highest performing SNFs for this 
adjustment, we are limiting our adjustment to the top third of 
performers only.

[[Page 21387]]



                          Table 21--Example of the Measure Performance Scaler Assigned to SNFs Based on Performance by Measure
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                       Example SNF 1                  Example SNF 2                  Example SNF 3                  Example SNF 4
                              --------------------------------------------------------------------------------------------------------------------------
           Measure                Performance                    Performance                    Performance                   Performance
                                     group          Value           group          Value           group          Value          group          Value
--------------------------------------------------------------------------------------------------------------------------------------------------------
SNFRM *......................  Top third.......            2  Top Third.......            2  Top Third.......            2  Bottom Two-                0
                                                                                                                             Thirds.
SNF HAI Measure..............  Top third.......            2  Top Third.......            2  Top Third.......            2  Bottom Two-                0
                                                                                                                             Thirds.
Total Nurse Staffing Measure.  Top third.......            2  Bottom Two-                 0  Bottom Two-                 0  Top Third......            2
                                                               Thirds.                        Thirds.
DTC-PAC SNF Measure..........  Top third.......            2  Top Third.......            2  Bottom Two-                 0  Bottom Two-                0
                                                                                              Thirds.                        Thirds.
Falls with Major Injury (Long- Top Third.......            2  Top Third.......            2  Bottom Two-                 0  Bottom Two-                0
 Stay) Measure **.                                                                            Thirds.                        Thirds.
Discharge Function Measure **  Top Third.......            2  Top Third.......            2  Top Third.......            2  Bottom Two-                0
                                                                                                                             Thirds.
Long Stay Hospitalization      Top Third.......            2  Top Third.......            2  Top Third.......            2  Bottom Two-                0
 Measure **.                                                                                                                 Thirds.
Nursing Staff Turnover         Top Third.......            2  Top Third.......            2  Top Third.......            2  Bottom Two-                0
 Measure **.                                                                                                                 Thirds.
                               Measure                    16  Measure                    14  Measure                    10  Measure                    2
                                Performance                    Performance                    Performance                    Performance
                                Scaler.                        Scaler.                        Scaler.                        Scaler.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
* We are proposing to replace the SNFRM would be replaced with the SNF WS PPR beginning with the FY 2028 program year.
** We are proposing to adopt the Nursing Staff Turnover Measure beginning with the FY 2026 program year and the Falls with Major Injury (Long-Stay)
  Measure, Discharge Function Measure, and Long Stay Hospitalization Measure beginning with the FY 2027 program year.

Step Two--Calculate the Underserved Multiplier
    We propose to calculate an underserved multiplier, which, as stated 
previously, we propose to define as, for a SNF, the number representing 
the SNF's proportion of residents with DES out of its total resident 
population in the applicable program year, translated using a logistic 
exchange function. As stated previously, the primary goal of the 
adjustment is to appropriately measure performance by rewarding SNFs 
that are able to overcome the challenges of caring for high proportions 
of residents with DES while still providing high quality care. Another 
way that we are able to accomplish the goal of this adjustment is by 
utilizing a logistic exchange function to calculate the underserved 
multiplier, which would provide SNFs who care for the highest 
proportions of SNF residents with DES with the most HEA bonus points. 
Thus, we are proposing to utilize a logistic exchange function to 
calculate the underserved multiplier for scoring SNFs such that there 
would be a lower rate of increase at the beginning and the end of the 
curve. The formula for the underserved multiplier using a logistic 
exchange function would be as follows:
[GRAPHIC] [TIFF OMITTED] TP10AP23.006

    Due to the structure of the logistic exchange function, those SNFs 
with lower proportions of residents with DES have smaller underserved 
multipliers than their actual proportion of residents with DES and 
those SNFs with higher proportions of SNF residents with DES have 
underserved multipliers higher than their proportion of SNF residents 
with DES. A logistic exchange function assumes a large difference 
between SNFs treating the most and fewest residents with DES. 
Therefore, the logistic exchange function provides higher HEA bonus 
points to SNFs serving greater proportions of SNF residents with DES. 
For example, as shown in Figure A, if a SNF serves 70 percent of SNF 
residents with DES, the SNF would receive an underserved multiplier of 
0.78.
Figure A--Determining the Underserved Multiplier From a SNF's 
Proportion of Residents With DES Using the Logistic Exchange Function

[[Page 21388]]

[GRAPHIC] [TIFF OMITTED] TP10AP23.007

    We propose that SNFs would receive an underserved multiplier of 0 
if the SNF's proportions of SNF residents with DES is less than 20 
percent, thereby establishing a ``floor'' on the magnitude of the SNF's 
underserved population proportion in order for the SNF to be eligible 
for any HEA bonus points. Because SNFs with proportions of SNF 
residents with DES below 20 percent receive a value of 0 for their 
underserved multiplier, any multiplication with the measure performance 
scaler would be 0 and would lead to those SNFs receiving no HEA bonus 
points. Imposing a floor of 20 percent for the underserved multiplier 
for a SNF to be eligible to receive HEA bonus points, reinforces that 
the adjustment is intended to appropriately measure performance by 
rewarding SNFs that are serving higher proportions of SNF residents 
with DES while also achieving high levels of quality performance. We 
believe this approach is necessary to remain consistent with the goal 
to reward high quality care specifically among SNFs that care for 
higher proportions of SNF residents with DES. We anticipate the vast 
majority of SNFs would be able to earn HEA bonus points despite this 
floor, and we expect the percent of SNFs meeting the 20 percent floor 
for the underserved multiplier might increase over time, as existing 
SNFs seek to expand their resident population to earn HEA bonus points. 
We also believe that the challenges associated with caring for 
residents with DES, a complex resident population, would be negligible 
if 80 percent of a SNF's resident population is not underserved. This 
20 percent floor is consistent with the new health equity adjustment 
for ACOs that report all payer eCQMs/MIPS CQMs, as finalized in the CY 
2023 PFS final rule (87 FR 69849 through 69852).
    Alternatively, we considered establishing a floor of 60 percent 
such that all SNFs with proportions of SNF residents with DES below 60 
percent would receive an underserved multiplier of 0, and therefore, 
would not receive any HEA bonus points. Although this would provide a 
greater value-based incentive payment amount to top tier performing 
SNFs that serve the highest proportions of SNF residents with DES and 
thus would support the primary goal of the adjustment, it would also 
mean SNFs that care for high proportions of SNF residents with DES who 
likely face similar challenges, albeit to a lesser extent, would 
receive no adjustment at all.
Step Three--Calculate the HEA Bonus Points
    We are proposing to calculate the HEA bonus points that apply to a 
SNF for a program year by multiplying the measure performance scaler by 
the underserved multiplier. We believe that combining the measure 
performance scaler and the underserved multiplier to calculate the HEA 
bonus points allows for us to reward those SNFs with high quality that 
are also serving high proportions of SNF residents with DES, while 
incentivizing other SNFs to improve their performance (by a higher 
measure performance scaler) and serve more SNF residents with DES (by a 
higher underserved multiplier) in order to earn more HEA bonus points. 
Table 22 shows examples of how the measure performance scaler and 
underserved multiplier would be used to calculate the HEA bonus points. 
It also demonstrates how the logistic exchange function that we are 
proposing to use to calculate the underserved multiplier interacts with 
the measure performance scaler and results in SNFs serving higher 
proportion of SNF residents with DES receiving more HEA bonus points. 
For instance, example SNF 1 with 16 points and a proportion of 
residents with DES of 50 percent received a measure performance scaler 
of 16 and an underserved multiplier of 0.22. In other words, they would 
receive 22 percent of the points from their measure performance scaler 
because of how the logistic exchange function translates their 
proportion of residents with DES. Their measure performance scaler of 
16 and underserved multiplier of 0.22 would then be multiplied together 
to get their HEA bonus points of 3.52. Alternatively, example SNF 2 
with 14 points and a proportion of residents with DES of 70 percent, 
received an underserved multiplier of 0.78. Their measure performance 
scaler of 14 and underserved multiplier of 0.78 would then be 
multiplied together to get their HEA bonus points of 10.92. Note that 
although SNF 1 had a higher measure performance scaler, they received 
fewer HEA bonus points because they had a lower proportion of residents 
with DES. Finally, example SNF 3 had a proportion of SNF residents with 
DES of less than 20 percent and so they received an underserved 
multiplier of 0, resulting in no HEA bonus points

HEA Bonus Points = Measure Performance Scaler x Underserved Multiplier

[[Page 21389]]



                              Table 22--Example of the HEA Bonus Points Calculation
----------------------------------------------------------------------------------------------------------------
                                                      Measure      Proportion of
                   Example SNF                      performance   residents with    Underserved      HEA bonus
                                                      scaler          DES (%)       multiplier        points
                                                             [A]             [B]             [C]      [D] ([A] *
                                                                                                            [C])
----------------------------------------------------------------------------------------------------------------
SNF 1...........................................              16              50            0.22            3.52
SNF 2...........................................              14              70            0.78           10.92
SNF 3...........................................              10              10               0               0
SNF 4...........................................               2              80            0.92            1.84
----------------------------------------------------------------------------------------------------------------

Step Four--Add HEA Bonus Points to the Normalized Sum of all Points 
Awarded for Each Measure
    Finally, we are proposing that we would add a SNF's HEA bonus 
points as calculated in Step Three of this section to the normalized 
sum of all points awarded to a SNF for each measure. This normalized 
sum would be the SNF Performance Score earned by the SNF for the 
program year, except that we would cap the SNF's Performance Score at 
100 points to ensure the HEA creates a balanced incentive that has the 
potential to increase the SNF Performance Score without dominating the 
score and creating unintended incentives. Table 23 displays the final 
HEA bonus points added to the normalized sum of all points awarded to a 
SNF for each measure for 4 example SNFs.

                              Table 23--Example of the HEA Bonus Points Calculation
----------------------------------------------------------------------------------------------------------------
                                                                  Normalized sum
                                                                   of all points     HEA bonus          SNF
                           Example SNF                              awarded for    points (step     performance
                                                                   each measure   3, column [D])       score
                                                                             [A]             [B]     ([A] + [B])
----------------------------------------------------------------------------------------------------------------
SNF 1...........................................................              80            3.52           83.52
SNF 2...........................................................              65           10.92           75.92
SNF 3...........................................................              42               0           42.00
SNF 4...........................................................              10            1.84           11.84
----------------------------------------------------------------------------------------------------------------

    By adding these HEA bonus points to the normalized sum of all 
points awarded to a SNF for each measure, SNFs can be rewarded for 
delivering excellent care to all residents they serve and can be 
appropriately recognized for the resource intensity expended to achieve 
high performance when caring for higher proportion of SNF residents 
with DES. We believe this scoring adjustment, designed to advance 
health equity through the SNF VBP Program, is consistent with CMS's 
goal to incentivize greater inclusion of underserved populations, as 
well as the delivery of high-quality care to all.
    We invite public comment on this proposed scoring change and 
calculations including the use of the measure performance scaler, 
underserved multiplier, and HEA bonus points. We are proposing to amend 
our regulations at Sec.  413.338(e) and (k) to update the steps for 
performance scoring with the incorporated health equity scoring 
adjustment.
e. Proposal To Increase the Payback Percentage To Support the HEA
    We adopted 60 percent as the SNF VBP Program's payback percentage 
for FY 2019 and subsequent fiscal years, subject to increases as needed 
to implement the Program's Low-Volume Adjustment policy for SNFs 
without sufficient data on which to base measure scores. We based this 
decision on numerous considerations, including our estimates of the 
number of SNFs that would receive a positive payment adjustment under 
the Program, the marginal incentives for all SNFs to reduce hospital 
readmissions and make quality improvements, and the Medicare Program's 
long-term sustainability. We also stated that we intended to monitor 
the effects of the payback percentage policy on Medicare beneficiaries, 
on participating SNFs, and on their measured performance, and we stated 
that we intended to consider proposing to adjust the payback percentage 
in future rulemaking.
    In previous rules, we have received many public comments urging us 
to increase the payback percentage. For example, in the FY 2018 SNF PPS 
final rule (82 FR 36620), we responded to comments urging us to 
finalize a 70 percent payback percentage. We stated at that time that 
we did not believe that a 70 percent payback percentage appropriately 
balanced the policy considerations that we considered when we proposed 
the 60 percent policy. We responded to similar comments in the FY 2019 
SNF PPS final rule (83 FR 39281), where commenters urged us to revisit 
the payback percentage policy and adopt 70 percent as the Program's 
policy. We reiterated that we did not believe it was appropriate to 
revisit the payback percentage at that time, which was prior to the 
Program's first incentive payments taking effect on October 1, 2018.
    As part of our ongoing monitoring and evaluation efforts associated 
with the SNF VBP Program, we have considered whether to revise the 
Program's payback percentage policy to support the proposed HEA. 
Specifically, in conjunction with our HEA bonus point proposal, we are 
proposing to increase the total amount available for a fiscal year to 
fund the value-based incentive payment amounts beginning with the FY 
2027 program year.
    We are proposing this update to our payback percentage policy both 
to increase SNFs' incentives under the Program to undertake quality 
improvement efforts and to minimize

[[Page 21390]]

the impact of the proposed HEA on the distribution of value based 
incentive payments to SNFs that do not earn the HEA. Because the SNF 
VBP Program's value-based incentive payment amounts depend on the 
distribution of SNF Performance Scores in each SNF VBP program year, 
providing additional incentives to SNFs serving higher proportions of 
SNF residents with DES without increasing the payback percentage could 
reduce other SNFs' value-based incentive payment amounts. While we do 
not believe that those reductions would be significant, we view a 
change to the payback percentage to further increase SNFs' quality 
improvement incentives to be more effective.
    In determining how to modify the payback percentage, we considered 
the maximum number of HEA bonus points that would be awarded, as it is 
important that those points translate into meaningful enough rewards 
for SNFs to meet our goals of this adjustment to appropriately measure 
performance by rewarding SNFs that overcome the challenges of caring 
for higher proportions of SNF residents with DES and to incentivize 
SNFs who have not achieved such high-quality care to work towards 
improvement. However, we also have to ensure that the additional HEA 
bonus points available do not lead to value-based incentive payments 
that exceed the maximum 70 percent payback percentage authorized under 
section 1888(h)(5)(C)(ii)(III) of the Act. Additionally, we considered 
the maximum number of HEA bonus points that would be awarded in 
comparison to the average SNF Performance Score as we believe providing 
more HEA bonus points for our proposed HEA relative to the average a 
SNF receives for their performance on the Program measures could 
undermine the incentives for SNFs to perform in the SNF VBP Program.
    We conducted an analysis utilizing FY 2018-2021 measure data for 
our finalized and proposed measures, including a simulation of 
performance from all 8 finalized and proposed measures for the FY 2027 
Program, to determine what would be the greatest amount we could 
increase the payback percentage by for the HEA while not exceeding the 
70 percent maximum or allowing for too many HEA bonus points. We 
examined the interaction of the two factors that directly impact the 
size of the incentives, the assigned point value for each measure and 
the payback percentage. For the first factor, as stated previously, we 
are proposing to assign 2 points per measure to each SNF that is a top 
tier performing SNF for that measure. This assigned point value would 
be used to calculate the measure performance scaler and resulting HEA 
bonus points. In this analysis, we also tested alternatives of 
assigning a point value of 1 or 3 per measure to determine how each 
option would impact the payback percentage and resulting value-based 
incentive payment amounts. For the payback percentage factor, we tested 
increasing the payback percentage to a fixed amount of 65 percent. We 
also tested an option in which we allow the payback percentage to vary 
based on performance data such that SNFs that do receive the HEA would 
not experience a decrease in their value-based incentive payment 
amount, to the greatest extent possible, relative to no HEA in the 
Program and maintaining a payback percentage of 60 percent.
    Table 24 has three columns representing possible point values 
assigned to each measure that are then used to calculate the measure 
performance scaler. As shown in Table 24, regardless of the assigned 
points per measure, 78 percent of SNFs would receive the HEA in this 
analysis. This means that 78 percent of SNFs were top tier performing 
SNFs for at least 1 measure and had at least 20 percent of their 
residents with DES, so would have received some HEA bonus points. Table 
24 also shows the mean number of HEA bonus points per SNF receiving the 
HEA, as well as the HEA bonus points at the 90th percentile and the 
maximum HEA bonus points that would have been received for the HEA. 
Table 24 then provides an estimate of the payback percentage that would 
have been required such that SNFs that do receive the HEA would not 
experience a decrease in their value-based incentive payment amount, to 
the greatest extent possible, relative to no HEA in the Program and 
maintaining a payback percentage of 60 percent. This analysis also 
identified that the average SNF, prior to the implementation of the 
HEA, would have received a SNF Performance Score of 31.6 and that the 
90th percentile SNF Performance Score was 49.7.
    As stated previously, we are proposing to assign a point value of 2 
for each measure in which a SNF is a top tier performing SNF. Table 24 
shows that assigning a point value of 2 per measure would have resulted 
in a 66 percent payback percentage, meaning once all SNFs have been 
awarded HEA bonus points, the value-based incentive payment amounts 
would result in a payback percentage of 66 percent. Assigning a point 
value of any higher number, such as 3 points per measure could result 
in the payback percentage exceeding the 70 percent maximum. This is 
because the amount of HEA bonus points would vary with performance, and 
so we expect the HEA bonus points to vary from year to year, creating a 
significant risk that assigning a point value of 3 for each measure 
would result in a payback percentage above the 70 percent maximum. 
Further, assigning a point value of 3 for each measure would result in 
HEA bonus points as high as 20. Considering the average SNF Performance 
Score during this same time period would have been 31.6, the addition 
of 20 bonus points puts far too much weight on the HEA compared to each 
of the Program measures.

  Table 24--Estimated HEA Bonus Points and Payment Adjustments Resulting From Scoring Options Based on FY 2018-
                                                    2021 Data
----------------------------------------------------------------------------------------------------------------
                                                                    1 assigned      2 assigned      3 assigned
                                                                    point value     point value     point value
                                                                    per measure     per measure     per measure
----------------------------------------------------------------------------------------------------------------
                                               SNFs receiving HEA
----------------------------------------------------------------------------------------------------------------
Total Number of SNFs receiving HEA..............................          10,668          10,668          10,668
Percentage of SNFs receiving HEA................................             78%             78%             78%
----------------------------------------------------------------------------------------------------------------
                                   HEA bonus points (among SNFs receiving HEA)
----------------------------------------------------------------------------------------------------------------
Mean............................................................            0.89            1.78            2.68
90th percentile.................................................            2.25            4.50            6.76

[[Page 21391]]

 
Max.............................................................            6.67           13.33           20.00
----------------------------------------------------------------------------------------------------------------
                          Assume payback will vary based on assigned points per measure
----------------------------------------------------------------------------------------------------------------
Estimate of percent payback required such that SNFs not                      63%             66%             69%
 receiving the HEA would not experience a decrease in their
 value-based incentive payment amount *.........................
Amount to SNFs receiving HEA ($MM)..............................          $ 23.5          $ 27.6          $ 35.6
----------------------------------------------------------------------------------------------------------------
Notes:
* Relative to no HEA in the Program and maintaining a payback percentage of 60 percent.

    Because we are proposing to assign a point value of 2 for each 
measure in the Program and based on this analysis, we propose that the 
payback percentage would vary by program year to account for the 
application of the HEA such that SNFs that do receive the HEA would not 
experience a decrease in their value-based incentive payment amount, to 
the greatest extent possible, relative to no HEA in the Program and 
maintaining a payback percentage of 60 percent. Utilizing a variable 
approach ensures a very limited number of SNFs (if any) that do not 
receive HEA bonus points will experience a downward payment adjustment. 
For a given program year, we propose to calculate the final payback 
percentage using the following steps. First, we would calculate SNF 
value-based incentive payment amounts with a payback percentage of 60 
percent and without the application of the proposed HEA. Second, we 
would identify which SNFs receive the HEA and which do not based on 
their proportion of residents with DES and individual measure 
performance. Third, while maintaining the value-based incentive payment 
amounts calculated in the first step for those SNFs that do not receive 
the HEA, we would calculate the payback percentage needed to apply the 
HEA as described in section VII.E.4.d. of this proposed rule. As shown 
in Table 25, through our analysis, we estimate that assigning 2 points 
per measure would require an increase in the 60 percent payback 
percentage of 6.02 percentage points for the FY 2027 program year and 
5.40 percentage points for the FY 2028 program year. These are 
estimates and we would expect some variation that could be the result 
of SNFs with high proportions of residents with DES significantly 
changing their performance, changes in Medicaid eligibility 
requirements such that the proportions of residents with DES changes, 
changes to the Program such as adding additional measures which could 
add additional points available for the HEA, and other possible 
factors. For the last factor, increasing the points available could 
result in an increased payback percentage beyond the 70 percent 
maximum; however, we intend to adjust the number of points available 
through the rulemaking process if we add measures to the Program. With 
our current proposal of assigning a point value of 2 for each measure, 
we do not anticipate that any factors would result in an increase in 
payback beyond the 70 percent maximum. However, we will continue to 
monitor the data closely and intend to make further proposals if 
necessary in future rulemaking. Thus, as shown in Table 25, a variable 
payback percentage would allow all SNFs that receive the HEA to also 
receive increased value-based incentive payment amounts, and would also 
mean that SNFs that do receive the HEA would not experience a decrease 
in their value-based incentive payment amount, to the greatest extent 
possible, relative to no HEA in the Program and maintaining a payback 
percentage of 60 percent.
    We also explored setting a fixed payback percentage of 65 percent. 
This would mean that despite assigning higher point values for each 
measure, the resulting value-based incentive payment amounts would be 
capped to ensure the payback percentage would not exceed 65 percent. 
This would ensure that the payback percentage is below the 70 percent 
maximum. However, as shown in Table 25, including a 65 percentage 
payback would result in some SNFs, including SNFs that care for the 
highest quintile of residents with DES and almost one-third of rural 
SNFs, receiving reduced value-based incentive payment amounts compared 
to the absence of the HEA in the Program. This would be a significant 
negative consequence of this proposal, and our proposal is structured 
to avoid this outcome. We do not want SNFs that provide high quality 
care and that serve large proportions of residents who are underserved 
to be disadvantaged by this HEA.

Table 25--Estimated Differences for the FY 2027 and 2028 Program Years Between a Variable Payback Percentage and
                             a Fixed Payback Percentage Based on FY 2018-2021 Data *
----------------------------------------------------------------------------------------------------------------
                                                          FY 2027 Program                 FY 2028 Program
                                                 ---------------------------------------------------------------
                                                    Variable **        Fixed        Variable **        Fixed
----------------------------------------------------------------------------------------------------------------
Payback percentage..............................          66.02%             65%          65.40%             65%
----------------------------------------------------------------------------------------------------------------
                                           # (%) SNFs *** among . . .
----------------------------------------------------------------------------------------------------------------
All SNFs........................................          0 (0%)     5,233 (38%)          0 (0%)     4,105 (29%)
Rural SNFs......................................          0 (0%)     1,146 (32%)          0 (0%)       853 (23%)
SNFs that care for highest quintile of residents          0 (0%)       372 (14%)          0 (0%)       409 (15%)
 with DES.......................................
----------------------------------------------------------------------------------------------------------------

[[Page 21392]]

 
                      Mean value-based incentive payment amount change per SNF among . . .
----------------------------------------------------------------------------------------------------------------
All SNFs........................................          $2,162          $1,796          $1,901          $1,759
SNFs that are worse off ***.....................               0           (366)               0           (162)
SNFs that are better off ***....................           2,771           3,136           2,433           2,552
Rural SNFs......................................             969             808             940             877
SNFs that care for highest quintile of residents           5,997           5,691           4,949           4,846
 with DES.......................................
----------------------------------------------------------------------------------------------------------------
                                      Value-based incentive payment amounts
----------------------------------------------------------------------------------------------------------------
Amount of value-based incentive payments with             324.18          319.17          323.23          321.24
 HEA ($MM)......................................
Amount of value-based incentive payments without          294.62          294.62          296.53          296.53
 HEA (60% of withhold) ($MM)....................
Amount of increase due to HEA ($MM).............           29.56           24.55           26.70           24.71
----------------------------------------------------------------------------------------------------------------
Notes:
* Based on assigning a point value of 2 for each measure in which the SNF is a top tier performing SNF.
** Actual payback percentage may change from what was modeled based on final Program data.
*** Payment changes, ``worse off'', and ``better off'' all compare to the absence of the HEA in the Program and
  a payback percentage of 60 percent.

    We welcome public comment on this proposal to adopt a variable 
payback percentage. We are also proposing to amend our regulations at 
Sec.  413.338(c)(2)(i) to update this change to the payback percentage 
for FY 2027 and subsequent fiscal years.
    In developing this HEA proposal, we considered approaches other 
than providing HEA bonus points to top tier performing SNFs with a high 
proportion of SNF residents with DES that could be implemented in the 
SNF VBP Program. More specifically, we considered the addition of risk 
adjustment to the payment methodology, peer grouping, or providing an 
opportunity to earn additional improvement points. First, we considered 
risk adjusting the measures used in the SNF VBP program. Currently, 
most measures in the SNF VBP Program are risk adjusted for the clinical 
characteristics of the resident that are included in the calculation of 
the measure. We do not risk adjust for social risk factors. Although it 
would require us to respecify the measures and then revisit the pre-
rulemaking process for each measure, it is an operationally feasible 
approach. However, there is a significant concern around adding 
additional risk adjustment to the measures in the Program to account 
for social risk factors. Although additional risk adjustment can help 
account for factors outside of a SNF's control, such as social risk 
factors like socioeconomic status,\341\ it can also have potential 
unintended consequences. For instance, in a 2021 Report to Congress on 
Medicare and the Health Care Delivery System, the Medicare Payment 
Advisory Commission (MedPAC) recommended against adjusting SNF VBP 
measures results for social risk factors, stating that those types of 
adjustments can mask disparities.\342\ This would mean that disparities 
that currently exist would be more challenging to identify in the data, 
and thus harder for providers or the Program to eliminate. 
Additionally, in an analysis conducted by ASPE, it did not appear that 
additional risk adjustment would significantly impact SNF performance 
in the Program.\343\ Thus, we decided against incorporating additional 
risk adjustment into the SNF VBP Program at this time.
---------------------------------------------------------------------------

    \341\ https://mmshub.cms.gov/sites/default/files/Risk-Adjustment-in-Quality-Measurement.pdf.
    \342\ MedPAC, 2021 https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/jun21_medpac_report_to_congress_sec.pdf.
    \343\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. Second 
Report to Congress on Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program. 2020. https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------

    Second, we considered adding a peer grouping component to our 
scoring methodology, under which we would divide SNFs into groups based 
on the proportion of residents with DES that a SNF serves. With this 
peer grouping, different performance standards would then be set for 
each group, and thus payment adjustments would be made based on the 
group or strata in which a SNF falls.\344\ However, ASPE noted in their 
second report to congress on Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program that although they support 
stratifying quality measures by DES to identify disparities, they had 
concerns that peer grouping could risk setting different standards of 
care for SNFs caring for underserved populations.\345\
---------------------------------------------------------------------------

    \344\ Chen, A, Ghosh, A, Gwynn, KB, Newby, C, Henry, TL, Pearce, 
J, Fleurant, M, Schmidt, S, Bracey, J, & Jacobs, EA (2022). Society 
of General Internal Medicine Position Statement on Social Risk and 
Equity in Medicare's Mandatory Value-Based Payment Programs. Journal 
of General Internal Medicine, 37(12), 3178-3187. https://doi.org/10.1007/s11606-022-07698-9.
    \345\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. Second 
Report to Congress on Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program. 2020. https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------

    Finally, we considered an approach of adding additional improvement 
points to the Program. This could be achieved by either providing bonus 
points to SNFs for measures in which they had significant improvement 
or by increasing the points available for improvement from 9 points to 
some higher quantity, such as 15 points. It is important that even 
poorer performing SNFs be provided incentives to improve as all 
residents should have the opportunity to receive high quality care, and 
currently lower performers have the greatest opportunity for 
improvement. Since SNFs that care for higher proportions of SNF 
residents with DES tend to have lower SNF Performance Scores compared 
to SNFs that do not care for higher proportions of SNF residents with 
DES, this Program adjustment could address health equity by providing 
lower performing SNFs that care for higher proportions of SNF residents 
with DES additional

[[Page 21393]]

incentives to improve the care they provide. However, we had concerns 
with this approach. First, this approach is not focused specifically on 
populations that are underserved, and it is unclear whether the 
additional improvement points available would provide sufficient 
incentives for SNFs that care for higher proportions of SNF residents 
with DES to invest the limited resources they have to make the changes 
necessary to benefit from it. We were also concerned that this change 
could primarily incentivize poorer performing SNFs that do not care for 
a higher proportion of SNF residents with DES. Although we aim to 
incentivize improvement in care for all SNFs, this alternative approach 
has a significant risk of not meeting the goals of a health equity-
focused adjustment in the Program. Therefore, in considering how to 
modify the existing SNF VBP Program to advance health equity, we 
believe that rather than utilizing risk adjustment, peer grouping or 
adjusting the improvement point allocation process, it would be more 
appropriate to adopt an approach that rewards overall high-quality 
performance and incentivizes health equity.
    In conclusion, we believe the HEA proposal would allow us to 
appropriately measure performance by rewarding SNFs that overcome the 
challenges of caring for higher proportions of SNF residents with DES 
and to incentivize those who have not achieved such high-quality care 
to work towards improvement. As the Program greatly expands beyond one 
measure, we believe this HEA will support high-quality care for all 
populations and recognize top tier performing SNFs serving residents 
with DES. We seek comment on all aspects of the proposed methodology. 
In particular, we seek comment on the following:
     Using the proportion of SNF residents with DES as a 
measure of the proportion of residents who are underserved.
     The requirement that a SNF be in the top third of 
performance for a measure to receive any points for the measure 
performance scaler.
     Assigning a point value of 2 for each measure as opposed 
to a higher point value such as 3.
     Using a logistic exchange function based off the 
proportion of SNF residents with DES to calculate the underserved 
multiplier.
     The requirement that a SNF's proportion of residents with 
DES be at least 20 percent for a SNF to be eligible for HEA bonus 
points.
     Increasing the payback percentage and allowing for it to 
vary such that SNFs that do receive the HEA would not experience a 
decrease in their value-based incentive payment amounts, to the 
greatest extent possible, relative to no HEA in the Program and 
maintaining a payback percentage of 60 percent.
    Given that the proposed approach, if finalized, would be the 
initial implementation of a health equity adjustment under the SNF VBP 
Program, we note our intent to monitor the impact of the adjustment to 
ensure it achieves the goal of rewarding SNFs for high-quality 
performance while caring for higher proportions of SNF residents with 
DES. As necessary, we would consider modifications to the design of the 
HEA through future rulemaking. We invite public comment on our proposal 
to adopt the HEA proposal beginning with the FY 2027 program year.
5. Health Equity Approaches Under Consideration for Future Program 
Years: Request for Information (RFI)
    As described in section VII.E.4. of this proposed rule, we are 
committed to achieving equity in health outcomes for residents by 
promoting SNF accountability for health disparities, supporting SNFs' 
quality improvement activities to reduce these disparities, and 
incentivizing better care for all residents. The proposed Health Equity 
Adjustment, as described previously, would revise the SNF VBP scoring 
methodology to reward SNFs that provide high quality care to residents 
with DES and create an incentive for all SNFs to treat residents with 
DES. We also aim to incentivize the achievement of health equity in the 
SNF VBP Program in other ways, including focusing specifically on 
reducing disparities to ensure we are incentivizing improving care for 
all populations, including residents who may be underserved. In order 
to do so, we are seeking comments on possible health equity advancement 
approaches to incorporate into the Program in future program years that 
could supplement the proposed Health Equity Adjustment described in 
section VII.E.4 of this proposed rule. We are also seeking input on 
potential ways to assess improvements in health equity in SNFs. As is 
the case across healthcare settings, significant disparities persist in 
the skilled nursing environment.\346\ \347\ \348\ \349\ The goal of 
explicitly incorporating health equity-focused components into the 
Program is to both measure and incentivize equitable care in SNFs. By 
doing so, we not only aim to encourage SNFs to focus on achieving 
equity for all residents, but also to afford individuals and families 
the opportunity to make more informed decisions about their healthcare.
---------------------------------------------------------------------------

    \346\ Li, Y, Glance, LG, Yin, J, & Mukamel, DB (2011). Racial 
Disparities in Rehospitalization Among Medicare Patients in Skilled 
Nursing Facilities. American Journal of Public Health, 101(5), 875-
882. https://doi.org/10.2105/AJPH.2010.300055.
    \347\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \348\ Rivera-Hernandez, M, Rahman, M, Mukamel, D, Mor, V, & 
Trivedi, A (2019). Quality of Post-Acute Care in Skilled Nursing 
Facilities That Disproportionately Serve Black and Hispanic 
Patients. The Journals of Gerontology. Series A, Biological Sciences 
and Medical Sciences, 74(5). https://doi.org/10.1093/gerona/gly089.
    \349\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
---------------------------------------------------------------------------

    This RFI consists of four main sections. The first section requests 
input on resident-level demographic and social risk indicators, as well 
as geographic-level indices that could be used to assess health equity 
gaps. The second section requests input on possible health equity 
advancement approaches that could be added to the Program and describes 
questions that should be considered for each. The third section 
requests input on other approaches that could be considered for 
inclusion in the SNF VBP Program in conjunction with the approaches 
described in the second section. Finally, the fourth section requests 
input on adopting domains that could incorporate health equity.
a. Resident-Level Indicators and Geographic-Level Indices To Assess 
Disparities in Healthcare Quality
    To identify SNFs that care for residents who are underserved and 
determine their performance among these populations, we need to select 
an appropriate indicator of such. Identifying and prioritizing social 
risk or demographic variables to consider for measuring equity 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 or quality of standardized data. Each 
source of data has advantages and disadvantages in identifying 
populations to assess the presence of underlying disparities. Income-
based indicators are a frequently used measure for assessing 
disparities,\350\ but other

[[Page 21394]]

social risk indicators can also provide important insights. As 
described in section VII.E.4. of this proposed rule, we are proposing 
to utilize dual eligibility status (DES) to measure the underserved 
population in SNFs, as this data is readily available and DES as a 
metric has been used extensively to study the SNF population.\351\ 
\352\ However, as additional data and research becomes available we may 
be able to utilize other social risk factors to define the underserved 
population. We refer readers to the ASPE Report to Congress on Social 
Risk Factors and Performance Under Medicare's Value-Based Purchasing 
Programs for additional indicators we could consider for use in the 
Program, including the LIS Program, ADI, and others.\353\ We invite 
comment on which demographic variables, social risk indicators, or 
combination of indicators would be most appropriate for assessing 
disparities and measuring improvements in health equity in the SNF VBP 
Program for the health equity approaches described in this RFI.
---------------------------------------------------------------------------

    \350\ 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.
    \351\ Rahman, M, Grabowski, DC, Gozalo, PL, Thomas, KS, & Mor, V 
(2014). Are Dual Eligibles Admitted to Poorer Quality Skilled 
Nursing Facilities? Health Services Research, 49(3), 798-817. 
https://doi.org/10.1111/1475-6773.12142.
    \352\ Zuckerman, RB, Wu, S, Chen, LM, Joynt Maddox, KE, 
Sheingold, SH, & Epstein, AM (2019). The Five-Star Skilled Nursing 
Facility Rating System and Care of Disadvantaged Populations. 
Journal of the American Geriatrics Society, 67(1), 108-114. https://doi.org/10.1111/jgs.15629.
    \353\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. First Report 
to Congress on Social Risk Factors and Performance in Medicare's 
Value-Based Purchasing Program. 2016. https://aspe.hhs.gov/sites/default/files/migrated_legacy_files/171041/ASPESESRTCfull.pdf.
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b. Approaches To Assessing Health Equity Advancement in the SNF VBP 
Program
    CMS is interested in developing approaches that would incentivize 
the advancement of health equity for all SNFs, focusing on improving 
care for all residents, including those who may currently face 
disparities in their care. Such an approach would aim to include as 
many SNFs as possible and would not be restricted to those serving 20 
percent or more of residents with DES like the Health Equity Adjustment 
proposed in section VII.E.4. of this proposed rule. There are many 
different ways to add a health equity-focused component or adjustment 
to the Program to meet these objectives. In the FY 2023 proposed rule 
(87 FR 22789), we requested commenters' views on which adjustments 
would be most effective for the SNF VBP Program to account for any 
equity gaps that we may observe in the SNF setting. Although many 
commenters were supportive of incorporating health equity-focused 
adjustments into the Program, there was no clear consensus on the type 
of adjustment that would be most effective. In this proposed rule, we 
are requesting additional comments on potential approaches to assessing 
health equity advancement in the Program. We have outlined approaches 
to assess underlying equity gaps or designed to promote health equity, 
which may be considered for use in the Program and grouped them into 
three broad categories for assessment: applying points to current 
measures, equity-focused measures, and composite measures. The 
remainder of this section discusses these categories and relevant 
questions to consider for each. We also highlight two methods used for 
calculating disparities.
    We identified four key considerations that CMS should consider when 
employing quality measurement as a tool to address health disparities 
and advance health equity. When considering which equity-focused 
measures could be prioritized for development for SNF VBP, we examined 
past reports that assess such measures and encourage commenters to 
review each category against the following considerations:\354\ \355\
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    \354\ Office of the Assistant Secretary for Planning and 
Evaluation, U.S. Department of Health & Human Services. Second 
Report to Congress on Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program. 2020. https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
    \355\ RAND Health Care. 2021. Developing Health Equity Measures. 
Washington, DC: US Department of Health and Human Services, Office 
of the Assistant Secretary for Planning and Evaluation, and RAND 
Health Care.
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     To what extent does the approach support consumer choice? 
It is essential that quality measures reflect consumer needs and allow 
consumers to make informed choices about their care.\356\ \357\ In the 
Program, measure data is available on the Provider Data Catalog 
website. Having access to and understanding this data would empower 
consumers with more information in selecting their optimal SNF, 
including one that demonstrates greater performance in advancing 
equity.
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    \356\ Heenan, MA, Randall, GE & Evans, JM (2022). Selecting 
Performance Indicators and Targets in Health Care: An International 
Scoping Review and Standardized Process Framework. Risk Management 
and Healthcare Policy, 15, 747-764. https://doi.org/10.2147/RMHP.S357561.
    \357\ Meyer, GS, Nelson, EC, Pryor, DB, James, B, Swensen, SJ, 
Kaplan, GS, Weissberg, JI, Bisognano, M, Yates, GR, & Hunt, GC 
(2012). More quality measures versus measuring what matters: A call 
for balance and parsimony. BMJ Quality & Safety, 21(11), 964-968. 
https://doi.org/10.1136/bmjqs-2012-001081.
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     How long would it take to include this approach in the 
program? Some approaches may take considerably longer than others to 
include in the Program. For instance, we intend to consult the CMS 
appointed consensus-based entity for any new measures we propose to 
ensure we have appropriate feedback, which would add additional time to 
their development. Although we do not want this time to deter 
interested parties from recommending their inclusion in the program, we 
are interested in understanding commenters' prioritization of measures 
as it relates to the amount of time they may take to implement when 
deciding on the best approach for the Program.
     Is this approach aligned with other Medicare quality 
reporting and VBP programs? Implementing quality initiatives requires 
time and resources.\358\ It is one of our top priorities to ensure 
alignment between quality programs to limit the burden of quality 
reporting and implementation. Thus, it is important for us to consider 
in developing a health equity component, if and how other programs are 
incorporating health equity to align and standardize measures wherever 
possible.
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    \358\ Blanchfield, BB, Demehin, AA, Cummings, CT, Ferris, TG, & 
Meyer, GS (2018). The Cost of Quality: An Academic Health Center's 
Annual Costs for Its Quality and Patient Safety Infrastructure. 
Joint Commission Journal on Quality and Patient Safety, 44(10), 583-
589. https://doi.org/10.1016/j.jcjq.2018.03.012.
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     What is the impact on populations that are underserved or 
the SNFs that serve these populations? Although the goal of a health 
equity-focused adjustment to the Program would be to decrease 
disparities and incentivize high-quality care for all populations 
including those who are underserved, we also want to create appropriate 
guardrails that protect SNFs against potential unintended consequences. 
It is important for us to understand if any proposed approach may 
create potential negative consequences for residents who are 
underserved or the SNFs that treat these individuals and any steps we 
can take to mitigate that.
(1) Applying Points to Current Measures To Assess Health Equity
    The first category of health equity advancement approaches we are 
requesting comments on are mechanisms that apply points to current 
measures to assess health equity, rewarding SNFs based on the extent to 
which they provide equitable care. This category affords each SNF the 
ability to

[[Page 21395]]

score additional points for all measures where they demonstrate a high 
level of equity or a reduction in disparities over time. An approach 
that applies points to current measures to assess health equity could 
include, but is not limited to, the following:
     Points applied to one, some, or all measures for SNFs that 
achieve higher health equity performance on those measures. This would 
include measuring a SNF's performance on each measure for residents who 
are undeserved and comparing that to the same SNF's performance among 
all other residents on the same measures effectively assessing health 
equity gaps. This approach would utilize a Within-Facility Disparity 
method for assessing disparities, as described in more detail later in 
this section of this proposed rule.
     Points applied to one, some, or all measures for SNFs that 
have better performance among residents who are underserved. This would 
include only measuring performance among residents who are underserved 
and comparing that performance across all SNFs. This approach would 
utilize an Across-Facility Disparity method for assessing disparities, 
as described in more detail later in this section of this proposed 
rule.
     Points applied to one, some, or all measures based on a 
weighted average of each SNF's performance among resident groups with 
the worst and best outcomes for each measure. We could define resident 
groups by any social risk indicator, for example DES. This approach 
measures performance among all residents in the SNF and places greater 
weight on the performance of the worst performing group, with the goal 
of raising the quality floor at every SNF.
    Note, any social risk indicator could be used to assess health 
equity gaps. We welcome comments on any approach in this section or any 
other approach that applies additional points to current measures to 
assess health equity that should be considered for inclusion in the SNF 
VBP Program.
(2) New Measure Approach
    The second category of health equity advancement approaches we are 
requesting comments on is a new health equity-focused measure, which 
would be included as one of the 10 allowable measures in the Program. 
This category includes the development of a new measure that assesses 
health equity and could include a structural, process, or outcome 
measure. A health equity-focused measure would be included as one of 
the measures in the program and thus would be included in the scoring 
calculations like other measures. A health equity-focused measure could 
include, but is not limited to, the following:
     A structural measure. For example, a facility commitment 
to health equity measure, in which SNFs are assessed on factors like 
leadership engagement, data collection, and improvement activities that 
support addressing disparities in quality outcomes. This measure could 
be similar to the ``Hospital Commitment to Health Equity'' measure that 
was finalized in the FY 2023 Inpatient Prospective Payment System/Long 
Term Care Hospital Prospective Payment System final rule (87 FR 48785).
     A process measure. For example, a drivers of health 
measure, in which residents are screened for specific health-related 
social needs (HRSNs) to ensure a successful transition home, like 
transportation or food insecurity. This measure could be similar to the 
``Screening for Social Drivers of Health'' measure that was finalized 
in the FY 2023 Inpatient Prospective Payment System/Long Term Care 
Hospital Prospective Payment System final rule (87 FR 48785).
     An outcome measure. For example, a measure that is 
calculated using data stratified for specific populations that are 
underserved, such as residents with DES.
    Note each of these possible measures are only suggestions for what 
might be included in the Program. We welcome comments on any measures 
that should be considered for inclusion in the SNF VBP Program 
including the ones described in this section and what data sources 
should be considered to construct those measures.
(3) Composite Measure Approach
    The third category of health equity advancement approaches we are 
requesting comments on is the development and implementation of a new 
health equity-focused composite measure. An equity-focused composite 
measure would be included as one of the 10 allowable measures in the 
program and thus would be included in the scoring calculations like 
other measures. Generally, a composite measure can provide a simplified 
view of a rather complex topic by combining multiple factors into one 
measure. A composite measure could include, but is not limited to, the 
following:
     A composite of all measure scores for residents who are 
underserved to compare across all SNFs. This could utilize an Across-
Facility Disparity method for assessing disparities, as described in 
more detail later in this section of this proposed rule.
     A composite of the health disparity performance within 
each SNF for some or all measures. This approach could utilize a 
Within-Facility Disparity method for assessing disparities, as 
described in more detail later in this section of this proposed rule.
    Note any social risk indicator could be used to assess health 
equity gaps. We welcome comments on each of the composite measures 
described in this section. We also welcome comments on the specific 
factors or measures that should be included in a composite measure.
    In considering whether to include in the Program any of the 
approaches described in this section, points applied to current 
measures based on equity, new measures, or composite measures, we 
encourage commenters to consider the following questions:
     To what extent do these approaches support 
consumer choice? What approaches described in this section best support 
consumer choice? Would any approach be easier to interpret than others? 
Would any of the approaches described in this section provide 
information that other approaches would not that would aid consumer 
choice? Are there other factors we should consider in developing any of 
the approaches described in this section that are easiest for consumers 
to utilize and understand? How should any of the approaches described 
in this section be displayed and shared with consumers to facilitate 
understanding of how to interpret the approach?
     How long would it take to include this approach 
in the program? If some approaches would take longer to implement, 
should they still be considered for inclusion in the Program or should 
a different approach be prioritized? For instance, a measure that is 
already being utilized by another program could be implemented sooner 
than a measure that still needs to be developed. Should any of the 
approaches described in this section be considered regardless of the 
time it would take to include the approach in the Program?
     Is this approach aligned with other Medicare 
quality reporting and VBP programs? Are there similar approaches to 
those described in this section that are aligned with other programs 
that we should consider for SNF VBP? If any of the approaches described 
in this section are not aligned with other programs, should they still 
be considered for inclusion in the Program? If these approaches are 
only aligned somewhat with other programs, should they still be 
considered for inclusion in the Program? Several other programs,

[[Page 21396]]

including the End-Stage Renal Disease Quality Incentive Program, the 
Merit-based Incentive Payment System, the Hospital Inpatient Quality 
Reporting Program, the Inpatient Psychiatric Facility Quality Reporting 
Program, and the PPS-Exempt Cancer Hospital Quality Reporting Program 
also submitted equity-focused measures to the 2022 MUC List that could 
be considered for the Program.\359\ Further, we are in the process of 
developing a Hospital Equity Index. Should any of these measures be 
considered for SNF VBP?
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    \359\ https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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     What is the impact on populations that are 
underserved or the SNFs that serve these populations? Are there any 
potential impacts, including negative or positive unintended 
consequences, that could occur when implementing the approaches 
described in this section? Are there steps we should take to mitigate 
any potential negative unintended consequences? How can we ensure these 
approaches provide a strong enough incentive to improve care for all 
populations by identifying areas of inequities? We are interested in 
all perspectives and particularly of those living in and serving 
underserved communities.
(4) Disparity Method Approaches
    Many of the approaches described previously in this section of this 
proposed rule would rely on calculating disparities. There are several 
different conceptual approaches to calculating disparities to assess 
health equity gaps. Currently in the acute care setting, two 
complementary approaches are used to confidentially provide disparity 
information to hospitals for a subset of existing measures. The first 
approach, referred to as the Within-Facility 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 Across-Facility Disparity 
method, provides performance on measures for only the subgroup of 
patients with a particular social risk factor. These approaches can be 
used by a SNF 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 Across-
Facility Disparity method indicates that a SNF underperformed (when 
compared to other SNFs on average) for patients with a given social 
risk indicator, which would signal the need to improve care for this 
population. However, if the SNF also underperformed for patients 
without that social risk indicator (the Within-Facility Disparity 
method, as described earlier in this section), the measured difference, 
or disparity in care, could be negligible even though performance for 
the group that particular social risk factor 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 at https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    We request comments on whether similar approaches to the two 
discussed in the previous paragraph could be used for calculating 
disparities to assess health equity in a SNF. These calculations would 
then be used for scoring purposes for each of the approaches described 
previously in this section, either to calculate a SNF's performance on 
a new measure or a composite measure, or to determine the amount of 
points that should be applied to current measures to assess heath 
equity.
c. Other Approaches To Assessing Health Equity Advancement in the SNF 
VBP Program
    There are also many other health equity approaches that could be 
considered for inclusion in the Program. In particular, we explored 
risk adjustment, stratification/peer grouping, and adding improvement 
points when developing the proposed Health Equity Adjustment in section 
VII.E.4. We have specific concerns when applying each of these 
approaches to the SNF VBP Program independently; however, we are 
requesting comment on the potential of incorporating these approaches 
in conjunction with the approaches outlined previously in this section 
of this proposed rule.
d. The Development of Domains and Domain Weighting for Inclusion in the 
SNF VBP Program
    As we expand the number of measures on which we assess performance 
under the SNF VBP, we are considering whether we should group the 
measures into measure domains. Creating domains would align SNF VBP 
with other CMS programs such as the Hospital Value-Based Purchasing 
(VBP) Program. The HVBP Program currently groups its measures into four 
domains that are defined based on measure type, and then weights the 
sum of a hospital's performance score on each measure in the domain 
such that the domain is weighted at 25 percent of the hospital's total 
performance score. Although the HVBP Program uses four domains, each 
with a 25 percent weight, we could consider for the SNF VBP grouping 
measures into a different number of domains and then weighting each 
domain by different amounts.
    We request comments on whether we should consider proposing the 
addition of quality domains for future program years. We also request 
comments on if those domains should be utilized to advance health 
equity in the Program.

F. Proposed Update to the Extraordinary Circumstances Exception Policy 
Regulation Text

    In the FY 2019 SNF PPS final rule (83 FR 39280 through 39281), we 
adopted an Extraordinary Circumstances Exception (ECE) policy for the 
SNF VBP Program. We have also codified this policy in our regulations 
at Sec.  413.338(d)(4).
    To accommodate the SNF VBP Program's expansion to additional 
quality measures and apply the ECE policy to those measures, we are 
proposing to update our regulations at Sec.  413.338(d)(4)(v) to remove 
the specific reference to the SNF Readmission Measure. The proposed new 
language would specify, in part, that CMS would calculate a SNF 
performance score for a program year that does not include the SNF's 
``performance during the calendar months affected by the extraordinary 
circumstance.''
    We invite public comment on this proposal.

G. Proposal to Update the Validation Processes for the SNF VBP Program

1. Background
    Section 1888(h)(12) of the Act requires the Secretary to apply a 
validation process to SNF VBP Program measures and ``the data submitted 
under [section 1888(e)(6)] [. . .] as appropriate[. . .].''

[[Page 21397]]

    We have finalized a validation approach for the SNFRM and codified 
that approach at section 413.338(j) of our regulations. In the FY 2023 
SNF PPS proposed rule, we requested comment on the validation of 
additional SNF measures and assessment data (87 FR 22788 through 
22789). In the FY 2023 SNF PPS final rule, we summarized commenters' 
views and stated that we would take this feedback into consideration as 
we develop our policies for future rulemaking (87 FR 47595 through 
47596).
    Beginning with the FY 2026 program year, the SNFRM will no longer 
be the only measure in the SNF VBP. We have adopted a second claims-
based measure, SNF HAI, beginning with that program year and have 
proposed to replace the SNFRM with another claims-based measure, the 
SNF WS PPR measure, beginning with the FY 2028 program year. We have 
adopted the DTC PAC SNF measure beginning with the FY 2027 program year 
and we are proposing to adopt a fourth claims-based measure, Long Stay 
Hospitalization, beginning with that program year. We have adopted the 
total nurse staffing measure, which is calculated using Payroll Based 
Journal (PBJ) data, beginning with the FY 2026 program year and are 
proposing to adopt the nursing staff turnover measure, which is also 
calculated using PBJ data, beginning with the FY 2026 program year. We 
are also proposing to adopt the DC Function and the Falls with Major 
Injury (Long-Stay) measures calculated using Minimum Data Set (MDS) 
data beginning with the FY 2027 program year. The addition of measures 
calculated from these data sources has prompted us to consider the most 
feasible way to expand our validation program under the SNF VBP 
Program.
    After considering our existing validation process and the data 
sources for the new measures, and for the reasons discussed more fully 
below, we are proposing to: (1) apply the validation process we have 
adopted for the SNFRM to all claims-based measures; (2) adopt a 
validation process that would apply to SNF VBP measures for which the 
data source is PBJ data; and (3) adopt a validation process that would 
apply to SNF VBP measures for which the data source is MDS data. We 
believe these proposals would ensure that the data we use to calculate 
the SNF VBP measures are accurate for quality measurement purposes.
    We note that these proposals would apply only to the SNF VBP 
Program, and we intend to propose a validation process that would apply 
to the data SNFs report under the SNF QRP, in future rulemaking.
2. Proposal To Apply the Existing Validation Process for the SNFRM to 
All Claims-Based Measures Reported in the SNF VBP Program
    Beginning with the FY 2026 program year, we would need to validate 
the SNF HAI measure and beginning with the FY 2027 program year, we 
would need to validate the Long Stay Hospitalization and DTC PAC SNF 
measures to meet our statutory requirements. Beginning with the FY 2028 
program year, we would also need to validate the SNF WS PPR measure. 
Therefore, we are proposing to expand the previously adopted SNFRM 
validation process to include all claims-based measures, including the 
SNF HAI, Long Stay Hospitalization, DTC PAC SNF, and SNF WS PPR 
measures, as well as any other claims-based measures we could adopt for 
the SNF VBP in the future.
    The SNF HAI measure is calculated using Medicare SNF FFS claims 
data and Medicare inpatient hospital claims data. As discussed in the 
FY 2023 SNF PPS final rule (87 FR 47590), information reported through 
claims are validated for accuracy by Medicare Administrative 
Contractors (MACs) who use software to determine whether billed 
services are medically necessary and should be covered by Medicare, 
review claims to identify any ambiguities or irregularities, and use a 
quality assurance process to help ensure quality and consistency in 
claim review and processing. They conduct prepayment and post-payment 
audits of Medicare claims, using both random selection and targeted 
reviews based on analyses of claims data.
    Beginning with the FY 2027 program year, we are proposing to adopt 
the Long Stay Hospitalization measure in the SNF VBP Program. This 
measure utilizes SNF FFS claims and inpatient hospital claims data. We 
believe that adopting the existing MAC's process of validating claims 
for medical necessity through targeted and random audits, as detailed 
in the prior paragraph, would satisfy our statutory requirement to 
adopt a validation process for the Long Stay Hospitalization measure 
for the SNF VBP Program.
    The DTC PAC SNF measure also uses claims-based data, including data 
from the ``Patient Discharge Status Code''. We refer readers to the FY 
2023 SNF PPS final rule (87 FR 47577 through 47578) for additional 
discussion of the data source for the DTC PAC SNF measure. We also 
refer readers to the FY 2017 SNF PPS final rule (81 FR 52021 through 
52029) for a thorough analysis on the accuracy of utilizing the 
discharge status field. We believe that adopting the existing MAC's 
process for validating the claims portion of the DTC PAC SNF measure 
for payment accuracy would satisfy our statutory requirement to adopt a 
validation process for the SNF VBP Program because MACs review claims 
for medical necessity, ambiguities and quality assurance through random 
and targeted reviews, as detailed in the second paragraph in this 
section.
    Beginning with the FY 2028 program year, we are proposing to 
replace the SNFRM with the SNF WS PPR. The SNFRM and SNF WS PPR utilize 
the same claims-based data sources. Therefore, the SNFRM's validation 
process based on data that are validated for accuracy by MACs as 
detailed in the second paragraph in this section, would fulfill the 
statutory requirement to adopt a validation process for the SNF WS PPR 
measure for the SNF VBP Program.
    We invite the public to comment on this proposal and also propose 
to codify it at Sec.  413.338(j).
3. Proposal To Adopt a Validation Process That Applies to SNF VBP 
Measures That Are Calculated Using PBJ Data
    Beginning with the FY 2026 program year, the Total Nurse Staffing 
measure, adopted in the FY 2023 SNF PPS final rule, and the Nursing 
Staff Turnover measure, which we are proposing to adopt in this 
proposed rule, would be calculated using PBJ data that nursing 
facilities with SNF beds are already required to report to CMS. PBJ 
data includes direct care staffing information (including agency and 
contract staff) based on payroll and other auditable data.\360\ CMS 
conducts quarterly audits aimed at verifying that the staffing hours 
submitted by facilities are aligned with the hours staff were paid to 
work over the same timeframe. The PBJ audit process requires selected 
facilities to submit documentation, that may include payroll, invoice, 
or contractual obligation data, supporting the staffing hours reported 
in the PBJ data.\361\ This

[[Page 21398]]

documentation of hours is compared against the reported PBJ staffing 
hours data and a facility whose audit identifies significant 
inaccuracies between the hours reported and the hours verified will be 
presumed to have low levels of staffing. We believe that this existing 
PBJ data audit process is sufficient to ensure that the PBJ data we use 
to calculate the Total Nurse Staffing and Nursing Staff Turnover 
measures are an accurate representation of a facility's staffing. 
Accordingly, we are proposing to adopt that process for purposes of 
validating SNF VBP measures that are calculated using PBJ data. We are 
also proposing to codify this policy at Sec.  413.338(j) in our 
regulations.
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    \360\ Centers for Medicare and Medicaid Services. (2022, October 
12). Staffing Data Submission Payroll Based Journal (PBJ). https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/staffing-data-submission-pbj.
    \361\ Centers for Medicare and Medicaid (CMS). (2018). 
Transition to Payroll-Based Journal (PBJ) Staffing Measures on the 
Nursing Home Compare tool on Medicare.gov and the Five Star Quality 
Rating System. Center for Clinical Standards and Quality/Quality, 
Safety and Oversight Group. https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/QSO18-17-NH.pdf.
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    We invite public comment on this proposal.
4. Proposal To Adopt a Validation Process That Applies to SNF VBP 
Measures That Are Calculated Using MDS Data
    In section VII.B.4. of this proposed rule, we are proposing to 
adopt two MDS measures in the SNF VBP Program, the DC Function and 
Falls with Major Injury (Long Stay) measures beginning with the FY 2027 
program year/FY 2025 performance period. The MDS is a federally 
mandated resident assessment instrument that is required to be 
completed for all residents in a Medicare or Medicaid certified nursing 
facility, and for patients whose stay is covered under SNF PPS in a 
non-critical access hospital swing bed facility. The MDS ``includes the 
resident in the assessment process, and [uses] standard protocols used 
in other settings. . .supporting the primary legislative intent that 
MDS be a tool to improve clinical assessment and supports the 
credibility of programs that rely on MDS''.\362\ There is no current 
process to verify that the MDS data submitted by providers to CMS for 
quality measure calculations is accurate for use in our SNF quality 
reporting and value-based purchasing programs. While MDS data are 
audited to ensure accurate payments, we do not believe that this audit 
process focuses sufficiently on the Program's quality measurement data 
for use in a quality reporting or value-based purchasing program. While 
the update to MDS 3.0 was designed to improve the reliability, 
accuracy, and usefulness of reporting than prior versions,\363\ we 
believe we need to validate MDS data when those data would be used for 
the purpose of a quality reporting or value-based purchasing program. 
We are proposing to adopt a new validation method that we would apply 
to the SNF VBP measures that are calculated using MDS data to meet our 
statutory requirement. This proposed method is similar to the method we 
use to validate measures reported by hospitals under the Hospital 
Inpatient Quality Reporting Program.
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    \362\ Centers for Medicare and Medicaid Services (CMS). (2023, 
March 29). Minimum Data Set (MDS) 3.0 for Nursing Homes and Swing 
Bed Providers. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqimds30.
    \363\ Centers for Medicare and Medicaid Services (CMS). (2023, 
March 29). Minimum Data Set (MDS) 3.0 for Nursing Homes and Swing 
Bed Providers. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/nursinghomequalityinits/nhqimds30.
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    We are proposing to validate the MDS data used to calculate these 
measures as follows:
     We propose to randomly select, on an annual basis, up to 
1,500 active and current SNFs, including non-critical access hospital 
swing bed facilities providing SNF-level services, that submit at least 
one MDS record in the calendar year 3 years prior to the fiscal year of 
the relevant program year or were included in the SNF VBP Program in 
the year prior to the relevant program year. For example, for the FY 
2027 SNF VBP Program, we would choose up to 1,500 SNFs that submitted 
at least one MDS record in calendar year 2024 or were participating in 
the FY 2026 SNF VBP Program/FY 2024 performance period for validation 
in FY 2025.
     We propose that the validation contractor would, for each 
quarter that applies to validation, request up to 10 randomly selected 
medical charts from each of the selected SNFs.
     We propose that the validation contractor would request 
either digital or paper copies of the randomly selected medical charts 
from each SNF selected for audit. The SNF would have 45 days from the 
date of the request (as documented on the request) to submit the 
requested records to the validation contractor. If the SNF has not 
complied within 30 days, the validation contractor would send the SNF a 
reminder to inform the SNF that it must return digital or paper copies 
of the requested medical records within 45 calendar days following the 
date of the initial validation contractor medical record request.
    We believe the process would be minimally burdensome on SNFs 
selected to submit up to 10 charts.
    We intend to propose a penalty that would apply to a SNF that 
either does not submit the requested number of charts or that we 
otherwise conclude has not achieved a certain validation threshold in 
future rulemaking. We also intend to propose in future rulemaking the 
process by which we would evaluate the submitted medical charts against 
the MDS to determine the validity of the MDS data used to calculate the 
measure results. We invite public comment on what that process could 
include.
    We invite the public to comment on our proposal to adopt the above 
validation process for MDS measures beginning with the FY 2027 program 
year.

H. SNF Value-Based Incentive Payments for FY 2024

    We refer readers to the FY 2018 SNF PPS final rule (82 FR 36616 
through 36621) for discussion of the exchange function methodology that 
we have adopted for the Program, as well as the specific form of the 
exchange function (logistic, or S-shaped curve) that we finalized, and 
the payback percentage of 60 percent of the amounts withheld from SNFs' 
Medicare payments as required by the SNF VBP Program statute.
    We also discussed the process that we undertake for reducing SNFs' 
adjusted Federal per diem rates under the Medicare SNF PPS and awarding 
value-based incentive payments in the FY 2019 SNF PPS final rule (83 FR 
39281 through 39282).
    For the FY 2024 SNF VBP Program Year, we will reduce SNFs' adjusted 
Federal per diem rates for the fiscal year by the applicable percentage 
specified under section 1888(h)(6)(B) of the Act, 2 percent, and will 
remit value-based incentive payments to each SNF based on their SNF 
Performance Score, which is calculated based on their performance on 
the Program's quality measure.

I. Public Reporting on the Provider Data Catalog Website

    Section 1888(g)(6) of the Act requires the Secretary to establish 
procedures to make SNFs' performance information on SNF VBP Program 
measures available to the public on the Nursing Home Compare website or 
a successor website, and to provide SNFs an opportunity to review and 
submit corrections to that information prior to its publication. We 
began publishing SNFs' performance information on the SNFRM in 
accordance with this directive and the statutory deadline of October 1, 
2017. In December 2020, we retired the Nursing Home Compare website and 
are now using the Provider Data Catalog website (https://data.cms.gov/provider-data/) to make quality data available to the public, including 
SNF VBP performance information.

[[Page 21399]]

    Additionally, section 1888(h)(9)(A) of the Act requires the 
Secretary to make available to the public certain information on SNFs' 
performance under the SNF VBP Program, including SNF Performance Scores 
and their ranking. Section 1888(h)(9)(B) of the Act requires the 
Secretary to post aggregate information on the Program, including the 
range of SNF Performance Scores and the number of SNFs receiving value-
based incentive payments, and the range and total amount of those 
payments.
    In the FY 2017 SNF PPS final rule (81 FR 52006 through 52009), we 
discussed the statutory requirements governing confidential feedback 
reports and public reporting of SNFs' performance information under the 
SNF VBP Program and finalized our two-phased review and correction 
process. In the FY 2018 SNF PPS final rule (82 FR 36621 through 36623), 
we finalized additional requirements for phase two of our review and 
correction process, a policy to publish SNF VBP Program performance 
information on the Nursing Home Compare or a successor website after 
SNFs have had the opportunity to review and submit corrections to that 
information. In that final rule, we also finalized the requirements to 
rank SNFs and adopted data elements that are included in the ranking to 
provide consumers and interested parties with the necessary information 
to evaluate SNF's performance under the Program. In the FY 2020 SNF PPS 
final rule (84 FR 38823 through 38825), we finalized a policy to 
suppress from public display SNF VBP performance information for low-
volume SNFs, and finalized updates to the phase one review and 
correction deadline. In the FY 2021 SNF PPS final rule (85 FR 47626 
through 47627), we finalized additional updates to the phase one review 
and correction deadline. In the FY 2022 SNF PPS final rule (86 FR 42516 
through 42517), we finalized a phase one review and correction claims 
``snapshot'' policy. In the FY 2023 SNF PPS final rule (87 FR 47591 
through 47592), we finalized updates to our data suppression policy for 
low-volume SNFs due to the addition of new measures and case and 
measure minimum policies.

IX. Civil Money Penalties: Waiver of Hearing, Automatic Reduction of 
Penalty Amount

    Section 488.436 provides a facility the option to waive its right 
to a hearing in writing and receive a 35 percent reduction in the 
amount of civil money penalties (CMPs) owed in lieu of contesting the 
enforcement action. This regulation was first adopted in a 1994 final 
rule (59 FR 56116, 56243), with minor corrections made to the 
regulation text in 1997 (62 FR 44221) and in 2011 (76 FR 15127) to 
implement section 6111 of the Affordable Care Act of 2010. Over the 
years, we have observed that most facilities who have been imposed CMPs 
do not request a hearing to appeal the survey findings of noncompliance 
on which their CMPs are based.
    In CY 2016, 81 percent of LTC facilities submitted a written waiver 
of a hearing and an additional 15 percent of facilities failed to 
submit a waiver although they did not contest the penalty and its 
basis. Only 4 percent of facilities availed themselves of the full 
hearing process. The data from CY 2018 and CY 2019 stayed fairly 
consistent with 80 percent of facilities submitting a written waiver of 
a hearing and 14 percent of facilities failing to submit the waiver nor 
contest the penalty and its basis. Only 6 percent of facilities availed 
themselves of the full hearing process. In CY 2020, 81 percent of 
facilities submitted a written waiver of the hearing, 15 percent of 
facilities did not submit a waiver nor contest the penalty and its 
basis, and only 4 percent of facilities availed themselves of the full 
hearing process. In CY 2021, 91 percent of facilities submitted a 
written waiver of the hearing, 7 percent of facilities did not submit 
the waiver nor contest the penalty and its basis, and only 2 percent of 
facilities utilized the full hearing process. Data from CY 2022 
continues this trend showing that 81 percent of LTC facilities 
submitted a written waiver of their hearing rights and 17 percent of 
facilities did not submit a waiver of appeal rights but did not contest 
the penalty nor its basis. Again, only 2 percent of facilities availed 
themselves of the full hearing process in CY2022. Therefore, based on 
our experience with LTC facilities with imposed CMPs and the input 
provided by our CMS Locations (formerly referred to as Regional 
Offices) who impose and collect CMPs, we propose to revise these 
requirements at Sec.  488.436 by creating a constructive waiver process 
that would produce the same results for less money and effort.
    Specifically, we propose to revise the current express written 
waiver process to one that seamlessly flows to a constructive waiver 
and retains the accompanying 35 percent penalty reduction. Removal of 
the facility's requirement to submit a written request to avail itself 
of this widely used option would result in lower costs for most LTC 
facilities facing CMPs and would streamline and reduce the 
administrative burden for all interested parties. We propose to amend 
the language at Sec.  488.436(a), by eliminating the requirement to 
submit a written waiver and create in its place a constructive waiver 
process that would operate by default when a timely request for a 
hearing has not been received. Facilities that wish to request a 
hearing to contest the noncompliance leading to the imposition of the 
CMP would continue to follow all applicable appeals process 
requirements, including those at Sec.  498.40, as currently referenced 
at Sec.  488.431(d).
    Specifically, we propose to revise Sec.  488.436(a) to state that a 
facility is deemed to have waived its rights to a hearing if the time 
period for requesting a hearing has expired and timely request for a 
hearing has not been received. We have observed that many facilities 
submitting a request for a waiver of hearing wait until close to the 
end of the 60-day timeframe within which a waiver must be submitted, 
thus delaying the ultimate due date of the CMP amount. Under this 
proposed process, the 35 percent reduction would be applied after the 
60-day timeframe.
    We note that we continue to have the opportunity under Sec.  
488.444, to settle CMP cases at any time prior to a final 
administrative decision for Medicare-only SNFs, State-operated 
facilities, or other facilities for which our enforcement action 
prevails, in accordance with Sec.  488.30. This provides the 
opportunity to settle a case, even if the facility's hearing right was 
not previously waived. Even if a hearing had been requested, if all 
parties can reach an agreement over deficiencies to be corrected and 
the CMP to be paid until corrections are made (for example, CMS agrees 
to lower a CMP amount based on actions the facility has taken to 
protect resident health and safety), then costly hearing procedures 
could be avoided. We believe that eliminating the current requirements 
at Sec.  488.436 for a written waiver will not negatively impact 
facilities, and as such, we especially welcome comments from the public 
addressing any potential circumstances in which facilities' needs or 
the public interest could best be met or only be met by the use of an 
express, written waiver.
    In addition to the changes to Sec.  488.436(a), we propose 
corresponding changes to Sec. Sec.  488.432 and 488.442 which currently 
reference only the written waiver process. We propose to make 
conforming changes that establish that a facility is deemed to have 
waived its rights to a hearing if the time period for requesting a 
hearing has expired, in lieu of a written waiver of appeal rights. 
Finally, we note that the current

[[Page 21400]]

requirements at Sec.  488.436(b) would remain unchanged.
    These proposed revisions were previously proposed and published in 
the July 18, 2019 proposed rule entitled, ``Medicare and Medicaid 
Programs; Requirements for Long-Term Care Facilities: Regulatory 
Provisions to Promote Efficiency, and Transparency'' (84 FR 34737, 
34751). Although on July 14, 2022, we announced an extension of the 
timeline for publication of the final rule for the 2019 proposals (see 
87 FR 42137), we are withdrawing that proposal revising Sec.  488.436 
and are re-proposing here the proposed revisions for a facility to 
waive its hearing rights in an effort to gather additional feedback 
from interested parties. While this regulatory action is administrative 
in nature, in the future, we may assess whether the 35 percent penalty 
reduction is functioning as intended to make the civil money penalties 
administrative process more efficient, or whether a lesser penalty 
reduction is warranted.

IX. Collection of Information Requirements

    Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et 
seq.), 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. For the purpose of the PRA and this section of 
the preamble, collection of information is defined under 5 CFR 
1320.3(c) of the PRA's implementing regulations.
    To fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the PRA 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.
    We are soliciting public comment (see section IX.D. of this 
proposed rule) on each of these issues for the following sections of 
this document that contain information collection requirements. 
Comments, if received, will be responded to within the subsequent final 
rule.

A. Wage Estimates

    To derive average private sector costs, we used data from the U.S. 
Bureau of Labor Statistics' (BLS') May 2021 National Occupational 
Employment and Wage Estimates for all salary estimates (http://www.bls.gov/oes/current/oes_nat.htm). In this regard, Table 26 presents 
BLS' mean hourly wage, our estimated cost of fringe benefits and other 
indirect costs (calculated at 100 percent of salary), and our adjusted 
hourly wage.

                          Table 26--National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
                                                                                      Fringe
                                                    Occupation      Mean hourly    benefits and      Adjusted
                Occupation title                       code         wage ($/hr)   other indirect  hourly wage ($/
                                                                                   costs ($/hr)         hr)
----------------------------------------------------------------------------------------------------------------
Computer Programmer.............................         15-1251           46.46           46.46           92.92
Licensed Vocational Nurse (LVN).................         29-2061           24.93           24.93           49.86
Medical Records Specialist......................         29-2072           23.23           23.23           46.46
Occupational Therapist (OT).....................         29-1122           43.02           43.02           86.04
Physical Therapist (PT).........................         29-1123           44.67           44.67           89.34
Registered Nurse (RN)...........................         29-1141           39.78           39.78           79.56
Speech Language Pathologist (SLP)...............         29-1127           41.26           41.26           82.52
----------------------------------------------------------------------------------------------------------------

    As mentioned above, we have adjusted the private sector's employee 
hourly wage estimates by a factor of 100 percent. This is necessarily a 
rough adjustment, both because fringe benefits and other indirect costs 
vary significantly across employers, and because methods of estimating 
these costs vary widely across studies. Nonetheless, we believe that 
doubling the hourly wage to estimate total cost is a reasonably 
accurate estimation method.
    Cost for Beneficiaries We believe that the cost for beneficiaries 
undertaking administrative and other tasks on their own time is a post-
tax wage of $20.71/hr.
    The Valuing Time in U.S. Department of Health and Human Services 
Regulatory Impact Analyses: Conceptual Framework and Best Practices 
\364\ identifies the approach for valuing time when individuals 
undertake activities on their own time. To derive the costs for 
beneficiaries, a measurement of the usual weekly earnings of wage and 
salary workers of $998, divided by 40 hours to calculate an hourly pre-
tax wage rate of $24.95/hr. This rate is adjusted downwards by an 
estimate of the effective tax rate for median income households of 
about 17%, resulting in the post-tax hourly wage rate of $20.71/hr. 
Unlike our private sector wage adjustments, we are not adjusting 
beneficiary wages for fringe benefits and other indirect costs since 
the individuals' activities, if any, would occur outside the scope of 
their employment.
---------------------------------------------------------------------------

    \364\ Office of the Assistant Secretary for Planning an 
Evaluation. Valuing Time in U.S. Department of Health and Human 
Services Regulatory Impact Analyses: Conceptual Framework and Best 
Practices. Final Report. June 2017. Available at https://aspe.hhs.gov/sites/default/files/migrated_legacy_files//176806/VOT.pdf.
---------------------------------------------------------------------------

B. Proposed Information Collection Requirements (ICRs)

1. ICRs Regarding the Skilled Nursing Facility Quality Reporting 
Program (SNF QRP)
    In accordance with section 1888(e)(6)(A)(i) of the Act, the 
Secretary must reduce by 2-percentage points the otherwise applicable 
annual payment update to a SNF for a fiscal year if the SNF does not 
comply with the requirements of the SNF QRP for that fiscal year.
    In section VI.C. of this proposed rule, we are proposing to modify 
one measure, adopt three new measures, and remove three measures from 
the SNF QRP. In section VI.F. of this proposed rule, we are also 
proposing to increase the data completion thresholds for the MDS items. 
We discuss these information collections below.
    As stated in section VI.C.1.a. of this rule, we are proposing to 
modify the

[[Page 21401]]

COVID-19 Vaccination Coverage Among Healthcare Personnel (HCP COVID-19 
Vaccine) measure beginning with the FY 2025 SNF QRP. While we are not 
proposing any changes to the data submission process for the HCP COVID-
19 Vaccine measure, we are proposing that for purposes of meeting FY 
2025 SNF QRP compliance, SNFs would report data on the modified measure 
beginning with reporting period of the fourth quarter of CY 2023. Under 
the proposal, SNFs would continue to report data for the HCP COVID-19 
Vaccine measure to the CDC's National Healthcare Safety Network (NHSN) 
for at least one self-selected week during each month of the reporting 
quarter. The burden associated with the HCP COVID-19 Vaccine measure is 
accounted for under OMB control number 0920-1317, entitled ``[NCEZID] 
National Healthcare Safety Network (NHSN) Coronavirus (COVID-19) 
Surveillance in Healthcare Facilities.'' Because we are not proposing 
any updates to the form, manner, and timing of data submission for this 
measure, we are not proposing any changes to the currently approved 
(active) requirements or burden estimates under control number 0920-
1317. See the FY 2022 SNF PPS final rule (86 FR 42480 through 42489) 
for a discussion of the form, manner, and timing of data submission of 
this measure.
    In this proposed rule, we are proposing to adopt three new measures 
and remove two measures from the SNF QRP. We present the burden 
associated with these proposals in the same order they were proposed in 
section VI.C. of this proposed rule.
    As stated in section VI.C.1.b. of this rule, we propose to adopt 
the Discharge Function Score (DC Function) measure beginning with the 
FY 2025 SNF QRP. This proposed assessment-based quality measure would 
be calculated using data from the minimum data set (MDS) that are 
already reported to the Medicare program for payment and quality 
reporting purposes. The burden is currently approved under OMB control 
number 0938-1140 (CMS-10387). Under this proposal, there would be no 
additional burden for SNFs since it does not require the collection of 
new or revised data elements.
    As stated in section VI.C.1.c. of this rule, we propose to remove 
the Application of Percent of Long-Term Care Hospital (LTCH) Patients 
with an Admission and Discharge Functional Assessment and a Care Plan 
that Addresses Function (Application of Functional Assessment/Care 
Plan) measure beginning with the FY 2025 SNF QRP. We believe that the 
removal of the measure would result in a decrease of 18 seconds (0.3 
min or 0.005 hr) of clinical staff time at admission beginning with the 
FY 2025 SNF QRP. We believe that the MDS item affected by the proposed 
removal of the Application of Functional Assessment/Care Plan measure 
is completed by Occupational Therapists (OT), Physical Therapists (PT), 
Registered Nurses (RN), Licensed Practical and Licensed Vocational 
Nurses (LVN), and/or Speech-Language Pathologists (SLP) depending on 
the functional goal selected. We identified the staff type per MDS item 
based on past SNF burden calculations. Our assumptions for staff type 
were based on the categories generally necessary to perform an 
assessment, however, individual SNFs determine the staffing resources 
necessary. Therefore, we averaged BLS' National Occupational Employment 
and Wage Estimates (See Table 26) for these labor types and established 
a composite cost estimate using our adjusted wage estimates. The 
composite estimate of $86.21/hr was calculated by weighting each hourly 
wage based on the following breakdown (see Table 27) regarding provider 
types most likely to collect this data: OT 45 percent at $86.04/hr; PT 
45 percent at $89.34/hr; RN 5 percent at $79.56/hr; LVN 2.5 percent at 
$49.86/hr; and SLP 2.5 percent at $82.52/hr.
    For purposes of deriving the composite wage we also estimate 
2,406,401 admission assessments from 15,471 SNFs annually.

                            Table 27--Estimated Composite Wage for the Application of Functional Assessment/Care Plan Measure
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                            Mean hourly
                                                                           wage, fringe     Percent of       Number of
                    Occupation title                        Occupation     benefits, and    assessments     assessments     Total hours    Total burden
                                                               code       other indirect     collected      collected *                         ($)
                                                                           costs ($/hr)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Occupational Therapist (OT).............................         29-1122           86.04              45     1,082,880.5           5,414         465,855
Physical Therapist (PT).................................         29-1123           89.34              45     1,082,880.5           5,414         483,723
Registered Nurse (RN)...................................         29-1141           79.56               5         120,320             602          47,863
Licensed Vocational Nurse (LVN).........................         29-2061           49.86             2.5          60,160             301          14,998
Speech Language Pathologist (SLP).......................         29-1127           82.52             2.5          60,160             301          24,822
                                                         -----------------------------------------------------------------------------------------------
    Total...............................................             n/a             n/a             100       2,406,401          12,032       1,037,261
                                                         -----------------------------------------------------------------------------------------------
Composite Wage..........................................................      $1,037,261/12,032 hours = $86.2085/hour
--------------------------------------------------------------------------------------------------------------------------------------------------------

    We estimate the total burden for complying with the SNF QRP 
requirements would be decreased by minus 12,032 hours (0.005 hr x 
2,406,401 admission assessments) and minus $1,037,261 (12,032 hrs x 
$86.2085/hr) for all SNFs annually based on the proposed removal of the 
Application of Functional Assessment/Care Plan measure. The burden 
associated with the Application of Functional Assessment/Care Plan 
measure is included in the currently approved (active) burden estimates 
under OMB control number 0938-1140 (CMS-10387). The proposal to remove 
this measure in section VI.C.1.c. of this rule would remove this 
burden.
    As stated in section VI.C.1.d. of this rule, we propose to remove 
the Application of IRF Functional Outcome Measure: Change in Self-Care 
Score for Medical Rehabilitation Patients (Change in Self-Care Score) 
measure as well as the Application of IRF Functional Outcome Measure: 
Change in Mobility Score for Medical Rehabilitation Patients (Change in 
Mobility) measure beginning with the FY 2025 SNF QRP. While these 
assessment-based quality measures are proposed for removal, the data 
elements used to calculate the measures would still be reported by SNFs 
for other payment and quality reporting purposes. Therefore, we believe 
that the proposal to remove the

[[Page 21402]]

Change in Self-Care and Change in Mobility measures would not have any 
impact on our currently approved reporting burden for SNFs.
    As stated in section VI.C.3.a. of this rule, we propose to adopt 
the COVID-19 Vaccine: Percent of Patients/Residents Who Are Up to Date 
(Patient/Resident COVID-19 Vaccine) measure beginning with the FY 2026 
SNF QRP. This proposed assessment-based quality measure would be 
collected using the MDS. The MDS 3.0 is currently approved under OMB 
control number 0938-1140 (CMS-10387). One data element would need to be 
added to the MDS at discharge in order to allow for the collection of 
the Patient/Resident COVID-19 Vaccine measure. We believe this would 
result in an increase of 18 seconds (0.3 min or 0.005 hr) of clinical 
staff time at discharge beginning with the FY 2026 SNF QRP. We believe 
that the added data element for the proposed Patient/Resident COVID-19 
Vaccine measure would be completed equally by registered nurses (0.0025 
hr/2 at $79.56/hr) and licensed vocational nurses (0.0025 hr/2 at 
$49.86/hr), however, individual SNFs determine the staffing resources 
necessary. Therefore, we averaged BLS' National Occupational Employment 
and Wage Estimates (see Table 26) for these labor types and established 
a composite cost estimate using our adjusted wage estimates. The 
composite estimate of $64.71/hr was calculated by weighting each hourly 
wage based on the following breakdown (see Table 28) regarding provider 
types most likely to collect this data: RN 50 percent at $79.56/hr and 
LVN 50 percent at $49.86/hr.
    For purposes of deriving the burden impact, we estimate a total of 
2,406,401 discharges from 15,471 SNFs annually.

                            Table 28--Estimated Composite Wage for the Application of Functional Assessment/Care Plan Measure
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                            Mean hourly
                                                                           wage, fringe     Percent of       Number of
                    Occupation title                        Occupation     benefits, and    assessments     assessments     Total hours    Total burden
                                                               code       other indirect     collected      collected *                         ($)
                                                                           costs ($/hr)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Registered Nurse (RN)...................................         29-1141           79.56              50     1,203,200.5           6,016         478,633
Licensed Vocational Nurse (LVN).........................         29-2061           49.86              50     1,203,200.5           6,016         299,958
                                                         -----------------------------------------------------------------------------------------------
    Total...............................................             n/a             n/a             100       2,406,401          12,032         778,591
                                                         -----------------------------------------------------------------------------------------------
Composite Wage..........................................................        $778,591/12,032 hours = $64.71/hour
--------------------------------------------------------------------------------------------------------------------------------------------------------

    We estimate the total burden for complying with the SNF QRP 
requirements would be increased by 12,032 hours (0.005 hr x 2,406,401 
discharge assessments) and $778,591 (12,032 hrs x $64.71/hr) for all 
SNFs annually based on the proposed adoption of the Patient/Resident 
COVID-19 Vaccine measure. The burden would be accounted for in a future 
revised information collection request under OMB control number 0938-
1140 (CMS-10387).
    As stated in section VI.F.6. of this rule, we propose to increase 
the SNF QRP data completion thresholds for MDS data items beginning 
with the FY 2026 SNF QRP. We propose that SNFs would be required to 
report 100 percent of the required quality measures data and 
standardized patient assessment data collected using the MDS on at 
least 90 percent of the assessments they submit through the CMS 
designated submission system. Because SNFs have been required to submit 
MDS quality measures data and standardized patient assessment data for 
the SNF QRP since October 1, 2016, we are not making any changes to the 
burden that is currently approved by OMB under control number 0938-1140 
(CMS-10387).
    In summary, we estimate the proposed SNF QRP changes associated 
with proposed removal of the Application of Functional Assessment/Care 
Plan measure and the proposed adoption of Patient/Resident COVID-19 
measure would result in no change in the total time and a decrease of 
$258,670 (see Table 29).

                                      Table 29--Proposals Associated With OMB Control Number 0938-1140 (CMS-10387)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Total         Time per       Total time
             Requirement                  Number respondents        responses     response (hr)       (hr)             Wage ($/hr)        Total cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Change in Burden associated with       15,471 SNFs.............     (2,406,401)         (0.005)        (12,032)  Varies.................     (1,037,261)
 proposed removal of the Application
 of Functional Assessment/Care Plan
 measure beginning with the FY 2025
 SNF QRP.
Change in Burden associated with       15,471 SNFs.............       2,406,401           0.005          12,032  Varies.................         778,591
 proposed Patient/Resident COVID-19
 Vaccine measure beginning with the
 FY 2026 SNF QRP.
                                      ------------------------------------------------------------------------------------------------------------------
    Total Change.....................  n/a.....................               0               0               0  n/a....................       (258,670)
--------------------------------------------------------------------------------------------------------------------------------------------------------

    In section VI.C.2.a. of this rule, we propose to adopt the CoreQ: 
Short Stay Discharge (CoreQ: SS DC) measure, beginning with the FY 2026 
SNF QRP. We describe in this section the following sources of burden 
associated with the proposed adoption of the CoreQ: SS DC measure: (1) 
exemption requests; (2) vendor costs; (3) submission of resident 
information files; and (4) costs to beneficiaries. We have provided an 
estimate burden here and in Tables 28 and 29, and note that the 
increase in burden would be accounted

[[Page 21403]]

for in a new information collection request.
    Under this proposal, SNFs would be required to participate in the 
CoreQ: SS DC measure's survey requirements unless they meet the 
proposed low volume exemption criteria (see section VI.F.3.b.(1) of 
this proposed rule). Using data from July 1, 2021 through June 30, 
2022, we estimate 3,272 SNFs (out of 15,435 total SNFs) would meet the 
proposed low volume exemption criteria for the measure's reporting 
requirements, and therefore would be expected to request an exemption. 
We believe the submission of a request for exemption would be completed 
by a medical record specialist. Our assumption for staff type is based 
on our experience with the home health and hospice Community Assessment 
of Healthcare Providers and Systems (CAHPS[supreg]) surveys which have 
been in place since 2010 and 2015, respectively. However, individual 
SNFs determine the staffing resources necessary. We believe it would 
take 35 minutes (0.58 hr) at $46.46/hr for a medical record specialist 
to submit a request for exemption from the CoreQ: SS DC measure's 
survey requirement. In aggregate, we estimate a burden of 1,898 hours 
(3,272 exemptions x 0.58 hr per request at a cost of $88,181 (1,898 hr 
x $46.46./hr) for all SNFs requesting an exemption from the CoreQ: SS 
DC measure survey requirement.
    Under this proposal, SNFs that do not qualify for an exemption 
would be required to contract with a CMS-approved CoreQ survey vendor 
to administer the CoreQ: SS DC measure's survey on their behalf and 
submit the results to the CoreQ Survey Data Center (see section VI.F.3. 
of this proposed rule). We estimate a SNF's annual cost of contracting 
with a CMS-approved CoreQ survey vendor to be $4,000. Our assumption 
for the cost of a CMS-approved CoreQ survey vendor is based on our 
experience with the home health and hospice CAHPS[supreg] surveys which 
have been in place since 2010 and 2015, respectively. Therefore, we 
estimate the cost to SNFs participating in the CoreQ SS DC measure 
(15,435 total SNFs-3,272 SNF exemptions = 12,163 SNFs) would be 
increased by $48,652,000 ($4,000 x 12,163 SNFs).
    After contracting with a CMS-approved CoreQ survey vendor, SNFs 
would be required to submit one resident information file (as described 
in section VI.F.3.c. of this proposed rule) to their CMS-approved CoreQ 
survey vendor during the initial submission period from January 1, 2024 
through June 30, 2024. Beginning July 1, 2024, SNFs would be required 
to submit resident information files to their CMS-approved CoreQ survey 
vendor no less than weekly for the remainder of CY 2024. Our 
assumptions for staff type who would be responsible for collecting 
information for the proposed CoreQ: SS DC measure were based on our 
experience with the home health and hospice CAHPS[supreg] surveys which 
have been in place since 2010 and 2015, respectively. However, 
individual SNFs determine the staffing resources necessary. We believe 
it would take 4 hours at $92.92/hr for a computer programmer to 
complete the initial set-up of the resident information files. After 
the initial set-up, we believe it would take 30 minutes per week (or 26 
hr/year) at $46.46/hr for a medical record specialist to create and 
submit the resident information file to the CMS-approved CoreQ survey 
vendor.
    For the FY 2026 SNF QRP (data submission period January 1, 2024 
through December 31, 2024), we estimate a burden of 212,853 hours 
(12,163 SNFs x [4 hr for a computer programmer/SNF + (0.5 hr for a 
medical record specialist x 27 resident information files/SNF)]) at a 
cost of $12,149,449 (12,163 SNFs x [4 hr x $92.92/hr to initially set 
up the resident information file/SNF) + (13.5 hr x $46.46/hr to submit 
27 resident information files to the CMS-approved CoreQ survey vendor/
SNF]).
    Beginning with the FY 2027 SNF QRP (data submission period January 
1, 2025 through December 31, 2025), we estimate a burden of 316,238 
hours (12,163 SNFs x [0.5 hr for a medical record specialist x 52 
weeks]) at a cost of $14,692,417 (316,238 hrs across all SNFs x $46.46/
hr to submit resident information files to the CMS-approved CoreQ 
survey vendor).
    The CoreQ: SS DC measure's survey contains a total of 6 questions 
(four primary questions and two help provided questions) and is 
estimated to require a SNF respondent an average of 6 minutes (0.1 hr) 
to complete. This is based on the original testing of the CoreQ: SS DC 
measure described in the CoreQ National Quality Forum (NQF) 
application. Using data from July 1, 2021 through June 30, 2022, we 
estimate there would be 1,330,284 completed surveys (27 weeks/52 weeks 
= 0.52); (0.52 x 2,558,238 completed surveys) in the first year of data 
submission (January 1, 2024 through December 31, 2024). In aggregate, 
we estimate a burden of 133,028 hours (1,330,284 x 0.1 hr/completed 
survey) at a cost of $2,755,010 (133,028 hr x $20.71/hr for 
beneficiaries). Beginning with the FY 2027 SNF QRP (data submission 
period January 1, 2025 through December 31, 2025), we estimate a burden 
of 255,824 hr (2,558,238 completed surveys x 0.1 hr/survey) at a cost 
of $5,298,115 = (255,824 hrs x $20.71/hr).
    Table 30 estimates the overall SNF burden for the proposed CoreQ: 
SS DC measure while Table 31 estimates the overall respondent burden 
for the proposed CoreQ: SS DC Measure.

                                      Table 30--Proposed SNF Burden for the CoreQ Survey (OMB 0938-TBD, CMS-10852)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                          Number of         Total                                  Total time
             Requirement                 respondents      responses     Time per response (hr)        (hr)         Wage ($/hr)        Total cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                           FY 2026 CoreQ: SS DC Measure Burden
--------------------------------------------------------------------------------------------------------------------------------------------------------
Requesting an exemption to the CoreQ:      3,272 SNFs           3,272  0.58....................           1,898           46.46  88,181
 SS DC measure survey reporting
 requirements.
Contracting with a CMS-approved CoreQ     12,163 SNFs          12,163  NA......................              NA              NA  48,652,000 (12,163 x
 survey vendor.                                                                                                                   $4,000)
Data submission requirements for the      12,163 SNFs         328,401  0.50/wk after initial 4          212,853        * Varies  12,149,499
 proposed CoreQ: SS DC measure for                                      hr set-up.
 the FY 2026 SNF QRP *.
                                      ------------------------------------------------------------------------------------------------------------------

[[Page 21404]]

 
    Total............................     15,435 SNFs         331,673  5.05....................         214,751          Varies  88,181 for exempted
                                                                                                                                  SNFs
                                                                                                                                 60,801,499 for
                                                                                                                                  participating SNFs
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                 Burden Beginning with the FY 2027 CoreQ: SS DC Measure
--------------------------------------------------------------------------------------------------------------------------------------------------------
Requesting an exemption to the CoreQ:      3,272 SNFs           3,272  0.58....................            1898          $46.46  88,181
 SS DC measure survey reporting
 requirements.
Contracting with a CMS-approved CoreQ     12,163 SNFs          12,163  NA......................              NA           4,000  48,652,000 (12,163 x
 survey vendor.                                                                                                                   $4,000)
Data submission requirements for the      12,163 SNFs         632,476  0.50....................         316,238           46.46  14,692,417
 proposed CoreQ: SS DC measure
 beginning with the FY 2027 SNF QRP.
                                      ------------------------------------------------------------------------------------------------------------------
    Total............................     15,435 SNFs         635,748  1.08....................         318,147              NA  88,181 for exempted
                                                                                                                                  SNFs
                                                                                                                                 63,344,417 for
                                                                                                                                  participating SNFs
--------------------------------------------------------------------------------------------------------------------------------------------------------
* For the first year of implementation (January 1, 2024 through December 31, 2024), we estimate 4 hours of computer programmer time and 13.5 hours of
  medical record specialist time.
** Burden is calculated based on 27 weeks of required participation: submission at least one weekly resident information file to the CMS-approved CoreQ
  survey vendor January 1, 2024 through June 30, 2024; submission of resident information file to the CMS-approved CoreQ survey vendor no less than
  weekly July 1, 2024 through December 31, 2024.


                                Table 31--Proposed Burden to Beneficiaries for the CoreQ Survey (OMB 0938-TBD, CMS-10852)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                             Number of         Total         Time per       Total time
                       Requirement                          respondents      responses     response (hr)       (hr)         Wage ($/hr)   Total cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                     FY 2026 CoreQ: SS DC Measure Beneficiary Burden
--------------------------------------------------------------------------------------------------------------------------------------------------------
Completing the CoreQ: SS DC survey......................       1,330,284       1,330,284             0.1         133,028           20.71       2,755,010
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                     FY 2027 CoreQ: SS DC Measure Beneficiary Burden
--------------------------------------------------------------------------------------------------------------------------------------------------------
Completing the CoreQ: SS DC survey......................       2,558,238       2,558,238             0.1         255,824           20.71       5,298,115
--------------------------------------------------------------------------------------------------------------------------------------------------------

2. ICRs Regarding the Skilled Nursing Facility Value-Based Purchasing 
Program
    In section VII.B.3. of this rule, we are proposing to replace the 
SNFRM with the SNF WS PPR measure beginning with the FY 2028 SNF VBP 
program year. The measure is calculated using Medicare FFS claims data, 
which are the same data we use to calculate the SNFRM, and therefore, 
this measure would not create any new or revised burden for SNFs.
    We are also proposing to adopt four new quality measures in the SNF 
VBP Program as discussed in section VII.B.4. of this proposed rule. One 
of the measures is the Total Nursing Staff Turnover Measure beginning 
with the FY 2026 SNF VBP Program Year. This measure is calculated using 
PBJ data that nursing facilities with SNF beds currently report to CMS 
as part of the Five Star Quality Rating System, and therefore, this 
measure would not create new or revised burden for SNFs. We are also 
proposing to adopt three additional quality measures beginning with the 
FY 2027 SNF VBP Program Year: (1) the Percent of Residents Experiencing 
One or More Falls with Major Injury (Long-Stay) Measure (``Falls with 
Major Injury (Long-Stay) measure''), (2) the Skilled Nursing Facility 
Cross-Setting Discharge Function Score Measure (``DC Function 
measure''), and (3) the Number of Hospitalizations per 1,000 Long-Stay 
Resident Days Measure (``Long-Stay Hospitalizations measure''). The 
Falls with Major Injury (Long-Stay) measure, and the DC Function 
measure are calculated using MDS 3.0 data and are calculated by CMS 
under the Nursing Home Quality Initiative and SNF QRP Program, 
respectively. The Long-Stay Hospitalization measure is calculated using 
Medicare FFS claims data. Therefore, these three measures would not 
create new or revised burden for SNFs.
    Furthermore, in section VII.F. of this proposed rule, we are 
proposing to update the validation process for the SNF VBP Program, 
including adopting a new process for the Minimum Data Set (MDS) 
measures beginning with the FY 2027 SNF VBP program year. Under this 
proposal, we would validate data used to calculate the measures used in 
the

[[Page 21405]]

SNF VBP Program, and 1,500 randomly selected SNFs a year would be 
required to submit up to 10 charts that would be audited to validate 
the MDS measures.
    Finally, in section VII.E.5. of this rule, we are proposing to 
adopt a Health Equity Adjustment beginning with FY 2027 SNF VBP program 
year. The source of data we would use to calculate this adjustment is 
the State Medicare Modernization Act (MMA) file of dual eligibility, 
and therefore our calculation of this adjustment would not create any 
additional reporting burden for SNFs.
    The aforementioned FFS-related claims submission requirements and 
burden, which are previously mentioned in the preceding paragraphs, are 
active and approved by OMB under control number 0938-1140 (CMS-10387). 
The aforementioned MDS submission requirements and burden are active 
and approved by OMB under control number 0938-1140 and the burden 
associated with the items used to calculate the measures is already 
accounted for in the currently approved information collection since it 
is used for the SNF QRP. The aforementioned PBJ submission requirements 
and burden are PRA exempt (as are all nursing home requirements for 
participation). The increase in burden for the SNFs would be accounted 
for in the submission of up to 10 charts for review, and the proposed 
process would not begin until FY 2025. The required 60-day and 30-day 
notices would be published in the Federal Register and the comment 
periods would be separate from those associated with this rulemaking. 
The proposals in this proposed rule would have no impact on any of the 
requirements and burden that are currently approved under these control 
numbers.
C. Summary of Proposed Burden Estimates

                                               Table 32--Summary of Proposed Burden Estimates for FY 2025
--------------------------------------------------------------------------------------------------------------------------------------------------------
   Regulatory section(s) under      OMB Control No.        Number of       Total number      Time per       Total time    Labor cost ($/
       title 42 of the CFR            (CMS ID No.)        respondents      of responses    response (hr)       (hr)             hr)       Total cost ($)
--------------------------------------------------------------------------------------------------------------------------------------------------------
413.360(b)(1)...................  0938-1140 CMS-10387        15,471 SNFs     (2,406,401)           0.005        (12,032)           86.21     (1,037,261)
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                                                   Table 33--Summary of Proposed Burden Estimates for FY 2026
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Regulatory section(s) under title 42   OMB Control No. (CMS ID                             Total number                              Total time    Labor cost ($/
              of the CFR                         No.)              Number of respondents    of responses    Time per response (hr)       (hr)             hr)              Total cost ($)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
413.360..............................  0938-1140 CMS-10387.....  15,471 SNFs.............       2,406,401  0.005..................          12,032           79.56                       778,591
413.360..............................  0938-TBD CMS-10852......  3,272 exempted SNFs.....           3,272  0.58...................           1,898           46.46                        88,181
413.360(b)(2)........................  0938-INSERT CMS-10852...  1,330,284 beneficiaries.       1,330,284  0.1....................         133,028           20.71                     2,755,010
413.360(b)(2)........................  0938-TBD CMS-10852......  12,163 participating             328,401  0.5/wk after initial 4          212,853          Varies                    12,149,449
                                                                  SNFs.                                     hr set up.
413.360(b)(2)........................  0938-INSERT CMS-10852...  12,163 participating              12,163  NA.....................              NA              NA                    48,652,000
                                                                  SNFs.                                                                                                        (12,163 x $4,000)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
  Total for SNFs exempt from CoreQ AND reporting Patient/        18,743..................       2,409,673  Varies.................          13,930          Varies                       866,772
   Resident COVID-19 Vaccine measure data.
                                                                --------------------------------------------------------------------------------------------------------------------------------
Total for SNFs not exempt from CoreQ AND reporting Patient/      1,370,081...............       4,077,249  Varies.................         357,913          Varies                    61,580,040
 Resident COVID-19 Vaccine measure data *.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------


                                               Table 34--Summary of Proposed Burden Estimates for FY 2027
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                  Time per
 Regulatory section(s) under   OMB Control No.     Number of      Total number    response    Total time    Labor cost ($/         Total cost ($)
     title 42 of the CFR         (CMS ID No.)     respondents     of responses      (hr)         (hr)             hr)
--------------------------------------------------------------------------------------------------------------------------------------------------------
413.360......................  0938-TBD CMS-    3,272 exempted            3,272       0.58           1,898           46.46                        88,181
                                10852.           SNFs.
413.360(b)(2)................  0938-INSERT CMS- 2,558,238             2,558,238        0.1         255,824           20.71                     5,298,115
                                10852.           beneficiaries.

[[Page 21406]]

 
413.360(b)(2)................  0938-TBD CMS-    12,163                  632,476        0.5         316,238          Varies                    14,692,417
                                10852.           participating
                                                 SNFs.
413.360(b)(2)................  0938-TBD CMS-    12,163                   12,163         NA              NA              NA                    48,652,000
                                10852.           participating                                                                         (12,163 x $4,000)
                                                 SNFs.
--------------------------------------------------------------------------------------------------------------------------------------------------------
  Total for SNFs exempt from CoreQ reporting    3,272..........           3,272       0.58           1,878           46.46                        88,181
                 requirements
                              --------------------------------------------------------------------------------------------------------------------------
Total for SNFs not exempt from CoreQ reporting  2,582,564......       3,202,877        0.6         572,062          Varies                    63,344,417
                requirements *
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Totals represent SNF burden only and do not include the beneficiary burden.

D. Submission of PRA-Related Comments

    We have submitted a copy of this proposed rule's information 
collection requirements to OMB for their review. The requirements are 
not effective until they have been approved by OMB.
    To obtain copies of the supporting statement and any related forms 
for the proposed collections discussed above, please visit the CMS 
website at https://www.cms.gov/regulations-and-guidance/legislation/paperworkreductionactof1995/pra-listing, or call the Reports Clearance 
Office at 410-786-1326.
    We invite public comments on these potential information collection 
requirements. If you wish to comment, please submit your comments 
electronically as specified in the DATES and ADDRESSES sections of this 
proposed rule and identify the rule (CMS-1779-P), the ICR's CFR 
citation, and OMB control number.

X. Response to Comments

    Because of the large number of public comments we normally receive 
on Federal Register documents, we are not able to acknowledge or 
respond to them individually. We will consider all comments we receive 
by the date and time specified in the DATES section of this preamble, 
and, when we proceed with a subsequent document, we will respond to the 
comments in the preamble to that document.

XI. Economic Analyses

A. Regulatory Impact Analysis

1. Statement of Need
a. Statutory Provisions
    This rule proposes updates to the FY 2024 SNF prospective payment 
rates as required under section 1888(e)(4)(E) of the Act. It also 
responds to section 1888(e)(4)(H) of the Act, which requires the 
Secretary to provide for publication in the Federal Register before the 
August 1 that precedes the start of each FY, the unadjusted Federal per 
diem rates, the case-mix classification system, and the factors to be 
applied in making the area wage adjustment. These are statutory 
provisions that prescribe a detailed methodology for calculating and 
disseminating payment rates under the SNF PPS, and we do not have the 
discretion to adopt an alternative approach on these issues.
    With respect to the SNF QRP, this proposed rule proposes updates 
beginning with the FY 2025, FY 2026, and FY 2027 SNF QRP. Specifically, 
we are proposing a modification to a current measure in the SNF QRP 
beginning with the FY 2025 SNF QRP, which we believe will encourage 
healthcare personnel to remain up to date with the COVID-19 vaccine, 
resulting in fewer cases, less hospitalizations, and lower mortality 
associated with the virus. We are proposing three new measures: (1) one 
to meet the requirements of the IMPACT Act which would replace the 
current cross-setting process measure with one more strongly associated 
with desired patient functional outcomes beginning with the FY 2025 SNF 
QRP; (2) one that supports the goals of CMS Meaningful Measures 
Initiative 2.0 to empower consumers, as well as assist SNFs leverage 
their care processes to increase vaccination coverage in their settings 
to protect residents and prevent negative outcomes beginning with the 
FY 2027 SNF QRP; and (3) one that would measure residents' satisfaction 
in order to assess whether the goals of person-centered care are 
achieved beginning with the FY 2026 SNF QRP. We are proposing the 
removal of three measures from the SNF QRP, beginning with the FY 2025 
SNF QRP, as they meet the criteria specified at Sec.  413.360(b)(2) for 
measure removal. We are further proposing to increase the data 
completion threshold for Minimum Data Set (MDS) data items, beginning 
with the FY 2026 SNF QRP, which we believe would improve our ability to 
appropriately analyze quality measure data for the purposes of 
monitoring SNF outcomes. For consistency in our regulations, we are 
also proposing conforming revisions to the requirements related to 
these proposals under the SNF QRP at Sec.  413.360.
    With respect to the SNF VBP Program, this rule proposes updates to 
the SNF VBP Program requirements for FY 2024 and subsequent years. 
Section 1888(h)(2)(A)(ii) of the Act (as amended by section 
111(a)(2)(C) of the CAA 2021) allows the Secretary to add up to nine 
new measures to the SNF VBP Program. We are proposing to adopt four new 
measures for the SNF VBP Program. We propose to adopt one new measure 
beginning with the FY 2026 SNF VBP program year and three new measures 
beginning with the FY 2027 program year. We are also proposing to 
replace the SNFRM with the SNF WS PPR measure beginning with the FY 
2028 SNF VBP Program year. Additionally, to better address health 
disparities and achieve health equity we are proposing to adopt a 
Health Equity Adjustment (HEA) beginning with the FY 2027 program year. 
As part of the HEA, we plan to adopt a variable payback percentage (for 
additional information on the HEA and the fluctuating payback 
percentage see section VII.E.4. of this proposed rule). Section 
1888(h)(3) of the Act requires the Secretary to establish and announce 
performance standards

[[Page 21407]]

for SNF VBP Program measures no later than 60 days before the 
performance period, and this proposed rule estimates numerical values 
of the performance standards for the SNFRM, the SNF Healthcare-
Associated Infection Requiring Hospitalization (SNF HAI), Total Nurse 
Staffing, Nursing Staff Turnover, and the Discharge to Community--Post-
Acute Care (DTC PAC SNF) measures. Section 1888(h)(12)(A) of the Act 
requires the Secretary to apply a validation process to SNF VBP Program 
measures and ``the data submitted under [section 1888(e)(6)] [. . .] as 
appropriate[. . .].'' We are proposing to adopt new validation 
processes for measures beginning in FY 2026.
b. Discretionary Provisions
    In addition, this proposed rule includes the following 
discretionary provisions:
(1) PDPM Parity Adjustment Recalibration
    In the FY 2023 SNF final rule (87 FR 47502), we finalized a 
recalibration of the PDPM parity adjustment with a 2-year phase-in 
period, resulting in a reduction of 2.3 percent, or $780 million, in FY 
2023 and a planned reduction in FY 2024 of 2.3 percent. We finalized 
the phased-in approach to implementing this adjustment based on a 
significant number of comments supporting this approach. Accordingly, 
we are implementing the second phase of the 2-year phase-in period, 
resulting in a reduction of 2.3 percent, or approximately $745 million, 
in FY 2024.
(2) SNF Forecast Error Adjustment
    Each year, we evaluate the SNF market basket forecast error for the 
most recent year for which historical data is available. The forecast 
error is determined by comparing the projected SNF market basket 
increase in a given year with the actual SNF market basket increase in 
that year. In evaluating the data for FY 2022, we found that the 
forecast error for FY 2022 was 3.6 percentage points, exceeding the 0.5 
percentage point threshold we established in regulation for proposing 
adjustments to correct for forecast error. Given that the forecast 
error exceeds the 0.5 percentage point threshold, current regulations 
require that the SNF market basket percentage increase for FY 2024 be 
adjusted upward by 3.6 percentage points to account for forecasting 
error in the FY 2022 SNF market basket update.
(3) Technical Updates to ICD-10 Mappings
    In the FY 2019 SNF PPS final rule (83 FR 39162), we finalized the 
implementation of the PDPM, effective October 1, 2019. The PDPM 
utilizes ICD-10 codes in several ways, including using the patient's 
primary diagnosis to assign patients to clinical categories under 
several PDPM components, specifically the PT, OT, SLP and NTA 
components. In this proposed rule, we propose several substantive 
changes to the PDPM ICD-10 code mapping.
(4) Civil Money Penalties: Waiver of Hearing, Automatic Reduction of 
Penalty Amount
    We are proposing to eliminate the requirement for facilities to 
actively waive their right to a hearing in writing and create in its 
place a constructive waiver process that would operate by default when 
CMS has not received a timely request for a hearing. The accompanying 
35 percent penalty reduction would remain. This revision eliminating 
the LTC requirement to submit a written request for a reduced penalty 
amount when a hearing has been waived would simplify and streamline the 
current requirement, while maintaining a focus on providing high 
quality care to residents. Ultimately, this proposal would reduce 
administrative burden for facilities and for CMS.
2. Introduction
    We have examined the impacts of this proposed rule as required by 
Executive Order 12866 on Regulatory Planning and Review (September 30, 
1993), Executive Order 13563 on Improving Regulation and Regulatory 
Review (January 18, 2011), the Regulatory Flexibility Act (RFA, 
September 19, 1980, Pub. L. 96-354), section 1102(b) of the Act, 
section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, March 
22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 
4, 1999).
    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). Executive 
Order 13563 emphasizes the importance of quantifying both costs and 
benefits, of reducing costs, of harmonizing rules, and of promoting 
flexibility. Based on our estimates, OMB's Office of Information and 
Regulatory Affairs has determined this rulemaking is ``significant'' as 
measured by the $100 million threshold. Accordingly, we have prepared a 
regulatory impact analysis (RIA) as further discussed below.
3. Overall Impacts
    This rule updates the SNF PPS rates contained in the SNF PPS final 
rule for FY 2023 (87 FR 47502). We estimate that the aggregate impact 
will be an increase of approximately $1.2 billion (3.7 percent) in Part 
A payments to SNFs in FY 2024. This reflects a $2 billion (6.1 percent) 
increase from the proposed update to the payment rates and a $745 
million (2.3 percent) decrease as a result of the second phase of the 
parity adjustment recalibration. We note in this proposed rule that 
these impact numbers do not incorporate the SNF VBP Program reductions 
that we estimate would total $184.85 million in FY 2024. We note that 
events may occur to limit the scope or accuracy of our impact analysis, 
as this analysis is future-oriented, and thus, very susceptible to 
forecasting errors due to events that may occur within the assessed 
impact time period.
    In accordance with sections 1888(e)(4)(E) and (e)(5) of the Act and 
implementing regulations at Sec.  413.337(d), we are updating the FY 
2023 payment rates by a factor equal to the market basket percentage 
increase adjusted for the forecast error adjustment and reduced by the 
productivity adjustment to determine the payment rates for FY 2024. The 
impact to Medicare is included in the total column of Table 35. The 
annual update in this rule applies to SNF PPS payments in FY 2024. 
Accordingly, the analysis of the impact of the annual update that 
follows only describes the impact of this single year. Furthermore, in 
accordance with the requirements of the Act, we will publish a rule or 
notice for each subsequent FY that will provide for an update to the 
payment rates and include an associated impact analysis.
4. Detailed Economic Analysis
    The FY 2024 SNF PPS payment impacts appear in Table 35. Using the 
most recently available data, in this case FY 2022 we apply the current 
FY 2023 CMIs, wage index and labor-related share value to the number of 
payment days to simulate FY 2023 payments. Then, using the same FY 2022 
data, we apply the FY 2024 CMIs, wage index and labor-related share 
value to simulate FY 2024 payments. We tabulate the resulting payments 
according to the classifications in Table

[[Page 21408]]

35 (for example, facility type, geographic region, facility ownership), 
and compare the simulated FY 2023 payments to the simulated FY 2024 
payments to determine the overall impact. The breakdown of the various 
categories of data in Table 35 is as follows:
     The first column shows the breakdown of all SNFs by urban 
or rural status, hospital-based or freestanding status, census region, 
and ownership.
     The first row of figures describes the estimated effects 
of the various proposed changes on all facilities. The next six rows 
show the effects on facilities split by hospital-based, freestanding, 
urban, and rural categories. The next nineteen rows show the effects on 
facilities by urban versus rural status by census region. The last 
three rows show the effects on facilities by ownership (that is, 
government, profit, and non-profit status).
     The second column shows the number of facilities in the 
impact database.
     The third column shows the effect of the second phase of 
the parity adjustment recalibration discussed in section III.C. of this 
rule.
     The fourth column shows the effect of the annual update to 
the wage index. This represents the effect of using the most recent 
wage data available as well as accounts for the 5 percent cap on wage 
index transitions. The total impact of this change is 0.0 percent; 
however, there are distributional effects of the proposed change.
     The fifth column shows the effect of all of the changes on 
the FY 2024 payments. The update of 6.1 percent is constant for all 
providers and, though not shown individually, is included in the total 
column. It is projected that aggregate payments would increase by 6.1 
percent, assuming facilities do not change their care delivery and 
billing practices in response.
    As illustrated in Table 35, the combined effects of all of the 
changes vary by specific types of providers and by location. For 
example, due to changes in this proposed rule, rural providers would 
experience a 3.0 percent increase in FY 2024 total payments.
    In this chart and throughout the rule, we use a multiplicative 
formula to derive total percentage change. This formula is:

(1 + Parity Adjustment Percentage) * (1 + Wage Index Update Percentage) 
* (1 + Payment Rate Update Percentage)-1 = Total Percentage Change

    For example, the figures shown in Column 5 of Table 35 are 
calculated by multiplying the percentage changes using this formula. 
Thus, the Total Change figure for the Total Group Category is 3.7 
percent, which is (1-2.3%) * (1 + 0.0%) * (1 + 6.1%)-1.
    As a result of rounding and the use of this multiplicative formula 
based on percentages, derived dollar estimates may not sum.

                                   Table 35--Impact to the SNF PPS for FY 2024
----------------------------------------------------------------------------------------------------------------
                                                                      Parity
                                                     Number of      adjustment      Update wage    Total change
                Impact categories                   facilities     recalibration     data (%)           (%)
                                                                        (%)
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total...........................................          15,435            -2.3             0.0             3.7
Urban...........................................          11,206            -2.3             0.1             3.8
Rural...........................................           4,229            -2.2            -0.7             3.0
Hospital-based urban............................             359            -2.3             0.1             3.7
Freestanding urban..............................          10,847            -2.3             0.1             3.8
Hospital-based rural............................             375            -2.2            -0.4             3.3
Freestanding rural..............................           3,854            -2.2            -0.7             3.0
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................................             734            -2.3            -0.7             2.9
Middle Atlantic.................................           1,468            -2.4             1.4             5.1
South Atlantic..................................           1,935            -2.3             0.0             3.7
East North Central..............................           2,176            -2.3            -0.7             3.0
East South Central..............................             555            -2.2             0.0             3.7
West North Central..............................             957            -2.3            -0.7             3.0
West South Central..............................           1,432            -2.3             0.0             3.7
Mountain........................................             545            -2.3            -0.8             2.9
Pacific.........................................           1,398            -2.4             0.2             3.7
Outlying........................................               6            -2.0            -2.5             1.4
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................................             114            -2.3            -1.0             2.6
Middle Atlantic.................................             205            -2.2            -0.4             3.3
South Atlantic..................................             484            -2.2            -0.1             3.7
East North Central..............................             906            -2.2            -0.8             2.9
East South Central..............................             490            -2.2            -1.0             2.8
West North Central..............................           1,009            -2.2            -0.9             2.8
West South Central..............................             732            -2.2            -0.5             3.3
Mountain........................................             197            -2.3            -0.6             3.1
Pacific.........................................              91            -2.3            -2.0             1.5
Outlying........................................               1            -2.3             0.0             3.6
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
For profit......................................          10,884            -2.3             0.0             3.7

[[Page 21409]]

 
Non-profit......................................           3,550            -2.3             0.0             3.6
Government......................................           1,001            -2.3            -0.4             3.3
----------------------------------------------------------------------------------------------------------------
Note: The Total column includes the FY 2024 6.1 percent market basket update factor. The values presented in
  Table 35 may not sum due to rounding.

5. Impacts for the Skilled Nursing Facility Quality Reporting Program 
(SNF QRP) for FY 2025
    Estimated impacts for the SNF QRP are based on analysis discussed 
in section VI.C. of this proposed rule. In accordance with section 
1888(e)(6)(A)(i) of the Act, the Secretary must reduce by 2 percentage 
points the annual payment update applicable to a SNF for a fiscal year 
if the SNF does not comply with the requirements of the SNF QRP for 
that fiscal year.
    As discussed in section VI.C.1.a. of this proposed rule, we propose 
to modify one measure in the SNF QRP beginning with the FY 2025 SNF 
QRP, the COVID-19 Vaccination Coverage among Healthcare Personnel (HCP 
COVID-19 Vaccine) measure. We believe that the burden associated with 
the SNF QRP is the time and effort associated with complying with the 
non-claims-based measures requirements of the SNF QRP. The burden 
associated with the COVID-19 Vaccination Coverage among HCP measure is 
accounted for under the CDC PRA package currently approved under OMB 
control number 0938-1317 (expiration January 31, 2024).
    As discussed in section VI.C.1.b. of this proposed rule, we propose 
that SNFs would collect data on one new quality measure, the Discharge 
Function Score (DC Function) measure, beginning with resident 
assessments completed on October 1, 2023. However, the DC Function 
measure utilizes data items that SNFs already report to CMS for payment 
and quality reporting purposes, and therefore, the burden is accounted 
for in the PRA package approved under OMB control number 0938-1140 
(expiration November 30, 2025).
    As discussed in section VI.C.1.c. of this proposed rule, we propose 
to remove a measure from the SNF QRP, the Application of Percent of 
Long-Term Care Hospital Patients with an Admission and Discharge 
Functional Assessment and a Care Plan That Addresses Function 
(Application of Functional Assessment/Care Plan) measure, beginning 
with admission assessments completed on October 1, 2023. Although the 
proposed decrease in burden will be accounted for in a revised 
information collection request under OMB control number (0938-1140), we 
are providing impact information.
    With 2,406,401 admissions from 15,471 SNFs annually, we estimate an 
annual burden decrease of 12,032 fewer hours (2,406,401 admissions x 
0.005 hr) and a decrease of $1,037,261 (12,038 hrs x $86.2085/hr). For 
each SNF we estimate an annual burden decrease of 0.78 hours [(12,032 
hours/15,471 SNFs) at a savings of $67.05 ($1,037,261 total burden/
15,471 SNFs).
    As discussed in section VI.C.1.d. of this rule, we propose to 
remove two measures from the SNF QRP, the Application of IRF Functional 
Outcome Measure: Change in Self-Care Score for Medical Rehabilitation 
Patients (Change in Self-Care Score) and Application of IRF Functional 
Outcome Measure: Change in Mobility Score for Medical Rehabilitation 
Patients (Change in Mobility Score) measures, beginning with 
assessments completed on October 1, 2023. However, the data items used 
in the calculation of the Change in Self-Care Score and Change in 
Mobility Score measures are used for other payment and quality 
reporting purposes, and therefore there is no change in burden 
associated with this proposal.
    As discussed in section VI.C.3.a. of this rule, we propose to add a 
second measure to the SNF QRP, the COVID-19 Vaccine: Percent of 
Patients/Residents Who are Up to Date (Patient/Resident COVID-19 
Vaccine) measure, which would result in an increase of 0.005 hours of 
clinical staff time beginning with discharge assessments completed on 
October 1, 2024. Although the proposed increase in burden will be 
accounted for in a revised information collection request under OMB 
control number (0938-1140), we are providing impact information. With 
2,406,401 discharges from 15,471 SNFs annually, we estimate an annual 
burden increase of 12,032 hours (2,406,401 discharges x 0.005 hr) and 
an increase of $778,5914 (12,032 hrs x $64.71/hr). For each SNF we 
estimate an annual burden increase of 0.78 hours (12,032 hrs/15,471 
SNFs) at an additional cost of $50.33 ($778,591 total burden/15,471 
SNFs).
    We also propose in section VI.F.5. of this proposed rule that SNFs 
would begin reporting 100 percent of the required quality measures data 
and standardized patient assessment data collected using the MDS on at 
least 90 percent of the assessments they submit through the CMS 
designated submission system beginning January 1, 2024. As discussed in 
section IX.B.1. of this proposed rule, this change would not affect the 
information collection burden for the SNF QRP.
    Finally, we propose in section VI.C.2. of this proposed rule to 
adopt the CoreQ: Short Stay Discharge (CoreQ: SS DC) measure to the SNF 
QRP beginning with the FY 2026 SNF QRP. Although the proposed increase 
in burden will be accounted for in a new information collection 
request, we are providing impact information. The impact of the 
proposed CoreQ: SS DC measure is discussed in three parts: (1) the 
burden for small SNFs requesting an exemption; (2) the burden for 
participating SNFs in the first year of national implementation; and 
(3) the burden for participating SNFs beginning with the second year of 
implementation. We describe each of these next and in Table 36.
    As described in section VI.C.2.a.(5)(i) of this proposed rule, 
eligible SNFs may request an exemption from the proposed CoreQ: SS DC 
measure's reporting requirements. We estimate an increase of 0.58 hours 
of staff time for SNFs who request this exemption.
    We estimate 3,272 SNFs would request an exemption, resulting in an 
annual burden increase of 1,898 hours (3,272 SNFs x 0.58 hrs) and an 
increase of $88,181 [3,272 SNFs x (0.58 hrs x $46.46/hr)]. For each SNF 
requesting an exemption, we estimate an annual burden increase of 0.58 
hours and $26.95 (0.58 hrs x $46.46/hr).
    In the first year of implementation of the proposed CoreQ: SS DC 
measure (January 1, 2024 through December 31, 2024), participating SNFs 
would need to

[[Page 21410]]

contract with an independent, CMS approved survey vendor to administer 
the CoreQ survey on their behalf and submit the results to the CoreQ 
Data Center. We estimate $4,000 annual cost for a participating SNF to 
contract with a survey vendor, resulting in an annual cost increase of 
$48,652,000 ($4,000 x 12,163 estimated participating SNFs). 
Participating SNFs would also incur an increase of 17.5 hours of staff 
time to assemble and submit the resident information files, 
specifically four hours of computer programmer's time and 30 minutes 
per week for 27 weeks of a medical record specialist's time. We 
estimate a burden increase in CY 2024 of 212,853 hours (12,163 SNFs x 
17.5 hours) and an increase of $12,149,499 [((4 hours x $92.92) + (13.5 
hours x $46.46)) x 12,163]. For each SNF, we estimate an annual burden 
increase of 17.5 hours [4 + ((27 weeks x 30 min)/60)] and $998.89 [(4 
hours x $92.92) + (13.5 hours x $46.46)].
    Beginning with the second year of implementation of the proposed 
CoreQ: SS DC measure (January 1, 2025 through December 31, 2025), the 
potential impact of requesting an exemption or contracting with a 
survey vendor would not change and be the same as described above. 
However, as described in section VI.F.5.b. of this proposed rule, the 
second year of implementation of the proposed CoreQ measure requires 
participating SNFs to submit data for the entire CY. Therefore, we 
estimate the additional impact for participating SNFs would be 26 hours 
of medical record specialist time to assemble and submit the resident 
information files (52 weeks x 0.5 hr). We estimate an additional impact 
in CY 2025 of 316,238 hours (12,163 SNFs x 26 hours) and an increase of 
$14,692,417 [(26 hours x $46.46) x 12,163]. For each participating SNF, 
we estimate an additional impact of 26 hours and $1,207.96 (26 hours x 
$46.46).

                     Table 36--Estimated SNF QRP Program Impacts for FY 2025 Through FY 2027
----------------------------------------------------------------------------------------------------------------
                                                              Per SNF                        All SNFs
                                                 ---------------------------------------------------------------
      Total benefit for the FY2025 SNF QRP           Change in                       Change in
                                                   annual burden     Change in     annual burden     Change in
                                                       hours        annual cost        hours        annual cost
----------------------------------------------------------------------------------------------------------------
Decrease in burden from the removal of the                (0.78)           ($67)        (12,032)    ($1,037,261)
 Functional Assessment/Care Plan measure........
----------------------------------------------------------------------------------------------------------------
                                       Total burden for the FY2026 SNF QRP
----------------------------------------------------------------------------------------------------------------
Total burden for SNFs exempt from the proposed              1.36              77          13,941         866,772
 CoreQ: SS DC measure reporting AND Increase in
 burden from the addition of the Patient/
 Resident COVID-19 Vaccine measure..............
Total burden for SNFs participating in the                 18.28           5,049         224,885      61,580,090
 proposed CoreQ: SS DC measure reporting AND
 Increase in burden from the addition of the
 Patient/Resident COVID-19 Vaccine measure......
----------------------------------------------------------------------------------------------------------------
                                      Total burden for the FY 2027 SNF QRP
----------------------------------------------------------------------------------------------------------------
Total for SNFs exempt from the proposed CoreQ:              0.58           26.95           1,898          88,181
 SS DC measure reporting........................
Total for SNFs participating in the proposed                  26           1,208         316,238      63,344,417
 CoreQ: SS DC measure reporting.................
----------------------------------------------------------------------------------------------------------------

    We invite public comments on the overall impact of the SNF QRP 
proposals for FY 2025, 2026 and 2027.
6. Impacts for the SNF VBP Program
    The estimated impacts of the FY 2024 SNF VBP Program are based on 
historical data and appear in Table 37. We modeled SNF performance in 
the Program using SNFRM data from FY 2019 as the baseline period and FY 
2021 as the performance period. Additionally, we modeled a logistic 
exchange function with a payback percentage of 60 percent, as we 
finalized in the FY 2018 SNF PPS final rule (82 FR 36619 through 
36621).
    For the FY 2024 year, we will award each participating SNF 60 
percent of their 2 percent withhold. Additionally, in the FY 2023 SNF 
PPS final rule (87 FR 47585 through 47587), we finalized our proposal 
to apply a case minimum requirement for the SNFRM. As a result of these 
provisions, SNFs that do not meet the case minimum specified for the 
SNFRM for the FY 2024 program year will be excluded from the Program 
and will receive their full Federal per diem rate for that fiscal year. 
As previously finalized, this policy will maintain the overall payback 
percentage at 60 percent for the FY 2024 program year. Based on the 60 
percent payback percentage, we estimated that we would redistribute 
approximately $277.27 million (of the estimated $462.12 million in 
withheld funds) in value-based incentive payments to SNFs in FY 2024, 
which means that the SNF VBP Program is estimated to result in 
approximately $184.85 million in savings to the Medicare Program in FY 
2024.
    Our detailed analysis of the impacts of the FY 2024 SNF VBP Program 
is shown in Table 37.

[[Page 21411]]



                             Table 37--Estimated SNF VBP Program Impacts for FY 2024
----------------------------------------------------------------------------------------------------------------
                                                    Mean risk-
                                                   standardized        Mean       Mean incentive
         Characteristic              Number of      readmission     performance       payment       Percent of
                                    facilities     rate (SNFRM)        score        multiplier     total payment
                                                        (%)
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total *.........................          11,176           20.47         28.3029         0.99140          100.00
Urban...........................           8,710           20.58         27.1026         0.99084           87.12
Rural...........................           2,436           20.07         32.7202         0.99346           12.88
Hospital-based urban **.........             196           19.92         36.8240         0.99531            1.72
Freestanding urban **...........           8,501           20.60         26.8949         0.99074           85.38
Hospital-based rural **.........              87           19.58         39.2697         0.99636            0.36
Freestanding rural **...........           2,275           20.08         32.6780         0.99347           12.38
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................             627           20.62         27.4602         0.99121            5.45
Middle Atlantic.................           1,287           20.35         30.2740         0.99220           18.03
South Atlantic..................           1,691           20.83         25.4855         0.99011           17.75
East North Central..............           1,593           20.88         22.3914         0.98856           12.69
East South Central..............             468           20.83         24.1778         0.98938            3.55
West North Central..............             620           20.24         29.7294         0.99207            3.87
West South Central..............             912           21.11         18.7872         0.98700            6.75
Mountain........................             384           19.95         34.9771         0.99429            3.79
Pacific.........................           1,125           19.93         36.2085         0.99528           15.24
Outlying........................               3           20.46         23.6945         0.98431            0.00
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................              75           19.51         40.6317         0.99752            0.55
Middle Atlantic.................             164           19.56         39.1621         0.99692            0.91
South Atlantic..................             340           20.37         29.6459         0.99162            2.06
East North Central..............             602           19.94         33.4406         0.99376            3.07
East South Central..............             383           20.48         28.5196         0.99167            2.14
West North Central..............             364           19.81         34.7097         0.99451            1.29
West South Central..............             345           20.74         24.3765         0.98937            1.68
Mountain........................              92           19.34         42.4305         0.99792            0.53
Pacific.........................              71           18.48         58.5164         1.00597            0.64
Outlying........................               0
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
Government......................             464           19.98         34.5948         0.99435            2.86
Profit..........................           8,101           20.60         26.4146         0.99049           75.05
Non-Profit......................           2,581           20.16         33.2172         0.99378           22.08
----------------------------------------------------------------------------------------------------------------
* The total group category excludes 3,721 SNFs that failed to meet the finalized measure minimum policy. The
  total group category includes 30 SNFs that did not have facility characteristics in the CMS Provider of
  Services (POS) file or historical payment data used for this analysis.
** The group category which includes hospital-based/freestanding by urban/rural excludes 87 swing bed SNFs that
  satisfied the current measure minimum policy.

    In section VII.B.4.b. of this proposed rule, we are proposing to 
adopt one additional measure (Nursing Staff Turnover measure) beginning 
with the FY 2026 program year. Additionally, in section VII.E.2.b. of 
this proposed rule, we are proposing to adopt a case minimum 
requirement for the Nursing Staff Turnover measure. In section 
VII.E.2.c. of this proposed rule, we are proposing to maintain the 
previously finalized measure minimum for FY 2026. Therefore, we are 
providing estimated impacts of the FY 2026 SNF VBP Program, which are 
based on historical data and appear in Tables 38 and 39. We modeled SNF 
performance in the Program using measure data from FY 2019 as the 
baseline period and FY 2021 as the performance period for the SNFRM, 
SNF HAI, Total Nurse Staffing, and Nursing Staff Turnover measures. 
Additionally, we modeled a logistic exchange function with a payback 
percentage of 60 percent. Based on the 60 percent payback percentage, 
we estimated that we will redistribute approximately $294.75 million 
(of the estimated $491.24 million in withheld funds) in value-based 
incentive payments to SNFs in FY 2026, which means that the SNF VBP 
Program is estimated to result in approximately $196.50 million in 
savings to the Medicare Program in FY 2026.
    Our detailed analysis of the impacts of the FY 2026 SNF VBP Program 
is shown in Tables 38 and 39.

[[Page 21412]]



                             Table 38--Estimated SNF VBP Program Impacts for FY 2026
----------------------------------------------------------------------------------------------------------------
                                                                                    Mean risk-
                                                    Mean risk-      Mean total     standardized     Mean total
                                                   standardized    nursing hours      rate of      nursing staff
         Characteristic              Number of      readmission    per resident      hospital-     turnover rate
                                    facilities     rate (SNFRM)     day (total       acquired     (nursing staff
                                                        (%)            nurse        infections     turnover) (%)
                                                                     staffing)     (SNF HAI) (%)
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total *.........................          13,879           20.39            3.91            7.67           52.74
Urban...........................          10,266           20.52            3.93            7.69           52.43
Rural...........................           3,613           20.04            3.87            7.61           53.62
Hospital-based urban **.........             239           20.01            5.22            6.52           45.90
Freestanding urban **...........          10,018           20.53            3.90            7.72           52.57
Hospital-based rural **.........             143           19.75            4.82            6.88           45.57
Freestanding rural **...........           3,399           20.04            3.83            7.68           53.93
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................             706           20.54            4.04            7.09           45.50
Middle Atlantic.................           1,408           20.31            3.68            7.55           46.06
South Atlantic..................           1,810           20.77            4.01            7.86           51.79
East North Central..............           1,956           20.74            3.59            7.72           55.47
East South Central..............             538           20.73            3.96            8.02           55.78
West North Central..............             839           20.18            4.19            7.41           57.73
West South Central..............           1,207           20.97            3.74            8.02           59.10
Mountain........................             490           19.94            4.15            7.15           56.54
Pacific.........................           1,309           19.98            4.45            7.84           46.97
Outlying........................               3           20.46            3.30            6.20             N/A
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................             106           19.55            4.30            6.63           54.74
Middle Atlantic.................             192           19.60            3.42            7.17           53.04
South Atlantic..................             432           20.24            3.72            7.79           52.83
East North Central..............             802           19.94            3.63            7.46           53.02
East South Central..............             451           20.43            3.93            8.18           51.90
West North Central..............             802           19.85            4.12            7.50           53.49
West South Central..............             577           20.58            3.82            7.99           55.76
Mountain........................             168           19.54            4.18            7.16           55.96
Pacific.........................              83           18.64            4.34            6.73           53.75
Outlying........................               0
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
Government......................             735           20.00            4.34            7.36           48.93
Profit..........................           9,975           20.51            3.72            7.89           54.29
Non-Profit......................           3,169           20.11            4.43            7.04           48.74
----------------------------------------------------------------------------------------------------------------
* The total group category excludes 1,028 SNFs that failed to meet the finalized measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 80 swing bed SNFs that
  satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.


                             Table 39--Estimated SNF VBP Program Impacts for FY 2026
----------------------------------------------------------------------------------------------------------------
                                                                       Mean       Mean incentive
                 Characteristic                      Number of      performance       payment       Percent of
                                                    facilities         score        multiplier     total payment
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total *.........................................          13,879         24.5877         0.99108          100.00
Urban...........................................          10,266         24.4964         0.99106           85.88
Rural...........................................           3,613         24.8470         0.99112           14.12
Hospital-based urban **.........................             239         40.2184         1.00671            1.60
Freestanding urban **...........................          10,018         24.1217         0.99069           84.26
Hospital-based rural **.........................             143         41.0606         1.00583            0.38
Freestanding rural **...........................           3,399         24.0807         0.99041           13.62
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................................             706         30.1328         0.99463            5.31

[[Page 21413]]

 
Middle Atlantic.................................           1,408         26.0014         0.99182           17.27
South Atlantic..................................           1,810         24.1128         0.99014           17.07
East North Central..............................           1,956         18.8610         0.98737           12.69
East South Central..............................             538         21.3335         0.98858            3.49
West North Central..............................             839         26.4267         0.99302            3.99
West South Central..............................           1,207         16.8688         0.98557            7.20
Mountain........................................             490         27.4320         0.99295            3.81
Pacific.........................................           1,309         34.7925         0.99925           15.02
Outlying........................................               3         21.6999         0.98682            0.00
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................................             106         33.4096         0.99729            0.59
Middle Atlantic.................................             192         22.9268         0.98939            0.91
South Atlantic..................................             432         21.3377         0.98797            2.10
East North Central..............................             802         22.3282         0.98960            3.20
East South Central..............................             451         24.1187         0.99020            2.17
West North Central..............................             802         29.2268         0.99485            1.80
West South Central..............................             577         21.1394         0.98792            2.10
Mountain........................................             168         30.0191         0.99532            0.63
Pacific.........................................              83         37.8989         1.00119            0.62
Outlying........................................               0  ..............  ..............            0.00
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
Government......................................             735         33.4591         0.99976            3.20
Profit..........................................           9,975         21.0738         0.98806           75.04
Non-Profit......................................           3,169         33.5907         0.99856           21.76
----------------------------------------------------------------------------------------------------------------
* The total group category excludes 1,028 SNFs that failed to meet the finalized measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 80 swing bed SNFs that
  satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.

    In section VII.B.4. of this proposed rule, we are proposing to 
adopt three additional measures (Falls with Major Injury (Long-Stay), 
DC Function, and Long Stay Hospitalization measures) beginning with the 
FY 2027 program year. Additionally, in section VII.E.2.b. of this 
proposed rule, we are proposing to adopt case minimum requirements for 
the Falls with Major Injury (Long-Stay), DC Function, and Long Stay 
Hospitalization measures. In section VII.E.2.d. of this proposed rule, 
we are also proposing to update our previously finalized measure 
minimum for the FY 2027 program year. Therefore, we are providing 
estimated impacts of the FY 2027 SNF VBP Program, which are based on 
historical data and appear in Tables 40 and 41. We modeled SNF 
performance in the Program using measure data from FY 2019 (SNFRM, SNF 
HAI, Total Nurse Staffing, Nursing Staff Turnover, Falls with Major 
Injury (Long-Stay), and DC Function measures), CY 2019 (Long Stay 
Hospitalization measure), and FY 2018 through FY 2019 (DTC PAC SNF 
measure) as the baseline period and FY 2021 (SNFRM, SNF HAI, Total 
Nurse Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-
Stay), and DC Function measures), CY 2021 (Long Stay Hospitalization 
measure), and FY 2020 through FY 2021 (DTC PAC SNF measure) as the 
performance period. Additionally, we modeled a logistic exchange 
function with an approximate payback percentage of 66.02 percent, as we 
propose in section VII.E.4.e. of this proposed rule. Based on the 
increase in payback percentage, we estimated that we will redistribute 
approximately $324.18 million (of the estimated $491.03 million in 
withheld funds) in value-based incentive payments to SNFs in FY 2027, 
which means that the SNF VBP Program is estimated to result in 
approximately $166.86 million in savings to the Medicare Program in FY 
2027.
    Our detailed analysis of the impacts of the FY 2027 SNF VBP Program 
is shown in Tables 40 and 41.

[[Page 21414]]



                                                                     Table 40--Estimated SNF VBP Program Impacts for FY 2027
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                                 Mean number of        Mean            Mean
                                                                                 Mean case-mix                                                    risk-adjusted    percentage of   percentage of
                                                                  Mean risk-    adjusted total    Mean risk-      Mean total      Mean risk-    hospitalizations   stays meeting   stays with a
                                                                 standardized    nursing hours   standardized    nursing staff   standardized    per 1,000 long-   or exceeding      fall with
                Characteristic                     Number of      readmission    per resident      hospital-     turnover rate   discharge to     stay resident      expected      major injury
                                                  facilities     rate (SNFRM)     day (total       acquired     (nursing staff  community rate   days (long stay     discharge      (falls with
                                                                      (%)            nurse      infection rate   turnover) (%)   (DTC PAC) (%)  hospitalization)  function score   major injury
                                                                                   staffing)     (SNF HAI) (%)                                     (Hosp. per      (DC function)   (long-stay))
                                                                                                                                                     1,000)             (%)             (%)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                              Group
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total *.......................................          13,672           20.39            3.92            7.68           52.64           51.28             1.47            51.96            3.36
Urban.........................................          10,083           20.52            3.94            7.69           52.30           52.03             1.50            51.72            3.07
Rural.........................................           3,589           20.03            3.86            7.63           53.58           49.18             1.39            52.61            4.16
Hospital-based urban **.......................             227           20.00            5.26            6.47           46.33           60.97             1.10            46.90            2.17
Freestanding urban **.........................           9,852           20.53            3.91            7.72           52.42           51.82             1.51            51.84            3.09
Hospital-based rural **.......................             138           19.72            4.84            6.86           45.96           52.78             1.07            49.82            4.22
Freestanding rural **.........................           3,409           20.04            3.82            7.68           53.87           48.80             1.40            52.85            4.16
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                         Urban by region
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
New England...................................             706           20.54            4.05            7.09           45.51           55.47             1.41            56.04            3.67
Middle Atlantic...............................           1,397           20.31            3.67            7.56           45.98           49.63             1.40            54.87            2.95
South Atlantic................................           1,805           20.76            4.02            7.86           51.79           52.38             1.52            50.96            3.10
East North Central............................           1,871           20.76            3.62            7.72           55.11           52.56             1.52            48.29            3.23
East South Central............................             533           20.75            3.97            8.04           55.79           50.89             1.49            48.03            3.37
West North Central............................             827           20.17            4.19            7.41           57.62           51.24             1.51            55.00            3.82
West South Central............................           1,183           20.98            3.74            8.03           58.96           49.37             1.73            52.38            3.24
Mountain......................................             472           19.93            4.16            7.13           56.75           57.52             1.17            55.02            2.96
Pacific.......................................           1,286           19.97            4.44            7.84           47.08           52.86             1.52            49.62            1.89
Outlying......................................               3           20.46            3.30            6.20             N/A           66.54              N/A            50.77            0.00
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                         Rural by region
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
New England...................................             108           19.54            4.32            6.65           54.60           53.27             1.04            57.92            4.18
Middle Atlantic...............................             191           19.57            3.41            7.13           52.89           47.82             1.13            53.15            3.99
South Atlantic................................             421           20.24            3.73            7.79           52.89           48.10             1.42            49.41            3.84
East North Central............................             799           19.94            3.63            7.47           52.80           51.48             1.30            49.59            4.14
East South Central............................             439           20.42            3.92            8.25           51.98           48.11             1.57            48.57            3.65
West North Central............................             800           19.84            4.10            7.51           53.61           47.74             1.35            56.70            4.77
West South Central............................             577           20.55            3.82            8.02           55.64           47.69             1.73            53.31            4.17
Mountain......................................             173           19.55            4.17            7.16           55.65           51.94             1.02            58.19            4.22
Pacific.......................................              81           18.63            4.32            6.76           54.33           54.64             0.96            55.69            3.11
Outlying......................................               0
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                         Rural by region
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Government....................................             717           19.96            4.34            7.38           49.01           50.37             1.41            51.75            3.80
Profit........................................           9,825           20.52            3.73            7.90           54.16           50.32             1.53            51.24            3.17
Non-Profit....................................           3,130           20.10            4.44            7.04           48.71           54.49             1.33            54.25            3.85
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
* The total group category excludes 1,235 SNFs that failed to meet the proposed four out of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 46 swing bed SNFs that satisfied the proposed measure minimum policy.
N/A = Not available because no facilities in this group received a measure result.


[[Page 21415]]


                             Table 41--Estimated SNF VBP Program Impacts for FY 2027
----------------------------------------------------------------------------------------------------------------
                                                    Mean health        Mean       Mean incentive
         Characteristic              Number of     equity bonus     performance       payment       Percent of
                                    facilities      points ***      score ****      multiplier     total payment
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total *.........................          13,672          1.3922         32.9455         0.99185          100.00
Urban...........................          10,083          1.4065         33.2266         0.99208           85.82
Rural...........................           3,589          1.3522         32.1558         0.99119           14.18
Hospital-based urban **.........             227          1.0527         45.8943         1.00332            1.59
Freestanding urban **...........           9,852          1.4151         32.9329         0.99182           84.23
Hospital-based rural **.........             138          1.0851         43.4161         1.00072            0.38
Freestanding rural **...........           3,409          1.3752         31.5523         0.99069           13.70
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................             706          1.6512         37.2281         0.99477            5.32
Middle Atlantic.................           1,397          1.5283         34.0874         0.99249           17.29
South Atlantic..................           1,805          1.2317         32.5500         0.99129           17.10
East North Central..............           1,871          0.9931         28.9562         0.98911           12.59
East South Central..............             533          0.9183         29.0674         0.98909            3.49
West North Central..............             827          0.7315         32.7553         0.99175            3.98
West South Central..............           1,183          1.3010         27.3676         0.98777            7.18
Mountain........................             472          1.0725         39.2626         0.99648            3.82
Pacific.........................           1,286          2.8460         42.4505         0.99940           15.04
Outlying........................               3          0.0000         36.5564         0.99256            0.00
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................             108          1.9869         42.3485         0.99953            0.61
Middle Atlantic.................             191          1.7348         31.4130         0.99020            0.91
South Atlantic..................             421          1.6187         29.0528         0.98846            2.09
East North Central..............             799          1.1916         31.2626         0.99059            3.22
East South Central..............             439          1.6169         29.8730         0.98945            2.16
West North Central..............             800          0.6760         33.9294         0.99251            1.81
West South Central..............             577          1.7368         29.1213         0.98892            2.12
Mountain........................             173          1.3443         39.8837         0.99746            0.64
Pacific.........................              81          2.3226         45.2226         1.00188            0.62
Outlying........................               0  ..............  ..............  ..............            0.00
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
Government......................             717          1.5059         37.5369         0.99586            3.17
Profit..........................           9,825          1.5991         30.8612         0.99018           75.10
Non-Profit......................           3,130          0.7168         38.4361         0.99618           21.72
----------------------------------------------------------------------------------------------------------------
* The total group category excludes 1,235 SNFs that failed to meet the proposed four out of eight measure
  minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 46 swing bed SNFs that
  satisfied the proposed measure minimum policy.
*** Because performance scores are capped at 100 points, SNFs may not receive all health equity bonus points
  they earn.
**** The mean total performance score is calculated by adding the proposed Health Equity Adjustment bonus points
  to the normalized sum of individual measure scores.
N/A = Not available because no facilities in this group received a measure result.

    In section VII.B.3. of this proposed rule, we are proposing to 
replace the SNFRM with the SNF WS PPR measure beginning with the FY 
2028 program year. Additionally, in section VII.E.2.b. of this rule, we 
are proposing to adopt a case minimum requirement for the SNF WS PPR 
measure. Therefore, we are providing estimated impacts of the FY 2028 
SNF VBP Program, which are based on historical data and appear in 
Tables 42 and 43. We modeled SNF performance in the Program using 
measure data from FY 2019 (SNF HAI, Total Nurse Staffing, Nursing Staff 
Turnover, Falls with Major Injury (Long-Stay), and DC Function 
measures), CY 2019 (Long Stay Hospitalization measure), FY 2018 through 
FY 2019 (DTC PAC SNF measure), and FY 2019 through FY 2020 (SNF WS PPR 
measure) as the baseline period and FY 2021 (SNF HAI, Total Nurse 
Staffing, Nursing Staff Turnover, Falls with Major Injury (Long-Stay), 
and DC Function measures), CY 2021 (Long Stay Hospitalization measure), 
FY 2020 through FY 2021(DTC PAC SNF measure), and FY 2020 through FY 
2021 (SNF WS PPR measure) as the performance period. Additionally, we 
modeled a logistic exchange function with an approximate payback 
percentage of 65.4 percent, as we propose in section VII.E.4.e. of this 
proposed rule. Based on the increase in payback percentage, we 
estimated that we will redistribute approximately $323.23 million (of 
the estimated $494.21 million in withheld funds) in value-based 
incentive payments to SNFs in FY 2028, which means that the SNF VBP 
Program is estimated to result in approximately $170.98 million in 
savings to the Medicare Program in FY 2028.
    Our detailed analysis of the impacts of the FY 2028 SNF VBP Program 
is shown in Tables 42 and 43.

[[Page 21416]]



                                                 Table 42--Estimated SNF VBP Program Impacts for FY 2028
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                    Mean         Mean
                                                                                    Mean total                 Mean number of    percentage   percentage
                                             Mean SNF    Mean total   Mean risk-     nursing                    risk-adjusted     of stays     of stays
                                           within-stay    nursing    standardized     staff      Mean risk-   hospitalizations   meeting or  with a fall
                                           potentially   hours per     hospital-     turnover   standardized   per 1,000 long-   exceeding    with major
       Characteristic          Number of   preventable    resident     acquired        rate     discharge to    stay resident     expected      injury
                               facilities  readmission   day (total    infection     (nursing     community    days (Long Stay   discharge   (falls with
                                            rate (SNF      nurse       rate (SNF      staff       rate (DTC   Hospitalization)    function      major
                                           WS PPR) (%)   staffing)     HAI) (%)     turnover)     PAC) (%)       (Hosp. per      score (DC      injury
                                                                                       (%)                         1,000)        Function)      (long-
                                                                                                                                    (%)       stay)) (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                          Group
--------------------------------------------------------------------------------------------------------------------------------------------------------
Total *.....................       14,048        11.57         3.92          7.67        52.74         51.18            1.47          51.96         3.36
Urban.......................       10,313        11.71         3.94          7.69        52.41         51.94            1.51          51.75         3.07
Rural.......................        3,735        11.18         3.87          7.62        53.66         49.10            1.39          52.53         4.15
Hospital-based urban **.....          230         9.07         5.26          6.48        46.22         60.88            1.10          46.91         2.27
Freestanding urban **.......       10,079        11.77         3.91          7.72        52.53         51.73            1.51          51.87         3.09
Hospital-based rural **.....          142         9.44         4.84          6.88        45.96         52.54            1.06          49.90         4.19
Freestanding rural **.......        3,548        11.30         3.83          7.67        53.95         48.71            1.40          52.75         4.14
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     Urban by region
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England.................          712        10.70         4.05          7.09        45.49         55.47            1.41          55.98         3.67
Middle Atlantic.............        1,411        11.66         3.67          7.56        46.02         49.60            1.40          54.80         2.95
South Atlantic..............        1,827        11.86         4.04          7.85        51.78         52.34            1.53          51.03         3.11
East North Central..........        1,935        11.88         3.61          7.73        55.28         52.39            1.52          48.33         3.22
East South Central..........          539        11.77         3.96          8.03        55.87         50.88            1.49          48.20         3.34
West North Central..........          858        11.27         4.17          7.41        57.92         51.11            1.51          55.12         3.83
West South Central..........        1,235        12.75         3.73          8.02        59.06         49.27            1.73          52.68         3.21
Mountain....................          482        10.17         4.17          7.14        56.57         57.32            1.17          54.76         2.98
Pacific.....................        1,310        11.70         4.45          7.84        47.13         52.81            1.53          49.52         1.90
Outlying....................            4         8.14         4.70          6.52          N/A         64.89             N/A          47.36         0.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                     Rural by region
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England.................          112         9.98         4.33          6.67        54.86         52.92            1.05          57.56         4.20
Middle Atlantic.............          195        10.38         3.41          7.16        53.05         47.85            1.14          52.95         3.94
South Atlantic..............          436        11.43         3.72          7.76        53.00         48.14            1.42          49.32         3.79
East North Central..........          824        10.90         3.63          7.48        53.03         51.45            1.30          49.40         4.12
East South Central..........          451        12.06         3.93          8.23        51.93         48.13            1.57          48.54         3.64
West North Central..........          854        10.77         4.12          7.50        53.54         47.56            1.34          56.37         4.72
West South Central..........          603        12.40         3.83          8.02        55.74         47.62            1.72          53.46         4.16
Mountain....................          178        10.02         4.17          7.15        55.81         51.79            1.03          58.21         4.25
Pacific.....................           82         9.32         4.37          6.76        54.33         54.46            0.97          56.23         3.12
Outlying....................            0
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                        Ownership
--------------------------------------------------------------------------------------------------------------------------------------------------------
Government..................          737        10.84         4.36          7.38        48.97         50.33            1.42          51.79         3.85
Profit......................       10,119        11.98         3.72          7.90        54.28         50.25            1.52          51.27         3.17
Non-Profit..................        3,192        10.45         4.45          7.04        48.74         54.35            1.32          54.19         3.85
--------------------------------------------------------------------------------------------------------------------------------------------------------
* The total group category excludes 859 SNFs that failed to meet the proposed four of eight measure minimum policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 49 swing bed SNFs that satisfied the proposed measure minimum
  policy.
N/A = Not available because no facilities in this group received a measure result.


                             Table 43--Estimated SNF VBP Program Impacts for FY 2028
----------------------------------------------------------------------------------------------------------------
                                                    Mean health        Mean       Mean incentive
         Characteristic              Number of     equity bonus     performance       payment       Percent of
                                    facilities      points ***      score ****      multiplier     total payment
----------------------------------------------------------------------------------------------------------------
                                                      Group
----------------------------------------------------------------------------------------------------------------
Total *.........................          14,048          1.3866         33.7117         0.99216          100.00
Urban...........................          10,313          1.3834         33.8699         0.99229           85.72
Rural...........................           3,735          1.3952         33.2749         0.99180           14.28
Hospital-based urban **.........             230          1.0999         50.6699         1.00718            1.59
Freestanding urban **...........          10,079          1.3903         33.4786         0.99194           84.13
Hospital-based rural **.........             142          1.1789         46.3840         1.00274            0.38
Freestanding rural **...........           3,548          1.4162         32.4459         0.99108           13.80
----------------------------------------------------------------------------------------------------------------
                                                 Urban by region
----------------------------------------------------------------------------------------------------------------
New England.....................             712          1.6450         38.8562         0.99580            5.30
Middle Atlantic.................           1,411          1.4441         34.5592         0.99248           17.19
South Atlantic..................           1,827          1.2259         33.1678         0.99158           17.04
East North Central..............           1,935          1.0242         29.8652         0.98953           12.61
East South Central..............             539          0.9089         30.1968         0.98983            3.48
West North Central..............             858          0.7433         33.4543         0.99206            4.01

[[Page 21417]]

 
West South Central..............           1,235          1.2998         28.0800         0.98804            7.28
Mountain........................             482          1.1398         41.1899         0.99784            3.83
Pacific.........................           1,310          2.7134         41.8142         0.99832           14.99
Outlying........................               4          0.0000         49.0903         1.00665            0.00
----------------------------------------------------------------------------------------------------------------
                                                 Rural by region
----------------------------------------------------------------------------------------------------------------
New England.....................             112          2.1095         43.5189         1.00029            0.61
Middle Atlantic.................             195          1.6914         32.6276         0.99092            0.91
South Atlantic..................             436          1.6562         30.1287         0.98926            2.10
East North Central..............             824          1.2515         32.2562         0.99102            3.24
East South Central..............             451          1.6207         30.7335         0.99007            2.16
West North Central..............             854          0.7418         35.6622         0.99352            1.85
West South Central..............             603          1.7832         29.8043         0.98910            2.14
Mountain........................             178          1.4983         41.1638         0.99796            0.64
Pacific.........................              82          2.2569         45.2986         1.00159            0.62
Outlying........................               0  ..............  ..............  ..............            0.00
----------------------------------------------------------------------------------------------------------------
                                                    Ownership
----------------------------------------------------------------------------------------------------------------
Government......................             737          1.5601         38.6989         0.99642            3.18
Profit..........................          10,119          1.5762         31.3261         0.99022           75.13
Non-Profit......................           3,192          0.7454         40.1229         0.99730           21.69
----------------------------------------------------------------------------------------------------------------
* The total group category excludes 859 SNFs that failed to meet the proposed four out of eight measure minimum
  policy.
** The group category that includes hospital-based/freestanding by urban/rural excludes 49 swing bed SNFs that
  satisfied the proposed measure minimum policy.
*** Because performance scores are capped at 100 points, SNFs may not receive all health equity bonus points
  they earn.
**** The mean total performance score is calculated by adding the proposed Health Equity Adjustment bonus points
  to the normalized sum of individual measure scores.
N/A = Not available because no facilities in this group received a measure result.

7. Impacts for Civil Money Penalties (CMP): Waiver Process Changes
    Current requirements at Sec.  488.436(a) set forth a process for 
submitting a written waiver of a hearing to appeal deficiencies that 
lead to the imposition of a CMP which, when properly filed, results in 
the reduction by CMS or the State of a facility's CMP by 35 percent, as 
long as the CMP has not also been reduced by 50 percent under Sec.  
488.438. We propose to restructure the waiver process by establishing a 
constructive waiver at Sec.  488.436(a) that would operate by default 
when CMS has not received a timely request for a hearing. Since a large 
majority of facilities facing CMPs typically submit the currently 
required express, written waiver, this proposed change to provide for a 
constructive waiver (after the 60-day timeframe in which to file an 
appeal following notice of CMP imposition) would reduce the costs and 
paperwork burden for most facilities.
    In CY 2022, 81 percent of facilities facing CMPs filed an express 
waiver; whereas only 2 percent of facilities facing CMPs filed an 
appeal and went through the hearing process. The remaining 17 percent 
of facilities are those who fail to waive at all or fail to waive 
timely when they do not appeal. We estimate that moving to a 
constructive waiver process would eliminate the time and paperwork 
necessary to complete and send in a written waiver and would thereby 
result, as detailed below, in a total annual savings of $2,299,716 in 
administrative costs for LTC facilities facing CMPs as estimated in the 
following savings estimates ($861,678 plus $1,438,038 = $2,299,716).
    We estimate that, at a minimum, facilities would save the routine 
cost of preparing and filing a letter (estimated at $200 per letter) to 
waive their hearing rights. In CY 2022, there were 5,319 facilities who 
were imposed CMPs. Roughly 81 percent (4,308) of these facilities filed 
an express, written waiver, therefore, we estimate an annual savings of 
$861,678 (4,308 x $200) since such letters would no longer be required 
to receive a 35 percent penalty reduction.
    In addition, we believe that nationally some 17 percent of 
facilities fail to submit a waiver even though they had no intention of 
contesting the penalty and its basis. Under the proposed change to 
offer a constructive waiver by default, this 17 percent of facilities 
would now be eligible for the 35 percent CMP amount cost reduction. We 
note that in CY 2022, CMS imposed a combined total of $190,967,833 in 
per day and per instance CMPs, with a median total amount due of 
$4,545. Since CMS imposed CMPs on 5,319 facilities in CY 2022, we 
estimate a cost savings for 904 facilities (17 percent of 5,319), the 
typical 17 percent who fail to submit a timely waiver request. We 
estimate the annual cost savings for these facilities at $1,438,038 
((35 percent x $4,545) x 904 facilities).
    Furthermore, we believe that the proposal to offer facilities a 
constructive waiver process would also ease the administrative burden 
for the CMS Locations. Based on our knowledge and experience, we 
estimate that, together, an array of individuals in each CMS Location 
collectively spend close to one hour (0.80 hours) per cases where a CMP 
is imposed to track and manage receipt of paperwork from facilities 
expressly requesting a waiver. Given that in CY 2022, CMS imposed a 
total of 11,475 CMPs on 5,319 facilities, with an average of 2.16 CMPs 
per facility, we estimate that CMS Locations spend a total of 9,191 
hours each year (0.80 hours per CMP x 5,319 facilities x 2.16 CMPs per 
facility) to manage the waiver paperwork. As noted previously in this 
section, in CY 2022 we saw that 81 percent (4,308) of the 5,319 
facilities with imposed CMPs submitted written waivers. Because the 
activities involved

[[Page 21418]]

in processing facilities' written waivers requires input from 
individuals at varying levels within CMS, we base our estimate on the 
rate of $84.00 per hour on average, assuming a GS-12, step 5 salary 
rate of $42.00 per hour with a 100 percent benefits and overhead 
package. Thus, we estimate that CMS would save $772,044 per year 
($84.00 per hour x 9,191 hours per year).
    Total annual savings from these reforms to facilities and the 
Federal government together would therefore be $3,071,760 ($2,299,716 
plus $772,044).
8. Alternatives Considered
    As described in this section, we estimate that the aggregate impact 
of the provisions in this proposed rule will result in an increase of 
approximately $1.2 billion (3.7 percent) in Part A payments to SNFs in 
FY 2024. This reflects a $2 billion (6.1 percent) increase from the 
proposed update to the payment rates and a $745 million (2.3 percent) 
decrease as a result of the second phase of the parity adjustment 
recalibration, using the formula to multiply the percentage change 
described in section III.A.4. of this proposed rule.
    Section 1888(e) of the Act establishes the SNF PPS for the payment 
of Medicare SNF services for cost reporting periods beginning on or 
after July 1, 1998. This section of the statute prescribes a detailed 
formula for calculating base payment rates under the SNF PPS, and does 
not provide for the use of any alternative methodology. It specifies 
that the base year cost data to be used for computing the SNF PPS 
payment rates must be from FY 1995 (October 1, 1994, through September 
30, 1995). In accordance with the statute, we also incorporated a 
number of elements into the SNF PPS (for example, case-mix 
classification methodology, a market basket update, a wage index, and 
the urban and rural distinction used in the development or adjustment 
of the Federal rates). Further, section 1888(e)(4)(H) of the Act 
specifically requires us to disseminate the payment rates for each new 
FY through the Federal Register, and to do so before the August 1 that 
precedes the start of the new FY; accordingly, we are not pursuing 
alternatives for this process.
    With regard to the proposal to modify the COVID-19 Vaccination 
Coverage Among Healthcare Personnel (HCP COVID-19 Vaccine) measure and 
to adopt the COVID-19 Vaccine: Percent of Patients/Residents Who are Up 
to Date (Patient/Resident COVID-19 Vaccine) measure to the SNF QRP 
Program, the COVID-19 pandemic has exposed the importance of 
implementing infection prevention strategies, including the promotion 
of COVID-19 vaccination for healthcare personnel (HCP) and patients/
residents. We believe these measures would encourage healthcare 
personnel to be ``up to date'' with the COVID-19 vaccine, in accordance 
with current recommendations of the Centers for Disease Control and 
Prevention (CDC), and increase vaccine uptake in residents resulting in 
fewer cases, less hospitalizations, and lower mortality associated with 
the virus. However, we were unable to identify any alternative methods 
for collecting the data. There is still an overwhelming public need to 
target infection control and related quality improvement activities 
among SNF providers as well as provide data to patients and caregivers 
about the rate of COVID-19 vaccination among SNFs' healthcare personnel 
and residents through transparency of data. Therefore, these proposed 
measures have the potential to generate actionable data on COVID-19 
vaccination rates for SNFs.
    While we proposed to remove the Application of Percent of Long-Term 
Care Hospital Patients with an Admission and Discharge Functional 
Assessment and a Care Plan That Addresses Function (Application of 
Functional Assessment/Care Plan) process measure, we also propose to 
adopt the Discharge Function Score (DC Function) measure, which has 
strong scientific acceptability, and satisfies the requirement that 
there be at least one cross-setting function measure in the Post-Acute 
Care QRPs that uses standardized functional assessment data elements 
from standardized patient assessment instruments. We considered the 
alternative of delaying the proposal of the DC Function measure, but 
given its strong scientific acceptability, the fact that it provides an 
opportunity to replace the current cross-setting process measure with 
an outcome measure, and uses standardized functional assessment data 
elements that are already collected, we believe further delay is 
unwarranted. With regard to the proposal to remove the Application of 
Functional Assessment/Care Plan, the removal of this measure meets 
measure removal factors one and six set forth in Sec.  413.360(b)(2), 
and no longer provides meaningful distinctions in improvements in 
performance.
    The proposal to remove the Change in Self-Care Score and Change in 
Mobility Score measures meets measure removal factor eight set forth in 
Sec.  413.360(b)(2), and the costs associated with a measure outweigh 
the benefits of its use in the program. Therefore, no alternatives were 
considered.
    With regard to the proposal to adopt the CoreQ: Short Stay 
Discharge (CoreQ: SS DC) measure, the proposed measure fills a 
significant measurement gap in the SNF QRP: resident satisfaction with 
the quality of care received by SNFs. While the SNF QRP currently 
includes measures of process and outcomes that provide information on 
whether structural processes and interventions are working, measuring 
resident satisfaction would provide SNFs compelling information to use 
when examining the results of their clinical care, and can help SNFs 
identify deficiencies that other quality metrics may struggle to 
identify, such as communication between a resident and the SNF's 
clinical staff Additionally, the CoreQ survey, the basis of the CoreQ: 
SS DC measure, is already in use across the country by over 1,500 SNFs, 
and those SNFs that use the CoreQ survey(s) have reported they like the 
fact that the questionnaire is short (four questions), and residents 
report appreciation that their satisfaction (or lack thereof) is being 
measured. Therefore, given the importance of adding this domain 
measuring resident satisfaction to the SNF QRP, and the fact that the 
CoreQ: SS DC measure is a parsimonious survey that is highly reliable, 
valid and reportable, we believe adoption of the CoreQ: SS DC measure 
represents an essential addition to the SNF QRP measure set and no 
comparable alternative exists.
    With regard to the proposal to increase the data completion 
threshold for the Minimum Data Set (MDS) items submitted to meet the 
SNF QRP reporting requirements, the proposed increased threshold of 90 
percent is based on the need for substantially complete records, which 
allows appropriate analysis of quality measure data for the purposes of 
updating quality measure specifications. These data are ultimately 
reported to the public, allowing our beneficiaries to gain a more 
complete understanding of SNF performance related to these quality 
metrics, and helping them to make informed healthcare choices. We 
considered the alternative of not increasing the data completion 
threshold, but our data suggest that SNFs are already in compliance 
with or exceeding this proposed threshold, and therefore, there is no 
additional burden anticipated.
    With regard to the proposals for the SNF VBP Program, we discuss 
alternatives considered within those sections. In section VII.E.5. of 
this proposed rule, we discuss other approaches to incorporating health 
equity into the program.

[[Page 21419]]

9. Accounting Statement
    As required by OMB Circular A-4 (available online at https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/), in Tables 44 
through 49, we have prepared an accounting statement showing the 
classification of the expenditures associated with the provisions of 
this proposed rule for FY 2024. Tables 35 and 44 provide our best 
estimate of the possible changes in Medicare payments under the SNF PPS 
as a result of the policies in this proposed rule, based on the data 
for 15,435 SNFs in our database. Tables 36 and 45 through 47 provide 
our best estimate of the additional cost to SNFs to submit the data for 
the SNF QRP as a result of the policies in this proposed rule. Table 48 
provides our best estimate of the possible changes in Medicare payments 
under the SNF VBP as a result of the policies for this program. Table 
49 provides our best estimate of the amount saved by LTC facilities and 
CMS by removing the requirement to submit a written request and 
establishing a constructive waiver process instead at Sec.  488.436(a) 
that would operate by default when CMS has not received notice of a 
facility's intention to submit a timely request for a hearing.

       Table 44--Accounting Statement: Classification of Estimated
   Expenditures, From the 2023 SNF PPS Fiscal Year to the 2024 SNF PPS
                               Fiscal Year
------------------------------------------------------------------------
                Category                            Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers.........  $1.2 billion.*
From Whom To Whom?.....................  Federal Government to SNF
                                          Medicare Providers.
------------------------------------------------------------------------
* The net increase of $1.2 billion in transfer payments reflects a 3.7
  percent increase, which is the product of the multiplicative formula
  described in section XI.A.4 of this rule. It reflects the proposed 6.1
  percent SNF payment update increase (approximately $2 billion) from
  the proposed update to the payment rates, as well as a negative 2.3
  percent decrease (approximately $745 million) from the second phase of
  the parity adjustment recalibration. Due to rounding and the nature of
  the multiplicative formula, dollar figures are approximations and may
  not sum.


Table 45--Accounting Statement: Classification of Estimated Expenditures
                       for the FY 2025 QRP Program
------------------------------------------------------------------------
                        Category                         Transfers/costs
------------------------------------------------------------------------
Savings to SNFs to Submit Data for QRP.................    ($1,037,261)
------------------------------------------------------------------------


Table 46--Accounting Statement: Classification of Estimated Expenditures
                     for the FY 2026 SNF QRP Program
------------------------------------------------------------------------
                        Category                         Transfers/costs
------------------------------------------------------------------------
Costs for SNFs to Submit Data for QRP..................     $61,668,221
------------------------------------------------------------------------


Table 47--Accounting Statement: Classification of Estimated Expenditures
                     for the FY 2027 SNF QRP Program
------------------------------------------------------------------------
                        Category                         Transfers/costs
------------------------------------------------------------------------
Costs for SNFs to Submit Data for QRP..................     $63,432,598
------------------------------------------------------------------------


Table 48--Accounting Statement: Classification of Estimated Expenditures
                     for the FY 2024 SNF VBP Program
------------------------------------------------------------------------
                Category                            Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers.........  $277.27 million.*
From Whom To Whom?.....................  Federal Government to SNF
                                          Medicare Providers.
------------------------------------------------------------------------
* This estimate does not include the 2 percent reduction to SNFs'
  Medicare payments (estimated to be $462.12 million) required by
  statute.


    Table 49--Accounting Statement: Civil Money Penalties: Waiver of
                  Hearing, Reduction of Penalty Amount
------------------------------------------------------------------------
                        Category                         Transfers/costs
------------------------------------------------------------------------
Cost Savings of Constructive Waiver....................      $4,509,798
------------------------------------------------------------------------
* The cost savings of $4.5 million is expected to occur in the first
  full year and be an ongoing savings for LTC Facilities and the Federal
  Government.

10. Conclusion
    This rule updates the SNF PPS rates contained in the SNF PPS final 
rule for FY 2023 (87 FR 47502). Based on the above, we estimate that 
the overall payments for SNFs under the SNF PPS in FY 2024 are 
projected to increase by approximately $1.2 billion, or 3.7 percent, 
compared with those in FY 2023. We estimate that in FY 2024, SNFs in 
urban and rural areas would experience, on average, a 3.8 percent 
increase and 3.0 percent increase, respectively, in estimated payments 
compared with FY 2023. Providers in the urban Middle Atlantic region 
would experience the largest estimated increase in payments of 
approximately 5.1 percent. Providers in the urban Outlying region would 
experience the smallest estimated increase in payments of 1.4 percent.

B. Regulatory Flexibility Act Analysis

    The RFA requires agencies to analyze options for regulatory relief 
of small entities, if a rule has a significant impact on a substantial 
number of small entities. For purposes of the RFA, small entities 
include small businesses, non-profit organizations, and small 
governmental jurisdictions. Most SNFs and most other providers and 
suppliers are small entities, either by reason of their non-profit 
status or by having revenues of $30 million or less in any 1 year. We 
utilized the revenues of individual SNF providers (from recent Medicare 
Cost Reports) to classify a small business, and not the revenue of a 
larger firm with which they may be affiliated. As a result, for the 
purposes of the RFA, we estimate that almost all SNFs are small 
entities as that term is used in the RFA, according to the Small 
Business Administration's latest size standards (NAICS 623110), with 
total revenues of $30 million or less in any 1 year. (For details, see 
the Small Business Administration's website at https://www.sba.gov/category/navigation-structure/contracting/contracting-officials/eligibility-size-standards) In addition, approximately 20 percent of 
SNFs classified as small entities are non-profit organizations. 
Finally, individuals and states are not

[[Page 21420]]

included in the definition of a small entity.
    This rule updates the SNF PPS rates contained in the SNF PPS final 
rule for FY 2023 (87 FR 47502). Based on the above, we estimate that 
the aggregate impact for FY 2024 will be an increase of $1.2 billion in 
payments to SNFs, resulting from the proposed SNF market basket update 
to the payment rates, reduced by the second phase of the parity 
adjustment recalibration discussed in section III.C. of this proposed 
rule, using the formula described in section XI.A.4. of this rule. 
While it is projected in Table 34 that all providers would experience a 
net increase in payments, we note that some individual providers within 
the same region or group may experience different impacts on payments 
than others due to the distributional impact of the FY 2024 wage 
indexes and the degree of Medicare utilization.
    Guidance issued by the Department of Health and Human Services on 
the proper assessment of the impact on small entities in rulemakings, 
utilizes a cost or revenue impact of 3 to 5 percent as a significance 
threshold under the RFA. In their March 2023 Report to Congress 
(available at https://www.medpac.gov/wp-content/uploads/2023/03/Ch7_Mar23_MedPAC_Report_To_Congress_SEC.pdf), MedPAC states that 
Medicare covers approximately 10 percent of total patient days in 
freestanding facilities and 16 percent of facility revenue (March 2023 
MedPAC Report to Congress, 207). As indicated in Table 34, the effect 
on facilities is projected to be an aggregate positive impact of 3.7 
percent for FY 2024. As the overall impact on the industry as a whole, 
and thus on small entities specifically, exceeds the 3 to 5 percent 
threshold discussed previously, the Secretary has determined that this 
proposed rule will have a significant impact on a substantial number of 
small entities for FY 2024.
    In addition, section 1102(b) of the Act requires us to prepare a 
regulatory impact analysis if a rule 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. For 
purposes of section 1102(b) of the Act, we define a small rural 
hospital as a hospital that is located outside of an MSA and has fewer 
than 100 beds. This proposed rule will affect small rural hospitals 
that: (1) furnish SNF services under a swing-bed agreement or (2) have 
a hospital-based SNF. We anticipate that the impact on small rural 
hospitals would be similar to the impact on SNF providers overall. 
Moreover, as noted in previous SNF PPS final rules (most recently, the 
one for FY 2023 (87 FR 47502)), the category of small rural hospitals 
is included within the analysis of the impact of this proposed rule on 
small entities in general. As indicated in Table 19, the effect on 
facilities for FY 2024 is projected to be an aggregate positive impact 
of 3.7 percent. As the overall impact on the industry as a whole 
exceeds the 3 to 5 percent threshold discussed above, the Secretary has 
determined that this proposed rule will have a significant impact on a 
substantial number of small rural hospitals for FY 2024.

C. Unfunded Mandates Reform Act Analysis

    Section 202 of the Unfunded Mandates Reform Act of 1995 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 2023, that 
threshold is approximately $177 million. This proposed rule will impose 
no mandates on State, local, or Tribal governments or on the private 
sector.

D. Federalism Analysis

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it issues 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 will have no substantial direct effect 
on State and local governments, preempt State law, or otherwise have 
federalism implications.

E. Regulatory Review Costs

    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 this year's proposed rule will be the number of reviewers 
of last year's 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 this year's proposed rule in 
detail, and it is also possible that some reviewers chose not to 
comment on that proposed rule. For these reasons, we believe that the 
number of commenters on this year's proposed rule is a fair estimate of 
the number of reviewers of this year's 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.
    Using the national mean hourly wage data from the May 2021 BLS 
Occupational Employment and Wage Statistics (OEWS) for medical and 
health service managers (SOC 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 4 
hours for the staff to review half of the proposed rule. For each SNF 
that reviews the rule, the estimated cost is $460.88 (4 hours x 
$115.22). Therefore, we estimate that the total cost of reviewing this 
regulation is $3,129,719.04 ($460.88 x 6,849 reviewers).
    In accordance with the provisions of Executive Order 12866, this 
proposed rule was reviewed by the Office of Management and Budget.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on March 29, 2023.

List of Subjects

42 CFR Part 411

    Diseases, Medicare, Reporting and recordkeeping requirements.

42 CFR Part 413

    Diseases, Health facilities, Medicare, Puerto Rico, Reporting and 
recordkeeping.

42 CFR Part 488

    Administrative practice and procedure, Health facilities, Health 
professions, Medicare, Reporting and recordkeeping requirements.

42 CFR Part 489

    Health facilities, Medicare, Reporting and recordkeeping 
requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
& Medicaid Services proposes to amend 42 CFR chapter IV as set forth 
below:

PART 411--EXCLUSIONS FROM MEDICARE AND LIMITATIONS ON MEDICARE 
PAYMENT

0
1. The authority citation for part 411 continues to read as follows:


[[Page 21421]]


    Authority: 42 U.S.C. 1302, 1395w-101 through 1395w-152, 1395hh, 
and 1395nn.

0
2. Amend Sec.  411.15 by--
0
a. Redesignating paragraphs (p)(2)(vi) through (xviii) as (p)(2)(viii) 
through (xx); and
0
b. Adding new paragraphs (p)(2)(vi) and (vii).
    The additions read as follows:


Sec.  411.15  Particular services excluded from coverage.

* * * * *
    (p) * * *
    (2) * * *
    (vi) Services performed by a marriage and family therapist, as 
defined in section 1861(lll)(2) of the Act.
    (vii) Services performed by a mental health counselor, as defined 
in section 1861(lll)(4) of the Act.
* * * * *

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
3. 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), 1395m, 1395x(v), 1395x(kkk), 1395hh, 1395rr, 1395tt, 
and 1395ww.

0
4. Amend Sec.  413.338 by--
0
a. Removing the paragraph designations for paragraphs (a)(1) through 
(17);
0
b. Adding in paragraph (a) definitions in alphabetical order for 
``Health equity adjustment bonus points'', ``Measure performance 
scaler'', ``Top tier performing SNF'', ``Underserved multiplier'', and 
``Underserved population'';
0
c. Revising paragraphs (c)(2)(i), (d)(4)(v), and (e)(2) introductory 
text;
0
d. Adding paragraph (e)(3);
0
e. Revising paragraph (j)(1); and
0
f. Adding paragraphs (j)(2) and (3) and (k).
    The additions and revisions read as follows:


Sec.  413.338  Skilled nursing facility value-based purchasing program.

    (a) * * *
    Health equity adjustment (HEA) bonus points means the product of 
the measure performance scaler and the underserved multiplier.
* * * * *
    Measure performance scaler means the sum of the points assigned to 
a SNF for each measure on which the SNF is a top tier performing SNF.
* * * * *
    Top tier performing SNF means a SNF whose performance on a measure 
during the applicable program year meets or exceeds the 66.67th 
percentile of SNF performance on the measure during the same program 
year.
    Underserved multiplier means, for a SNF, the number representing 
the SNF's proportion of residents with DES out of its total resident 
population in the applicable program year, translated using a logistic 
exchange function.
    Underserved population means residents with dual eligibility status 
(DES).
* * * * *
    (c) * * *
    (2) * * *
    (i) Total amount available for a fiscal year. The total amount 
available for value-based incentive payments for a fiscal year is at 
least 60 percent of the total amount of the reduction to the adjusted 
SNF PPS payments for that fiscal year, as estimated by CMS, and will be 
increased as appropriate for each fiscal year to account for the 
assignment of a performance score to low-volume SNFs under paragraph 
(d)(3) of this section. Beginning with the FY 2023 SNF VBP, the total 
amount available for value-based incentive payments for a fiscal year 
is 60 percent of the total amount of the reduction to the adjusted SNF 
PPS payments for that fiscal year, as estimated by CMS. Beginning with 
the FY 2027 SNF VBP, the total amount available for value-based 
incentive payments for a fiscal year is at least 60 percent of the 
total amount of the reduction to the adjusted SNF PPS payments for that 
fiscal year, as estimated by CMS, and will be increased as appropriate 
for each fiscal year to account for the application of the Health 
Equity Adjustment described at paragraph (k) of this section.
* * * * *
    (d) * * *
    (4) * * *
    (v) CMS will calculate a SNF Performance Score for a fiscal year 
for a SNF for which it has granted an exception request that does not 
include its performance on a quality measure during the calendar months 
affected by the extraordinary circumstance.
* * * * *
    (e) * * *
    (2) Calculation of the SNF performance score for fiscal year 2026. 
The SNF performance score for FY 2026 is calculated as follows:
* * * * *
    (3) Calculation of the SNF performance score beginning with fiscal 
year 2027. The SNF performance score for a fiscal year is calculated as 
follows:
    (i) CMS will sum all points awarded to a SNF as described in 
paragraph (e)(1) of this section for each measure applicable to a 
fiscal year.
    (ii) CMS will normalize the SNF's point total such that the 
resulting point total is expressed as a number of points earned out of 
a total of 100.
    (iii) CMS will add to the SNF's point total under paragraph 
(e)(3)(ii) of this section any applicable health equity adjustment 
bonus points calculated under paragraph (k) of this section such that 
the resulting point total is the SNF Performance Score for the fiscal 
year, except that no SNF Performance Score may exceed 100 points.
* * * * *
    (j) * * *
    (1) Beginning with the FY 2023 Program year, for the SNFRM measure, 
and beginning with the FY 2026 Program year for all other claims-based 
measures, the information reported through claims are validated for 
accuracy by Medicare Administrative Contractors (MACs).
    (2) Beginning with the FY 2026 Program year, for all measures that 
are calculated using Payroll-Based Journal System data, information 
reported through the Payroll-Based Journal system is validated for 
accuracy by CMS and its contractors through quarterly audits.
    (3) Beginning with the FY 2027 program year, for all measure that 
are calculated using Minimum Data Set (MDS) information, such 
information is validated for accuracy by CMS and its contractors 
through periodic audits not to exceed 1,500 SNFs per calendar year.
    (k) Calculation of the Health Equity Adjustment (HEA) bonus points. 
CMS calculates the number of HEA bonus points that are added to a SNF's 
point total calculated under paragraph (e)(3)(iii) of this section by:
    (1) Determining for each measure whether the SNF is a top tier 
performing SNF and assigning two points to the SNF for each such 
measure;
    (2) Summing the points calculated under paragraph (k)(1) of this 
section to calculate the measure performance scaler;
    (3) Calculating the underserved multiplier for the SNF; and
    (4) Multiplying the measure performance scaler calculated under 
paragraph (k)(2) of this section by the underserved multiplier 
calculated under paragraph (k)(3) of this section.
0
5. Amend Sec.  413.360 by--

[[Page 21422]]

0
a. Redesignating paragraph (b)(2) as paragraph (b)(3),
0
b. Adding new paragraph (b)(2); and
0
c. Revising paragraphs (f)(1) and (2);
    The addition and revisions read as follows:


Sec.  413.360  Requirements under the Skilled Nursing Facility (SNF) 
Quality Reporting Program (QRP).

* * * * *
    (b) * * *
    (2) Resident satisfaction data. A SNF must submit to CMS data 
regarding resident satisfaction after a short-stay discharge in the 
form and manner, and at a time, specified by CMS.
    (i) Requirements. A SNF must contract with an independent survey 
vendor, approved by CMS in accordance with paragraph (b)(2)(ii) of this 
section, to administer the resident satisfaction questionnaire on its 
behalf.
    (ii) CMS approval of survey vendor. CMS approves an application for 
an entity to administer the resident satisfaction questionnaire on 
behalf of one or more SNFs when an applicant has met the resident 
satisfaction survey's Protocols and Guidelines minimum business 
requirements that can be found on the official resident satisfaction 
measure website, and agrees to comply with the current survey 
administration protocols that can be found on the resident satisfaction 
measure website. An entity must be a CMS-approved survey vendor in 
order to administer and submit the resident satisfaction survey data to 
CMS on behalf of one or more SNFs.
    (iii) Compliance with oversight activities. SNFs and CMS-approved 
survey vendors must fully comply with resident satisfaction measure 
oversight activities, including allowing CMS to perform site visits at 
the survey vendors' company locations.
* * * * *
    (f) * * *
    (1) SNFs must meet or exceed the following data completeness 
thresholds with respect to a calendar year:
    (i) The threshold set at 100 percent completion of measures data 
and standardized patient assessment data collected using the Minimum 
Data Set (MDS) on at least 80 percent of the assessments SNFs submit 
through the CMS designated data submission system for FY 2018 through 
FY 2025.
    (ii) The threshold set at 100 percent completion of measures data 
and standardized patient assessment data collected using the MDS on at 
least 90 percent of the assessments SNFs submit through the CMS 
designated data submission system beginning with the FY 2026 program 
year.
    (iii) The threshold set at 100 percent for measures data collected 
and submitted through the Centers for Disease Control and Prevention's 
(CDC) National Healthcare Safety Network (NHSN) for FY 2023 and for all 
subsequent payment updates.
    (iv) The threshold set at 75 percent of the weeks in a reporting 
year for submission of resident information files and 90 percent 
completion of the data required in resident information files for the 
resident satisfaction measure for FY 2026 and for all subsequent 
payment updates.
    (2) These thresholds apply to all measures and standardized patient 
assessment data requirements adopted into the SNF QRP.
* * * * *

PART 488--SURVEY, CERTIFICATION, AND ENFORCEMENT PROCEDURES

0
6. The authority citation for part 488 continues to read as follows:

    Authority: 42 U.S.C. 1302 and 1395hh.

0
7. Amend Sec.  488.432 by revising paragraphs (c)(1) and (2) to read as 
follows:


Sec.  488.432  Civil money penalties imposed by the State: NF-only.

* * * * *
    (c) * * *
    (1) If a facility waives its right to a hearing as specified in 
Sec.  488.436, the State initiates collection of civil money penalty 
imposed per day of noncompliance after 60 days from the date of the 
notice imposing the penalty and the State has not received a timely 
request for a hearing.
    (2) If a facility waives its right to a hearing as specified in 
Sec.  488.436, the State initiates collection of civil money penalty 
imposed per instance of noncompliance after 60 days from the date of 
the notice imposing the penalty and the State has not received a timely 
request for a hearing.
* * * * *
0
8. Amend Sec.  488.436 by revising paragraph (a) to read as follows:


Sec.  488.436  Civil money penalties: Waiver of hearing, reduction of 
penalty amount.

    (a) Constructive waiver of a hearing. A facility is deemed to have 
waived its right to a hearing after 60 days from the date of the notice 
imposing the civil money penalty if CMS has not received a request for 
a hearing from the facility.
* * * * *
0
9. Amend Sec.  488.442 by revising paragraph (a)(2) introductory text 
to read as follows:


Sec.  488.442  Civil money penalties: Due date for payment of penalty.

    (a) * * *
    (2) After the facility waives its right to a hearing in accordance 
with Sec.  488.436(a). Except as provided for in Sec.  488.431, a civil 
money penalty is due 75 days after the notice of the penalty in 
accordance with Sec.  488.436 and a hearing request was not received 
when:
* * * * *

PART 489--PROVIDER AGREEMENTS AND SUPPLIER APPROVAL

0
10. The authority citation for part 489 continues to read as follows:

    Authority:  42 U.S.C. 1302, 1395i-3, 1395x, 1395aa(m), 1395cc, 
1395ff, and 1395hh.

0
11. Amend Sec.  489.20 by--
0
a. Redesignating paragraphs (s)(6) through (18) as paragraphs (s)(8) 
through (20), respectively; and
0
b. Adding new paragraphs (s)(6) and (7).
    The additions read as follows:


Sec.  489.20  Basis commitments.

* * * * *
    (s) * * *
    (6) Services performed by a marriage and family therapist, as 
defined in section 1861(lll)(2) of the Act.
    (7) Services performed by a mental health counselor, as defined in 
section 1861(lll)(4) of the Act.
* * * * *

    Dated: March 31, 2023.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2023-07137 Filed 4-4-23; 4:15 pm]
BILLING CODE 4120-01-P